diff --git a/.gitignore b/.gitignore deleted file mode 100644 index cc9b755..0000000 --- a/.gitignore +++ /dev/null @@ -1,9 +0,0 @@ -*result -*_example -*_ACDC -*__pycache__ -# *_slices -# *_volumes -*metrics_fast* -*figure* -*Abdomen* diff --git a/README.md b/README.md new file mode 100644 index 0000000..144c764 --- /dev/null +++ b/README.md @@ -0,0 +1,2 @@ +# DMSPS +Dynamically Mixed Soft Pseudo-label Supervision for Scribble-Supervised Medical Image Segmentation diff --git a/bash.sh b/bash.sh deleted file mode 100644 index 547d69f..0000000 --- a/bash.sh +++ /dev/null @@ -1,21 +0,0 @@ - -# PyMICPATH=/home/disk4t/projects/PyMIC_project/PyMIC -# export PYTHONPATH=$PYTHONPATH:/home/disk4t/student_code/DMSPS/code - - -# python image_process.py 0 -# pymic_train config/acdc_dmsps.cfg -python run.py train config/acdc_dmsps_r4.cfg - -# pymic_test config/acdc_dmsps.cfg -# pymic_eval_seg --metric dice --cls_num 4 \ -# --gt_dir data/ACDC2017/ACDC/TestSet/labels --seg_dir ./result/acdc_dmsps \ -# --name_pair ./config/image_test_gt_seg.csv -# pymic_test config/acdc_dmsps.cfg --test_csv data/ACDC2017/ACDC_for2D/trainvol.csv \ -# --dmsps_test_mode 1 --output_dir result/acdc_dmsps_train -# python image_process.py 1 -# pymic_train config/acdc_dmsps_stage2.cfg -# pymic_test config/acdc_dmsps_stage2.cfg -# pymic_eval_seg --metric dice --cls_num 4 \ -# --gt_dir data/ACDC2017/ACDC/TestSet/labels --seg_dir ./result/acdc_dmsps_stage2 \ -# --name_pair ./config/image_test_gt_seg.csv diff --git a/code/DMSPS_trainTest_2d.sh b/code/DMSPS_trainTest_2d.sh index cb62715..7a8a2d6 100644 --- a/code/DMSPS_trainTest_2d.sh +++ b/code/DMSPS_trainTest_2d.sh @@ -30,7 +30,7 @@ CUDA_LAUNCH_BLOCKING=1 CUDA_VISIBLE_DEVICES=0 python train/A_train_weaklySup_SPS --model unet_cct --exp A_weakly_SPS_2d --fold stage2 --sup_type pseudoLab --trainData trainReT01.txt # test for stage2 -CUDA_LAUNCH_BLOCKING=1 CUDA_VISIBLE_DEVICES=0 python test/test_2d_forall_fast_txtver.py \ +CUDA_LAUNCH_BLOCKING=1 CUDA_VISIBLE_DEVICES=0 python python test/test_2d_forall_fast_txtver.py \ --data_root_path /mnt/data/HM/Datasets/ACDC2017/ACDC_for2D \ --model unet_cct --exp A_weakly_SPS_2d --fold stage2 diff --git a/code/dataloader/ACDC_scribble_reduce_enhance.py b/code/dataloader/ACDC_scribble_reduce_enhance.py index 8264d83..2ea7cbe 100644 --- a/code/dataloader/ACDC_scribble_reduce_enhance.py +++ b/code/dataloader/ACDC_scribble_reduce_enhance.py @@ -17,8 +17,8 @@ valid_scri_dir = "val/scribbles"#30 def get_largest_connectted_component(binary_map): - s = ndimage.generate_binary_structure(2,1) #4 - # s = ndimage.generate_binary_structure(2,2) # 8 + s = ndimage.generate_binary_structure(2,1) #4联通 + # s = ndimage.generate_binary_structure(2,2) # 8联通 labeled_array,num_features = ndimage.label(binary_map, s) if num_features == 0: return np.zeros_like(binary_map) @@ -26,13 +26,13 @@ def get_largest_connectted_component(binary_map): counts = np.bincount(labeled_array.flatten())[1:] if len(counts) == 0: return np.zeros_like(binary_map) - max_label = labels[np.argmax(counts)] + max_label = labels[np.argmax(counts)] #使用 np.bincount() 函数统计标记后的图像中每个连通域的像素数量，并找到像素数量最多的连通域的标记值 max_label。 max_component = np.zeros_like(labeled_array) max_component[labeled_array == max_label] = 1 return max_component -def reduce_volume_judgeByAbsoluteLength(binary_matrix, reduce_num = 1/2): +def reduce_volume_judgeByAbsoluteLength(binary_matrix, reduce_num = 1/2): #保留最大连通域 # Find connected regions in the binary matrix regions = label(binary_matrix) # Iterate through each connected region @@ -50,9 +50,9 @@ def reduce_volume_judgeByAbsoluteLength(binary_matrix, reduce_num = 1/2): print("center_row:{}, center_col:{}".format(center_row, center_col)) if abs(min_row-max_row)>abs(min_col-max_col): - binary_matrix[min_row:center_row, :] = 0 #leave the right area + binary_matrix[min_row:center_row, :] = 0 #保留右边的领域 else: - binary_matrix[:, min_col:center_col] = 0 #leave the bottom area + binary_matrix[:, min_col:center_col] = 0 #保留下面的领域 binary_matrix = get_largest_connectted_component(binary_matrix) return binary_matrix diff --git a/code/dataloader/preprocess_ACDC.py b/code/dataloader/preprocess_ACDC.py index 401403b..53fbd6c 100644 --- a/code/dataloader/preprocess_ACDC.py +++ b/code/dataloader/preprocess_ACDC.py @@ -5,7 +5,7 @@ from numpy import * import logging import glob -from collections import defaultdict +from collections import defaultdict # 嵌套字典的使用 import pandas as pd import h5py import copy @@ -17,6 +17,7 @@ data_root = "/mnt/data/HM/Datasets/ACDC2017/ACDC" # data_root = "/mnt/data/HM/Datasets/ACDC2017/ACDC_resample" +"""scribble_less指的是处理过长度后的scribble, 质量更差""" def show_images_info(img_dir ="train"): input_root = data_root @@ -30,8 +31,8 @@ def show_images_info(img_dir ="train"): info_img_dir = input_root + "/" + img_dir + "/images" - # img_names = sorted(os.listdir(info_img_dir)) - ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) + # img_names = sorted(os.listdir(info_img_dir)) # 只是类似word_0002.nii.gz这样集合的list + ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) #path集合的list image_num = 0 z_min = 1000 z_max = 0 @@ -125,9 +126,10 @@ def deal_dataSet_to_volumes(subdir = "train"):#for volumes image = sitk.GetArrayFromImage(image_itk) - scribble_path = case.replace("labels", "scribbles_rlessd16").replace("_gt","_scribble") + scribble_path = case.replace("labels", "scribbles_rlessd16").replace("_gt","_scribble")#前一个是文件名，后面是case名 scribble_itk = sitk.ReadImage(scribble_path) scribble = sitk.GetArrayFromImage(scribble_itk) + if image.shape != label.shape: @@ -150,7 +152,7 @@ def write_images_nametxt(subdir = "train"): # img_dir = subdir + "_volumes" img_dir = subdir + "rlessdf16" + "_slices" #trainfor2D orless8_slices info_img_dir = input_root + "/" + img_dir - img_names = sorted(os.listdir(info_img_dir)) # + img_names = sorted(os.listdir(info_img_dir)) # 只是类似word_0002.nii.gz这样集合的list if subdir == "train": name = img_dir.split("_")[0] @@ -201,7 +203,7 @@ def deal_dataSet_to_slices(subdir = "train"): for slice_ind in range(image.shape[0]): f = h5py.File(save_sub_dir + '/{}_slice_{}.h5'.format(item_name, slice_ind), 'w') f.create_dataset( - 'image', data=image[slice_ind], compression="gzip") + 'image', data=image[slice_ind], compression="gzip")#压缩成gzip的形式 f.create_dataset('label', data=label[slice_ind], compression="gzip") if subdir =="train": f.create_dataset('scribble', data=scribble[slice_ind], compression ="gzip") @@ -233,11 +235,11 @@ def image_resample(subdir = "train"): direction = img_obj.GetDirection() input_size = img_obj.GetSize() - output_spacing = [1.0,1.0,1.0] + output_spacing = [1.0,1.0,1.0] #更改空间插值 output_size = [int((input_size[i] * spacing[i]) / output_spacing[i]) for i in range(3)] transform = sitk.Transform(3, sitk.sitkIdentity) #what's mean? - interp = sitk.sitkLinear if "images" in sub_dir else sitk.sitkNearestNeighbor + interp = sitk.sitkLinear if "images" in sub_dir else sitk.sitkNearestNeighbor #是Im是线性插值，是label是最近邻插值 resampled_img = sitk.Resample(img_obj, output_size, transform, interp, origin, output_spacing, direction) sitk.WriteImage(resampled_img, output_dir + '/' + img_name) diff --git a/code/dataloader/preprocess_BraTS2020.py b/code/dataloader/preprocess_BraTS2020.py deleted file mode 100644 index b377c9b..0000000 --- a/code/dataloader/preprocess_BraTS2020.py +++ /dev/null @@ -1,457 +0,0 @@ -import sys -import os -import SimpleITK as sitk -import numpy as np -from numpy import * -import logging -import glob -from collections import defaultdict -import pandas as pd -import h5py -import copy -import random -import math -os.environ["CUDA_VISIBLE_DEVICES"] = "0" -data_root = "/mnt/data/HM/Datasets/BraTS2020/MICCAI_BraTS2020_TrainingData" -predata_root = "/mnt/data/HM/Datasets/BraTS2020/MICCAI_BraTS2020_TrainingPre" -img_dirs = ["t1", "t1ce", "t2", "flair"] - -def convert_BraTSLabel_into2(): - # img_names_root = sorted(glob.glob(data_root +"BraTS20*")) - # print(img_names_root) - seg_data_path = sorted(glob.glob(data_root + "/*_seg.nii.gz" ))#369 cases - # print(len(seg_data_path)) - - for item in seg_data_path: - seg_obj = sitk.ReadImage(item) - seg_np = sitk.GetArrayFromImage(seg_obj) - new_label = copy.deepcopy(seg_np) - new_label[new_label==4] = 1 - print(np.unique(new_label)) - - new_label_save_name = item.replace("_seg", "_2label") - lab_out_obj = sitk.GetImageFromArray(new_label) - lab_out_obj.SetSpacing(seg_obj.GetSpacing()) - lab_out_obj.SetOrigin(seg_obj.GetOrigin()) - lab_out_obj.SetDirection(seg_obj.GetDirection()) - sitk.WriteImage(lab_out_obj, new_label_save_name) - -def brain_bbox(data, gt): - mask = (data != 0) - brain_voxels = np.where(mask != 0) - # print("brain_voxels[0]:{}, num:{}".format(brain_voxels[0], len(brain_voxels[0]))) - minZidx = int(np.min(brain_voxels[0])) - maxZidx = int(np.max(brain_voxels[0])) - minXidx = int(np.min(brain_voxels[1])) - maxXidx = int(np.max(brain_voxels[1])) - minYidx = int(np.min(brain_voxels[2])) - maxYidx = int(np.max(brain_voxels[2])) - data_bboxed = data[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - gt_bboxed = gt[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - return data_bboxed, gt_bboxed - -def get_boundingBox_id(data): - mask = (data != 0) - brain_voxels = np.where(mask != 0) - minZidx = int(np.min(brain_voxels[0])) - maxZidx = int(np.max(brain_voxels[0])) - minXidx = int(np.min(brain_voxels[1])) - maxXidx = int(np.max(brain_voxels[1])) - minYidx = int(np.min(brain_voxels[2])) - maxYidx = int(np.max(brain_voxels[2])) - return minZidx, maxZidx, minXidx, maxXidx, minYidx, maxYidx - -def brain_bbox_4modalData(data_t1, data_t1ce, data_t2, data_flair, gt): - minZidx_t1, maxZidx_t1, minXidx_t1, \ - maxXidx_t1, minYidx_t1, maxYidx_t1 = get_boundingBox_id(data_t1) - minZidx_t1ce, maxZidx_t1ce, minXidx_t1ce, \ - maxXidx_t1ce, minYidx_t1ce, maxYidx_t1ce = get_boundingBox_id(data_t1ce) - minZidx_t2, maxZidx_t2, minXidx_t2, \ - maxXidx_t2, minYidx_t2, maxYidx_t2 = get_boundingBox_id(data_t2) - minZidx_flair, maxZidx_flair, minXidx_flair, \ - maxXidx_flair, minYidx_flair, maxYidx_flair = get_boundingBox_id(data_flair) - minZidx = int(np.min([minZidx_t1, minZidx_t1ce, minZidx_t2, minZidx_flair])) - maxZidx = int(np.max([maxZidx_t1, maxZidx_t1ce, maxZidx_t2, maxZidx_flair])) - minXidx = int(np.min([minXidx_t1, minXidx_t1ce, minXidx_t2, minXidx_flair])) - maxXidx = int(np.max([maxXidx_t1, maxXidx_t1ce, maxXidx_t2, maxXidx_flair])) - minYidx = int(np.min([minYidx_t1, minYidx_t1ce, minYidx_t2, minYidx_flair])) - maxYidx = int(np.max([maxYidx_t1, maxYidx_t1ce, maxYidx_t2, maxYidx_flair])) - data_t1_bboxed = data_t1[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - data_t1ce_bboxed = data_t1ce[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - data_t2_bboxed = data_t2[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - data_flair_bboxed = data_flair[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - gt_bboxed = gt[minZidx:maxZidx, minXidx:maxXidx, minYidx:maxYidx] - return data_t1_bboxed, data_t1ce_bboxed, data_t2_bboxed, data_flair_bboxed, gt_bboxed - ################################### - - -def itensity_normalize_one_volume(volume): - """ - normalize the itensity of an nd volume based on the mean and std of nonzeor region - inputs: - volume: the input nd volume - outputs: - out: the normalized nd volume - """ - - pixels = volume[volume > 0] - mean = pixels.mean() - std = pixels.std() - out = (volume - mean)/std - # out_random = np.random.normal(0, 1, size=volume.shape) - # out[volume == 0] = out_random[volume == 0] - out = out.astype(np.float32) - return out - -class MedicalImageDeal(object): - def __init__(self, img, percent=1): - self.img = img - self.percent = percent - - @property - def valid_img(self): - from skimage import exposure - cdf = exposure.cumulative_distribution(self.img) - watershed = cdf[1][cdf[0] >= self.percent][0] - return np.clip(self.img, self.img.min(), watershed) - - @property - def norm_img(self): - return (self.img - self.img.min()) / (self.img.max() - self.img.min()) - - -def show_preBraTS_image_info(): - input_root = predata_root - output_info_dir = "./log/preBraTS" - if not os.path.exists(output_info_dir): - os.makedirs(output_info_dir) - - logging.basicConfig(filename = output_info_dir + "/preBraTS_info.txt", level = logging.INFO, - format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - info_img_dir = input_root + "/" + img_dirs[0] # take t1 as example - print("info_img_dir:{}".format(info_img_dir)) - ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) - image_num = 0 - z_min = 10000 - z_max = 0 - h_min = 10000 - h_max = 0 - w_min = 10000 - w_max = 0 - - for img_name in ori_img_path: - case_name = img_name.split("/")[-1] - logging.info("case name :{}".format(case_name)) - img_obj = sitk.ReadImage(img_name) - space = img_obj.GetSpacing() - size = img_obj.GetSize() - - imageTr = sitk.GetArrayFromImage(img_obj) - logging.info("image_np_shape: {}".format(imageTr.shape)) - if size[2]>z_max: - z_max = size[2] - if size[2]h_max: - h_max = size[0] - if size[0]w_max: - w_max = size[1] - if size[1]z_max: - z_max = size[2] - if size[2]h_max: - h_max = size[0] - if size[0]w_max: - w_max = size[1] - if size[1] 0) + d_idx, h_idx, w_idx = np.where(seg_np > 0) #返回的是array形式 d_min, d_max = d_idx.min(), d_idx.max() h_min, h_max = h_idx.min(), h_idx.max() w_min, w_max = w_idx.min(), w_idx.max() @@ -106,7 +106,7 @@ def get_3d_bounding_box(seg_np = None): def cropW_single_image(img_name, input_img_dir, idx_min, idx_max, output_img_dir, convert=False): img_name_full = input_img_dir + "/" + img_name img_obj = sitk.ReadImage(img_name_full) - img = sitk.GetArrayFromImage(img_obj) + img = sitk.GetArrayFromImage(img_obj) #可以看成是np型 if convert == True: img = Load_LabelConvert_abdomenWORD(label_path=img_name_full) print("convert successfully") @@ -157,7 +157,7 @@ def cropW_3d_images_WORD(flag ="train"): if flag == "train": os.makedirs(output_scri_dir) - img_names = sorted(os.listdir(input_img_dir)) + img_names = sorted(os.listdir(input_img_dir)) # list type 这里这么写是因为WORD里img、lab和scribble的name都是一样的 crop_location_d = defaultdict(defaultdict) for img_name in img_names: @@ -216,7 +216,7 @@ def cropWL_3d_images_dealLabel_WORD(flag="train"): if flag == "train": os.makedirs(output_scri_dir) - img_names = sorted(os.listdir(input_img_dir)) + img_names = sorted(os.listdir(input_img_dir)) # list type,只是图片的名字 crop_location_d = defaultdict(defaultdict) for img_name in img_names: @@ -288,7 +288,7 @@ def deal_trainSet_to_slices():#for 2d f.create_dataset( 'scribble', data=scribbleTr[slice_ind], compression="gzip") f.close() - training_slice_num += 1 #slice num +1 + training_slice_num += 1 #切片数量加1 print("Converted all Abdomen training volumes to 2D slices") print("Total {} training slices".format(training_slice_num)) #original total 20115 # after cropping there are totally 17554 training slices @@ -361,12 +361,12 @@ def write_images_nametxt(flag ="train"): else: img_dir = "Abdomen_"+flag+"_volumes" info_img_dir = input_root + "/" + img_dir - img_names = sorted(os.listdir(info_img_dir)) - # ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) + img_names = sorted(os.listdir(info_img_dir)) # 只是类似word_0002.nii.gz这样集合的list + # ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) #path集合的list f = open(output_info_dir + "/" + flag +".txt", "w") # with open(output_info_dir + "/" + flag +"_name.txt", "w") as file: - # file.write(os.path.join(img_dir,img_name)) + # file.write(os.path.join(img_dir,img_name)) #只能写入最后一行 for img_name in img_names: f.write(os.path.join(img_dir,img_name) + "\n") f.close() @@ -385,12 +385,12 @@ def write_images_nametxt_for2D(flag ="train"): elif flag == "valid": img_dir = "Abdomen_Val_volumes" info_img_dir = input_root + "/" + img_dir - img_names = sorted(os.listdir(info_img_dir)) - # ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) + img_names = sorted(os.listdir(info_img_dir)) # 只是类似word_0002.nii.gz这样集合的list + # ori_img_path = sorted(glob.glob(info_img_dir + "/*.nii.gz")) #path集合的list f = open(output_info_dir + "/" + flag +".txt", "w") # with open(output_info_dir + "/" + flag +"_name.txt", "w") as file: - # file.write(os.path.join(img_dir,img_name)) + # file.write(os.path.join(img_dir,img_name)) #只能写入最后一行 for img_name in img_names: f.write(os.path.join(img_dir,img_name) + "\n") f.close() @@ -402,7 +402,7 @@ def show_rotate(): load_data_root = data_root + "_cropWL/imagesTr/word_0002.nii.gz" load_label_root = data_root + "_cropWL/labelsTr/word_0002.nii.gz" img_obj = sitk.ReadImage(load_data_root) - img = sitk.GetArrayFromImage(img_obj) + img = sitk.GetArrayFromImage(img_obj) #可以看成是np型 # image_1 = ndimage.rotate(img, 50, order=0, reshape=False) # img_crop_obj = sitk.GetImageFromArray(image_1) @@ -431,7 +431,7 @@ def show_rotate(): lab_obj = sitk.ReadImage(load_label_root) - lab = sitk.GetArrayFromImage(lab_obj) + lab = sitk.GetArrayFromImage(lab_obj) #可以看成是np型 # lab_1 = ndimage.rotate(lab, 50, order=0, reshape=False) # img_crop_obj = sitk.GetImageFromArray(lab_1) @@ -459,7 +459,7 @@ def show_rotate(): sitk.WriteImage(img_crop_obj, img_out_name) -def deal_scribblePerN_to_volumes(flag):#flag: Per1, Per3... default: train +def deal_scribblePerN_to_volumes(flag):#flag: Per1, Per3... 默认是train input_root = data_root + "_cropWL" save_root_path = input_root + "_for3D" # if os.path.exists(save_root_path + "/Abdomen_" + name + "_volumes"): @@ -513,27 +513,29 @@ def deal_scribblePerN_to_volumes(flag):#flag: Per1, Per3... default: train cropW_3d_images_WORD(flag = "valid") elif func == 3: deal_trainSet_to_slices() # before train_slices = 17554 - # after label convertthere are only total 9223 training slices + # 进行label convert后就只有Total 9223 training slices elif func ==4 : deal_dataSet_to_volumes(flag = "valid") # 20 validation volumes deal_dataSet_to_volumes(flag = "test") #30 test volumes - elif func == 5: #select 7 organs + elif func == 5: #挑了7个器官 cropWL_3d_images_dealLabel_WORD(flag = "train") cropWL_3d_images_dealLabel_WORD(flag = "test") cropWL_3d_images_dealLabel_WORD(flag = "valid") - elif func == 6: # + elif func == 6: #为了3d做的数据处理，为此还更改了deal_dataSet_to_volumes这个代码 deal_dataSet_to_volumes(flag = "train") # deal_dataSet_to_volumes(flag = "test") # deal_dataSet_to_volumes(flag = "valid") elif func == 7: - write_images_nametxt(flag1 + "Tr") - elif func == 8: + write_images_nametxt(flag1 + "Tr") # scribble修正 + elif func == 8: #显示旋转 show_rotate() - elif func == 9: #more poor scribble + elif func == 9: #更加稀疏的scribble deal_scribblePerN_to_volumes(flag1) elif func == 10: write_images_nametxt_for2D(flag = "train") write_images_nametxt_for2D(flag = "test") write_images_nametxt_for2D(flag = "valid") +""" +如果要处理新的scribble, 要先9[处理成volumes]后7[处理成txt],将路径记录到txt""" diff --git a/code/dataloader/retrain_postProcess_WORD_uncertainty.py b/code/dataloader/retrain_postProcess_WORD_uncertainty.py index 573f41e..55065d7 100644 --- a/code/dataloader/retrain_postProcess_WORD_uncertainty.py +++ b/code/dataloader/retrain_postProcess_WORD_uncertainty.py @@ -11,16 +11,16 @@ parser.add_argument('--data_root_path', type=str, default='/mnt/data/HM/Datasets/Abdomen_word/WORD-V0.1.0-Admin_cropWL', help='Name of Experiment') parser.add_argument('--data_type', type=str, - default='Abdomen', help='Data category') + default='AbdomenM', help='Data category') parser.add_argument('--data_name', type=str, default='word_3d', help='Data name') parser.add_argument('--savedir', type=str, default='TrResult', help='TsResult for testSet, ValResult for valSet, TrResult for trainSet') parser.add_argument('--model', type=str, - default='unet_cct_dp_3D', help='model_name') + default='unet_cct_dropout_3D', help='model_name') parser.add_argument('--exp', type=str, - default='W_weakly_PLS_soft_3d', help='experiment_name') + default='A3_weakly_PLS_3d', help='experiment_name') parser.add_argument('--fold', type=str, default='stage1', help='') parser.add_argument('--num_classes', type=int, default=8, @@ -28,7 +28,7 @@ parser.add_argument('--tt_num', type=int, default=3, help='test times num') -parser.add_argument('--func', type=int, default=1, +parser.add_argument('--func', type=int, default=0, help='function') parser.add_argument('--txtName', type=str, default="trainReT03", help='txt name') @@ -83,13 +83,13 @@ def deal_retrainData_to_volumes(pred_data_path, flag, subdir = "Tr" ):#for retra print("Converted data re" + subdir + " data to volumes") print("Total {} re{} volumes".format(volume_num, subdir)) -def write_images_nametxt(flag): +def write_images_nametxt(flag, subdir = "Tr"): input_root = FLAGS.data_root_path + "_for3D" output_info_dir = input_root - img_dir = flag + img_dir = subdir + flag info_img_dir = input_root + "/" + img_dir - img_names = sorted(os.listdir(info_img_dir)) + img_names = sorted(os.listdir(info_img_dir)) # 只是类似word_0002.nii.gz这样集合的list txtname = flag.replace("_volumes","") f = open(output_info_dir + "/" + txtname +".txt", "w") diff --git a/code/dataloader/scribble_generater.py b/code/dataloader/scribble_generater.py index 95a1664..964e142 100644 --- a/code/dataloader/scribble_generater.py +++ b/code/dataloader/scribble_generater.py @@ -37,22 +37,24 @@ random.seed(seed) -def random_rotation(image, max_angle=15): +def random_rotation(image, max_angle=15):#生成随机角度 angle = np.random.uniform(-max_angle, max_angle) img = Image.fromarray(image) img_rotate = img.rotate(angle) return img_rotate -def translate_img(img, x_shift, y_shift): +def translate_img(img, x_shift, y_shift):#仿射变换 (height, width) = img.shape[:2] matrix = np.float32([[1, 0, x_shift], [0, 1, y_shift]]) trans_img = cv2.warpAffine(img, matrix, (width, height)) + #cv2.warpAffine仿射变换； img输入图像，matrix 变换矩阵， + # (w,h)共同组成dsize参数，表示输出图像的大小 return trans_img -def get_largest_two_component_2D(img, print_info=False, threshold=None): +def get_largest_two_component_2D(img, print_info=False, threshold=None):#获得2d图像的两个最大连通图 """ Get the largest two components of a binary volume inputs: @@ -61,8 +63,8 @@ def get_largest_two_component_2D(img, print_info=False, threshold=None): outputs: out_img: the output volume """ - s = ndimage.generate_binary_structure(2, 2) - labeled_array, numpatches = ndimage.label(img, s) + s = ndimage.generate_binary_structure(2, 2) # iterate structure + labeled_array, numpatches = ndimage.label(img, s) # labeling sizes = ndimage.sum(img, labeled_array, range(1, numpatches+1)) sizes_list = [sizes[i] for i in range(len(sizes))] sizes_list.sort() @@ -77,9 +79,9 @@ def get_largest_two_component_2D(img, print_info=False, threshold=None): if max_label1.shape[0] > 1: max_label1 = max_label1[0] component1 = labeled_array == max_label1 - out_img = [component1] + out_img = [component1] #最大连通域 for temp_size in sizes_list: - if(temp_size > threshold): + if(temp_size > threshold):#将超过阈值的连通域加入 temp_lab = np.where(sizes == temp_size)[0] + 1 temp_cmp = labeled_array == temp_lab[0] out_img.append(temp_cmp) @@ -96,7 +98,7 @@ def get_largest_two_component_2D(img, print_info=False, threshold=None): component1 = labeled_array == max_label1 component2 = labeled_array == max_label2 if(max_size2*10 > max_size1): - out_img = [component1, component2] + out_img = [component1, component2]#对第二大的连通域还是有约束的。 else: out_img = [component1] return out_img @@ -142,7 +144,7 @@ def __detect_pt_bifur_state(self, lab, pt, direction): else: return False - def __detect_neighbor_bifur_state(self, lab, pt): + def __detect_neighbor_bifur_state(self, lab, pt):#递归，看不懂，大概是找连接区域？ directions = [] for i in range(9): if i == 4: @@ -180,7 +182,7 @@ def __call__(self, lab, seg_lab, iterations=1): self.previous_bifurPts = [] self.output = np.zeros_like(lab) self.lst_output = np.zeros_like(lab) - components = get_largest_two_component_2D(lab, threshold=15) + components = get_largest_two_component_2D(lab, threshold=15)#将超过15大小的连通域都得到 if len(components) > 1: for c in components: start = self.__find_start(c) @@ -196,7 +198,7 @@ def __call__(self, lab, seg_lab, iterations=1): shift_y = random.randint(-6, 6) shift_x = random.randint(-6, 6) if np.sum(seg_lab) > 1000: - output = translate_img(output.astype(np.uint8), shift_x, shift_y) + output = translate_img(output.astype(np.uint8), shift_x, shift_y)#变换，变换的知识我不是很懂 output = random_rotation(output) output = output * seg_lab return output @@ -267,7 +269,7 @@ def scrible_2d_PerNSclices(label, interNum, iteration=[4, 10]): def scribble4class_PerNSclices(label, class_id, class_num, interNum, iteration=[4, 10], cut_branch=True): - label = (label == class_id) + label = (label == class_id) # 选出当前的class，返回[0 1]图 sk_map = scrible_2d_PerNSclices(label, interNum, iteration=iteration) if cut_branch and class_id != 0: cut = Cutting_branch() @@ -283,7 +285,7 @@ def scribble4class_PerNSclices(label, class_id, class_num, interNum, iteration=[ def generate_scribble_PerNSclices(label, interNum, iterations, cut_branch=True): class_num = np.max(label) + 1 output = np.zeros_like(label, dtype=np.uint8) - for i in range(class_num): + for i in range(class_num): #一个一个器官进行scribble生成 it = iterations[i] if isinstance(iterations, list) else iterations scribble = scribble4class_PerNSclices( label, i, class_num, interNum, it, cut_branch=cut_branch) @@ -311,7 +313,7 @@ def generate_scribble_PerNSclices(label, interNum, iterations, cut_branch=True): label = sitk.GetArrayFromImage(itk_data) # num_classes = 3 num_classes = 8 - output = generate_scribble_PerNSclices(label, interval_layer+1, tuple([1, num_classes-1])) + output = generate_scribble_PerNSclices(label, interval_layer+1, tuple([1, num_classes-1]))#隔1层是2，隔3层步长是4 output[output == 0] = 255 # ignore index output[output == num_classes] = 0 itk_scr = sitk.GetImageFromArray(output) @@ -319,7 +321,7 @@ def generate_scribble_PerNSclices(label, interNum, iterations, cut_branch=True): # sitk.WriteImage(itk_scr, i.replace('_lab.nii.gz', '_scribble.nii.gz')) # output_path = i.replace('label', 'scribble') - sitk.WriteImage(itk_scr, i.replace('labels', 'scribblesPer'+str(interval_layer))) + sitk.WriteImage(itk_scr, i.replace('labels', 'scribblesPer'+str(interval_layer)))#保存图片，保存路径 print("{} End".format(i.split("/")[-1])) print(num) num += 1 \ No newline at end of file diff --git a/code/dataloader/transform_2D.py b/code/dataloader/transform_2D.py index a50469c..6cc88b1 100644 --- a/code/dataloader/transform_2D.py +++ b/code/dataloader/transform_2D.py @@ -15,7 +15,8 @@ class RandomCrop_2D(object): def __init__(self, output_size, num_class = 8, with_sdf=False): self.output_size = output_size self.num_class = num_class - self.with_sdf = with_sdf # + self.with_sdf = with_sdf # 不是很懂这个with_sdf的指标 + def __call__(self, sample): image, label, gt = sample['image'], sample['label'], sample['gt'] if self.with_sdf: @@ -87,13 +88,14 @@ def __init__(self, cval=8): self.cval = cval def __call__(self, sample): image, label, gt = sample['image'], sample['label'], sample['gt'] - angle = np.random.randint(-20,20) + angle = np.random.randint(-20,20)#返回范围内的整数值 image = ndimage.rotate(image, angle, order=0, reshape=False) label = ndimage.rotate(label, angle, order=0, reshape=False, mode="constant", cval=self.cval) gt = ndimage.rotate(gt, angle, order=0, reshape=False, mode="constant", cval=0) + #'costant' 通过使用cval参数定义的相同常量值填充边之外的所有值来扩展输入。mode默认是'constant'。在输入边之外不执行插值。Cval默认是0 return {'image': image, 'label': label, 'gt':gt} -def random_rot_flip(image, label,gt): +def random_rot_flip(image, label,gt):#随机旋转90, 翻转， 2d k = np.random.randint(0, 4) image = np.rot90(image, k) label = np.rot90(label, k) @@ -113,7 +115,7 @@ def random_rotate(image, label, gt, cval): #2d gt = ndimage.rotate(gt, angle, order=0, reshape=False, mode="constant", cval=0) return image, label, gt -class RandomGenerator(object): #2d +class RandomGenerator(object): #按照ACDC_WSL改的,2d def __init__(self, output_size, num_classes): self.output_size = output_size self.num_classes= num_classes @@ -137,7 +139,7 @@ def __call__(self, sample): sample = {"image": image, "label": label, "gt":gt} return sample -class RandomGenerator4Abdomen(object): +class RandomGenerator4Abdomen(object): #只有resize, for abdomen,2d def __init__(self, output_size, num_classes): self.output_size = output_size self.num_classes= num_classes diff --git a/code/dataloader/utils.py b/code/dataloader/utils.py index ff288d7..448c3df 100644 --- a/code/dataloader/utils.py +++ b/code/dataloader/utils.py @@ -8,7 +8,7 @@ -def recursive_glob(rootdir='.', suffix=''): +def recursive_glob(rootdir='.', suffix=''): #递归的glob """Performs recursive glob with given suffix and rootdir :param rootdir is the root directory :param suffix is the suffix to be searched @@ -184,7 +184,7 @@ def get_dice(pred, gt): return total_dice -def get_mc_dice(pred, gt, num=2): +def get_mc_dice(pred, gt, num=2): #好像是计算每个class的dice # num is the total number of classes, include the background total_dice = np.zeros(num-1) pred = pred.long() diff --git a/code/networks/UNETR_monai_2dual.py b/code/networks/UNETR_monai_2dual.py index b594372..e8fdb48 100644 --- a/code/networks/UNETR_monai_2dual.py +++ b/code/networks/UNETR_monai_2dual.py @@ -34,7 +34,7 @@ def __init__( out_channels: int, img_size: Tuple[int, int, int], feature_size: int = 16, - hidden_size: int = 768, + hidden_size: int = 768, #为啥hidden size比feature_size大？ mlp_dim: int = 3072, num_heads: int = 12, @@ -80,7 +80,7 @@ def __init__( if pos_embed not in ["conv", "perceptron"]: raise KeyError(f"Position embedding layer of type {pos_embed} is not supported.") - self.num_layers = 12 + self.num_layers = 12 #Vit的层数？ self.patch_size = (16, 16, 16) self.feat_size = ( img_size[0] // self.patch_size[0], @@ -256,7 +256,7 @@ def load_from(self, weights): self.vit.norm.bias.copy_(weights["state_dict"]["module.transformer.norm.bias"]) def forward(self, x_in): - x, hidden_states_out = self.vit(x_in)#x maybe the global information obtained by transformer + x, hidden_states_out = self.vit(x_in)#x应该是transformer获取的全局信息 enc1 = self.encoder1(x_in) x2 = hidden_states_out[3] enc2 = self.encoder2(self.proj_feat(x2, self.hidden_size, self.feat_size)) diff --git a/code/networks/unet_cct_3D.py b/code/networks/unet_cct_3D.py index 96a13b7..0eef1f0 100644 --- a/code/networks/unet_cct_3D.py +++ b/code/networks/unet_cct_3D.py @@ -68,7 +68,7 @@ def forward(self, inputs): center = self.center(maxpool4) return [conv1, conv2, conv3, conv4, center] - + class Decoder_dp(nn.Module): def __init__(self, params): super(Decoder_dp, self).__init__() diff --git a/code/networks/unet_nest_2dual.py b/code/networks/unet_nest_2dual.py index f330b12..c597dc2 100644 --- a/code/networks/unet_nest_2dual.py +++ b/code/networks/unet_nest_2dual.py @@ -13,8 +13,9 @@ #from pymic.net.net2d.unet2d import * import sys import os -BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) -sys.path.append(BASE_DIR) +#调用上级 +BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) #当前程序上上一级目录 +sys.path.append(BASE_DIR) #添加环境变量 from networks.unet import * def Dropout(x, p=0.5): @@ -22,7 +23,7 @@ def Dropout(x, p=0.5): return x class NestedUNet2D_2dual(nn.Module): - def __init__(self, in_chns,class_num): + def __init__(self, in_chns,class_num):#本来是params作为参数的 super(NestedUNet2D_2dual, self).__init__() # self.params = params # self.in_chns = self.params['in_chns'] diff --git a/code/test/__init__.py b/code/test/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/code/test/test_2d_forall_fast_txtver.py b/code/test/test_2d_forall_fast_txtver.py index 007a8c5..3ca4844 100644 --- a/code/test/test_2d_forall_fast_txtver.py +++ b/code/test/test_2d_forall_fast_txtver.py @@ -20,6 +20,7 @@ import pandas as pd from networks.net_factory import net_factory +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast from test.uttils import calculate_metric_percase, logInference os.environ["CUDA_VISIBLE_DEVICES"] = "0" @@ -38,9 +39,7 @@ parser.add_argument('--model', type=str, default='unet_cct', help='model_name:unet,unet_cct') parser.add_argument('--exp', type=str, - default='A_weakly_SPS_2d', help='Experiment name') -parser.add_argument('--fold', type=str, - default='stage1', help='fold name') + default='A3_weakly_PLS_soft_2d', help='Experiment name') parser.add_argument('--num_classes', type=int, default=4, help='output channel of network') parser.add_argument('--patch_size', type=list, default=[256,256], @@ -148,20 +147,10 @@ def Inference(FLAGS, test_save_path): os.makedirs(test_save_path) os.makedirs(test_save_path + "/log") - # logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', - # ) - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) # 控制台输出不带时间 - logger.addHandler(console_handler) + logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', + ) + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(FLAGS)) Inference(FLAGS, test_save_path) diff --git a/code/test/test_2d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py b/code/test/test_2d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py index fc8f4f0..55b3eec 100644 --- a/code/test/test_2d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py +++ b/code/test/test_2d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py @@ -21,7 +21,7 @@ import matplotlib.pyplot as plt from networks.net_factory import net_factory -from uttils import calculate_metric_percase, logInference, get_rgb_from_uncertainty, get_the_first_k_largest_components +from test.uttils import calculate_metric_percase, logInference, get_rgb_from_uncertainty, get_the_first_k_largest_components os.environ["CUDA_VISIBLE_DEVICES"] = "0" parser = argparse.ArgumentParser() @@ -30,7 +30,7 @@ parser.add_argument('--data_type', type=str, default='Heart', help='Data category') parser.add_argument('--data_name', type=str, - default='ACDC_example', help='Data name') + default='ACDC', help='Data name') parser.add_argument('--testData', type=str, default='trainvol.txt', help='Data text: trainvol.txt for retrain, test.txt, valid.txt') parser.add_argument('--savedir', type=str, @@ -39,16 +39,14 @@ parser.add_argument('--model', type=str, default='unet_cct', help='model_name:unet,unet_cct, etc. the name of pretrained model from stage1') parser.add_argument('--exp', type=str, - default='A_weakly_SPS_2d', help='experiment_name') -parser.add_argument('--fold', type=str, - default='stage1', help='fold name') + default='A3_weakly_PLS_soft_2d', help='experiment_name') parser.add_argument('--num_classes', type=int, default=4, help='output channel of network') -parser.add_argument('--tt_num', type=int, default=4, +parser.add_argument('--tt_num', type=int, default=3, help='test times num:3,4 for uncertainty') parser.add_argument('--threshold', type=float, default=0.1, help='uncertainty threshold') -parser.add_argument('--uncertainty_show_path', type=str, default="../../figure/MedIA_ACDC/uncertainty_thre01_250303trashs/", +parser.add_argument('--uncertainty_show_path', type=str, default="../../figure/MedIA_ACDC/uncertainty_thre01/", help='') parser.add_argument('--seed', type=int, default=2022, help='random seed') @@ -79,7 +77,7 @@ def get_rgb_from_label_ACDC(label): def convertMap(itk_map): # Convert the background and unannotated, the 5 here is actually class_num + 1 itk_map[itk_map == 0] = 5 - itk_map[itk_map == 4] = 0 + itk_map[itk_map == 4] = 0 # 4 is background itk_map[itk_map == 5] = 4 return itk_map @@ -159,9 +157,9 @@ def test_single_volume_2d_forTrainUncertainty(case_path, net, test_save_path, FL pred_uncertainty = pred * mask ## for visualization: pred_unannotated_temp = pred - pred_unannotated_temp = convertMap(pred_unannotated_temp) # 0 is unannotated, 4 is background + pred_unannotated_temp = convertMap(pred_unannotated_temp) # 0 is annotated, 4 is background pred_uncertainty_unanotated = pred_unannotated_temp * mask - pred_uncertainty_unanotated = convertMap(pred_uncertainty_unanotated) # 4 is unannotated, 0 is background + pred_uncertainty_unanotated_show = convertMap(pred_uncertainty_unanotated_show) # 4 is annotated, 0 is background pred_uncertainty_unannotated_show = get_rgb_from_label_ACDC(pred_uncertainty_unanotated) pred_uncertainty_unannotated_show.save(uncertainty_path_save + case_name + '_sclice{}_cu_unannotated.png'.format(ind)) @@ -245,8 +243,8 @@ def Inference(FLAGS, test_save_path): logging.info("test volume num:{}".format(len(image_list))) #definite net model - snapshot_path = "../../model/{}_{}/{}_{}_{}".format( - FLAGS.data_type, FLAGS.data_name, FLAGS.exp, FLAGS.model, FLAGS.fold) + snapshot_path = "../../model/{}_{}/{}_{}".format( + FLAGS.data_type, FLAGS.data_name, FLAGS.exp, FLAGS.model) net = net_factory(net_type = FLAGS.model, in_chns=1, class_num=FLAGS.num_classes) save_mode_path = os.path.join( @@ -295,20 +293,10 @@ def Inference(FLAGS, test_save_path): os.makedirs(test_save_path) os.makedirs(test_save_path + "/log") - # logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', - # ) - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) # 控制台输出不带时间 - logger.addHandler(console_handler) + logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', + ) + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(FLAGS)) Inference(FLAGS, test_save_path) diff --git a/code/test/test_3d_forall_fast_txtver.py b/code/test/test_3d_forall_fast_txtver.py index a56a052..0cd18e2 100644 --- a/code/test/test_3d_forall_fast_txtver.py +++ b/code/test/test_3d_forall_fast_txtver.py @@ -23,7 +23,8 @@ # from networks.efficientunet import UNet from networks.net_factory_3d import net_factory_3d -from uttils import calculate_metric_percase, logInference, get_the_first_k_largest_components, get_rgb_from_uncertainty +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast +from test.uttils import calculate_metric_percase, logInference, get_the_first_k_largest_components, get_rgb_from_uncertainty os.environ["CUDA_VISIBLE_DEVICES"] = "0" @@ -43,11 +44,9 @@ default='TsResult', help='TsResult for testSet, ValResult for valSet, TrResult for trainSet') parser.add_argument('--model', type=str, - default='unet_cct_dp_3D', help='select model: unet_3D, unet_cct_dropout_3D') + default='unet_cct_dropout_3D', help='select model: unet_3D, unet_cct_dropout_3D') parser.add_argument('--exp', type=str, default='W_weakly_SPS_3d', help='experiment_name') -parser.add_argument('--fold', type=str, - default='stage1', help='fold name') parser.add_argument('--num_classes', type=int, default=8, help='output channel of network') parser.add_argument('--tt_num', type=int, default=1, @@ -126,7 +125,7 @@ def pred_single_case_3d(net, net_type, image, stride_xy, stride_z, patch_size, n test_patch = torch.from_numpy(test_patch).cuda() with torch.no_grad(): if net_type == "unet_cct_dropout_3D" or net_type == "attention_unet_2dual_3d"\ - or net_type == "unetr_2dual_3d" or net_type =="unet_cct_dp_3D": + or net_type == "unetr_2dual_3d": y_main, _ = net(test_patch) else: y_main = net(test_patch) @@ -228,21 +227,10 @@ def Inference(FLAGS, test_save_path): os.makedirs(test_save_path) os.makedirs(test_save_path + "/log") - # logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', - # ) - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) # 控制台输出不带时间 - logger.addHandler(console_handler) + logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', + ) + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(FLAGS)) start_time = time.time() diff --git a/code/test/test_3d_forall_fast_txtver4BraTS.py b/code/test/test_3d_forall_fast_txtver4BraTS.py index 1b05c28..cd8de2b 100644 --- a/code/test/test_3d_forall_fast_txtver4BraTS.py +++ b/code/test/test_3d_forall_fast_txtver4BraTS.py @@ -23,6 +23,7 @@ # from networks.efficientunet import UNet from networks.net_factory_3d import net_factory_3d +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast from test.uttils import calculate_metric_percase, logInference, get_the_first_k_largest_components, get_rgb_from_uncertainty from test_3d_forall_fast_txtver import pred_single_case_3d @@ -43,11 +44,11 @@ default='TsResult', help='TsResult for testSet, ValResult for valSet, TrResult for trainSet') parser.add_argument('--model', type=str, - default='unet_cct_dp_3D', help='select mode: unet_3D, ') + default='unet_cct_dropout_3D', help='select mode: unet_3D, ') parser.add_argument('--exp', type=str, default='T3_weakly_SPS_3d', help='experiment_name') parser.add_argument('--fold', type=str, - default='stage1', help='fold name') + default='v280_ce_l001_240507', help='fold name') parser.add_argument('--num_classes', type=int, default=3, help='output channel of network') parser.add_argument('--tt_num', type=int, default=1, @@ -85,7 +86,9 @@ def test_single_volume_3d_BrsTS(case_path, net, test_save_path, FLAGS): metric_evalIndicatorsOfOrgans[i-1] = calculate_metric_percase( prediction == i, label == i, (spacing[2], spacing[0], spacing[1])) + #保存预测好的数据 imgt1_itk = sitk.GetImageFromArray(image[0].astype(np.float32)) + # logging.info("imgt1_itk size:{}".format(imgt1_itk.GetSize())) imgt1_itk.CopyInformation(org_img_itk) imgt1ce_itk = sitk.GetImageFromArray(image[1].astype(np.float32)) imgt1ce_itk.CopyInformation(org_img_itk) @@ -104,7 +107,7 @@ def test_single_volume_3d_BrsTS(case_path, net, test_save_path, FLAGS): sitk.WriteImage(imgt2_itk, test_save_path + "/" + case_name + "_img_t2.nii.gz") sitk.WriteImage(imgflair_itk, test_save_path + "/" + case_name + "_img_flair.nii.gz") sitk.WriteImage(lab_itk, test_save_path + "/" + case_name + "_gt.nii.gz") - return metric_evalIndicatorsOfOrgans + return metric_evalIndicatorsOfOrgans #长度为num_classes - 1 def Inference(FLAGS, test_save_path): with open(FLAGS.data_root_path + '/{}'.format(FLAGS.testData), 'r') as f: @@ -146,21 +149,10 @@ def Inference(FLAGS, test_save_path): os.makedirs(test_save_path) os.makedirs(test_save_path + "/log") - # logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', - # ) - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) # 控制台输出不带时间 - logger.addHandler(console_handler) + logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', + ) + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(FLAGS)) start_time = time.time() diff --git a/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py b/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py index 2c507b3..e83f35f 100644 --- a/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py +++ b/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py @@ -26,7 +26,8 @@ # from networks.efficientunet import UNet from networks.net_factory_3d import net_factory_3d -from uttils import calculate_metric_percase, logInference, get_the_first_k_largest_components, get_rgb_from_uncertainty +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast +from test.uttils import calculate_metric_percase, logInference, get_the_first_k_largest_components, get_rgb_from_uncertainty os.environ["CUDA_VISIBLE_DEVICES"] = "1" @@ -48,7 +49,7 @@ default='unet_cct_dp_3D', help='select mode: unet_cct_dp_3D, \ attention_unet_2dual_3d, unetr_2dual_3d') parser.add_argument('--exp', type=str, - default='W_weakly_PLS_soft_3d', help='experiment_name') + default='A_weakly_SPS_3d', help='experiment_name') parser.add_argument('--fold', type=str, default='stage1', help='fold name') parser.add_argument('--num_classes', type=int, default=8, @@ -329,8 +330,8 @@ def Inference(FLAGS, test_save_path): logging.info("test volume num:{}".format(len(image_list))) #definite net model - snapshot_path = "../../model/{}_{}/{}_{}_{}".format( - FLAGS.data_type, FLAGS.data_name, FLAGS.exp, FLAGS.model, FLAGS.fold) + snapshot_path = "../../model/{}_{}/{}_{}".format( + FLAGS.data_type, FLAGS.data_name, FLAGS.exp, FLAGS.model) net = net_factory_3d(net_type = FLAGS.model, in_chns=1, class_num=FLAGS.num_classes) save_mode_path = os.path.join( @@ -378,22 +379,10 @@ def Inference(FLAGS, test_save_path): os.makedirs(test_save_path) os.makedirs(test_save_path + "/log") - # logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', - # ) - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) # 控制台输出不带时间 - logger.addHandler(console_handler) - + logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', + ) + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(FLAGS)) start_time = time.time() Inference(FLAGS, test_save_path) diff --git a/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean4BraTS2020.py b/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean4BraTS2020.py index 1d07077..98485a6 100644 --- a/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean4BraTS2020.py +++ b/code/test/test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean4BraTS2020.py @@ -24,6 +24,9 @@ import random from networks.net_factory_3d import net_factory_3d +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast +from networks.net_factory_3d import net_factory_3d +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast from test.uttils import calculate_metric_percase, logInference, get_the_first_k_largest_components, get_rgb_from_uncertainty from test_3d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean import pred_single_case_3d_forTrainUncertainty os.environ["CUDA_VISIBLE_DEVICES"] = "0" @@ -43,7 +46,7 @@ default='TrResult', help='TsResult for testSet, ValResult for valSet, TrResult for trainSet') parser.add_argument('--model', type=str, - default='unet_cct_dp_3D', help='select mode: unet_cct_dp_3D, \ + default='unet_cct_dropout_3D', help='select mode: unet_cct_dp_3D, \ attention_unet_2dual_3d, unetr_2dual_3d ') parser.add_argument('--exp', type=str, default='T_weakly_SPS_3d', help='experiment_name') @@ -74,6 +77,18 @@ def weight_with_uncertainty_class_np(preds, C):#pred:numpy, [n, c, d, h, w] uncertainty = -1.0 * np.sum(preds * np.log(preds + 1e-16), axis=1, keepdims=True)/ np.log(C) return uncertainty +def calculate_metric_percase(pred, gt, spacing):#计算指标矩阵 + pred[pred > 0] = 1 + gt[gt > 0] = 1 + if pred.sum() > 0 and gt.sum() > 0: + dice = metric.binary.dc(pred, gt) + asd = asd_fast(pred, gt, voxelspacing=spacing) + hd95 = hd95_fast(pred, gt, voxelspacing=spacing) + # asd = metric.binary.asd(pred, gt, voxelspacing=spacing) + # hd95 = metric.binary.hd95(pred, gt, voxelspacing=spacing) + return np.array([dice, asd, hd95]) + else: + return np.array([0,0,0]) def test_single_volume_3d_braTS(case_path, net, test_save_path, FLAGS): case_name = case_path.split("/")[-1].replace(".h5","") @@ -178,7 +193,7 @@ def Inference(FLAGS, test_save_path): logging.info("init weight from {}".format(save_mode_path)) net.eval() - metric_onTest_all_list1 = [] + metric_onTest_all_list1 = [] #保存所有数据的列表 metric_onTest_all_list2 = [] metric_onTest_all_list3 = [] metric_onTest_all_list4 = [] @@ -217,20 +232,10 @@ def Inference(FLAGS, test_save_path): os.makedirs(test_save_path) os.makedirs(test_save_path + "/log") - # logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', - # ) - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) # 控制台输出不带时间 - logger.addHandler(console_handler) + logging.basicConfig(filename=test_save_path+"/log/test"+str(FLAGS.tt_num)+"_info.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S', + ) + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(FLAGS)) start_time = time.time() Inference(FLAGS, test_save_path) diff --git a/code/test/uttils.py b/code/test/uttils.py index fa590c3..c2d29ea 100644 --- a/code/test/uttils.py +++ b/code/test/uttils.py @@ -3,28 +3,28 @@ from scipy import ndimage import logging from PIL import Image -# from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast +from utils.distance_metrics_fast import hd95_fast, asd_fast, assd_fast def calculate_metric_percase(pred, gt, spacing): pred[pred > 0] = 1 gt[gt > 0] = 1 if pred.sum() > 0 and gt.sum() > 0: dice = metric.binary.dc(pred, gt) - asd = metric.binary.asd(pred, gt, voxelspacing=spacing) - hd95 = metric.binary.hd95(pred, gt, voxelspacing=spacing) - # asd = asd_fast(pred, gt, voxelspacing=spacing) - # hd95 = hd95_fast(pred, gt, voxelspacing=spacing) + # asd = metric.binary.asd(pred, gt, voxelspacing=spacing) + # hd95 = metric.binary.hd95(pred, gt, voxelspacing=spacing) + asd = asd_fast(pred, gt, voxelspacing=spacing) + hd95 = hd95_fast(pred, gt, voxelspacing=spacing) return np.array([dice, asd, hd95]) else: return np.array([0,0,0]) def logInference(metric_onTest_all_list): metric_onTest_all_list = np.asarray(metric_onTest_all_list) - avg_metric_on_list = np.mean(metric_onTest_all_list,axis=0) - logging.info("avg metric of each organ[dsc,asd,hd95]:{}".format(avg_metric_on_list)) + avg_metric_on_list = np.mean(metric_onTest_all_list,axis=0)#计算了30个数据的各器官各标签均值，得到16 * 3. + logging.info("avg metric of each organ[dsc,asd,hd95]:".format(avg_metric_on_list)) metricOf3 = np.mean(avg_metric_on_list,axis=0) logging.info("mean metric of all[dice,asd,hd95]:{}".format(metricOf3)) - std = np.std(metric_onTest_all_list,axis = 0) + std = np.std(metric_onTest_all_list,axis = 0)#变成16*3 logging.info("std of each organ[dice,asd,hd95]:{}".format(std)) std_1= np.mean(std,axis=0) logging.info("std of all[dsc,asd,hd95]:{}\n\n".format(std_1)) @@ -50,7 +50,7 @@ def get_the_first_k_largest_components(image, k = 1): #image is binary map sizes_sorted = sorted(list(sizes)) output = np.zeros_like(image, np.uint8) for i in range(k): - max_i_label = np.where(sizes == sizes_sorted[-1-i])[0] + 1 + max_i_label = np.where(sizes == sizes_sorted[-1-i])[0] + 1 #为1 output = output + np.asarray(labeled_array == max_i_label, np.uint8) return output diff --git a/code/train/A_train_weaklySup_PLS_2d_hard.py b/code/train/A_train_weaklySup_PLS_2d_hard.py index f266658..7506e57 100644 --- a/code/train/A_train_weaklySup_PLS_2d_hard.py +++ b/code/train/A_train_weaklySup_PLS_2d_hard.py @@ -257,20 +257,9 @@ def worker_init_fn(worker_id): __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) train(args, snapshot_path) time_s = time.time()-start_time diff --git a/code/train/A_train_weaklySup_SPS_2d_soft.py b/code/train/A_train_weaklySup_SPS_2d_soft.py index dedb98d..9105165 100644 --- a/code/train/A_train_weaklySup_SPS_2d_soft.py +++ b/code/train/A_train_weaklySup_SPS_2d_soft.py @@ -254,20 +254,9 @@ def worker_init_fn(worker_id): __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/train/A_train_weaklySup_SPS_2d_soft_retrainUncertainty.py b/code/train/A_train_weaklySup_SPS_2d_soft_retrainUncertainty.py index af34b6c..017dcf6 100644 --- a/code/train/A_train_weaklySup_SPS_2d_soft_retrainUncertainty.py +++ b/code/train/A_train_weaklySup_SPS_2d_soft_retrainUncertainty.py @@ -256,19 +256,9 @@ def worker_init_fn(worker_id): __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/train/T_train_weaklySup_SPS_3d_soft.py b/code/train/T_train_weaklySup_SPS_3d_soft.py index 0de483f..63144b4 100644 --- a/code/train/T_train_weaklySup_SPS_3d_soft.py +++ b/code/train/T_train_weaklySup_SPS_3d_soft.py @@ -272,22 +272,11 @@ def worker_init_fn(worker_id): run_id = datetime.now().strftime("%Y%m%d-%H%M") shutil.copyfile( __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) - ) - - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + )#将当前运行python的版本给保留下来 + + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/train/T_train_weaklySup_SPS_3d_soft_retrainUncertainty.py b/code/train/T_train_weaklySup_SPS_3d_soft_retrainUncertainty.py index 3c5cb29..151122a 100644 --- a/code/train/T_train_weaklySup_SPS_3d_soft_retrainUncertainty.py +++ b/code/train/T_train_weaklySup_SPS_3d_soft_retrainUncertainty.py @@ -51,7 +51,7 @@ parser.add_argument('--fold', type=str, default='stage2', help='train fold name') parser.add_argument('--sup_type', type=str, - default='pseudoLab', help='supervision type, select mode: label, scribble, pseudoLab') + default='pseudoLab', help='supervision type, select mode: label, scribble') parser.add_argument('--num_classes', type=int, default=3, help='output channel of network') parser.add_argument('--max_iterations', type=int, @@ -285,20 +285,9 @@ def worker_init_fn(worker_id): __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/train/W_train_weaklySup_PLS_3d_hard.py b/code/train/W_train_weaklySup_PLS_3d_hard.py index b11d0b0..6c2fbb4 100644 --- a/code/train/W_train_weaklySup_PLS_3d_hard.py +++ b/code/train/W_train_weaklySup_PLS_3d_hard.py @@ -282,20 +282,9 @@ def worker_init_fn(worker_id): ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/train/W_train_weaklySup_SPS_3d_soft.py b/code/train/W_train_weaklySup_SPS_3d_soft.py index de8da3f..7e8cb84 100644 --- a/code/train/W_train_weaklySup_SPS_3d_soft.py +++ b/code/train/W_train_weaklySup_SPS_3d_soft.py @@ -30,7 +30,7 @@ from utils import losses, metrics, ramps from val_3D import test_all_case_3D -os.environ["CUDA_VISIBLE_DEVICES"] = "0" +os.environ["CUDA_VISIBLE_DEVICES"] = "3" parser = argparse.ArgumentParser() parser.add_argument('--data_root_path', type=str, default='/mnt/data/HM/Datasets/Abdomen_word/WORD-V0.1.0-Admin_cropWL_for3D', @@ -49,7 +49,7 @@ default='unet_cct_dp_3D', help='select mode: unet_cct_dp_3D, \ attention_unet_2dual_3d, unetr_2dual_3d') parser.add_argument('--exp', type=str, - default='W_weakly_SPS_3d', help='experiment_name') + default='A3_weakly_PLS_soft_3d', help='experiment_name') parser.add_argument('--fold', type=str, default='stage1', help='train fold name') parser.add_argument('--sup_type', type=str, @@ -274,21 +274,9 @@ def worker_init_fn(worker_id): __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) - + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/train/W_train_weaklySup_SPS_3d_soft_retrainUncertainty.py b/code/train/W_train_weaklySup_SPS_3d_soft_retrainUncertainty.py index c045922..c8cdf3a 100644 --- a/code/train/W_train_weaklySup_SPS_3d_soft_retrainUncertainty.py +++ b/code/train/W_train_weaklySup_SPS_3d_soft_retrainUncertainty.py @@ -30,7 +30,7 @@ from utils import losses, metrics, ramps from val_3D import test_all_case_3D -os.environ["CUDA_VISIBLE_DEVICES"] = "0" +os.environ["CUDA_VISIBLE_DEVICES"] = "1" parser = argparse.ArgumentParser() # experiment base setting parser.add_argument('--data_root_path', type=str, @@ -49,7 +49,7 @@ default='unet_cct_dp_3D', help='select mode: unet_cct_dp_3D, \ attention_unet_2dual_3d, unetr_2dual_3d') parser.add_argument('--exp', type=str, - default='W_weakly_PLS_soft_3d', help='experiment_name') + default='A3_weakly_PLS_soft_3d', help='experiment_name') parser.add_argument('--fold', type=str, default='stage2', help='train fold name') parser.add_argument('--sup_type', type=str, @@ -86,8 +86,8 @@ def train(args, snapshot_path): model_parameter = sum(p.numel() for p in model.parameters()) logging.info("model_parameter:{}M".format(round(model_parameter / (1024*1024),2))) - snapshot_path_ori = "../../model/{}_{}/{}_{}_{}".format( - args.data_type, args.data_name, args.exp, args.model, 'stage1') + snapshot_path_ori = "../../model/{}_{}/{}_{}".format( + args.data_type, args.data_name, args.exp, args.model) save_mode_path_ori = os.path.join(snapshot_path_ori, '{}_best_model.pth'.format(args.model)) model.load_state_dict(torch.load(save_mode_path_ori)) @@ -277,20 +277,9 @@ def worker_init_fn(worker_id): __file__, os.path.join(snapshot_path, run_id + "_" + os.path.basename(__file__)) ) - # logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, - # format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') - # logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - - logger = logging.getLogger() - logger.handlers.clear() - file_handler = logging.FileHandler(snapshot_path+"/train_log.txt") - file_handler.setLevel(logging.INFO) - file_handler.setFormatter(logging.Formatter('[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S')) - logger.addHandler(file_handler) - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(logging.INFO) - console_handler.setFormatter(logging.Formatter('%(message)s')) - logger.addHandler(console_handler) + logging.basicConfig(filename=snapshot_path+"/train_log.txt", level=logging.INFO, + format='[%(asctime)s.%(msecs)03d] %(message)s', datefmt='%H:%M:%S') + logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) logging.info(str(args)) start_time = time.time() train(args, snapshot_path) diff --git a/code/utils/JSD_loss.py b/code/utils/JSD_loss.py new file mode 100644 index 0000000..0981136 --- /dev/null +++ b/code/utils/JSD_loss.py @@ -0,0 +1,418 @@ +import torch +import torchvision +import torch.nn as nn +import torch.nn.functional as F +from torch.nn.modules.loss import CrossEntropyLoss +import numpy as np + + +def calc_jsd_multiscale(weight, labels1_a, pred1, pred2, pred3, threshold=0.8, Mask_label255_sign='no',num_classes=17): + + Mask_label255 = (labels1_a < 2).float() # do not compute the area that is irrelavant[无关紧要的] (dataaug) b,h,w + weight_softmax = F.softmax(weight, dim=0) + + criterion = CrossEntropyLoss(ignore_index=num_classes, reduction='none') + + labels1_a = labels1_a.squeeze(axis=1).long() + loss1 = criterion(pred1 * weight_softmax[0], labels1_a) # * weight_softmax[0] + loss2 = criterion(pred2 * weight_softmax[1], labels1_a) # * weight_softmax[1] + loss3 = criterion(pred3 * weight_softmax[2], labels1_a) # * weight_softmax[2] + + loss = (loss1 + loss2 + loss3) #softmx函数是指数归一化函数。 + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + + weighted_probs = [weight_softmax[i] * prob for i, prob in enumerate(probs)] + + mixture_label = (torch.stack(weighted_probs)).sum(axis=0) #按照权重将三个pred叠起来产生新的pred + #mixture_label = torch.clamp(mixture_label, 1e-7, 1) # h,c,h,w + mixture_label = torch.clamp(mixture_label, 1e-3, 1-1e-3) # h,c,h,w + + # add this code block for early torch version where torch.amax is not available + if torch.__version__=="1.5.0" or torch.__version__=="1.6.0": + _, max_probs = torch.max(mixture_label*Mask_label255.unsqueeze(1), dim=-3, keepdim=True) + _, max_probs = torch.max(max_probs, dim=-2, keepdim=True) + _, max_probs = torch.max(max_probs, dim=-1, keepdim=True) + else: + max_probs = torch.amax(mixture_label*Mask_label255.unsqueeze(1), dim=(-3, -2, -1), keepdim=True) + mask = max_probs.ge(threshold).float() + + + logp_mixture = mixture_label.log() + + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none') * mask, dim=1) for prob in probs] + if Mask_label255_sign == 'yes': + consistency = sum(log_probs)*Mask_label255 + else: + consistency = sum(log_probs) + + return torch.mean(loss), torch.mean(consistency), consistency, mixture_label + +def calc_jsd_multiscale_no_weight_3d(label, pred1, pred2, pred3, threshold=0.8,num_classes = 17): + ce_loss = CrossEntropyLoss(ignore_index=num_classes) + loss_ce1 = ce_loss(pred1, label[:].long()) + loss_ce2 = ce_loss(pred2, label[:].long()) + loss_ce3 = ce_loss(pred3, label[:].long()) + loss_ce = (loss_ce1 + loss_ce2 + loss_ce3) + # print("loss_ce:{}".format(loss_ce)) # loss_ce是数 + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + # print("probs_shape_len:{}".format(len(probs))) # list 3 item + # print("probs_shape:{}".format(probs[0].shape)) # probs_shape:torch.Size([1, 8, 96, 96, 96]) + consistency = 0.0 + #计算kl散度 + consistency += F.kl_div(probs[1].log(), probs[0], reduction='none') + consistency += F.kl_div(probs[2].log(), probs[0], reduction='none') + consistency += F.kl_div(probs[0].log(), probs[1], reduction='none') + consistency += F.kl_div(probs[2].log(), probs[1], reduction='none') + consistency += F.kl_div(probs[0].log(), probs[2], reduction='none') + consistency += F.kl_div(probs[1].log(), probs[2], reduction='none') + # print("consistency_shape_before:{}".format(consistency.shape)) #consistency_shape_before:torch.Size([1, 8, 96, 96, 96]) + consistency = torch.sum(consistency, dim=1) + # print("consistency_shape_after:{}".format(consistency.shape)) # consistency_shape_after:torch.Size([1, 96, 96, 96]) + + # mixture_label = (torch.stack(probs)).sum(axis=0) #按照batch_size的维度堆起来 + # # print("mixture_label_shape_before:{}".format( mixture_label.shape)) + # # #mixture_label_shape_before:torch.Size([1, 8, 96, 96, 96]) + # mixture_label = torch.clamp(mixture_label, 1e-3, 1-1e-3) # b,c,d,h,w + # # print("mixture_label_shape_after:{}".format( mixture_label.shape)) + # # # mixture_label_shape_after:torch.Size([1, 8, 96, 96, 96]) + # max_probs = torch.amax(mixture_label.unsqueeze(1), dim=(-3, -2, -1), keepdim=True) + # # print("max_probs_shape:{}".format( max_probs.shape)) + # # # max_probs_shape:torch.Size([1, 1, 8, 1, 1, 1]) + # mask = max_probs.ge(threshold).float() + # # print("mask_shape:{}".format( mask.shape)) + # # # mask_shape:torch.Size([1, 1, 8, 1, 1, 1]) + # #torch.ge(a,b)比较a，b的大小，a为张量，b可以为和a相同形状的张量，也可以为一个常数。大于等于相应位置返回1，小于返回0. + # logp_mixture = mixture_label.log() + # log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none') * mask, dim=1) for prob in probs] + # here can replace [dim=1] into [keepdim=True] and mask no longer use 'unaqueeze' to increase a dim + # consistency = sum(log_probs) + # # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + # #consistency_shape_after_mixture:torch.Size([1, 8, 96, 96, 96]) + # # print(consistency) + + loss = (torch.mean(loss_ce) + torch.mean(consistency))/3 + return loss + +def calc_jsd_multiscale_no_weight_sum_3d(label, pred1, pred2, pred3, threshold=0.8, num_classes = 8): + ce_loss = CrossEntropyLoss(ignore_index=num_classes) + loss_ce1 = ce_loss(pred1, label[:].long()) + loss_ce2 = ce_loss(pred2, label[:].long()) + loss_ce3 = ce_loss(pred3, label[:].long()) + loss_ce = (loss_ce1 + loss_ce2 + loss_ce3) + # print("loss_ce:{}".format(loss_ce)) # loss_ce是数 + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + # print("probs_shape_len:{}".format(len(probs))) # list 3 item + # print("prob_shape:{}".format(probs[0].shape)) # prob_shape:torch.Size([1, 8, 96, 96, 96]) + # consistency = 0.0 + # #计算kl散度 + # consistency += F.kl_div(probs[1].log(), probs[0], reduction='none') + # consistency += F.kl_div(probs[2].log(), probs[0], reduction='none') + # consistency += F.kl_div(probs[0].log(), probs[1], reduction='none') + # consistency += F.kl_div(probs[2].log(), probs[1], reduction='none') + # consistency += F.kl_div(probs[0].log(), probs[2], reduction='none') + # consistency += F.kl_div(probs[1].log(), probs[2], reduction='none') + # # print("consistency_shape_before:{}".format(consistency.shape)) #consistency_shape_before:torch.Size([1, 8, 96, 96, 96]) + # consistency = torch.sum(consistency, dim=1) + # print("consistency_shape_after:{}".format(consistency.shape)) # consistency_shape_after:torch.Size([1, 96, 96, 96]) + + mixture_label = (torch.stack(probs)).sum(axis=0) #按照batch_size的维度堆起来 + # print("probs:{}".format(probs[0])) + # print("\n \n \n") + # print("mixture_label:{}".format(mixture_label)) + # print("mixture_label_shape_before:{}".format( mixture_label.shape)) + # #mixture_label_shape_before:torch.Size([1, 8, 96, 96, 96]) + mixture_label = torch.clamp(mixture_label, 1e-3, 1-1e-3) # b,c,d,h,w + # print("mixture_label_shape_after:{}".format( mixture_label.shape)) + # # mixture_label_shape_after:torch.Size([1, 8, 96, 96, 96]) + max_probs = torch.amax(mixture_label.unsqueeze(1), dim=(-3, -2, -1), keepdim=True)# torch.amax取出最大的数值 + # print("max_probs:{}".format(max_probs)) + # print("max_probs_shape:{}".format( max_probs.shape)) + # # max_probs_shape:torch.Size([1, 1, 8, 1, 1, 1]) + mask = max_probs.ge(threshold).float() + # print("mask_shape:{}".format( mask.shape)) + # # mask_shape:torch.Size([1, 1, 8, 1, 1, 1]) + #torch.ge(a,b)比较a，b的大小，a为张量，b可以为和a相同形状的张量，也可以为一个常数。大于等于相应位置返回1，小于返回0. + logp_mixture = mixture_label.log() + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none') * mask, dim=1) for prob in probs] + # print("log_prob shape:{}".format(log_probs[0].shape)) ##log_prob shape:torch.Size([2, 8, 96, 96, 96]) + # aa= [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("aa shape:{}".format(aa[0].shape)) # aa shape:torch.Size([2, 96, 96, 96]) + + consistency = sum(log_probs) + # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + #consistency_shape_after_mixture:torch.Size([1, 8, 96, 96, 96]) + # print(consistency) + consistency = torch.sum(consistency, dim=1)#这一步可能是FJ加的 + + loss = (torch.mean(loss_ce) + torch.mean(consistency))/3#这一步可能是FJ加的 + return loss + +def calc_jsd_multiscale_no_weight_mean_3d(label, pred1, pred2, pred3, threshold=0.5, num_classes = 8): + ce_loss = CrossEntropyLoss(ignore_index=num_classes) + loss_ce1 = ce_loss(pred1, label[:].long()) + loss_ce2 = ce_loss(pred2, label[:].long()) + loss_ce3 = ce_loss(pred3, label[:].long()) + loss_ce = (loss_ce1 + loss_ce2 + loss_ce3) + # print("loss_ce:{}".format(loss_ce)) # loss_ce是数 + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + # print("probs_shape_len:{}".format(len(probs))) # list 3 item + # print("prob_shape:{}".format(probs[0].shape)) # prob_shape:torch.Size([1, 8, 96, 96, 96]) + # consistency = 0.0 + # #计算kl散度 + # consistency += F.kl_div(probs[1].log(), probs[0], reduction='none') + # consistency += F.kl_div(probs[2].log(), probs[0], reduction='none') + # consistency += F.kl_div(probs[0].log(), probs[1], reduction='none') + # consistency += F.kl_div(probs[2].log(), probs[1], reduction='none') + # consistency += F.kl_div(probs[0].log(), probs[2], reduction='none') + # consistency += F.kl_div(probs[1].log(), probs[2], reduction='none') + # # print("consistency_shape_before:{}".format(consistency.shape)) #consistency_shape_before:torch.Size([1, 8, 96, 96, 96]) + # consistency = torch.sum(consistency, dim=1) + # print("consistency_shape_after:{}".format(consistency.shape)) # consistency_shape_after:torch.Size([1, 96, 96, 96]) + + mixture_label = (torch.stack(probs)).mean(axis=0) #按照batch_size的维度堆起来 + # print("probs:{}".format(probs[0])) + # print("\n \n \n") + # print("mixture_label:{}".format(mixture_label)) + # print("mixture_label_shape_before:{}".format( mixture_label.shape)) + # #mixture_label_shape_before:torch.Size([1, 8, 96, 96, 96]) + mixture_label = torch.clamp(mixture_label, 1e-3, 1-1e-3) # b,c,d,h,w + # print("mixture_label_shape_after:{}".format( mixture_label.shape)) + # # mixture_label_shape_after:torch.Size([1, 8, 96, 96, 96]) + max_probs = torch.amax(mixture_label.unsqueeze(1), dim=(-3, -2, -1), keepdim=True)# torch.amax取出最大的数值 + # print("max_probs:{}".format(max_probs)) + # print("max_probs_shape:{}".format(max_probs.shape)) + # # max_probs_shape:torch.Size([1, 1, 8, 1, 1, 1]) + mask = max_probs.ge(threshold).float() + # print("mask_shape:{}".format( mask.shape)) + # # mask_shape:torch.Size([1, 1, 8, 1, 1, 1]) + #torch.ge(a,b)比较a，b的大小，a为张量，b可以为和a相同形状的张量，也可以为一个常数。大于等于相应位置返回1，小于返回0. + logp_mixture = mixture_label.log() + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none') * mask, dim=1) for prob in probs] + # print("log_prob shape:{}".format(log_probs[0].shape)) ##log_prob shape:torch.Size([2, 8, 96, 96, 96]) + # aa= [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("aa shape:{}".format(aa[0].shape)) # aa shape:torch.Size([2, 96, 96, 96]) + + consistency = sum(log_probs) + # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + #consistency_shape_after_mixture:torch.Size([1, 8, 96, 96, 96]) + # print(consistency) + consistency = torch.sum(consistency, dim=1) + + loss = (torch.mean(loss_ce) + torch.mean(consistency))/3 + + return loss + +def calc_jsd_multiscale_no_weight_mean_HM_3d(label, pred1, pred2, pred3, threshold=0.5, num_classes = 8): + ce_loss = CrossEntropyLoss(ignore_index=num_classes) + loss_ce1 = ce_loss(pred1, label[:].long()) + loss_ce2 = ce_loss(pred2, label[:].long()) + loss_ce3 = ce_loss(pred3, label[:].long()) + loss_ce = (loss_ce1 + loss_ce2 + loss_ce3) + # print("loss_ce_shape:{}".format(loss_ce.shape)) + # loss_ce_shape:torch.Size([]) + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + + mixture_label = (torch.stack(probs)).mean(axis=0) #按照batch_size的维度堆起来 + logp_mixture = mixture_label.log() + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("log_prob shape:{}".format(log_probs[0].shape)) ##log_prob shape:torch.Size([2, 8, 96, 96, 96]) + # aa= [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("aa shape:{}".format(aa[0].shape)) # aa shape:torch.Size([2, 96, 96, 96]) + + consistency = sum(log_probs)#按照list的维度相加 + # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + # consistency_shape_after_mixture:torch.Size([1, 96, 96, 96]) # batch_size x D x H x W + + loss = (torch.mean(loss_ce) + torch.mean(consistency))/3# torch.mean不设置参数的时候，是返回所有元素的平均值 + # print("loss_type:{}".format(type(loss)))#loss_type: + return loss + +def calc_jsd_multiscale_no_weight_2d(label, pred1, pred2, pred3, threshold=0.8,num_classes = 17):#2d和3d代码是一样的 + ce_loss = CrossEntropyLoss(ignore_index=num_classes) + loss_ce1 = ce_loss(pred1, label[:].long()) + loss_ce2 = ce_loss(pred2, label[:].long()) + loss_ce3 = ce_loss(pred3, label[:].long()) + loss_ce = (loss_ce1 + loss_ce2 + loss_ce3) + # print("loss_ce:{}".format(loss_ce)) # loss_ce是数 + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + # print("probs_shape_len:{}".format(len(probs))) # list 3 item + # print("probs_shape:{}".format(probs[0].shape)) # probs_shape:torch.Size([12, 8, 256, 256]) + consistency = 0.0 + #计算kl散度 + consistency += F.kl_div(probs[1].log(), probs[0], reduction='none') + consistency += F.kl_div(probs[2].log(), probs[0], reduction='none') + consistency += F.kl_div(probs[0].log(), probs[1], reduction='none') + consistency += F.kl_div(probs[2].log(), probs[1], reduction='none') + consistency += F.kl_div(probs[0].log(), probs[2], reduction='none') + consistency += F.kl_div(probs[1].log(), probs[2], reduction='none') + # print("consistency_shape_before:{}".format(consistency.shape)) #consistency_shape_before:torch.Size([12, 8, 256, 256]) + consistency = torch.sum(consistency, dim=1) + # print("consistency_shape_after:{}".format(consistency.shape)) # consistency_shape_after:torch.Size([12, 256, 256]) + + # mixture_label = (torch.stack(probs)).sum(axis=0) #按照batch_size的维度堆起来 + # # print("mixture_label_shape_before:{}".format( mixture_label.shape)) + # # #mixture_label_shape_before:torch.Size([12, 8, 256, 256]) + # mixture_label = torch.clamp(mixture_label, 1e-3, 1-1e-3) # b,c,d,h,w + # # print("mixture_label_shape_after:{}".format( mixture_label.shape)) + # # # mixture_label_shape_after:torch.Size([12, 8, 256, 256]) + # max_probs = torch.amax(mixture_label.unsqueeze(1), dim=(-3, -2, -1), keepdim=True) + # # print("max_probs_shape:{}".format( max_probs.shape)) + # # # max_probs_shape:torch.Size([12, 1, 1, 1, 1]) + # mask = max_probs.ge(threshold).float() + # # print("mask_shape:{}".format( mask.shape)) + # # # mask_shape:torch.Size([12, 1, 1, 1, 1]) + # #torch.ge(a,b)比较a，b的大小，a为张量，b可以为和a相同形状的张量，也可以为一个常数。大于等于相应位置返回1，小于返回0. + # logp_mixture = mixture_label.log() + # log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none') * mask, dim=1) for prob in probs] + # # print("F.kl_div(logp_mixture, prob, reduction='none') * mask:{}".format(a.shape)) + # # F.kl_div(logp_mixture, prob, reduction='none') * mask:torch.Size([12, 12, 8, 256, 256]) + # consistency = sum(log_probs) + # # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + # # consistency_shape_after_mixture:torch.Size([12, 8, 256, 256]) + # # print(consistency) + + loss = (torch.mean(loss_ce) + torch.mean(consistency))/3 + return loss + +def weight_with_EM(p, C=8): + y1 = -1*torch.sum(p*torch.log(p+1e-6), dim=1, keepdim=True) / torch.tensor(np.log(C)).cuda() + y1 = torch.exp(-y1) #忘记了 + return y1 +def calc_meanKL_3d(pred1, pred2, pred3): #单单的KL_loss罢了，和calc_jsd_multiscale_no_weight_mean_HM_3d一致 + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + mixture_label = (torch.stack(probs)).mean(axis=0) #按照batch_size的维度堆起来并取平均，得到的依然是feature的维度 + + logp_mixture = mixture_label.log() + # print("mixture_label:{}".format(mixture_label)) #都是0~0.2的 + # print("mixture_label_shape:{}".format(mixture_label.shape)) #([1, 8, 80, 96, 96]) + + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("log_prob shape:{}".format(log_probs[0].shape)) ##log_prob shape:torch.Size([2, 8, 96, 96, 96]) + # aa= [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("aa shape:{}".format(aa[0].shape)) # aa shape:torch.Size([2, 96, 96, 96]) + consistency = sum(log_probs)#进行list维度的相加，这里list有三个元素 + # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + # consistency_shape_after_mixture:torch.Size([1, 96, 96, 96]) # batch_size x D x H x W + + loss = torch.mean(consistency)/3 + #这里的3指的是除以list的长度,torch.mean是按照矩阵内所有元素的平均直接得到一个数字 + return loss + +def calc_meanWKL_3d(pred1, pred2, pred3): #没有数学依据但效果最好 + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + mixture_label = (torch.stack(probs)).mean(axis=0) #按照batch_size的维度堆起来并取平均，得到的依然是feature的维度 + + weight = weight_with_EM(mixture_label) + # print("weight_shape:{}".format(weight.shape))#weight_shape:torch.Size([1, 80, 96, 96]) + # print("weight:{}".format(weight)) #都是0~1的 + + weight_mixture_label = mixture_label * weight + # print("weight_mixture_label:{}".format(weight_mixture_label.shape)) #weight_mixture_label:torch.Size([1, 8, 80, 96, 96]) + + logp_mixture = weight_mixture_label.log() + # print("mixture_label:{}".format(mixture_label)) #都是0~0.2的 + # print("mixture_label_shape:{}".format(mixture_label.shape)) #([1, 8, 80, 96, 96]) + + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("log_prob shape:{}".format(log_probs[0].shape)) ##log_prob shape:torch.Size([2, 8, 96, 96, 96]) + # aa= [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("aa shape:{}".format(aa[0].shape)) # aa shape:torch.Size([2, 96, 96, 96]) + consistency = sum(log_probs)#进行list维度的相加，这里list有三个元素 + # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + # consistency_shape_after_mixture:torch.Size([1, 96, 96, 96]) # batch_size x D x H x W + + loss = torch.mean(consistency)/3 + #这里的3指的是除以list的长度,torch.mean是按照矩阵内所有元素的平均直接得到一个数字 + return loss + +def calc_meanWKL_3d1(pred1, pred2, pred3): #weight loss + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + mixture_label = (torch.stack(probs)).mean(axis=0) #按照batch_size的维度堆起来并取平均，得到的依然是feature的维度 + # print("mixture_label_shape:{}".format(mixture_label.shape)) #mixture_label_shape:torch.Size([1, 8, 80, 96, 96]) + + weight = weight_with_EM(mixture_label) + # print("weight_shape:{}".format(weight.shape))#weight_shape:torch.Size([1, 80, 96, 96]) + # print("weight:{}".format(weight)) #都是0~1的 + + # weight_mixture_label = mixture_label * weight + # print("weight_mixture_label:{}".format(weight_mixture_label.shape)) #weight_mixture_label:torch.Size([1, 8, 80, 96, 96]) + + logp_mixture = mixture_label.log() + # print("mixture_label:{}".format(mixture_label)) #都是0~0.2的 + # print("mixture_label_shape:{}".format(mixture_label.shape)) #([1, 8, 80, 96, 96]) + + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none')*weight, dim=1) for prob in probs] + # print("log_prob shape:{}".format(log_probs[0].shape)) ##log_prob shape:torch.Size([2, 8, 96, 96, 96]) + # aa= [torch.sum(F.kl_div(logp_mixture, prob, reduction='none'), dim=1) for prob in probs] + # print("aa shape:{}".format(aa[0].shape)) # aa shape:torch.Size([2, 96, 96, 96]) + consistency = sum(log_probs)#进行list维度的相加，这里list有三个元素 + # print("consistency_shape_after_mixture:{}".format(consistency.shape)) + # consistency_shape_after_mixture:torch.Size([1, 96, 96, 96]) # batch_size x D x H x W + + loss = torch.mean(consistency)/3 + #这里的3指的是除以list的长度,torch.mean是按照矩阵内所有元素的平均直接得到一个数字 + return loss + +def calc_meanKL_Mask_3d(pred1, pred2, pred3, threshold=0.5): + + probs = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + + mixture_label = (torch.stack(probs)).mean(axis=0) #按照batch_size的维度堆起来 + + mixture_label = torch.clamp(mixture_label, 1e-3, 1-1e-3) # b,c,d,h,w + + max_probs = torch.amax(mixture_label.unsqueeze(1), dim=(-3, -2, -1), keepdim=True)# torch.amax取出最大的数值 + + mask = max_probs.ge(threshold).float() + + logp_mixture = mixture_label.log() + log_probs = [torch.sum(F.kl_div(logp_mixture, prob, reduction='none') * mask, dim=1) for prob in probs] + consistency = sum(log_probs) + consistency = torch.sum(consistency, dim=1) + loss = torch.mean(consistency)/3 + + return loss + +def KLLoss_3d(Q,P):#Q:mix_label_afterSoftmax, P:single_label_afterSoftmax + log_Q = Q.log() + log_probs = torch.sum(F.kl_div(log_Q, P, reduction='none'),dim=1) + return log_probs + +def interactive_KLLoss_3d(pred1, pred2, pred3): + pred_softmax = [F.softmax(logits, dim=1) for i, logits in enumerate([pred1, pred2, pred3])] + mixture12 = (torch.stack([pred_softmax[0],pred_softmax[1]])).mean(axis=0) + # print("mixture12:{}, shape:{},type:{}".format(mixture12, mixture12.shape, type(mixture12))) + # a = (pred_softmax[0] + pred_softmax[1])/2.0 + # print("a:{}, shape:{}, type:{}".format(a, a.shape, type(a))) + # print("\n******\n") #验证过，a和mixture12是一样的。 + mixture13 = (torch.stack([pred_softmax[0],pred_softmax[2]])).mean(axis=0) + mixture23 = (torch.stack([pred_softmax[1],pred_softmax[2]])).mean(axis=0) + + KL12 = KLLoss_3d(mixture12, pred_softmax[2]) + KL13 = KLLoss_3d(mixture13, pred_softmax[1]) + KL23 = KLLoss_3d(mixture23, pred_softmax[0]) + + # consistency = torch.mean((KL12+KL13+KL23))/3 + # print("consistenct_before:{}".format(consistency)) + + consistency = torch.mean((torch.stack([KL12,KL13,KL23])).mean(axis=0)) + # print("consistenct_after:{}".format(consistency)) + """ 好像是一样的 + consistenct_before:0.2933838367462158 + consistenct_after:0.2933838665485382 + consistenct_before:0.2955893278121948 + consistenct_after:0.2955893278121948 + consistenct_before:0.29341286420822144 + consistenct_after:0.29341286420822144""" + + return consistency + + + + diff --git a/code/utils/distance_metrics_fast.py b/code/utils/distance_metrics_fast.py new file mode 100644 index 0000000..248b3dc --- /dev/null +++ b/code/utils/distance_metrics_fast.py @@ -0,0 +1,912 @@ +""" +The code was borrowed from https://github.com/loli/medpy/blob/master/medpy/metric/binary.py. +The hd_fast or hd95_fast is faster than the original hd or hd95 10 times with simialr results. +Thanks to Mr. Yu Wu in SenseTime. +Please use this code and .whl package in HiLab, don't share it with others! +Please install the "med_utils" in python==3.10.x and numpy==1.23.x!!! or python==3.7.x and numpy==1.21.x!!! as follows: + pip install med_utils-0.0.1.1-cp310-cp310-linux_x86_64.whl # python==3.10.x +or + pip install med_utils-0.0.1.1-cp37-cp37-linux_x86_64.whl # python==3.7.x +""" +import time +from collections.abc import Iterable, Iterator + +import med_utils as medut +import numpy +import numpy as np +import scipy +from scipy.ndimage import _ni_support +from scipy.ndimage.morphology import (binary_erosion, distance_transform_edt, + generate_binary_structure) + +neighbour_code_to_normals = [ + [[0, 0, 0]], + [[0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125]], + [[-0.25, -0.25, 0.0], [0.25, 0.25, -0.0]], + [[0.125, -0.125, 0.125]], + [[-0.25, -0.0, -0.25], [0.25, 0.0, 0.25]], + [[0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[0.5, 0.0, -0.0], [0.25, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[-0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, 0.125, 0.125]], + [[-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25]], + [[0.5, 0.0, 0.0], [-0.25, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[0.5, 0.0, 0.0], [0.25, -0.25, 0.25], [-0.125, 0.125, -0.125]], + [[-0.5, 0.0, 0.0], [-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[0.5, 0.0, 0.0], [0.5, 0.0, 0.0]], + [[0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25]], + [[-0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, -0.5, 0.0], [0.25, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, 0.0, -0.5], [0.25, 0.25, 0.25], [-0.125, -0.125, -0.125]], + [[-0.125, -0.125, 0.125], [0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[-0.125, -0.125, -0.125], [-0.25, -0.25, -0.25], + [0.25, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25], [0.125, -0.125, -0.125]], + [[0.125, 0.125, 0.125], [0.375, 0.375, 0.375], + [0.0, -0.25, 0.25], [-0.25, 0.0, 0.25]], + [[0.125, -0.125, -0.125], [0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[0.375, 0.375, 0.375], [0.0, 0.25, -0.25], + [-0.125, -0.125, -0.125], [-0.25, 0.25, 0.0]], + [[-0.5, 0.0, 0.0], [-0.125, -0.125, -0.125], + [-0.25, -0.25, -0.25], [0.125, 0.125, 0.125]], + [[-0.5, 0.0, 0.0], [-0.125, -0.125, -0.125], [-0.25, -0.25, -0.25]], + [[0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.0, -0.25, 0.25], [0.0, 0.25, -0.25]], + [[0.0, -0.5, 0.0], [0.125, 0.125, -0.125], [0.25, 0.25, -0.25]], + [[0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.125, -0.125, 0.125], [-0.25, -0.0, -0.25], [0.25, 0.0, 0.25]], + [[0.0, -0.25, 0.25], [0.0, 0.25, -0.25], [0.125, -0.125, 0.125]], + [[-0.375, -0.375, 0.375], [-0.0, 0.25, 0.25], + [0.125, 0.125, -0.125], [-0.25, -0.0, -0.25]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125], [-0.125, 0.125, 0.125]], + [[-0.0, 0.0, 0.5], [-0.25, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.25, 0.25, -0.25], [0.25, 0.25, -0.25], + [0.125, 0.125, -0.125], [-0.125, -0.125, 0.125]], + [[0.125, -0.125, 0.125], [0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[0.5, 0.0, 0.0], [0.25, -0.25, 0.25], + [-0.125, 0.125, -0.125], [0.125, -0.125, 0.125]], + [[0.0, 0.25, -0.25], [0.375, -0.375, -0.375], + [-0.125, 0.125, 0.125], [0.25, 0.25, 0.0]], + [[-0.5, 0.0, 0.0], [-0.25, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.25, -0.25, 0.0], [-0.25, 0.25, 0.0]], + [[0.0, 0.5, 0.0], [-0.25, 0.25, 0.25], [0.125, -0.125, -0.125]], + [[0.0, 0.5, 0.0], [0.125, -0.125, 0.125], [-0.25, 0.25, -0.25]], + [[0.0, 0.5, 0.0], [0.0, -0.5, 0.0]], + [[0.25, -0.25, 0.0], [-0.25, 0.25, 0.0], [0.125, -0.125, 0.125]], + [[-0.375, -0.375, -0.375], [-0.25, 0.0, 0.25], + [-0.125, -0.125, -0.125], [-0.25, 0.25, 0.0]], + [[0.125, 0.125, 0.125], [0.0, -0.5, 0.0], + [-0.25, -0.25, -0.25], [-0.125, -0.125, -0.125]], + [[0.0, -0.5, 0.0], [-0.25, -0.25, -0.25], [-0.125, -0.125, -0.125]], + [[-0.125, 0.125, 0.125], [0.25, -0.25, 0.0], [-0.25, 0.25, 0.0]], + [[0.0, 0.5, 0.0], [0.25, 0.25, -0.25], + [-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.375, 0.375, -0.375], [-0.25, -0.25, 0.0], + [-0.125, 0.125, -0.125], [-0.25, 0.0, 0.25]], + [[0.0, 0.5, 0.0], [0.25, 0.25, -0.25], [-0.125, -0.125, 0.125]], + [[0.25, -0.25, 0.0], [-0.25, 0.25, 0.0], + [0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0], [-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0]], + [[-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0]], + [[-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.25, -0.25, 0.0], [0.25, 0.25, -0.0]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25]], + [[0.0, 0.0, 0.5], [0.25, -0.25, 0.25], [0.125, -0.125, 0.125]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.375, -0.375, 0.375], [0.0, -0.25, -0.25], + [-0.125, 0.125, -0.125], [0.25, 0.25, 0.0]], + [[-0.125, -0.125, 0.125], [-0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125], [-0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25]], + [[0.5, 0.0, 0.0], [-0.25, -0.25, 0.25], + [-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.0, 0.5, 0.0], [-0.25, 0.25, -0.25], [0.125, -0.125, 0.125]], + [[-0.25, 0.25, -0.25], [-0.25, 0.25, -0.25], + [-0.125, 0.125, -0.125], [-0.125, 0.125, -0.125]], + [[-0.25, 0.0, -0.25], [0.375, -0.375, -0.375], + [0.0, 0.25, -0.25], [-0.125, 0.125, 0.125]], + [[0.5, 0.0, 0.0], [-0.25, 0.25, -0.25], [0.125, -0.125, 0.125]], + [[-0.25, 0.0, 0.25], [0.25, 0.0, -0.25]], + [[-0.0, 0.0, 0.5], [-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.25, 0.0, 0.25], [0.25, 0.0, -0.25]], + [[-0.25, -0.0, -0.25], [-0.375, 0.375, 0.375], + [-0.25, -0.25, 0.0], [-0.125, 0.125, 0.125]], + [[0.0, 0.0, -0.5], [0.25, 0.25, -0.25], [-0.125, -0.125, 0.125]], + [[-0.0, 0.0, 0.5], [0.0, 0.0, 0.5]], + [[0.125, 0.125, 0.125], [0.125, 0.125, 0.125], + [0.25, 0.25, 0.25], [0.0, 0.0, 0.5]], + [[0.125, 0.125, 0.125], [0.25, 0.25, 0.25], [0.0, 0.0, 0.5]], + [[-0.25, 0.0, 0.25], [0.25, 0.0, -0.25], [-0.125, 0.125, 0.125]], + [[-0.0, 0.0, 0.5], [0.25, -0.25, 0.25], + [0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25], + [-0.25, 0.0, 0.25], [0.25, 0.0, -0.25]], + [[0.125, -0.125, 0.125], [0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[0.25, 0.0, 0.25], [-0.375, -0.375, 0.375], + [-0.25, 0.25, 0.0], [-0.125, -0.125, 0.125]], + [[-0.0, 0.0, 0.5], [0.25, -0.25, 0.25], [0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[-0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125], [0.0, -0.25, 0.25], [0.0, 0.25, -0.25]], + [[0.0, -0.5, 0.0], [0.125, 0.125, -0.125], + [0.25, 0.25, -0.25], [-0.125, -0.125, 0.125]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25], [0.125, -0.125, 0.125]], + [[0.0, 0.0, 0.5], [0.25, -0.25, 0.25], + [0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25], + [0.0, -0.25, 0.25], [0.0, 0.25, -0.25]], + [[0.0, 0.25, 0.25], [0.0, 0.25, 0.25], [0.125, -0.125, -0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, 0.125], + [-0.125, -0.125, 0.125], [0.125, 0.125, 0.125]], + [[-0.0, 0.0, 0.5], [-0.25, -0.25, 0.25], + [-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[-0.0, 0.5, 0.0], [-0.25, 0.25, -0.25], + [0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.5, 0.0, -0.0], [0.25, -0.25, -0.25], [0.125, -0.125, -0.125]], + [[-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125], + [-0.25, 0.25, 0.25], [0.125, -0.125, -0.125]], + [[0.375, -0.375, 0.375], [0.0, 0.25, 0.25], + [-0.125, 0.125, -0.125], [-0.25, 0.0, 0.25]], + [[0.0, -0.5, 0.0], [-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[-0.375, -0.375, 0.375], [0.25, -0.25, 0.0], + [0.0, 0.25, 0.25], [-0.125, -0.125, 0.125]], + [[-0.125, 0.125, 0.125], [-0.25, 0.25, 0.25], [0.0, 0.0, 0.5]], + [[0.125, 0.125, 0.125], [0.0, 0.25, 0.25], [0.0, 0.25, 0.25]], + [[0.0, 0.25, 0.25], [0.0, 0.25, 0.25]], + [[0.5, 0.0, -0.0], [0.25, 0.25, 0.25], + [0.125, 0.125, 0.125], [0.125, 0.125, 0.125]], + [[0.125, -0.125, 0.125], [-0.125, -0.125, 0.125], [0.125, 0.125, 0.125]], + [[-0.25, -0.0, -0.25], [0.25, 0.0, 0.25], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.25, -0.25, 0.0], [0.25, 0.25, -0.0], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.25, -0.25, 0.0], [0.25, 0.25, -0.0], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.25, -0.0, -0.25], [0.25, 0.0, 0.25], [0.125, 0.125, 0.125]], + [[0.125, -0.125, 0.125], [-0.125, -0.125, 0.125], [0.125, 0.125, 0.125]], + [[0.5, 0.0, -0.0], [0.25, 0.25, 0.25], + [0.125, 0.125, 0.125], [0.125, 0.125, 0.125]], + [[0.0, 0.25, 0.25], [0.0, 0.25, 0.25]], + [[0.125, 0.125, 0.125], [0.0, 0.25, 0.25], [0.0, 0.25, 0.25]], + [[-0.125, 0.125, 0.125], [-0.25, 0.25, 0.25], [0.0, 0.0, 0.5]], + [[-0.375, -0.375, 0.375], [0.25, -0.25, 0.0], + [0.0, 0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.0, -0.5, 0.0], [-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[0.375, -0.375, 0.375], [0.0, 0.25, 0.25], + [-0.125, 0.125, -0.125], [-0.25, 0.0, 0.25]], + [[-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125], + [-0.25, 0.25, 0.25], [0.125, -0.125, -0.125]], + [[0.5, 0.0, -0.0], [0.25, -0.25, -0.25], [0.125, -0.125, -0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[-0.0, 0.5, 0.0], [-0.25, 0.25, -0.25], + [0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[-0.0, 0.0, 0.5], [-0.25, -0.25, 0.25], + [-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, 0.125], + [-0.125, -0.125, 0.125], [0.125, 0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[0.0, 0.25, 0.25], [0.0, 0.25, 0.25], [0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25], [0.0, 0.25, 0.25], [0.0, 0.25, 0.25]], + [[0.0, 0.0, 0.5], [0.25, -0.25, 0.25], + [0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25], [0.125, -0.125, 0.125]], + [[0.0, -0.5, 0.0], [0.125, 0.125, -0.125], + [0.25, 0.25, -0.25], [-0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125], [0.0, -0.25, 0.25], [0.0, 0.25, -0.25]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[0.125, 0.125, 0.125], [0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[-0.0, 0.0, 0.5], [0.25, -0.25, 0.25], [0.125, -0.125, 0.125]], + [[0.25, 0.0, 0.25], [-0.375, -0.375, 0.375], + [-0.25, 0.25, 0.0], [-0.125, -0.125, 0.125]], + [[0.125, -0.125, 0.125], [0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[-0.25, -0.0, -0.25], [0.25, 0.0, 0.25], + [0.25, 0.0, 0.25], [0.25, 0.0, 0.25]], + [[-0.0, 0.0, 0.5], [0.25, -0.25, 0.25], + [0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.25, 0.0, 0.25], [0.25, 0.0, -0.25], [-0.125, 0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.25, 0.25, 0.25], [0.0, 0.0, 0.5]], + [[0.125, 0.125, 0.125], [0.125, 0.125, 0.125], + [0.25, 0.25, 0.25], [0.0, 0.0, 0.5]], + [[-0.0, 0.0, 0.5], [0.0, 0.0, 0.5]], + [[0.0, 0.0, -0.5], [0.25, 0.25, -0.25], [-0.125, -0.125, 0.125]], + [[-0.25, -0.0, -0.25], [-0.375, 0.375, 0.375], + [-0.25, -0.25, 0.0], [-0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.25, 0.0, 0.25], [0.25, 0.0, -0.25]], + [[-0.0, 0.0, 0.5], [-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[-0.25, 0.0, 0.25], [0.25, 0.0, -0.25]], + [[0.5, 0.0, 0.0], [-0.25, 0.25, -0.25], [0.125, -0.125, 0.125]], + [[-0.25, 0.0, -0.25], [0.375, -0.375, -0.375], + [0.0, 0.25, -0.25], [-0.125, 0.125, 0.125]], + [[-0.25, 0.25, -0.25], [-0.25, 0.25, -0.25], + [-0.125, 0.125, -0.125], [-0.125, 0.125, -0.125]], + [[-0.0, 0.5, 0.0], [-0.25, 0.25, -0.25], [0.125, -0.125, 0.125]], + [[0.5, 0.0, 0.0], [-0.25, -0.25, 0.25], + [-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125], [-0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125], [-0.125, 0.125, 0.125]], + [[0.375, -0.375, 0.375], [0.0, -0.25, -0.25], + [-0.125, 0.125, -0.125], [0.25, 0.25, 0.0]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.0, 0.0, 0.5], [0.25, -0.25, 0.25], [0.125, -0.125, 0.125]], + [[0.0, -0.25, 0.25], [0.0, -0.25, 0.25]], + [[-0.125, -0.125, 0.125], [-0.25, -0.25, 0.0], [0.25, 0.25, -0.0]], + [[-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, -0.125, 0.125]], + [[-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0]], + [[0.125, 0.125, 0.125], [-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0]], + [[-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0], [-0.125, -0.125, 0.125]], + [[-0.25, -0.25, 0.0], [-0.25, -0.25, 0.0], + [-0.25, -0.25, 0.0], [0.25, 0.25, -0.0]], + [[0.0, 0.5, 0.0], [0.25, 0.25, -0.25], [-0.125, -0.125, 0.125]], + [[-0.375, 0.375, -0.375], [-0.25, -0.25, 0.0], + [-0.125, 0.125, -0.125], [-0.25, 0.0, 0.25]], + [[0.0, 0.5, 0.0], [0.25, 0.25, -0.25], + [-0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.25, -0.25, 0.0], [-0.25, 0.25, 0.0]], + [[0.0, -0.5, 0.0], [-0.25, -0.25, -0.25], [-0.125, -0.125, -0.125]], + [[0.125, 0.125, 0.125], [0.0, -0.5, 0.0], + [-0.25, -0.25, -0.25], [-0.125, -0.125, -0.125]], + [[-0.375, -0.375, -0.375], [-0.25, 0.0, 0.25], + [-0.125, -0.125, -0.125], [-0.25, 0.25, 0.0]], + [[0.25, -0.25, 0.0], [-0.25, 0.25, 0.0], [0.125, -0.125, 0.125]], + [[0.0, 0.5, 0.0], [0.0, -0.5, 0.0]], + [[0.0, 0.5, 0.0], [0.125, -0.125, 0.125], [-0.25, 0.25, -0.25]], + [[0.0, 0.5, 0.0], [-0.25, 0.25, 0.25], [0.125, -0.125, -0.125]], + [[0.25, -0.25, 0.0], [-0.25, 0.25, 0.0]], + [[-0.5, 0.0, 0.0], [-0.25, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.0, 0.25, -0.25], [0.375, -0.375, -0.375], + [-0.125, 0.125, 0.125], [0.25, 0.25, 0.0]], + [[0.5, 0.0, 0.0], [0.25, -0.25, 0.25], + [-0.125, 0.125, -0.125], [0.125, -0.125, 0.125]], + [[0.125, -0.125, 0.125], [0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[0.25, 0.25, -0.25], [0.25, 0.25, -0.25], + [0.125, 0.125, -0.125], [-0.125, -0.125, 0.125]], + [[-0.0, 0.0, 0.5], [-0.25, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125], [-0.125, 0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, 0.125]], + [[-0.375, -0.375, 0.375], [-0.0, 0.25, 0.25], + [0.125, 0.125, -0.125], [-0.25, -0.0, -0.25]], + [[0.0, -0.25, 0.25], [0.0, 0.25, -0.25], [0.125, -0.125, 0.125]], + [[0.125, -0.125, 0.125], [-0.25, -0.0, -0.25], [0.25, 0.0, 0.25]], + [[0.125, -0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.0, -0.5, 0.0], [0.125, 0.125, -0.125], [0.25, 0.25, -0.25]], + [[0.0, -0.25, 0.25], [0.0, 0.25, -0.25]], + [[0.125, 0.125, 0.125], [0.125, -0.125, 0.125]], + [[0.125, -0.125, 0.125]], + [[-0.5, 0.0, 0.0], [-0.125, -0.125, -0.125], [-0.25, -0.25, -0.25]], + [[-0.5, 0.0, 0.0], [-0.125, -0.125, -0.125], + [-0.25, -0.25, -0.25], [0.125, 0.125, 0.125]], + [[0.375, 0.375, 0.375], [0.0, 0.25, -0.25], + [-0.125, -0.125, -0.125], [-0.25, 0.25, 0.0]], + [[0.125, -0.125, -0.125], [0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[0.125, 0.125, 0.125], [0.375, 0.375, 0.375], + [0.0, -0.25, 0.25], [-0.25, 0.0, 0.25]], + [[-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25], [0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[-0.125, 0.125, 0.125], [0.125, -0.125, -0.125]], + [[-0.125, -0.125, -0.125], [-0.25, -0.25, -0.25], + [0.25, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125], [0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, 0.0, -0.5], [0.25, 0.25, 0.25], [-0.125, -0.125, -0.125]], + [[0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, -0.5, 0.0], [0.25, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[-0.125, -0.125, 0.125], [0.125, -0.125, -0.125]], + [[0.0, -0.25, -0.25], [0.0, 0.25, 0.25]], + [[0.125, -0.125, -0.125]], + [[0.5, 0.0, 0.0], [0.5, 0.0, 0.0]], + [[-0.5, 0.0, 0.0], [-0.25, 0.25, 0.25], [-0.125, 0.125, 0.125]], + [[0.5, 0.0, 0.0], [0.25, -0.25, 0.25], [-0.125, 0.125, -0.125]], + [[0.25, -0.25, 0.0], [0.25, -0.25, 0.0]], + [[0.5, 0.0, 0.0], [-0.25, -0.25, 0.25], [-0.125, -0.125, 0.125]], + [[-0.25, 0.0, 0.25], [-0.25, 0.0, 0.25]], + [[0.125, 0.125, 0.125], [-0.125, 0.125, 0.125]], + [[-0.125, 0.125, 0.125]], + [[0.5, 0.0, -0.0], [0.25, 0.25, 0.25], [0.125, 0.125, 0.125]], + [[0.125, -0.125, 0.125], [-0.125, -0.125, 0.125]], + [[-0.25, -0.0, -0.25], [0.25, 0.0, 0.25]], + [[0.125, -0.125, 0.125]], + [[-0.25, -0.25, 0.0], [0.25, 0.25, -0.0]], + [[-0.125, -0.125, 0.125]], + [[0.125, 0.125, 0.125]], + [[0, 0, 0]]] + + +def _normalize_sequence(input, rank): + """If input is a scalar, create a sequence of length equal to the + rank by duplicating the input. If input is a sequence, + check if its length is equal to the length of array. + """ + is_str = isinstance(input, str) + if not is_str and isinstance(input, Iterable): + normalized = list(input) + if len(normalized) != rank: + err = "sequence argument must have length equal to input rank" + raise RuntimeError(err) + else: + normalized = [input] * rank + return normalized + + +def __surface_distances(result, reference, voxelspacing=None, connectivity=1): + """ + The distances between the surface voxel of binary objects in result and their + nearest partner surface voxel of a binary object in reference. + """ + result = numpy.atleast_1d(result.astype(numpy.bool)) + reference = numpy.atleast_1d(reference.astype(numpy.bool)) + if voxelspacing is not None: + voxelspacing = _ni_support._normalize_sequence( + voxelspacing, result.ndim) + voxelspacing = numpy.asarray(voxelspacing, dtype=numpy.float64) + if not voxelspacing.flags.contiguous: + voxelspacing = voxelspacing.copy() + + # binary structure + footprint = generate_binary_structure(result.ndim, connectivity) + + # test for emptiness + if 0 == numpy.count_nonzero(result): + raise RuntimeError( + 'The first supplied array does not contain any binary object.') + if 0 == numpy.count_nonzero(reference): + raise RuntimeError( + 'The second supplied array does not contain any binary object.') + + # extract only 1-pixel border line of objects + result_border = result ^ binary_erosion( + result, structure=footprint, iterations=1) + reference_border = reference ^ binary_erosion( + reference, structure=footprint, iterations=1) + + # compute average surface distance + # Note: scipys distance transform is calculated only inside the borders of the + # foreground objects, therefore the input has to be reversed + dt = distance_transform_edt(~reference_border, sampling=voxelspacing) + sds = dt[result_border] + + return sds + + +def __surface_distances_fast(result, reference, voxelspacing=None, connectivity=1): + """ + The distances between the surface voxel of binary objects in result and their + nearest partner surface voxel of a binary object in reference. + """ + result = numpy.atleast_1d(result.astype(numpy.bool)) + reference = numpy.atleast_1d(reference.astype(numpy.bool)) + if voxelspacing is not None: + voxelspacing = _ni_support._normalize_sequence( + voxelspacing, result.ndim) + voxelspacing = numpy.asarray(voxelspacing, dtype=numpy.float64) + if not voxelspacing.flags.contiguous: + voxelspacing = voxelspacing.copy() + + # binary structure + footprint = generate_binary_structure(result.ndim, connectivity) + + # test for emptiness + if 0 == numpy.count_nonzero(result): + raise RuntimeError( + 'The first supplied array does not contain any binary object.') + if 0 == numpy.count_nonzero(reference): + raise RuntimeError( + 'The second supplied array does not contain any binary object.') + + # extract only 1-pixel border line of objects + result_border = result ^ binary_erosion( + result, structure=footprint, iterations=1) + reference_border = reference ^ binary_erosion( + reference, structure=footprint, iterations=1) + + # compute average surface distance + # Note: scipys distance transform is calculated only inside the borders of the + # foreground objects, therefore the input has to be reversed +# dt = distance_transform_edt(~reference_border, sampling=voxelspacing) + dt = medut.morphology.distance_transform_edt( + ~reference_border, label=0, spacing=voxelspacing, device="cuda", num_workers=8) # device="cuda" or "cpu" + sds = dt[result_border] + + return sds + + +def hd(result, reference, voxelspacing=None, connectivity=1): + hd1 = __surface_distances( + result, reference, voxelspacing, connectivity).max() + hd2 = __surface_distances( + reference, result, voxelspacing, connectivity).max() + hd = max(hd1, hd2) + return hd + + +def hd_fast(result, reference, voxelspacing=None, connectivity=1): + hd1 = __surface_distances( + result, reference, voxelspacing, connectivity).max() + hd2 = __surface_distances( + reference, result, voxelspacing, connectivity).max() + hd = max(hd1, hd2) + return hd + + +def hd95(result, reference, voxelspacing=None, connectivity=1): + hd1 = __surface_distances(result, reference, voxelspacing, connectivity) + hd2 = __surface_distances(reference, result, voxelspacing, connectivity) + hd95 = numpy.percentile(numpy.hstack((hd1, hd2)), 95) + return hd95 + + +def hd95_fast(result, reference, voxelspacing=None, connectivity=1): + hd1 = __surface_distances_fast( + result, reference, voxelspacing, connectivity) + hd2 = __surface_distances_fast( + reference, result, voxelspacing, connectivity) + hd95 = numpy.percentile(numpy.hstack((hd1, hd2)), 95) + return hd95 + + +def assd(result, reference, voxelspacing=None, connectivity=1): + assd = numpy.mean((__surface_distances(result, reference, voxelspacing, connectivity), + __surface_distances(reference, result, voxelspacing, connectivity))) + return assd + + +def assd_fast(result, reference, voxelspacing=None, connectivity=1): + assd = numpy.mean((__surface_distances_fast(result, reference, voxelspacing, connectivity), + __surface_distances_fast(reference, result, voxelspacing, connectivity))) + return assd + + +def asd(result, reference, voxelspacing=None, connectivity=1): + sds = __surface_distances(result, reference, voxelspacing, connectivity) + asd = sds.mean() + return asd + + +def asd_fast(result, reference, voxelspacing=None, connectivity=1): + sds = __surface_distances_fast( + result, reference, voxelspacing, connectivity) + asd = sds.mean() + return asd + + +def compute_surface_distances(mask_gt, mask_pred, spacing_mm): + """Compute closest distances from all surface points to the other surface. + + Finds all surface elements "surfels" in the ground truth mask `mask_gt` and + the predicted mask `mask_pred`, computes their area in mm^2 and the distance + to the closest point on the other surface. It returns two sorted lists of + distances together with the corresponding surfel areas. If one of the masks + is empty, the corresponding lists are empty and all distances in the other + list are `inf` + + Args: + mask_gt: 3-dim Numpy array of type bool. The ground truth mask. + mask_pred: 3-dim Numpy array of type bool. The predicted mask. + spacing_mm: 3-element list-like structure. Voxel spacing in x0, x1 and x2 + direction + + Returns: + A dict with + "distances_gt_to_pred": 1-dim numpy array of type float. The distances in mm + from all ground truth surface elements to the predicted surface, + sorted from smallest to largest + "distances_pred_to_gt": 1-dim numpy array of type float. The distances in mm + from all predicted surface elements to the ground truth surface, + sorted from smallest to largest + "surfel_areas_gt": 1-dim numpy array of type float. The area in mm^2 of + the ground truth surface elements in the same order as + distances_gt_to_pred + "surfel_areas_pred": 1-dim numpy array of type float. The area in mm^2 of + the predicted surface elements in the same order as + distances_pred_to_gt + + """ + + # compute the area for all 256 possible surface elements + # (given a 2x2x2 neighbourhood) according to the spacing_mm + neighbour_code_to_surface_area = np.zeros([256]) + for code in range(256): + normals = np.array(neighbour_code_to_normals[code]) + sum_area = 0 + for normal_idx in range(normals.shape[0]): + # normal vector + n = np.zeros([3]) + n[0] = normals[normal_idx, 0] * spacing_mm[1] * spacing_mm[2] + n[1] = normals[normal_idx, 1] * spacing_mm[0] * spacing_mm[2] + n[2] = normals[normal_idx, 2] * spacing_mm[0] * spacing_mm[1] + area = np.linalg.norm(n) + sum_area += area + neighbour_code_to_surface_area[code] = sum_area + + # compute the bounding box of the masks to trim + # the volume to the smallest possible processing subvolume + mask_all = mask_gt | mask_pred + bbox_min = np.zeros(3, np.int64) + bbox_max = np.zeros(3, np.int64) + + # max projection to the x0-axis + proj_0 = np.max(np.max(mask_all, axis=2), axis=1) + idx_nonzero_0 = np.nonzero(proj_0)[0] + if len(idx_nonzero_0) == 0: + return {"distances_gt_to_pred": np.array([]), + "distances_pred_to_gt": np.array([]), + "surfel_areas_gt": np.array([]), + "surfel_areas_pred": np.array([])} + + bbox_min[0] = np.min(idx_nonzero_0) + bbox_max[0] = np.max(idx_nonzero_0) + + # max projection to the x1-axis + proj_1 = np.max(np.max(mask_all, axis=2), axis=0) + idx_nonzero_1 = np.nonzero(proj_1)[0] + bbox_min[1] = np.min(idx_nonzero_1) + bbox_max[1] = np.max(idx_nonzero_1) + + # max projection to the x2-axis + proj_2 = np.max(np.max(mask_all, axis=1), axis=0) + idx_nonzero_2 = np.nonzero(proj_2)[0] + bbox_min[2] = np.min(idx_nonzero_2) + bbox_max[2] = np.max(idx_nonzero_2) + + # print("bounding box min = {}".format(bbox_min)) + # print("bounding box max = {}".format(bbox_max)) + + # crop the processing subvolume. + # we need to zeropad the cropped region with 1 voxel at the lower, + # the right and the back side. This is required to obtain the "full" + # convolution result with the 2x2x2 kernel + cropmask_gt = np.zeros((bbox_max - bbox_min) + 2, np.uint8) + cropmask_pred = np.zeros((bbox_max - bbox_min) + 2, np.uint8) + + cropmask_gt[0:-1, 0:-1, 0:-1] = mask_gt[bbox_min[0]:bbox_max[0] + 1, + bbox_min[1]:bbox_max[1] + 1, + bbox_min[2]:bbox_max[2] + 1] + + cropmask_pred[0:-1, 0:-1, 0:-1] = mask_pred[bbox_min[0]:bbox_max[0] + 1, + bbox_min[1]:bbox_max[1] + 1, + bbox_min[2]:bbox_max[2] + 1] + + # compute the neighbour code (local binary pattern) for each voxel + # the resultsing arrays are spacially shifted by minus half a voxel in each axis. + # i.e. the points are located at the corners of the original voxels + kernel = np.array([[[128, 64], + [32, 16]], + [[8, 4], + [2, 1]]]) + neighbour_code_map_gt = scipy.ndimage.filters.correlate( + cropmask_gt.astype(np.uint8), kernel, mode="constant", cval=0) + neighbour_code_map_pred = scipy.ndimage.filters.correlate(cropmask_pred.astype(np.uint8), kernel, mode="constant", + cval=0) + + # create masks with the surface voxels + borders_gt = ((neighbour_code_map_gt != 0) & + (neighbour_code_map_gt != 255)) + borders_pred = ((neighbour_code_map_pred != 0) & + (neighbour_code_map_pred != 255)) + + # compute the distance transform (closest distance of each voxel to the surface voxels) + if borders_gt.any(): + distmap_gt = scipy.ndimage.morphology.distance_transform_edt( + ~borders_gt, sampling=spacing_mm) + # distmap_gt = medut.morphology.distance_transform_edt( + # ~borders_gt, label=0, spacing=spacing_mm, device="cuda", num_workers=8) # device="cuda" or "cpu" + else: + distmap_gt = np.Inf * np.ones(borders_gt.shape) + + if borders_pred.any(): + distmap_pred = scipy.ndimage.morphology.distance_transform_edt( + ~borders_pred, sampling=spacing_mm) + # distmap_pred = medut.morphology.distance_transform_edt( + # ~borders_pred, label=0, spacing=spacing_mm, device="cuda", num_workers=8) # device="cuda" or "cpu" + else: + distmap_pred = np.Inf * np.ones(borders_pred.shape) + + # compute the area of each surface element + surface_area_map_gt = neighbour_code_to_surface_area[neighbour_code_map_gt] + surface_area_map_pred = neighbour_code_to_surface_area[neighbour_code_map_pred] + + # create a list of all surface elements with distance and area + distances_gt_to_pred = distmap_pred[borders_gt] + distances_pred_to_gt = distmap_gt[borders_pred] + surfel_areas_gt = surface_area_map_gt[borders_gt] + surfel_areas_pred = surface_area_map_pred[borders_pred] + + # sort them by distance + if distances_gt_to_pred.shape != (0,): + sorted_surfels_gt = np.array( + sorted(zip(distances_gt_to_pred, surfel_areas_gt))) + distances_gt_to_pred = sorted_surfels_gt[:, 0] + surfel_areas_gt = sorted_surfels_gt[:, 1] + + if distances_pred_to_gt.shape != (0,): + sorted_surfels_pred = np.array( + sorted(zip(distances_pred_to_gt, surfel_areas_pred))) + distances_pred_to_gt = sorted_surfels_pred[:, 0] + surfel_areas_pred = sorted_surfels_pred[:, 1] + + return {"distances_gt_to_pred": distances_gt_to_pred, + "distances_pred_to_gt": distances_pred_to_gt, + "surfel_areas_gt": surfel_areas_gt, + "surfel_areas_pred": surfel_areas_pred} + + +def compute_surface_distances_fast(mask_gt, mask_pred, spacing_mm): + """Compute closest distances from all surface points to the other surface. + + Finds all surface elements "surfels" in the ground truth mask `mask_gt` and + the predicted mask `mask_pred`, computes their area in mm^2 and the distance + to the closest point on the other surface. It returns two sorted lists of + distances together with the corresponding surfel areas. If one of the masks + is empty, the corresponding lists are empty and all distances in the other + list are `inf` + + Args: + mask_gt: 3-dim Numpy array of type bool. The ground truth mask. + mask_pred: 3-dim Numpy array of type bool. The predicted mask. + spacing_mm: 3-element list-like structure. Voxel spacing in x0, x1 and x2 + direction + + Returns: + A dict with + "distances_gt_to_pred": 1-dim numpy array of type float. The distances in mm + from all ground truth surface elements to the predicted surface, + sorted from smallest to largest + "distances_pred_to_gt": 1-dim numpy array of type float. The distances in mm + from all predicted surface elements to the ground truth surface, + sorted from smallest to largest + "surfel_areas_gt": 1-dim numpy array of type float. The area in mm^2 of + the ground truth surface elements in the same order as + distances_gt_to_pred + "surfel_areas_pred": 1-dim numpy array of type float. The area in mm^2 of + the predicted surface elements in the same order as + distances_pred_to_gt + + """ + + # compute the area for all 256 possible surface elements + # (given a 2x2x2 neighbourhood) according to the spacing_mm + neighbour_code_to_surface_area = np.zeros([256]) + for code in range(256): + normals = np.array(neighbour_code_to_normals[code]) + sum_area = 0 + for normal_idx in range(normals.shape[0]): + # normal vector + n = np.zeros([3]) + n[0] = normals[normal_idx, 0] * spacing_mm[1] * spacing_mm[2] + n[1] = normals[normal_idx, 1] * spacing_mm[0] * spacing_mm[2] + n[2] = normals[normal_idx, 2] * spacing_mm[0] * spacing_mm[1] + area = np.linalg.norm(n) + sum_area += area + neighbour_code_to_surface_area[code] = sum_area + + # compute the bounding box of the masks to trim + # the volume to the smallest possible processing subvolume + mask_all = mask_gt | mask_pred + bbox_min = np.zeros(3, np.int64) + bbox_max = np.zeros(3, np.int64) + + # max projection to the x0-axis + proj_0 = np.max(np.max(mask_all, axis=2), axis=1) + idx_nonzero_0 = np.nonzero(proj_0)[0] + if len(idx_nonzero_0) == 0: + return {"distances_gt_to_pred": np.array([]), + "distances_pred_to_gt": np.array([]), + "surfel_areas_gt": np.array([]), + "surfel_areas_pred": np.array([])} + + bbox_min[0] = np.min(idx_nonzero_0) + bbox_max[0] = np.max(idx_nonzero_0) + + # max projection to the x1-axis + proj_1 = np.max(np.max(mask_all, axis=2), axis=0) + idx_nonzero_1 = np.nonzero(proj_1)[0] + bbox_min[1] = np.min(idx_nonzero_1) + bbox_max[1] = np.max(idx_nonzero_1) + + # max projection to the x2-axis + proj_2 = np.max(np.max(mask_all, axis=1), axis=0) + idx_nonzero_2 = np.nonzero(proj_2)[0] + bbox_min[2] = np.min(idx_nonzero_2) + bbox_max[2] = np.max(idx_nonzero_2) + + # print("bounding box min = {}".format(bbox_min)) + # print("bounding box max = {}".format(bbox_max)) + + # crop the processing subvolume. + # we need to zeropad the cropped region with 1 voxel at the lower, + # the right and the back side. This is required to obtain the "full" + # convolution result with the 2x2x2 kernel + cropmask_gt = np.zeros((bbox_max - bbox_min) + 2, np.uint8) + cropmask_pred = np.zeros((bbox_max - bbox_min) + 2, np.uint8) + + cropmask_gt[0:-1, 0:-1, 0:-1] = mask_gt[bbox_min[0]:bbox_max[0] + 1, + bbox_min[1]:bbox_max[1] + 1, + bbox_min[2]:bbox_max[2] + 1] + + cropmask_pred[0:-1, 0:-1, 0:-1] = mask_pred[bbox_min[0]:bbox_max[0] + 1, + bbox_min[1]:bbox_max[1] + 1, + bbox_min[2]:bbox_max[2] + 1] + + # compute the neighbour code (local binary pattern) for each voxel + # the resultsing arrays are spacially shifted by minus half a voxel in each axis. + # i.e. the points are located at the corners of the original voxels + kernel = np.array([[[128, 64], + [32, 16]], + [[8, 4], + [2, 1]]]) + neighbour_code_map_gt = scipy.ndimage.filters.correlate( + cropmask_gt.astype(np.uint8), kernel, mode="constant", cval=0) + neighbour_code_map_pred = scipy.ndimage.filters.correlate(cropmask_pred.astype(np.uint8), kernel, mode="constant", + cval=0) + + # create masks with the surface voxels + borders_gt = ((neighbour_code_map_gt != 0) & + (neighbour_code_map_gt != 255)) + borders_pred = ((neighbour_code_map_pred != 0) & + (neighbour_code_map_pred != 255)) + + # compute the distance transform (closest distance of each voxel to the surface voxels) + if borders_gt.any(): + # distmap_gt = scipy.ndimage.morphology.distance_transform_edt( + # ~borders_gt, sampling=spacing_mm) + distmap_gt = medut.morphology.distance_transform_edt( + ~borders_gt, label=0, spacing=spacing_mm, device="cuda", num_workers=8) # device="cuda" or "cpu" + else: + distmap_gt = np.Inf * np.ones(borders_gt.shape) + + if borders_pred.any(): + # distmap_pred = scipy.ndimage.morphology.distance_transform_edt( + # ~borders_pred, sampling=spacing_mm) + distmap_pred = medut.morphology.distance_transform_edt( + ~borders_pred, label=0, spacing=spacing_mm, device="cuda", num_workers=8) # device="cuda" or "cpu" + else: + distmap_pred = np.Inf * np.ones(borders_pred.shape) + + # compute the area of each surface element + surface_area_map_gt = neighbour_code_to_surface_area[neighbour_code_map_gt] + surface_area_map_pred = neighbour_code_to_surface_area[neighbour_code_map_pred] + + # create a list of all surface elements with distance and area + distances_gt_to_pred = distmap_pred[borders_gt] + distances_pred_to_gt = distmap_gt[borders_pred] + surfel_areas_gt = surface_area_map_gt[borders_gt] + surfel_areas_pred = surface_area_map_pred[borders_pred] + + # sort them by distance + if distances_gt_to_pred.shape != (0,): + sorted_surfels_gt = np.array( + sorted(zip(distances_gt_to_pred, surfel_areas_gt))) + distances_gt_to_pred = sorted_surfels_gt[:, 0] + surfel_areas_gt = sorted_surfels_gt[:, 1] + + if distances_pred_to_gt.shape != (0,): + sorted_surfels_pred = np.array( + sorted(zip(distances_pred_to_gt, surfel_areas_pred))) + distances_pred_to_gt = sorted_surfels_pred[:, 0] + surfel_areas_pred = sorted_surfels_pred[:, 1] + + return {"distances_gt_to_pred": distances_gt_to_pred, + "distances_pred_to_gt": distances_pred_to_gt, + "surfel_areas_gt": surfel_areas_gt, + "surfel_areas_pred": surfel_areas_pred} + + +def compute_average_surface_distance(surface_distances): + distances_gt_to_pred = surface_distances["distances_gt_to_pred"] + distances_pred_to_gt = surface_distances["distances_pred_to_gt"] + surfel_areas_gt = surface_distances["surfel_areas_gt"] + surfel_areas_pred = surface_distances["surfel_areas_pred"] + average_distance_gt_to_pred = np.sum( + distances_gt_to_pred * surfel_areas_gt) / np.sum(surfel_areas_gt) + average_distance_pred_to_gt = np.sum( + distances_pred_to_gt * surfel_areas_pred) / np.sum(surfel_areas_pred) + return (average_distance_gt_to_pred, average_distance_pred_to_gt) + + +def compute_robust_hausdorff(surface_distances, percent): + distances_gt_to_pred = surface_distances["distances_gt_to_pred"] + distances_pred_to_gt = surface_distances["distances_pred_to_gt"] + surfel_areas_gt = surface_distances["surfel_areas_gt"] + surfel_areas_pred = surface_distances["surfel_areas_pred"] + if len(distances_gt_to_pred) > 0: + surfel_areas_cum_gt = np.cumsum( + surfel_areas_gt) / np.sum(surfel_areas_gt) + idx = np.searchsorted(surfel_areas_cum_gt, percent / 100.0) + perc_distance_gt_to_pred = distances_gt_to_pred[min( + idx, len(distances_gt_to_pred) - 1)] + else: + perc_distance_gt_to_pred = np.Inf + + if len(distances_pred_to_gt) > 0: + surfel_areas_cum_pred = np.cumsum( + surfel_areas_pred) / np.sum(surfel_areas_pred) + idx = np.searchsorted(surfel_areas_cum_pred, percent / 100.0) + perc_distance_pred_to_gt = distances_pred_to_gt[min( + idx, len(distances_pred_to_gt) - 1)] + else: + perc_distance_pred_to_gt = np.Inf + + return max(perc_distance_gt_to_pred, perc_distance_pred_to_gt) + + +def compute_surface_overlap_at_tolerance(surface_distances, tolerance_mm): + distances_gt_to_pred = surface_distances["distances_gt_to_pred"] + distances_pred_to_gt = surface_distances["distances_pred_to_gt"] + surfel_areas_gt = surface_distances["surfel_areas_gt"] + surfel_areas_pred = surface_distances["surfel_areas_pred"] + rel_overlap_gt = np.sum( + surfel_areas_gt[distances_gt_to_pred <= tolerance_mm]) / np.sum(surfel_areas_gt) + rel_overlap_pred = np.sum( + surfel_areas_pred[distances_pred_to_gt <= tolerance_mm]) / np.sum(surfel_areas_pred) + return (rel_overlap_gt, rel_overlap_pred) + + +def compute_surface_dice_at_tolerance(surface_distances, tolerance_mm): + distances_gt_to_pred = surface_distances["distances_gt_to_pred"] + distances_pred_to_gt = surface_distances["distances_pred_to_gt"] + surfel_areas_gt = surface_distances["surfel_areas_gt"] + surfel_areas_pred = surface_distances["surfel_areas_pred"] + overlap_gt = np.sum(surfel_areas_gt[distances_gt_to_pred <= tolerance_mm]) + overlap_pred = np.sum( + surfel_areas_pred[distances_pred_to_gt <= tolerance_mm]) + surface_dice = (overlap_gt + overlap_pred) / ( + np.sum(surfel_areas_gt) + np.sum(surfel_areas_pred)) + return surface_dice + + +def nsd(result, reference, voxelspacing=None, tolerance_mm=1): + nsd = compute_surface_dice_at_tolerance( + compute_surface_distances(reference, result, voxelspacing), tolerance_mm) + return nsd + + +def nsd_fast(result, reference, voxelspacing=None, tolerance_mm=1): + nsd = compute_surface_dice_at_tolerance( + compute_surface_distances_fast(reference, result, voxelspacing), tolerance_mm) + return nsd + + +if __name__ == "__main__": + import SimpleITK as sitk + gt = sitk.ReadImage("gt.nii.gz") + pred = sitk.ReadImage("pred.nii.gz") + + gt_array = sitk.GetArrayFromImage(gt) + pred_array = sitk.GetArrayFromImage(pred) + time1 = time.time() + for i in range(1,17): + print(hd95(pred_array==i, gt_array==i, gt.GetSpacing()[::-1])) + print("Original total time: ", time.time() - time1) + time2 = time.time() + for i in range(1,17): + print(hd95_fast(pred_array==i, gt_array==i, gt.GetSpacing()[::-1])) + print("Fast version total time: ", time.time() - time2) \ No newline at end of file diff --git a/code/utils/distance_metrics_fast/gt.nii.gz b/code/utils/distance_metrics_fast/gt.nii.gz new file mode 100644 index 0000000..db66cef Binary files /dev/null and b/code/utils/distance_metrics_fast/gt.nii.gz differ diff --git a/code/utils/distance_metrics_fast/med_utils-0.0.1.1-cp310-cp310-linux_x86_64.whl b/code/utils/distance_metrics_fast/med_utils-0.0.1.1-cp310-cp310-linux_x86_64.whl new file mode 100644 index 0000000..879941b Binary files /dev/null and b/code/utils/distance_metrics_fast/med_utils-0.0.1.1-cp310-cp310-linux_x86_64.whl differ diff --git a/code/utils/distance_metrics_fast/med_utils-0.0.1.1-cp37-cp37m-linux_x86_64.whl b/code/utils/distance_metrics_fast/med_utils-0.0.1.1-cp37-cp37m-linux_x86_64.whl new file mode 100644 index 0000000..39ca7c4 Binary files /dev/null and b/code/utils/distance_metrics_fast/med_utils-0.0.1.1-cp37-cp37m-linux_x86_64.whl differ diff --git a/code/utils/distance_metrics_fast/pred.nii.gz b/code/utils/distance_metrics_fast/pred.nii.gz new file mode 100644 index 0000000..91e3a2e Binary files /dev/null and b/code/utils/distance_metrics_fast/pred.nii.gz differ diff --git a/code/utils/drawCAM.py b/code/utils/drawCAM.py index 27678c3..78ba15a 100644 --- a/code/utils/drawCAM.py +++ b/code/utils/drawCAM.py @@ -9,59 +9,63 @@ def draw_CAM(model, img_path, save_path, transform=None, visual_heatmap=False): ''' - draw Class Activation Map - :param model: load Pytorch model - :param img_path: test iamge path - :param save_path: save path - :param transform: Input image preprocessing method - :param visual_heatmap: Whether to visualize the original heatmap (calling matplotlib) + 绘制 Class Activation Map + :param model: 加载好权重的Pytorch model + :param img_path: 测试图片路径 + :param save_path: CAM结果保存路径 + :param transform: 输入图像预处理方法 + :param visual_heatmap: 是否可视化原始heatmap（调用matplotlib） :return: ''' + # 图像加载&预处理 img = Image.open(img_path).convert('RGB') if transform: img = transform(img) img = img.unsqueeze(0) + # 获取模型输出的feature/score model.eval() features = model.features(img) output = model.classifier(features) + # 为了能读取到中间梯度定义的辅助函数 def extract(g): global features_grad features_grad = g - + # 预测得分最高的那一类对应的输出score pred = torch.argmax(output).item() pred_class = output[:, pred] features.register_hook(extract) - pred_class.backward() + pred_class.backward() # 计算梯度 - grads = features_grad + grads = features_grad # 获取梯度 pooled_grads = torch.nn.functional.adaptive_avg_pool2d(grads, (1, 1)) + # 此处batch size默认为1，所以去掉了第0维（batch size维） pooled_grads = pooled_grads[0] features = features[0] - + # 512是最后一层feature的通道数 for i in range(512): features[i, ...] *= pooled_grads[i, ...] - + # 以下部分同Keras版实现 heatmap = features.detach().numpy() heatmap = np.mean(heatmap, axis=0) heatmap = np.maximum(heatmap, 0) heatmap /= np.max(heatmap) - + # 可视化原始热力图 if visual_heatmap: plt.matshow(heatmap) plt.show() - img = cv2.imread(img_path) - heatmap = cv2.resize(heatmap, (img.shape[1], img.shape[0])) - heatmap = np.uint8(255 * heatmap) - heatmap = cv2.applyColorMap(heatmap, cv2.COLORMAP_JET) - superimposed_img = heatmap * 0.4 + img - cv2.imwrite(save_path, superimposed_img) + img = cv2.imread(img_path) # 用cv2加载原始图像 + heatmap = cv2.resize(heatmap, (img.shape[1], img.shape[0])) # 将热力图的大小调整为与原始图像相同 + heatmap = np.uint8(255 * heatmap) # 将热力图转换为RGB格式 + heatmap = cv2.applyColorMap(heatmap, cv2.COLORMAP_JET) # 将热力图应用于原始图像 + superimposed_img = heatmap * 0.4 + img # 这里的0.4是热力图强度因子 + cv2.imwrite(save_path, superimposed_img) # 将图像保存到硬盘 diff --git a/code/utils/ramps.py b/code/utils/ramps.py index d8b0f81..071f4c4 100644 --- a/code/utils/ramps.py +++ b/code/utils/ramps.py @@ -10,6 +10,9 @@ Each function takes the current training step or epoch, and the ramp length in the same format, and returns a multiplier between 0 and 1. + +用于向上或向下倾斜超参数的函数 +每个函数都采用相同格式的当前训练步长或epoch,以及渐变长度,并返回一个介于0和1之间的乘数。 """ @@ -17,14 +20,14 @@ def sigmoid_rampup(current, rampup_length):# - """Exponential rampup from https://arxiv.org/abs/1610.02242""" + """Exponential rampup from https://arxiv.org/abs/1610.02242 指数增长""" if rampup_length == 0: return 1.0 else: - current = np.clip(current, 0.0, rampup_length) - #rampup_length = t_max + current = np.clip(current, 0.0, rampup_length)#np.clip()将current数组里的数限定在0和t_max之间 + #rampup_length即t_max，指迭代的最大次数 phase = 1.0 - current / rampup_length - return float(np.exp(-5.0 * phase * phase))#exp[-5*(1-t/t_max)^2] + return float(np.exp(-5.0 * phase * phase))#返回的是，exp[-5*(1-t/t_max)^2] def linear_rampup(current, rampup_length): @@ -38,5 +41,5 @@ def linear_rampup(current, rampup_length): def cosine_rampdown(current, rampdown_length): """Cosine rampdown from https://arxiv.org/abs/1608.03983""" - assert 0 <= current <= rampdown_length + assert 0 <= current <= rampdown_length #定义假设空间，超出这个范围会警告 return float(.5 * (np.cos(np.pi * current / rampdown_length) + 1)) diff --git a/code/utils/util.py b/code/utils/util.py new file mode 100644 index 0000000..940f0d7 --- /dev/null +++ b/code/utils/util.py @@ -0,0 +1,150 @@ +# Copyright (c) 2017-present, Facebook, Inc. +# All rights reserved. +# +# This source code is licensed under the license found in the +# LICENSE file in the root directory of this source tree. +# +import os +import pickle +import numpy as np +from scipy.ndimage import distance_transform_edt as distance +from skimage import segmentation as skimage_seg +import torch +from torch.utils.data.sampler import Sampler + +import networks + +def load_model(path): + """Loads model and return it without DataParallel table.""" + if os.path.isfile(path): + print("=> loading checkpoint '{}'".format(path)) + checkpoint = torch.load(path) + + # size of the top layer + N = checkpoint['state_dict']['top_layer.bias'].size() + + # build skeleton of the model + sob = 'sobel.0.weight' in checkpoint['state_dict'].keys() + model = models.__dict__[checkpoint['arch']](sobel=sob, out=int(N[0])) + + # deal with a dataparallel table + def rename_key(key): + if not 'module' in key: + return key + return ''.join(key.split('.module')) + + checkpoint['state_dict'] = {rename_key(key): val + for key, val + in checkpoint['state_dict'].items()} + + # load weights + model.load_state_dict(checkpoint['state_dict']) + print("Loaded") + else: + model = None + print("=> no checkpoint found at '{}'".format(path)) + return model + + +class UnifLabelSampler(Sampler): + """Samples elements uniformely accross pseudolabels. + Args: + N (int): size of returned iterator. + images_lists: dict of key (target), value (list of data with this target) + """ + + def __init__(self, N, images_lists): + self.N = N + self.images_lists = images_lists + self.indexes = self.generate_indexes_epoch() + + def generate_indexes_epoch(self): + size_per_pseudolabel = int(self.N / len(self.images_lists)) + 1 + res = np.zeros(size_per_pseudolabel * len(self.images_lists)) + + for i in range(len(self.images_lists)): + indexes = np.random.choice( + self.images_lists[i], + size_per_pseudolabel, + replace=(len(self.images_lists[i]) <= size_per_pseudolabel) + ) + res[i * size_per_pseudolabel: (i + 1) * size_per_pseudolabel] = indexes + + np.random.shuffle(res) + return res[:self.N].astype('int') + + def __iter__(self): + return iter(self.indexes) + + def __len__(self): + return self.N + + +class AverageMeter(object): + """Computes and stores the average and current value""" + def __init__(self): + self.reset() + + def reset(self): + self.val = 0 + self.avg = 0 + self.sum = 0 + self.count = 0 + + def update(self, val, n=1): + self.val = val + self.sum += val * n + self.count += n + self.avg = self.sum / self.count + + +def learning_rate_decay(optimizer, t, lr_0): + for param_group in optimizer.param_groups: + lr = lr_0 / np.sqrt(1 + lr_0 * param_group['weight_decay'] * t) + param_group['lr'] = lr + + +class Logger(): + """ Class to update every epoch to keep trace of the results + Methods: + - log() log and save + """ + + def __init__(self, path): + self.path = path + self.data = [] + + def log(self, train_point): + self.data.append(train_point) + with open(os.path.join(self.path), 'wb') as fp: + pickle.dump(self.data, fp, -1) + + +def compute_sdf(img_gt, out_shape): + """ + compute the signed distance map of binary mask + input: segmentation, shape = (batch_size, x, y, z) + output: the Signed Distance Map (SDM) + sdf(x) = 0; x in segmentation boundary + -inf|x-y|; x in segmentation + +inf|x-y|; x out of segmentation + normalize sdf to [-1,1] + """ + + img_gt = img_gt.astype(np.uint8) + normalized_sdf = np.zeros(out_shape) + + for b in range(out_shape[0]): # batch size + posmask = img_gt[b].astype(np.bool) + if posmask.any(): + negmask = ~posmask + posdis = distance(posmask) + negdis = distance(negmask) + boundary = skimage_seg.find_boundaries(posmask, mode='inner').astype(np.uint8) + sdf = (negdis-np.min(negdis))/(np.max(negdis)-np.min(negdis)) - (posdis-np.min(posdis))/(np.max(posdis)-np.min(posdis)) + sdf[boundary==1] = 0 + normalized_sdf[b] = sdf + # assert np.min(sdf) == -1.0, print(np.min(posdis), np.max(posdis), np.min(negdis), np.max(negdis)) + # assert np.max(sdf) == 1.0, print(np.min(posdis), np.min(negdis), np.max(posdis), np.max(negdis)) + + return normalized_sdf \ No newline at end of file diff --git a/code/val_3D.py b/code/val_3D.py index 738bd53..454ffb0 100644 --- a/code/val_3D.py +++ b/code/val_3D.py @@ -64,8 +64,7 @@ def test_single_case_HM(net, net_type, image, stride_xy, stride_z, patch_size, sz = math.ceil((dd - patch_size[2]) / stride_z) + 1 score_map = np.zeros((num_classes, ) + (ww, hh, dd)).astype(np.float32) - #cnt = np.zeros(ww, hh, dd).astype(np.float32) - cnt=np.zeros((ww,hh,dd), dtype=np.float32) + cnt = np.zeros(ww, hh, dd).astype(np.float32) for x in range(0, sx): @@ -89,7 +88,7 @@ def test_single_case_HM(net, net_type, image, stride_xy, stride_z, patch_size, with torch.no_grad(): if net_type == "unet_3D_dv_semi": y1, _, _, _ = net(test_patch) - elif net_type == "unet_cct_dp_3D" or net_type == "attention_unet_2dual_3d"\ + elif net_type == "unet_cct_dropout_3D" or net_type == "attention_unet_2dual_3d"\ or net_type == "unetr_2dual_3d": y1, _ = net(test_patch) else: diff --git a/config/acdc_dmsps.cfg b/config/acdc_dmsps.cfg deleted file mode 100644 index 27cfaf5..0000000 --- a/config/acdc_dmsps.cfg +++ /dev/null @@ -1,78 +0,0 @@ -[dataset] -# tensor type (float or double) -tensor_type = float -task_type = seg -supervise_type = weak_sup - -train_dir = data/ACDC2017/ACDC_for2D -train_csv = data/ACDC2017/ACDC_for2D/train.csv -valid_csv = data/ACDC2017/ACDC_for2D/valid.csv -test_csv = data/ACDC2017/ACDC_for2D/trainvol.csv -train_dim = 2 -train_label_key = scribble -valid_dim = 3 -test_dim = 3 -train_batch_size = 24 - -# data transforms -train_transform = [CustomTransform, PartialLabelToProbability] -valid_transform = [Rescale, LabelToProbability] -test_transform = [Rescale] - -CustomTransform_output_size = [256, 256] -Rescale_output_size = [256, 256] - - -[network] -# type of network -net_type = DBNet - -# number of class, required for segmentation task -class_num = 4 -in_chns = 1 -feature_chns = [16, 32, 64, 128, 256] -dropout = [0.05, 0.1, 0.2, 0.3, 0.5] - -[training] -# list of gpus -gpus = [0] - -loss_type = CrossEntropyLoss - -# for optimizers -optimizer = SGD -nesterov = False -learning_rate = 1e-2 -momentum = 0.9 -weight_decay = 1e-4 - -# for lr schedular -lr_scheduler = PolynomialLR -lr_power = 0.9 -early_stop_patience = 10000 - -ckpt_dir = model/acdc_dmsps - -# start iter -iter_start = 0 -iter_max = 30000 -iter_valid = 100 -iter_save = [10000, 20000, 30000] - -[weakly_supervised_learning] -method_name = DMSPS -regularize_w = 8 -rampup_start = 0 -rampup_end = 100 - -[testing] -# list of gpus -gpus = [0] - -# checkpoint mode can be [0-latest, 1-best, 2-specified] -ckpt_mode = 1 -dmsps_test_mode = 0 -output_dir = result/acdc_dmsps - -sliding_window_enable = False - diff --git a/config/acdc_dmsps_r4.cfg b/config/acdc_dmsps_r4.cfg deleted file mode 100644 index 4aa91f3..0000000 --- a/config/acdc_dmsps_r4.cfg +++ /dev/null @@ -1,78 +0,0 @@ -[dataset] -# tensor type (float or double) -tensor_type = float -task_type = seg -supervise_type = weak_sup - -train_dir = data/ACDC2017/ACDC_for2D -train_csv = data/ACDC2017/ACDC_for2D/train.csv -valid_csv = data/ACDC2017/ACDC_for2D/valid.csv -test_csv = data/ACDC2017/ACDC_for2D/trainvol.csv -train_dim = 2 -train_label_key = scribble_rlessd4 -valid_dim = 3 -test_dim = 3 -train_batch_size = 24 - -# data transforms -train_transform = [CustomTransform, PartialLabelToProbability] -valid_transform = [Rescale, LabelToProbability] -test_transform = [Rescale] - -CustomTransform_output_size = [256, 256] -Rescale_output_size = [256, 256] - - -[network] -# type of network -net_type = DBNet - -# number of class, required for segmentation task -class_num = 4 -in_chns = 1 -feature_chns = [16, 32, 64, 128, 256] -dropout = [0.05, 0.1, 0.2, 0.3, 0.5] - -[training] -# list of gpus -gpus = [0] - -loss_type = CrossEntropyLoss - -# for optimizers -optimizer = SGD -nesterov = False -learning_rate = 1e-2 -momentum = 0.9 -weight_decay = 1e-4 - -# for lr schedular -lr_scheduler = PolynomialLR -lr_power = 0.9 -early_stop_patience = 10000 - -ckpt_dir = model/acdc_dmsps_r4 - -# start iter -iter_start = 0 -iter_max = 30000 -iter_valid = 100 -iter_save = [10000, 20000, 30000] - -[weakly_supervised_learning] -method_name = DMSPS -regularize_w = 8 -rampup_start = 0 -rampup_end = 100 - -[testing] -# list of gpus -gpus = [0] - -# checkpoint mode can be [0-latest, 1-best, 2-specified] -ckpt_mode = 1 -dmsps_test_mode = 0 -output_dir = result/acdc_dmsps_r4 - -sliding_window_enable = False - diff --git a/config/acdc_dmsps_stage2.cfg b/config/acdc_dmsps_stage2.cfg deleted file mode 100644 index 43bee15..0000000 --- a/config/acdc_dmsps_stage2.cfg +++ /dev/null @@ -1,80 +0,0 @@ -[dataset] -# tensor type (float or double) -tensor_type = float -task_type = seg -supervise_type = weak_sup - -train_dir = data/ACDC2017/ACDC_for2D -train_csv = data/ACDC2017/ACDC_for2D/train_stage2.csv -valid_csv = data/ACDC2017/ACDC_for2D/valid.csv -test_csv = data/ACDC2017/ACDC_for2D/test.csv -train_dim = 2 -train_label_key = expanded_seeds -valid_dim = 3 -test_dim = 3 -train_batch_size = 24 - -# data transforms -train_transform = [CustomTransform, PartialLabelToProbability] -valid_transform = [Rescale, LabelToProbability] -test_transform = [Rescale] - -CustomTransform_output_size = [256, 256] -Rescale_output_size = [256, 256] - - -[network] -# type of network -net_type = DBNet - -# number of class, required for segmentation task -class_num = 4 -in_chns = 1 -feature_chns = [16, 32, 64, 128, 256] -dropout = [0.05, 0.1, 0.2, 0.3, 0.5] - -[training] -# list of gpus -gpus = [0] - -loss_type = CrossEntropyLoss -#CrossEntropyLoss - -# for optimizers -optimizer = Adam -learning_rate = 1e-4 -momentum = 0.9 -weight_decay = 1e-5 - -# for lr schedular -lr_scheduler = PolynomialLR -lr_power = 0.9 -early_stop_patience = 10000 - -ckpt_dir = model/acdc_dmsps_stage2 -ckpt_init_name = ../acdc_dmsps/acdc_dmsps_best.pt -ckpt_init_mode = 0 - -# start iter -iter_start = 0 -iter_max = 20000 -iter_valid = 100 -iter_save = [10000,20000] - -[weakly_supervised_learning] -method_name = DMSPS -regularize_w = 8 -rampup_start = 0 -rampup_end = 100 - -[testing] -# list of gpus -gpus = [0] - -# checkpoint mode can be [0-latest, 1-best, 2-specified] -ckpt_mode = 1 -dmsps_test_mode = 0 -output_dir = result/acdc_dmsps_stage2 - -sliding_window_enable = False - diff --git a/config/image_test_gt_seg.csv b/config/image_test_gt_seg.csv deleted file mode 100644 index e8f491b..0000000 --- a/config/image_test_gt_seg.csv +++ /dev/null @@ -1,31 +0,0 @@ -ground truth,segmentation -patient004_frame15_gt.nii.gz,patient004_frame15.nii.gz -patient012_frame13_gt.nii.gz,patient012_frame13.nii.gz -patient013_frame14_gt.nii.gz,patient013_frame14.nii.gz -patient014_frame01_gt.nii.gz,patient014_frame01.nii.gz -patient015_frame01_gt.nii.gz,patient015_frame01.nii.gz -patient020_frame11_gt.nii.gz,patient020_frame11.nii.gz -patient025_frame09_gt.nii.gz,patient025_frame09.nii.gz -patient030_frame01_gt.nii.gz,patient030_frame01.nii.gz -patient034_frame16_gt.nii.gz,patient034_frame16.nii.gz -patient036_frame01_gt.nii.gz,patient036_frame01.nii.gz -patient038_frame11_gt.nii.gz,patient038_frame11.nii.gz -patient040_frame13_gt.nii.gz,patient040_frame13.nii.gz -patient045_frame13_gt.nii.gz,patient045_frame13.nii.gz -patient053_frame01_gt.nii.gz,patient053_frame01.nii.gz -patient058_frame01_gt.nii.gz,patient058_frame01.nii.gz -patient064_frame12_gt.nii.gz,patient064_frame12.nii.gz -patient066_frame11_gt.nii.gz,patient066_frame11.nii.gz -patient072_frame11_gt.nii.gz,patient072_frame11.nii.gz -patient074_frame01_gt.nii.gz,patient074_frame01.nii.gz -patient075_frame06_gt.nii.gz,patient075_frame06.nii.gz -patient076_frame01_gt.nii.gz,patient076_frame01.nii.gz -patient081_frame01_gt.nii.gz,patient081_frame01.nii.gz -patient085_frame09_gt.nii.gz,patient085_frame09.nii.gz -patient086_frame01_gt.nii.gz,patient086_frame01.nii.gz -patient089_frame01_gt.nii.gz,patient089_frame01.nii.gz -patient089_frame10_gt.nii.gz,patient089_frame10.nii.gz -patient093_frame01_gt.nii.gz,patient093_frame01.nii.gz -patient094_frame01_gt.nii.gz,patient094_frame01.nii.gz -patient096_frame01_gt.nii.gz,patient096_frame01.nii.gz -patient098_frame01_gt.nii.gz,patient098_frame01.nii.gz diff --git a/data/ACDC2017/ACDC_for2D/test.csv b/data/ACDC2017/ACDC_for2D/test.csv deleted file mode 100644 index 1d83a26..0000000 --- a/data/ACDC2017/ACDC_for2D/test.csv +++ /dev/null @@ -1,31 +0,0 @@ -image -../ACDC/TestSet/images_N/patient004_frame15.nii.gz -../ACDC/TestSet/images_N/patient012_frame13.nii.gz -../ACDC/TestSet/images_N/patient013_frame14.nii.gz -../ACDC/TestSet/images_N/patient014_frame01.nii.gz -../ACDC/TestSet/images_N/patient015_frame01.nii.gz -../ACDC/TestSet/images_N/patient020_frame11.nii.gz -../ACDC/TestSet/images_N/patient025_frame09.nii.gz -../ACDC/TestSet/images_N/patient030_frame01.nii.gz -../ACDC/TestSet/images_N/patient034_frame16.nii.gz -../ACDC/TestSet/images_N/patient036_frame01.nii.gz -../ACDC/TestSet/images_N/patient038_frame11.nii.gz -../ACDC/TestSet/images_N/patient040_frame13.nii.gz -../ACDC/TestSet/images_N/patient045_frame13.nii.gz -../ACDC/TestSet/images_N/patient053_frame01.nii.gz -../ACDC/TestSet/images_N/patient058_frame01.nii.gz -../ACDC/TestSet/images_N/patient064_frame12.nii.gz -../ACDC/TestSet/images_N/patient066_frame11.nii.gz -../ACDC/TestSet/images_N/patient072_frame11.nii.gz -../ACDC/TestSet/images_N/patient074_frame01.nii.gz -../ACDC/TestSet/images_N/patient075_frame06.nii.gz -../ACDC/TestSet/images_N/patient076_frame01.nii.gz -../ACDC/TestSet/images_N/patient081_frame01.nii.gz -../ACDC/TestSet/images_N/patient085_frame09.nii.gz -../ACDC/TestSet/images_N/patient086_frame01.nii.gz -../ACDC/TestSet/images_N/patient089_frame01.nii.gz -../ACDC/TestSet/images_N/patient089_frame10.nii.gz -../ACDC/TestSet/images_N/patient093_frame01.nii.gz -../ACDC/TestSet/images_N/patient094_frame01.nii.gz -../ACDC/TestSet/images_N/patient096_frame01.nii.gz -../ACDC/TestSet/images_N/patient098_frame01.nii.gz diff --git a/data/ACDC2017/ACDC_for2D/test.txt b/data/ACDC2017/ACDC_for2D/test.txt deleted file mode 100644 index ce36422..0000000 --- a/data/ACDC2017/ACDC_for2D/test.txt +++ /dev/null @@ -1,30 +0,0 @@ -TestSet_volumes/patient004_frame15.h5 -TestSet_volumes/patient012_frame13.h5 -TestSet_volumes/patient013_frame14.h5 -TestSet_volumes/patient014_frame01.h5 -TestSet_volumes/patient015_frame01.h5 -TestSet_volumes/patient020_frame11.h5 -TestSet_volumes/patient025_frame09.h5 -TestSet_volumes/patient030_frame01.h5 -TestSet_volumes/patient034_frame16.h5 -TestSet_volumes/patient036_frame01.h5 -TestSet_volumes/patient038_frame11.h5 -TestSet_volumes/patient040_frame13.h5 -TestSet_volumes/patient045_frame13.h5 -TestSet_volumes/patient053_frame01.h5 -TestSet_volumes/patient058_frame01.h5 -TestSet_volumes/patient064_frame12.h5 -TestSet_volumes/patient066_frame11.h5 -TestSet_volumes/patient072_frame11.h5 -TestSet_volumes/patient074_frame01.h5 -TestSet_volumes/patient075_frame06.h5 -TestSet_volumes/patient076_frame01.h5 -TestSet_volumes/patient081_frame01.h5 -TestSet_volumes/patient085_frame09.h5 -TestSet_volumes/patient086_frame01.h5 -TestSet_volumes/patient089_frame01.h5 -TestSet_volumes/patient089_frame10.h5 -TestSet_volumes/patient093_frame01.h5 -TestSet_volumes/patient094_frame01.h5 -TestSet_volumes/patient096_frame01.h5 -TestSet_volumes/patient098_frame01.h5 diff --git a/data/ACDC2017/ACDC_for2D/train.csv b/data/ACDC2017/ACDC_for2D/train.csv deleted file mode 100644 index cca6051..0000000 --- a/data/ACDC2017/ACDC_for2D/train.csv +++ /dev/null @@ -1,1357 +0,0 @@ -image -train_slices/patient001_frame01_slice_0.h5 -train_slices/patient001_frame01_slice_1.h5 -train_slices/patient001_frame01_slice_2.h5 -train_slices/patient001_frame01_slice_3.h5 -train_slices/patient001_frame01_slice_4.h5 -train_slices/patient001_frame01_slice_5.h5 -train_slices/patient001_frame01_slice_6.h5 -train_slices/patient001_frame01_slice_7.h5 -train_slices/patient001_frame01_slice_8.h5 -train_slices/patient001_frame01_slice_9.h5 -train_slices/patient001_frame12_slice_0.h5 -train_slices/patient001_frame12_slice_1.h5 -train_slices/patient001_frame12_slice_2.h5 -train_slices/patient001_frame12_slice_3.h5 -train_slices/patient001_frame12_slice_4.h5 -train_slices/patient001_frame12_slice_5.h5 -train_slices/patient001_frame12_slice_6.h5 -train_slices/patient001_frame12_slice_7.h5 -train_slices/patient001_frame12_slice_8.h5 -train_slices/patient001_frame12_slice_9.h5 -train_slices/patient002_frame01_slice_0.h5 -train_slices/patient002_frame01_slice_1.h5 -train_slices/patient002_frame01_slice_2.h5 -train_slices/patient002_frame01_slice_3.h5 -train_slices/patient002_frame01_slice_4.h5 -train_slices/patient002_frame01_slice_5.h5 -train_slices/patient002_frame01_slice_6.h5 -train_slices/patient002_frame01_slice_7.h5 -train_slices/patient002_frame01_slice_8.h5 -train_slices/patient002_frame01_slice_9.h5 -train_slices/patient002_frame12_slice_0.h5 -train_slices/patient002_frame12_slice_1.h5 -train_slices/patient002_frame12_slice_2.h5 -train_slices/patient002_frame12_slice_3.h5 -train_slices/patient002_frame12_slice_4.h5 -train_slices/patient002_frame12_slice_5.h5 -train_slices/patient002_frame12_slice_6.h5 -train_slices/patient002_frame12_slice_7.h5 -train_slices/patient002_frame12_slice_8.h5 -train_slices/patient002_frame12_slice_9.h5 -train_slices/patient003_frame01_slice_0.h5 -train_slices/patient003_frame01_slice_1.h5 -train_slices/patient003_frame01_slice_2.h5 -train_slices/patient003_frame01_slice_3.h5 -train_slices/patient003_frame01_slice_4.h5 -train_slices/patient003_frame01_slice_5.h5 -train_slices/patient003_frame01_slice_6.h5 -train_slices/patient003_frame01_slice_7.h5 -train_slices/patient003_frame01_slice_8.h5 -train_slices/patient003_frame01_slice_9.h5 -train_slices/patient003_frame15_slice_0.h5 -train_slices/patient003_frame15_slice_1.h5 -train_slices/patient003_frame15_slice_2.h5 -train_slices/patient003_frame15_slice_3.h5 -train_slices/patient003_frame15_slice_4.h5 -train_slices/patient003_frame15_slice_5.h5 -train_slices/patient003_frame15_slice_6.h5 -train_slices/patient003_frame15_slice_7.h5 -train_slices/patient003_frame15_slice_8.h5 -train_slices/patient003_frame15_slice_9.h5 -train_slices/patient004_frame01_slice_0.h5 -train_slices/patient004_frame01_slice_1.h5 -train_slices/patient004_frame01_slice_2.h5 -train_slices/patient004_frame01_slice_3.h5 -train_slices/patient004_frame01_slice_4.h5 -train_slices/patient004_frame01_slice_5.h5 -train_slices/patient004_frame01_slice_6.h5 -train_slices/patient004_frame01_slice_7.h5 -train_slices/patient004_frame01_slice_8.h5 -train_slices/patient004_frame01_slice_9.h5 -train_slices/patient005_frame01_slice_0.h5 -train_slices/patient005_frame01_slice_1.h5 -train_slices/patient005_frame01_slice_2.h5 -train_slices/patient005_frame01_slice_3.h5 -train_slices/patient005_frame01_slice_4.h5 -train_slices/patient005_frame01_slice_5.h5 -train_slices/patient005_frame01_slice_6.h5 -train_slices/patient005_frame01_slice_7.h5 -train_slices/patient005_frame01_slice_8.h5 -train_slices/patient005_frame01_slice_9.h5 -train_slices/patient005_frame13_slice_0.h5 -train_slices/patient005_frame13_slice_1.h5 -train_slices/patient005_frame13_slice_2.h5 -train_slices/patient005_frame13_slice_3.h5 -train_slices/patient005_frame13_slice_4.h5 -train_slices/patient005_frame13_slice_5.h5 -train_slices/patient005_frame13_slice_6.h5 -train_slices/patient005_frame13_slice_7.h5 -train_slices/patient005_frame13_slice_8.h5 -train_slices/patient005_frame13_slice_9.h5 -train_slices/patient006_frame16_slice_0.h5 -train_slices/patient006_frame16_slice_1.h5 -train_slices/patient006_frame16_slice_10.h5 -train_slices/patient006_frame16_slice_2.h5 -train_slices/patient006_frame16_slice_3.h5 -train_slices/patient006_frame16_slice_4.h5 -train_slices/patient006_frame16_slice_5.h5 -train_slices/patient006_frame16_slice_6.h5 -train_slices/patient006_frame16_slice_7.h5 -train_slices/patient006_frame16_slice_8.h5 -train_slices/patient006_frame16_slice_9.h5 -train_slices/patient007_frame01_slice_0.h5 -train_slices/patient007_frame01_slice_1.h5 -train_slices/patient007_frame01_slice_2.h5 -train_slices/patient007_frame01_slice_3.h5 -train_slices/patient007_frame01_slice_4.h5 -train_slices/patient007_frame01_slice_5.h5 -train_slices/patient007_frame01_slice_6.h5 -train_slices/patient007_frame01_slice_7.h5 -train_slices/patient007_frame01_slice_8.h5 -train_slices/patient007_frame01_slice_9.h5 -train_slices/patient007_frame07_slice_0.h5 -train_slices/patient007_frame07_slice_1.h5 -train_slices/patient007_frame07_slice_2.h5 -train_slices/patient007_frame07_slice_3.h5 -train_slices/patient007_frame07_slice_4.h5 -train_slices/patient007_frame07_slice_5.h5 -train_slices/patient007_frame07_slice_6.h5 -train_slices/patient007_frame07_slice_7.h5 -train_slices/patient007_frame07_slice_8.h5 -train_slices/patient007_frame07_slice_9.h5 -train_slices/patient008_frame13_slice_0.h5 -train_slices/patient008_frame13_slice_1.h5 -train_slices/patient008_frame13_slice_2.h5 -train_slices/patient008_frame13_slice_3.h5 -train_slices/patient008_frame13_slice_4.h5 -train_slices/patient008_frame13_slice_5.h5 -train_slices/patient008_frame13_slice_6.h5 -train_slices/patient008_frame13_slice_7.h5 -train_slices/patient008_frame13_slice_8.h5 -train_slices/patient008_frame13_slice_9.h5 -train_slices/patient009_frame01_slice_0.h5 -train_slices/patient009_frame01_slice_1.h5 -train_slices/patient009_frame01_slice_2.h5 -train_slices/patient009_frame01_slice_3.h5 -train_slices/patient009_frame01_slice_4.h5 -train_slices/patient009_frame01_slice_5.h5 -train_slices/patient009_frame01_slice_6.h5 -train_slices/patient009_frame01_slice_7.h5 -train_slices/patient009_frame01_slice_8.h5 -train_slices/patient009_frame01_slice_9.h5 -train_slices/patient010_frame01_slice_0.h5 -train_slices/patient010_frame01_slice_1.h5 -train_slices/patient010_frame01_slice_2.h5 -train_slices/patient010_frame01_slice_3.h5 -train_slices/patient010_frame01_slice_4.h5 -train_slices/patient010_frame01_slice_5.h5 -train_slices/patient010_frame01_slice_6.h5 -train_slices/patient010_frame01_slice_7.h5 -train_slices/patient010_frame01_slice_8.h5 -train_slices/patient010_frame01_slice_9.h5 -train_slices/patient010_frame13_slice_0.h5 -train_slices/patient010_frame13_slice_1.h5 -train_slices/patient010_frame13_slice_2.h5 -train_slices/patient010_frame13_slice_3.h5 -train_slices/patient010_frame13_slice_4.h5 -train_slices/patient010_frame13_slice_5.h5 -train_slices/patient010_frame13_slice_6.h5 -train_slices/patient010_frame13_slice_7.h5 -train_slices/patient010_frame13_slice_8.h5 -train_slices/patient010_frame13_slice_9.h5 -train_slices/patient011_frame01_slice_0.h5 -train_slices/patient011_frame01_slice_1.h5 -train_slices/patient011_frame01_slice_2.h5 -train_slices/patient011_frame01_slice_3.h5 -train_slices/patient011_frame01_slice_4.h5 -train_slices/patient011_frame01_slice_5.h5 -train_slices/patient011_frame01_slice_6.h5 -train_slices/patient011_frame01_slice_7.h5 -train_slices/patient011_frame01_slice_8.h5 -train_slices/patient011_frame08_slice_0.h5 -train_slices/patient011_frame08_slice_1.h5 -train_slices/patient011_frame08_slice_2.h5 -train_slices/patient011_frame08_slice_3.h5 -train_slices/patient011_frame08_slice_4.h5 -train_slices/patient011_frame08_slice_5.h5 -train_slices/patient011_frame08_slice_6.h5 -train_slices/patient011_frame08_slice_7.h5 -train_slices/patient011_frame08_slice_8.h5 -train_slices/patient012_frame01_slice_0.h5 -train_slices/patient012_frame01_slice_1.h5 -train_slices/patient012_frame01_slice_2.h5 -train_slices/patient012_frame01_slice_3.h5 -train_slices/patient012_frame01_slice_4.h5 -train_slices/patient012_frame01_slice_5.h5 -train_slices/patient012_frame01_slice_6.h5 -train_slices/patient012_frame01_slice_7.h5 -train_slices/patient012_frame01_slice_8.h5 -train_slices/patient012_frame01_slice_9.h5 -train_slices/patient013_frame01_slice_0.h5 -train_slices/patient013_frame01_slice_1.h5 -train_slices/patient013_frame01_slice_2.h5 -train_slices/patient013_frame01_slice_3.h5 -train_slices/patient013_frame01_slice_4.h5 -train_slices/patient013_frame01_slice_5.h5 -train_slices/patient013_frame01_slice_6.h5 -train_slices/patient013_frame01_slice_7.h5 -train_slices/patient013_frame01_slice_8.h5 -train_slices/patient013_frame01_slice_9.h5 -train_slices/patient014_frame13_slice_0.h5 -train_slices/patient014_frame13_slice_1.h5 -train_slices/patient014_frame13_slice_2.h5 -train_slices/patient014_frame13_slice_3.h5 -train_slices/patient014_frame13_slice_4.h5 -train_slices/patient014_frame13_slice_5.h5 -train_slices/patient014_frame13_slice_6.h5 -train_slices/patient014_frame13_slice_7.h5 -train_slices/patient014_frame13_slice_8.h5 -train_slices/patient014_frame13_slice_9.h5 -train_slices/patient015_frame10_slice_0.h5 -train_slices/patient015_frame10_slice_1.h5 -train_slices/patient015_frame10_slice_2.h5 -train_slices/patient015_frame10_slice_3.h5 -train_slices/patient015_frame10_slice_4.h5 -train_slices/patient015_frame10_slice_5.h5 -train_slices/patient015_frame10_slice_6.h5 -train_slices/patient015_frame10_slice_7.h5 -train_slices/patient015_frame10_slice_8.h5 -train_slices/patient016_frame12_slice_0.h5 -train_slices/patient016_frame12_slice_1.h5 -train_slices/patient016_frame12_slice_2.h5 -train_slices/patient016_frame12_slice_3.h5 -train_slices/patient016_frame12_slice_4.h5 -train_slices/patient016_frame12_slice_5.h5 -train_slices/patient016_frame12_slice_6.h5 -train_slices/patient016_frame12_slice_7.h5 -train_slices/patient016_frame12_slice_8.h5 -train_slices/patient016_frame12_slice_9.h5 -train_slices/patient017_frame01_slice_0.h5 -train_slices/patient017_frame01_slice_1.h5 -train_slices/patient017_frame01_slice_2.h5 -train_slices/patient017_frame01_slice_3.h5 -train_slices/patient017_frame01_slice_4.h5 -train_slices/patient017_frame01_slice_5.h5 -train_slices/patient017_frame01_slice_6.h5 -train_slices/patient017_frame01_slice_7.h5 -train_slices/patient017_frame01_slice_8.h5 -train_slices/patient017_frame09_slice_0.h5 -train_slices/patient017_frame09_slice_1.h5 -train_slices/patient017_frame09_slice_2.h5 -train_slices/patient017_frame09_slice_3.h5 -train_slices/patient017_frame09_slice_4.h5 -train_slices/patient017_frame09_slice_5.h5 -train_slices/patient017_frame09_slice_6.h5 -train_slices/patient017_frame09_slice_7.h5 -train_slices/patient017_frame09_slice_8.h5 -train_slices/patient018_frame01_slice_0.h5 -train_slices/patient018_frame01_slice_1.h5 -train_slices/patient018_frame01_slice_2.h5 -train_slices/patient018_frame01_slice_3.h5 -train_slices/patient018_frame01_slice_4.h5 -train_slices/patient018_frame01_slice_5.h5 -train_slices/patient018_frame01_slice_6.h5 -train_slices/patient018_frame01_slice_7.h5 -train_slices/patient018_frame10_slice_0.h5 -train_slices/patient018_frame10_slice_1.h5 -train_slices/patient018_frame10_slice_2.h5 -train_slices/patient018_frame10_slice_3.h5 -train_slices/patient018_frame10_slice_4.h5 -train_slices/patient018_frame10_slice_5.h5 -train_slices/patient018_frame10_slice_6.h5 -train_slices/patient018_frame10_slice_7.h5 -train_slices/patient019_frame11_slice_0.h5 -train_slices/patient019_frame11_slice_1.h5 -train_slices/patient019_frame11_slice_10.h5 -train_slices/patient019_frame11_slice_2.h5 -train_slices/patient019_frame11_slice_3.h5 -train_slices/patient019_frame11_slice_4.h5 -train_slices/patient019_frame11_slice_5.h5 -train_slices/patient019_frame11_slice_6.h5 -train_slices/patient019_frame11_slice_7.h5 -train_slices/patient019_frame11_slice_8.h5 -train_slices/patient019_frame11_slice_9.h5 -train_slices/patient020_frame01_slice_0.h5 -train_slices/patient020_frame01_slice_1.h5 -train_slices/patient020_frame01_slice_2.h5 -train_slices/patient020_frame01_slice_3.h5 -train_slices/patient020_frame01_slice_4.h5 -train_slices/patient020_frame01_slice_5.h5 -train_slices/patient020_frame01_slice_6.h5 -train_slices/patient020_frame01_slice_7.h5 -train_slices/patient021_frame01_slice_0.h5 -train_slices/patient021_frame01_slice_1.h5 -train_slices/patient021_frame01_slice_2.h5 -train_slices/patient021_frame01_slice_3.h5 -train_slices/patient021_frame01_slice_4.h5 -train_slices/patient021_frame01_slice_5.h5 -train_slices/patient021_frame01_slice_6.h5 -train_slices/patient021_frame01_slice_7.h5 -train_slices/patient021_frame01_slice_8.h5 -train_slices/patient021_frame01_slice_9.h5 -train_slices/patient021_frame13_slice_0.h5 -train_slices/patient021_frame13_slice_1.h5 -train_slices/patient021_frame13_slice_2.h5 -train_slices/patient021_frame13_slice_3.h5 -train_slices/patient021_frame13_slice_4.h5 -train_slices/patient021_frame13_slice_5.h5 -train_slices/patient021_frame13_slice_6.h5 -train_slices/patient021_frame13_slice_7.h5 -train_slices/patient021_frame13_slice_8.h5 -train_slices/patient021_frame13_slice_9.h5 -train_slices/patient022_frame01_slice_0.h5 -train_slices/patient022_frame01_slice_1.h5 -train_slices/patient022_frame01_slice_2.h5 -train_slices/patient022_frame01_slice_3.h5 -train_slices/patient022_frame01_slice_4.h5 -train_slices/patient022_frame01_slice_5.h5 -train_slices/patient022_frame01_slice_6.h5 -train_slices/patient022_frame11_slice_0.h5 -train_slices/patient022_frame11_slice_1.h5 -train_slices/patient022_frame11_slice_2.h5 -train_slices/patient022_frame11_slice_3.h5 -train_slices/patient022_frame11_slice_4.h5 -train_slices/patient022_frame11_slice_5.h5 -train_slices/patient022_frame11_slice_6.h5 -train_slices/patient023_frame01_slice_0.h5 -train_slices/patient023_frame01_slice_1.h5 -train_slices/patient023_frame01_slice_2.h5 -train_slices/patient023_frame01_slice_3.h5 -train_slices/patient023_frame01_slice_4.h5 -train_slices/patient023_frame01_slice_5.h5 -train_slices/patient023_frame01_slice_6.h5 -train_slices/patient023_frame01_slice_7.h5 -train_slices/patient023_frame01_slice_8.h5 -train_slices/patient024_frame09_slice_0.h5 -train_slices/patient024_frame09_slice_1.h5 -train_slices/patient024_frame09_slice_2.h5 -train_slices/patient024_frame09_slice_3.h5 -train_slices/patient024_frame09_slice_4.h5 -train_slices/patient024_frame09_slice_5.h5 -train_slices/patient024_frame09_slice_6.h5 -train_slices/patient024_frame09_slice_7.h5 -train_slices/patient025_frame01_slice_0.h5 -train_slices/patient025_frame01_slice_1.h5 -train_slices/patient025_frame01_slice_2.h5 -train_slices/patient025_frame01_slice_3.h5 -train_slices/patient025_frame01_slice_4.h5 -train_slices/patient025_frame01_slice_5.h5 -train_slices/patient025_frame01_slice_6.h5 -train_slices/patient025_frame01_slice_7.h5 -train_slices/patient025_frame01_slice_8.h5 -train_slices/patient026_frame01_slice_0.h5 -train_slices/patient026_frame01_slice_1.h5 -train_slices/patient026_frame01_slice_2.h5 -train_slices/patient026_frame01_slice_3.h5 -train_slices/patient026_frame01_slice_4.h5 -train_slices/patient026_frame01_slice_5.h5 -train_slices/patient026_frame01_slice_6.h5 -train_slices/patient026_frame01_slice_7.h5 -train_slices/patient026_frame01_slice_8.h5 -train_slices/patient026_frame01_slice_9.h5 -train_slices/patient026_frame12_slice_0.h5 -train_slices/patient026_frame12_slice_1.h5 -train_slices/patient026_frame12_slice_2.h5 -train_slices/patient026_frame12_slice_3.h5 -train_slices/patient026_frame12_slice_4.h5 -train_slices/patient026_frame12_slice_5.h5 -train_slices/patient026_frame12_slice_6.h5 -train_slices/patient026_frame12_slice_7.h5 -train_slices/patient026_frame12_slice_8.h5 -train_slices/patient026_frame12_slice_9.h5 -train_slices/patient027_frame01_slice_0.h5 -train_slices/patient027_frame01_slice_1.h5 -train_slices/patient027_frame01_slice_2.h5 -train_slices/patient027_frame01_slice_3.h5 -train_slices/patient027_frame01_slice_4.h5 -train_slices/patient027_frame01_slice_5.h5 -train_slices/patient027_frame01_slice_6.h5 -train_slices/patient027_frame01_slice_7.h5 -train_slices/patient027_frame01_slice_8.h5 -train_slices/patient027_frame01_slice_9.h5 -train_slices/patient027_frame11_slice_0.h5 -train_slices/patient027_frame11_slice_1.h5 -train_slices/patient027_frame11_slice_2.h5 -train_slices/patient027_frame11_slice_3.h5 -train_slices/patient027_frame11_slice_4.h5 -train_slices/patient027_frame11_slice_5.h5 -train_slices/patient027_frame11_slice_6.h5 -train_slices/patient027_frame11_slice_7.h5 -train_slices/patient027_frame11_slice_8.h5 -train_slices/patient027_frame11_slice_9.h5 -train_slices/patient028_frame01_slice_0.h5 -train_slices/patient028_frame01_slice_1.h5 -train_slices/patient028_frame01_slice_2.h5 -train_slices/patient028_frame01_slice_3.h5 -train_slices/patient028_frame01_slice_4.h5 -train_slices/patient028_frame01_slice_5.h5 -train_slices/patient028_frame01_slice_6.h5 -train_slices/patient028_frame01_slice_7.h5 -train_slices/patient028_frame01_slice_8.h5 -train_slices/patient028_frame01_slice_9.h5 -train_slices/patient028_frame09_slice_0.h5 -train_slices/patient028_frame09_slice_1.h5 -train_slices/patient028_frame09_slice_2.h5 -train_slices/patient028_frame09_slice_3.h5 -train_slices/patient028_frame09_slice_4.h5 -train_slices/patient028_frame09_slice_5.h5 -train_slices/patient028_frame09_slice_6.h5 -train_slices/patient028_frame09_slice_7.h5 -train_slices/patient028_frame09_slice_8.h5 -train_slices/patient028_frame09_slice_9.h5 -train_slices/patient029_frame12_slice_0.h5 -train_slices/patient029_frame12_slice_1.h5 -train_slices/patient029_frame12_slice_10.h5 -train_slices/patient029_frame12_slice_2.h5 -train_slices/patient029_frame12_slice_3.h5 -train_slices/patient029_frame12_slice_4.h5 -train_slices/patient029_frame12_slice_5.h5 -train_slices/patient029_frame12_slice_6.h5 -train_slices/patient029_frame12_slice_7.h5 -train_slices/patient029_frame12_slice_8.h5 -train_slices/patient029_frame12_slice_9.h5 -train_slices/patient030_frame12_slice_0.h5 -train_slices/patient030_frame12_slice_1.h5 -train_slices/patient030_frame12_slice_2.h5 -train_slices/patient030_frame12_slice_3.h5 -train_slices/patient030_frame12_slice_4.h5 -train_slices/patient030_frame12_slice_5.h5 -train_slices/patient030_frame12_slice_6.h5 -train_slices/patient030_frame12_slice_7.h5 -train_slices/patient030_frame12_slice_8.h5 -train_slices/patient030_frame12_slice_9.h5 -train_slices/patient031_frame01_slice_0.h5 -train_slices/patient031_frame01_slice_1.h5 -train_slices/patient031_frame01_slice_2.h5 -train_slices/patient031_frame01_slice_3.h5 -train_slices/patient031_frame01_slice_4.h5 -train_slices/patient031_frame01_slice_5.h5 -train_slices/patient031_frame01_slice_6.h5 -train_slices/patient031_frame01_slice_7.h5 -train_slices/patient031_frame01_slice_8.h5 -train_slices/patient031_frame01_slice_9.h5 -train_slices/patient032_frame12_slice_0.h5 -train_slices/patient032_frame12_slice_1.h5 -train_slices/patient032_frame12_slice_2.h5 -train_slices/patient032_frame12_slice_3.h5 -train_slices/patient032_frame12_slice_4.h5 -train_slices/patient032_frame12_slice_5.h5 -train_slices/patient032_frame12_slice_6.h5 -train_slices/patient032_frame12_slice_7.h5 -train_slices/patient032_frame12_slice_8.h5 -train_slices/patient032_frame12_slice_9.h5 -train_slices/patient033_frame01_slice_0.h5 -train_slices/patient033_frame01_slice_1.h5 -train_slices/patient033_frame01_slice_2.h5 -train_slices/patient033_frame01_slice_3.h5 -train_slices/patient033_frame01_slice_4.h5 -train_slices/patient033_frame01_slice_5.h5 -train_slices/patient033_frame01_slice_6.h5 -train_slices/patient033_frame01_slice_7.h5 -train_slices/patient033_frame01_slice_8.h5 -train_slices/patient033_frame01_slice_9.h5 -train_slices/patient033_frame14_slice_0.h5 -train_slices/patient033_frame14_slice_1.h5 -train_slices/patient033_frame14_slice_2.h5 -train_slices/patient033_frame14_slice_3.h5 -train_slices/patient033_frame14_slice_4.h5 -train_slices/patient033_frame14_slice_5.h5 -train_slices/patient033_frame14_slice_6.h5 -train_slices/patient033_frame14_slice_7.h5 -train_slices/patient033_frame14_slice_8.h5 -train_slices/patient033_frame14_slice_9.h5 -train_slices/patient034_frame01_slice_0.h5 -train_slices/patient034_frame01_slice_1.h5 -train_slices/patient034_frame01_slice_2.h5 -train_slices/patient034_frame01_slice_3.h5 -train_slices/patient034_frame01_slice_4.h5 -train_slices/patient034_frame01_slice_5.h5 -train_slices/patient034_frame01_slice_6.h5 -train_slices/patient034_frame01_slice_7.h5 -train_slices/patient034_frame01_slice_8.h5 -train_slices/patient034_frame01_slice_9.h5 -train_slices/patient035_frame01_slice_0.h5 -train_slices/patient035_frame01_slice_1.h5 -train_slices/patient035_frame01_slice_10.h5 -train_slices/patient035_frame01_slice_11.h5 -train_slices/patient035_frame01_slice_12.h5 -train_slices/patient035_frame01_slice_2.h5 -train_slices/patient035_frame01_slice_3.h5 -train_slices/patient035_frame01_slice_4.h5 -train_slices/patient035_frame01_slice_5.h5 -train_slices/patient035_frame01_slice_6.h5 -train_slices/patient035_frame01_slice_7.h5 -train_slices/patient035_frame01_slice_8.h5 -train_slices/patient035_frame01_slice_9.h5 -train_slices/patient035_frame11_slice_0.h5 -train_slices/patient035_frame11_slice_1.h5 -train_slices/patient035_frame11_slice_10.h5 -train_slices/patient035_frame11_slice_11.h5 -train_slices/patient035_frame11_slice_12.h5 -train_slices/patient035_frame11_slice_2.h5 -train_slices/patient035_frame11_slice_3.h5 -train_slices/patient035_frame11_slice_4.h5 -train_slices/patient035_frame11_slice_5.h5 -train_slices/patient035_frame11_slice_6.h5 -train_slices/patient035_frame11_slice_7.h5 -train_slices/patient035_frame11_slice_8.h5 -train_slices/patient035_frame11_slice_9.h5 -train_slices/patient036_frame12_slice_0.h5 -train_slices/patient036_frame12_slice_1.h5 -train_slices/patient036_frame12_slice_2.h5 -train_slices/patient036_frame12_slice_3.h5 -train_slices/patient036_frame12_slice_4.h5 -train_slices/patient036_frame12_slice_5.h5 -train_slices/patient036_frame12_slice_6.h5 -train_slices/patient036_frame12_slice_7.h5 -train_slices/patient037_frame01_slice_0.h5 -train_slices/patient037_frame01_slice_1.h5 -train_slices/patient037_frame01_slice_2.h5 -train_slices/patient037_frame01_slice_3.h5 -train_slices/patient037_frame01_slice_4.h5 -train_slices/patient037_frame01_slice_5.h5 -train_slices/patient037_frame01_slice_6.h5 -train_slices/patient037_frame12_slice_0.h5 -train_slices/patient037_frame12_slice_1.h5 -train_slices/patient037_frame12_slice_2.h5 -train_slices/patient037_frame12_slice_3.h5 -train_slices/patient037_frame12_slice_4.h5 -train_slices/patient037_frame12_slice_5.h5 -train_slices/patient037_frame12_slice_6.h5 -train_slices/patient038_frame01_slice_0.h5 -train_slices/patient038_frame01_slice_1.h5 -train_slices/patient038_frame01_slice_2.h5 -train_slices/patient038_frame01_slice_3.h5 -train_slices/patient038_frame01_slice_4.h5 -train_slices/patient038_frame01_slice_5.h5 -train_slices/patient038_frame01_slice_6.h5 -train_slices/patient038_frame01_slice_7.h5 -train_slices/patient039_frame01_slice_0.h5 -train_slices/patient039_frame01_slice_1.h5 -train_slices/patient039_frame01_slice_2.h5 -train_slices/patient039_frame01_slice_3.h5 -train_slices/patient039_frame01_slice_4.h5 -train_slices/patient039_frame01_slice_5.h5 -train_slices/patient039_frame01_slice_6.h5 -train_slices/patient039_frame01_slice_7.h5 -train_slices/patient039_frame01_slice_8.h5 -train_slices/patient039_frame10_slice_0.h5 -train_slices/patient039_frame10_slice_1.h5 -train_slices/patient039_frame10_slice_2.h5 -train_slices/patient039_frame10_slice_3.h5 -train_slices/patient039_frame10_slice_4.h5 -train_slices/patient039_frame10_slice_5.h5 -train_slices/patient039_frame10_slice_6.h5 -train_slices/patient039_frame10_slice_7.h5 -train_slices/patient039_frame10_slice_8.h5 -train_slices/patient040_frame01_slice_0.h5 -train_slices/patient040_frame01_slice_1.h5 -train_slices/patient040_frame01_slice_2.h5 -train_slices/patient040_frame01_slice_3.h5 -train_slices/patient040_frame01_slice_4.h5 -train_slices/patient040_frame01_slice_5.h5 -train_slices/patient040_frame01_slice_6.h5 -train_slices/patient040_frame01_slice_7.h5 -train_slices/patient040_frame01_slice_8.h5 -train_slices/patient040_frame01_slice_9.h5 -train_slices/patient041_frame01_slice_0.h5 -train_slices/patient041_frame01_slice_1.h5 -train_slices/patient041_frame01_slice_2.h5 -train_slices/patient041_frame01_slice_3.h5 -train_slices/patient041_frame01_slice_4.h5 -train_slices/patient041_frame01_slice_5.h5 -train_slices/patient041_frame11_slice_0.h5 -train_slices/patient041_frame11_slice_1.h5 -train_slices/patient041_frame11_slice_2.h5 -train_slices/patient041_frame11_slice_3.h5 -train_slices/patient041_frame11_slice_4.h5 -train_slices/patient041_frame11_slice_5.h5 -train_slices/patient042_frame01_slice_0.h5 -train_slices/patient042_frame01_slice_1.h5 -train_slices/patient042_frame01_slice_2.h5 -train_slices/patient042_frame01_slice_3.h5 -train_slices/patient042_frame01_slice_4.h5 -train_slices/patient042_frame01_slice_5.h5 -train_slices/patient042_frame01_slice_6.h5 -train_slices/patient042_frame01_slice_7.h5 -train_slices/patient042_frame01_slice_8.h5 -train_slices/patient042_frame16_slice_0.h5 -train_slices/patient042_frame16_slice_1.h5 -train_slices/patient042_frame16_slice_2.h5 -train_slices/patient042_frame16_slice_3.h5 -train_slices/patient042_frame16_slice_4.h5 -train_slices/patient042_frame16_slice_5.h5 -train_slices/patient042_frame16_slice_6.h5 -train_slices/patient042_frame16_slice_7.h5 -train_slices/patient042_frame16_slice_8.h5 -train_slices/patient043_frame01_slice_0.h5 -train_slices/patient043_frame01_slice_1.h5 -train_slices/patient043_frame01_slice_10.h5 -train_slices/patient043_frame01_slice_11.h5 -train_slices/patient043_frame01_slice_2.h5 -train_slices/patient043_frame01_slice_3.h5 -train_slices/patient043_frame01_slice_4.h5 -train_slices/patient043_frame01_slice_5.h5 -train_slices/patient043_frame01_slice_6.h5 -train_slices/patient043_frame01_slice_7.h5 -train_slices/patient043_frame01_slice_8.h5 -train_slices/patient043_frame01_slice_9.h5 -train_slices/patient043_frame07_slice_0.h5 -train_slices/patient043_frame07_slice_1.h5 -train_slices/patient043_frame07_slice_10.h5 -train_slices/patient043_frame07_slice_11.h5 -train_slices/patient043_frame07_slice_2.h5 -train_slices/patient043_frame07_slice_3.h5 -train_slices/patient043_frame07_slice_4.h5 -train_slices/patient043_frame07_slice_5.h5 -train_slices/patient043_frame07_slice_6.h5 -train_slices/patient043_frame07_slice_7.h5 -train_slices/patient043_frame07_slice_8.h5 -train_slices/patient043_frame07_slice_9.h5 -train_slices/patient044_frame01_slice_0.h5 -train_slices/patient044_frame01_slice_1.h5 -train_slices/patient044_frame01_slice_2.h5 -train_slices/patient044_frame01_slice_3.h5 -train_slices/patient044_frame01_slice_4.h5 -train_slices/patient044_frame01_slice_5.h5 -train_slices/patient044_frame01_slice_6.h5 -train_slices/patient044_frame01_slice_7.h5 -train_slices/patient044_frame01_slice_8.h5 -train_slices/patient044_frame11_slice_0.h5 -train_slices/patient044_frame11_slice_1.h5 -train_slices/patient044_frame11_slice_2.h5 -train_slices/patient044_frame11_slice_3.h5 -train_slices/patient044_frame11_slice_4.h5 -train_slices/patient044_frame11_slice_5.h5 -train_slices/patient044_frame11_slice_6.h5 -train_slices/patient044_frame11_slice_7.h5 -train_slices/patient044_frame11_slice_8.h5 -train_slices/patient045_frame01_slice_0.h5 -train_slices/patient045_frame01_slice_1.h5 -train_slices/patient045_frame01_slice_2.h5 -train_slices/patient045_frame01_slice_3.h5 -train_slices/patient045_frame01_slice_4.h5 -train_slices/patient045_frame01_slice_5.h5 -train_slices/patient045_frame01_slice_6.h5 -train_slices/patient045_frame01_slice_7.h5 -train_slices/patient046_frame01_slice_0.h5 -train_slices/patient046_frame01_slice_1.h5 -train_slices/patient046_frame01_slice_2.h5 -train_slices/patient046_frame01_slice_3.h5 -train_slices/patient046_frame01_slice_4.h5 -train_slices/patient046_frame01_slice_5.h5 -train_slices/patient046_frame01_slice_6.h5 -train_slices/patient046_frame01_slice_7.h5 -train_slices/patient046_frame01_slice_8.h5 -train_slices/patient046_frame10_slice_0.h5 -train_slices/patient046_frame10_slice_1.h5 -train_slices/patient046_frame10_slice_2.h5 -train_slices/patient046_frame10_slice_3.h5 -train_slices/patient046_frame10_slice_4.h5 -train_slices/patient046_frame10_slice_5.h5 -train_slices/patient046_frame10_slice_6.h5 -train_slices/patient046_frame10_slice_7.h5 -train_slices/patient046_frame10_slice_8.h5 -train_slices/patient047_frame01_slice_0.h5 -train_slices/patient047_frame01_slice_1.h5 -train_slices/patient047_frame01_slice_2.h5 -train_slices/patient047_frame01_slice_3.h5 -train_slices/patient047_frame01_slice_4.h5 -train_slices/patient047_frame01_slice_5.h5 -train_slices/patient047_frame01_slice_6.h5 -train_slices/patient047_frame01_slice_7.h5 -train_slices/patient047_frame01_slice_8.h5 -train_slices/patient048_frame01_slice_0.h5 -train_slices/patient048_frame01_slice_1.h5 -train_slices/patient048_frame01_slice_2.h5 -train_slices/patient048_frame01_slice_3.h5 -train_slices/patient048_frame01_slice_4.h5 -train_slices/patient048_frame01_slice_5.h5 -train_slices/patient048_frame01_slice_6.h5 -train_slices/patient048_frame01_slice_7.h5 -train_slices/patient049_frame01_slice_0.h5 -train_slices/patient049_frame01_slice_1.h5 -train_slices/patient049_frame01_slice_2.h5 -train_slices/patient049_frame01_slice_3.h5 -train_slices/patient049_frame01_slice_4.h5 -train_slices/patient049_frame01_slice_5.h5 -train_slices/patient049_frame01_slice_6.h5 -train_slices/patient049_frame11_slice_0.h5 -train_slices/patient049_frame11_slice_1.h5 -train_slices/patient049_frame11_slice_2.h5 -train_slices/patient049_frame11_slice_3.h5 -train_slices/patient049_frame11_slice_4.h5 -train_slices/patient049_frame11_slice_5.h5 -train_slices/patient049_frame11_slice_6.h5 -train_slices/patient050_frame01_slice_0.h5 -train_slices/patient050_frame01_slice_1.h5 -train_slices/patient050_frame01_slice_2.h5 -train_slices/patient050_frame01_slice_3.h5 -train_slices/patient050_frame01_slice_4.h5 -train_slices/patient050_frame01_slice_5.h5 -train_slices/patient050_frame01_slice_6.h5 -train_slices/patient050_frame01_slice_7.h5 -train_slices/patient050_frame01_slice_8.h5 -train_slices/patient050_frame01_slice_9.h5 -train_slices/patient050_frame12_slice_0.h5 -train_slices/patient050_frame12_slice_1.h5 -train_slices/patient050_frame12_slice_2.h5 -train_slices/patient050_frame12_slice_3.h5 -train_slices/patient050_frame12_slice_4.h5 -train_slices/patient050_frame12_slice_5.h5 -train_slices/patient050_frame12_slice_6.h5 -train_slices/patient050_frame12_slice_7.h5 -train_slices/patient050_frame12_slice_8.h5 -train_slices/patient050_frame12_slice_9.h5 -train_slices/patient051_frame01_slice_0.h5 -train_slices/patient051_frame01_slice_1.h5 -train_slices/patient051_frame01_slice_2.h5 -train_slices/patient051_frame01_slice_3.h5 -train_slices/patient051_frame01_slice_4.h5 -train_slices/patient051_frame01_slice_5.h5 -train_slices/patient051_frame01_slice_6.h5 -train_slices/patient051_frame01_slice_7.h5 -train_slices/patient051_frame01_slice_8.h5 -train_slices/patient051_frame01_slice_9.h5 -train_slices/patient051_frame11_slice_0.h5 -train_slices/patient051_frame11_slice_1.h5 -train_slices/patient051_frame11_slice_2.h5 -train_slices/patient051_frame11_slice_3.h5 -train_slices/patient051_frame11_slice_4.h5 -train_slices/patient051_frame11_slice_5.h5 -train_slices/patient051_frame11_slice_6.h5 -train_slices/patient051_frame11_slice_7.h5 -train_slices/patient051_frame11_slice_8.h5 -train_slices/patient051_frame11_slice_9.h5 -train_slices/patient052_frame01_slice_0.h5 -train_slices/patient052_frame01_slice_1.h5 -train_slices/patient052_frame01_slice_2.h5 -train_slices/patient052_frame01_slice_3.h5 -train_slices/patient052_frame01_slice_4.h5 -train_slices/patient052_frame01_slice_5.h5 -train_slices/patient052_frame01_slice_6.h5 -train_slices/patient052_frame01_slice_7.h5 -train_slices/patient052_frame09_slice_0.h5 -train_slices/patient052_frame09_slice_1.h5 -train_slices/patient052_frame09_slice_2.h5 -train_slices/patient052_frame09_slice_3.h5 -train_slices/patient052_frame09_slice_4.h5 -train_slices/patient052_frame09_slice_5.h5 -train_slices/patient052_frame09_slice_6.h5 -train_slices/patient052_frame09_slice_7.h5 -train_slices/patient053_frame12_slice_0.h5 -train_slices/patient053_frame12_slice_1.h5 -train_slices/patient053_frame12_slice_2.h5 -train_slices/patient053_frame12_slice_3.h5 -train_slices/patient053_frame12_slice_4.h5 -train_slices/patient053_frame12_slice_5.h5 -train_slices/patient053_frame12_slice_6.h5 -train_slices/patient054_frame01_slice_0.h5 -train_slices/patient054_frame01_slice_1.h5 -train_slices/patient054_frame01_slice_2.h5 -train_slices/patient054_frame01_slice_3.h5 -train_slices/patient054_frame01_slice_4.h5 -train_slices/patient054_frame01_slice_5.h5 -train_slices/patient054_frame01_slice_6.h5 -train_slices/patient054_frame01_slice_7.h5 -train_slices/patient054_frame12_slice_0.h5 -train_slices/patient054_frame12_slice_1.h5 -train_slices/patient054_frame12_slice_2.h5 -train_slices/patient054_frame12_slice_3.h5 -train_slices/patient054_frame12_slice_4.h5 -train_slices/patient054_frame12_slice_5.h5 -train_slices/patient054_frame12_slice_6.h5 -train_slices/patient054_frame12_slice_7.h5 -train_slices/patient055_frame10_slice_0.h5 -train_slices/patient055_frame10_slice_1.h5 -train_slices/patient055_frame10_slice_2.h5 -train_slices/patient055_frame10_slice_3.h5 -train_slices/patient055_frame10_slice_4.h5 -train_slices/patient055_frame10_slice_5.h5 -train_slices/patient055_frame10_slice_6.h5 -train_slices/patient055_frame10_slice_7.h5 -train_slices/patient055_frame10_slice_8.h5 -train_slices/patient056_frame01_slice_0.h5 -train_slices/patient056_frame01_slice_1.h5 -train_slices/patient056_frame01_slice_2.h5 -train_slices/patient056_frame01_slice_3.h5 -train_slices/patient056_frame01_slice_4.h5 -train_slices/patient056_frame01_slice_5.h5 -train_slices/patient056_frame01_slice_6.h5 -train_slices/patient056_frame01_slice_7.h5 -train_slices/patient056_frame01_slice_8.h5 -train_slices/patient056_frame12_slice_0.h5 -train_slices/patient056_frame12_slice_1.h5 -train_slices/patient056_frame12_slice_2.h5 -train_slices/patient056_frame12_slice_3.h5 -train_slices/patient056_frame12_slice_4.h5 -train_slices/patient056_frame12_slice_5.h5 -train_slices/patient056_frame12_slice_6.h5 -train_slices/patient056_frame12_slice_7.h5 -train_slices/patient056_frame12_slice_8.h5 -train_slices/patient057_frame01_slice_0.h5 -train_slices/patient057_frame01_slice_1.h5 -train_slices/patient057_frame01_slice_2.h5 -train_slices/patient057_frame01_slice_3.h5 -train_slices/patient057_frame01_slice_4.h5 -train_slices/patient057_frame01_slice_5.h5 -train_slices/patient057_frame01_slice_6.h5 -train_slices/patient057_frame01_slice_7.h5 -train_slices/patient058_frame14_slice_0.h5 -train_slices/patient058_frame14_slice_1.h5 -train_slices/patient058_frame14_slice_2.h5 -train_slices/patient058_frame14_slice_3.h5 -train_slices/patient058_frame14_slice_4.h5 -train_slices/patient058_frame14_slice_5.h5 -train_slices/patient058_frame14_slice_6.h5 -train_slices/patient058_frame14_slice_7.h5 -train_slices/patient058_frame14_slice_8.h5 -train_slices/patient059_frame01_slice_0.h5 -train_slices/patient059_frame01_slice_1.h5 -train_slices/patient059_frame01_slice_2.h5 -train_slices/patient059_frame01_slice_3.h5 -train_slices/patient059_frame01_slice_4.h5 -train_slices/patient059_frame01_slice_5.h5 -train_slices/patient059_frame01_slice_6.h5 -train_slices/patient059_frame01_slice_7.h5 -train_slices/patient059_frame01_slice_8.h5 -train_slices/patient059_frame09_slice_0.h5 -train_slices/patient059_frame09_slice_1.h5 -train_slices/patient059_frame09_slice_2.h5 -train_slices/patient059_frame09_slice_3.h5 -train_slices/patient059_frame09_slice_4.h5 -train_slices/patient059_frame09_slice_5.h5 -train_slices/patient059_frame09_slice_6.h5 -train_slices/patient059_frame09_slice_7.h5 -train_slices/patient059_frame09_slice_8.h5 -train_slices/patient060_frame14_slice_0.h5 -train_slices/patient060_frame14_slice_1.h5 -train_slices/patient060_frame14_slice_2.h5 -train_slices/patient060_frame14_slice_3.h5 -train_slices/patient060_frame14_slice_4.h5 -train_slices/patient060_frame14_slice_5.h5 -train_slices/patient060_frame14_slice_6.h5 -train_slices/patient060_frame14_slice_7.h5 -train_slices/patient060_frame14_slice_8.h5 -train_slices/patient061_frame01_slice_0.h5 -train_slices/patient061_frame01_slice_1.h5 -train_slices/patient061_frame01_slice_2.h5 -train_slices/patient061_frame01_slice_3.h5 -train_slices/patient061_frame01_slice_4.h5 -train_slices/patient061_frame01_slice_5.h5 -train_slices/patient061_frame01_slice_6.h5 -train_slices/patient061_frame01_slice_7.h5 -train_slices/patient061_frame01_slice_8.h5 -train_slices/patient061_frame10_slice_0.h5 -train_slices/patient061_frame10_slice_1.h5 -train_slices/patient061_frame10_slice_2.h5 -train_slices/patient061_frame10_slice_3.h5 -train_slices/patient061_frame10_slice_4.h5 -train_slices/patient061_frame10_slice_5.h5 -train_slices/patient061_frame10_slice_6.h5 -train_slices/patient061_frame10_slice_7.h5 -train_slices/patient061_frame10_slice_8.h5 -train_slices/patient062_frame01_slice_0.h5 -train_slices/patient062_frame01_slice_1.h5 -train_slices/patient062_frame01_slice_2.h5 -train_slices/patient062_frame01_slice_3.h5 -train_slices/patient062_frame01_slice_4.h5 -train_slices/patient062_frame01_slice_5.h5 -train_slices/patient062_frame01_slice_6.h5 -train_slices/patient062_frame01_slice_7.h5 -train_slices/patient062_frame01_slice_8.h5 -train_slices/patient062_frame01_slice_9.h5 -train_slices/patient062_frame09_slice_0.h5 -train_slices/patient062_frame09_slice_1.h5 -train_slices/patient062_frame09_slice_2.h5 -train_slices/patient062_frame09_slice_3.h5 -train_slices/patient062_frame09_slice_4.h5 -train_slices/patient062_frame09_slice_5.h5 -train_slices/patient062_frame09_slice_6.h5 -train_slices/patient062_frame09_slice_7.h5 -train_slices/patient062_frame09_slice_8.h5 -train_slices/patient062_frame09_slice_9.h5 -train_slices/patient063_frame16_slice_0.h5 -train_slices/patient063_frame16_slice_1.h5 -train_slices/patient063_frame16_slice_2.h5 -train_slices/patient063_frame16_slice_3.h5 -train_slices/patient063_frame16_slice_4.h5 -train_slices/patient063_frame16_slice_5.h5 -train_slices/patient063_frame16_slice_6.h5 -train_slices/patient063_frame16_slice_7.h5 -train_slices/patient064_frame01_slice_0.h5 -train_slices/patient064_frame01_slice_1.h5 -train_slices/patient064_frame01_slice_2.h5 -train_slices/patient064_frame01_slice_3.h5 -train_slices/patient064_frame01_slice_4.h5 -train_slices/patient064_frame01_slice_5.h5 -train_slices/patient064_frame01_slice_6.h5 -train_slices/patient064_frame01_slice_7.h5 -train_slices/patient064_frame01_slice_8.h5 -train_slices/patient064_frame01_slice_9.h5 -train_slices/patient066_frame01_slice_0.h5 -train_slices/patient066_frame01_slice_1.h5 -train_slices/patient066_frame01_slice_2.h5 -train_slices/patient066_frame01_slice_3.h5 -train_slices/patient066_frame01_slice_4.h5 -train_slices/patient066_frame01_slice_5.h5 -train_slices/patient066_frame01_slice_6.h5 -train_slices/patient066_frame01_slice_7.h5 -train_slices/patient066_frame01_slice_8.h5 -train_slices/patient067_frame01_slice_0.h5 -train_slices/patient067_frame01_slice_1.h5 -train_slices/patient067_frame01_slice_2.h5 -train_slices/patient067_frame01_slice_3.h5 -train_slices/patient067_frame01_slice_4.h5 -train_slices/patient067_frame01_slice_5.h5 -train_slices/patient067_frame01_slice_6.h5 -train_slices/patient067_frame01_slice_7.h5 -train_slices/patient067_frame01_slice_8.h5 -train_slices/patient067_frame01_slice_9.h5 -train_slices/patient067_frame10_slice_0.h5 -train_slices/patient067_frame10_slice_1.h5 -train_slices/patient067_frame10_slice_2.h5 -train_slices/patient067_frame10_slice_3.h5 -train_slices/patient067_frame10_slice_4.h5 -train_slices/patient067_frame10_slice_5.h5 -train_slices/patient067_frame10_slice_6.h5 -train_slices/patient067_frame10_slice_7.h5 -train_slices/patient067_frame10_slice_8.h5 -train_slices/patient067_frame10_slice_9.h5 -train_slices/patient068_frame01_slice_0.h5 -train_slices/patient068_frame01_slice_1.h5 -train_slices/patient068_frame01_slice_2.h5 -train_slices/patient068_frame01_slice_3.h5 -train_slices/patient068_frame01_slice_4.h5 -train_slices/patient068_frame01_slice_5.h5 -train_slices/patient068_frame01_slice_6.h5 -train_slices/patient069_frame01_slice_0.h5 -train_slices/patient069_frame01_slice_1.h5 -train_slices/patient069_frame01_slice_2.h5 -train_slices/patient069_frame01_slice_3.h5 -train_slices/patient069_frame01_slice_4.h5 -train_slices/patient069_frame01_slice_5.h5 -train_slices/patient069_frame01_slice_6.h5 -train_slices/patient070_frame01_slice_0.h5 -train_slices/patient070_frame01_slice_1.h5 -train_slices/patient070_frame01_slice_2.h5 -train_slices/patient070_frame01_slice_3.h5 -train_slices/patient070_frame01_slice_4.h5 -train_slices/patient070_frame01_slice_5.h5 -train_slices/patient071_frame09_slice_0.h5 -train_slices/patient071_frame09_slice_1.h5 -train_slices/patient071_frame09_slice_2.h5 -train_slices/patient071_frame09_slice_3.h5 -train_slices/patient071_frame09_slice_4.h5 -train_slices/patient071_frame09_slice_5.h5 -train_slices/patient071_frame09_slice_6.h5 -train_slices/patient071_frame09_slice_7.h5 -train_slices/patient071_frame09_slice_8.h5 -train_slices/patient071_frame09_slice_9.h5 -train_slices/patient072_frame01_slice_0.h5 -train_slices/patient072_frame01_slice_1.h5 -train_slices/patient072_frame01_slice_2.h5 -train_slices/patient072_frame01_slice_3.h5 -train_slices/patient072_frame01_slice_4.h5 -train_slices/patient072_frame01_slice_5.h5 -train_slices/patient072_frame01_slice_6.h5 -train_slices/patient072_frame01_slice_7.h5 -train_slices/patient073_frame10_slice_0.h5 -train_slices/patient073_frame10_slice_1.h5 -train_slices/patient073_frame10_slice_2.h5 -train_slices/patient073_frame10_slice_3.h5 -train_slices/patient073_frame10_slice_4.h5 -train_slices/patient073_frame10_slice_5.h5 -train_slices/patient073_frame10_slice_6.h5 -train_slices/patient074_frame12_slice_0.h5 -train_slices/patient074_frame12_slice_1.h5 -train_slices/patient074_frame12_slice_2.h5 -train_slices/patient074_frame12_slice_3.h5 -train_slices/patient074_frame12_slice_4.h5 -train_slices/patient074_frame12_slice_5.h5 -train_slices/patient074_frame12_slice_6.h5 -train_slices/patient074_frame12_slice_7.h5 -train_slices/patient075_frame01_slice_0.h5 -train_slices/patient075_frame01_slice_1.h5 -train_slices/patient075_frame01_slice_10.h5 -train_slices/patient075_frame01_slice_11.h5 -train_slices/patient075_frame01_slice_12.h5 -train_slices/patient075_frame01_slice_13.h5 -train_slices/patient075_frame01_slice_2.h5 -train_slices/patient075_frame01_slice_3.h5 -train_slices/patient075_frame01_slice_4.h5 -train_slices/patient075_frame01_slice_5.h5 -train_slices/patient075_frame01_slice_6.h5 -train_slices/patient075_frame01_slice_7.h5 -train_slices/patient075_frame01_slice_8.h5 -train_slices/patient075_frame01_slice_9.h5 -train_slices/patient076_frame12_slice_0.h5 -train_slices/patient076_frame12_slice_1.h5 -train_slices/patient076_frame12_slice_2.h5 -train_slices/patient076_frame12_slice_3.h5 -train_slices/patient076_frame12_slice_4.h5 -train_slices/patient076_frame12_slice_5.h5 -train_slices/patient076_frame12_slice_6.h5 -train_slices/patient076_frame12_slice_7.h5 -train_slices/patient077_frame09_slice_0.h5 -train_slices/patient077_frame09_slice_1.h5 -train_slices/patient077_frame09_slice_2.h5 -train_slices/patient077_frame09_slice_3.h5 -train_slices/patient077_frame09_slice_4.h5 -train_slices/patient077_frame09_slice_5.h5 -train_slices/patient077_frame09_slice_6.h5 -train_slices/patient077_frame09_slice_7.h5 -train_slices/patient078_frame01_slice_0.h5 -train_slices/patient078_frame01_slice_1.h5 -train_slices/patient078_frame01_slice_2.h5 -train_slices/patient078_frame01_slice_3.h5 -train_slices/patient078_frame01_slice_4.h5 -train_slices/patient078_frame01_slice_5.h5 -train_slices/patient078_frame01_slice_6.h5 -train_slices/patient078_frame01_slice_7.h5 -train_slices/patient078_frame09_slice_0.h5 -train_slices/patient078_frame09_slice_1.h5 -train_slices/patient078_frame09_slice_2.h5 -train_slices/patient078_frame09_slice_3.h5 -train_slices/patient078_frame09_slice_4.h5 -train_slices/patient078_frame09_slice_5.h5 -train_slices/patient078_frame09_slice_6.h5 -train_slices/patient078_frame09_slice_7.h5 -train_slices/patient079_frame01_slice_0.h5 -train_slices/patient079_frame01_slice_1.h5 -train_slices/patient079_frame01_slice_2.h5 -train_slices/patient079_frame01_slice_3.h5 -train_slices/patient079_frame01_slice_4.h5 -train_slices/patient079_frame01_slice_5.h5 -train_slices/patient079_frame01_slice_6.h5 -train_slices/patient079_frame01_slice_7.h5 -train_slices/patient079_frame01_slice_8.h5 -train_slices/patient079_frame11_slice_0.h5 -train_slices/patient079_frame11_slice_1.h5 -train_slices/patient079_frame11_slice_2.h5 -train_slices/patient079_frame11_slice_3.h5 -train_slices/patient079_frame11_slice_4.h5 -train_slices/patient079_frame11_slice_5.h5 -train_slices/patient079_frame11_slice_6.h5 -train_slices/patient079_frame11_slice_7.h5 -train_slices/patient079_frame11_slice_8.h5 -train_slices/patient080_frame01_slice_0.h5 -train_slices/patient080_frame01_slice_1.h5 -train_slices/patient080_frame01_slice_2.h5 -train_slices/patient080_frame01_slice_3.h5 -train_slices/patient080_frame01_slice_4.h5 -train_slices/patient080_frame01_slice_5.h5 -train_slices/patient080_frame10_slice_0.h5 -train_slices/patient080_frame10_slice_1.h5 -train_slices/patient080_frame10_slice_2.h5 -train_slices/patient080_frame10_slice_3.h5 -train_slices/patient080_frame10_slice_4.h5 -train_slices/patient080_frame10_slice_5.h5 -train_slices/patient081_frame07_slice_0.h5 -train_slices/patient081_frame07_slice_1.h5 -train_slices/patient081_frame07_slice_10.h5 -train_slices/patient081_frame07_slice_11.h5 -train_slices/patient081_frame07_slice_12.h5 -train_slices/patient081_frame07_slice_13.h5 -train_slices/patient081_frame07_slice_14.h5 -train_slices/patient081_frame07_slice_15.h5 -train_slices/patient081_frame07_slice_16.h5 -train_slices/patient081_frame07_slice_2.h5 -train_slices/patient081_frame07_slice_3.h5 -train_slices/patient081_frame07_slice_4.h5 -train_slices/patient081_frame07_slice_5.h5 -train_slices/patient081_frame07_slice_6.h5 -train_slices/patient081_frame07_slice_7.h5 -train_slices/patient081_frame07_slice_8.h5 -train_slices/patient081_frame07_slice_9.h5 -train_slices/patient082_frame01_slice_0.h5 -train_slices/patient082_frame01_slice_1.h5 -train_slices/patient082_frame01_slice_10.h5 -train_slices/patient082_frame01_slice_11.h5 -train_slices/patient082_frame01_slice_12.h5 -train_slices/patient082_frame01_slice_13.h5 -train_slices/patient082_frame01_slice_14.h5 -train_slices/patient082_frame01_slice_15.h5 -train_slices/patient082_frame01_slice_2.h5 -train_slices/patient082_frame01_slice_3.h5 -train_slices/patient082_frame01_slice_4.h5 -train_slices/patient082_frame01_slice_5.h5 -train_slices/patient082_frame01_slice_6.h5 -train_slices/patient082_frame01_slice_7.h5 -train_slices/patient082_frame01_slice_8.h5 -train_slices/patient082_frame01_slice_9.h5 -train_slices/patient082_frame07_slice_0.h5 -train_slices/patient082_frame07_slice_1.h5 -train_slices/patient082_frame07_slice_10.h5 -train_slices/patient082_frame07_slice_11.h5 -train_slices/patient082_frame07_slice_12.h5 -train_slices/patient082_frame07_slice_13.h5 -train_slices/patient082_frame07_slice_14.h5 -train_slices/patient082_frame07_slice_15.h5 -train_slices/patient082_frame07_slice_2.h5 -train_slices/patient082_frame07_slice_3.h5 -train_slices/patient082_frame07_slice_4.h5 -train_slices/patient082_frame07_slice_5.h5 -train_slices/patient082_frame07_slice_6.h5 -train_slices/patient082_frame07_slice_7.h5 -train_slices/patient082_frame07_slice_8.h5 -train_slices/patient082_frame07_slice_9.h5 -train_slices/patient083_frame01_slice_0.h5 -train_slices/patient083_frame01_slice_1.h5 -train_slices/patient083_frame01_slice_2.h5 -train_slices/patient083_frame01_slice_3.h5 -train_slices/patient083_frame01_slice_4.h5 -train_slices/patient083_frame01_slice_5.h5 -train_slices/patient084_frame01_slice_0.h5 -train_slices/patient084_frame01_slice_1.h5 -train_slices/patient084_frame01_slice_10.h5 -train_slices/patient084_frame01_slice_11.h5 -train_slices/patient084_frame01_slice_2.h5 -train_slices/patient084_frame01_slice_3.h5 -train_slices/patient084_frame01_slice_4.h5 -train_slices/patient084_frame01_slice_5.h5 -train_slices/patient084_frame01_slice_6.h5 -train_slices/patient084_frame01_slice_7.h5 -train_slices/patient084_frame01_slice_8.h5 -train_slices/patient084_frame01_slice_9.h5 -train_slices/patient084_frame10_slice_0.h5 -train_slices/patient084_frame10_slice_1.h5 -train_slices/patient084_frame10_slice_10.h5 -train_slices/patient084_frame10_slice_11.h5 -train_slices/patient084_frame10_slice_2.h5 -train_slices/patient084_frame10_slice_3.h5 -train_slices/patient084_frame10_slice_4.h5 -train_slices/patient084_frame10_slice_5.h5 -train_slices/patient084_frame10_slice_6.h5 -train_slices/patient084_frame10_slice_7.h5 -train_slices/patient084_frame10_slice_8.h5 -train_slices/patient084_frame10_slice_9.h5 -train_slices/patient085_frame01_slice_0.h5 -train_slices/patient085_frame01_slice_1.h5 -train_slices/patient085_frame01_slice_10.h5 -train_slices/patient085_frame01_slice_11.h5 -train_slices/patient085_frame01_slice_12.h5 -train_slices/patient085_frame01_slice_13.h5 -train_slices/patient085_frame01_slice_14.h5 -train_slices/patient085_frame01_slice_2.h5 -train_slices/patient085_frame01_slice_3.h5 -train_slices/patient085_frame01_slice_4.h5 -train_slices/patient085_frame01_slice_5.h5 -train_slices/patient085_frame01_slice_6.h5 -train_slices/patient085_frame01_slice_7.h5 -train_slices/patient085_frame01_slice_8.h5 -train_slices/patient085_frame01_slice_9.h5 -train_slices/patient087_frame01_slice_0.h5 -train_slices/patient087_frame01_slice_1.h5 -train_slices/patient087_frame01_slice_2.h5 -train_slices/patient087_frame01_slice_3.h5 -train_slices/patient087_frame01_slice_4.h5 -train_slices/patient087_frame01_slice_5.h5 -train_slices/patient087_frame01_slice_6.h5 -train_slices/patient087_frame01_slice_7.h5 -train_slices/patient088_frame01_slice_0.h5 -train_slices/patient088_frame01_slice_1.h5 -train_slices/patient088_frame01_slice_10.h5 -train_slices/patient088_frame01_slice_11.h5 -train_slices/patient088_frame01_slice_12.h5 -train_slices/patient088_frame01_slice_13.h5 -train_slices/patient088_frame01_slice_14.h5 -train_slices/patient088_frame01_slice_15.h5 -train_slices/patient088_frame01_slice_2.h5 -train_slices/patient088_frame01_slice_3.h5 -train_slices/patient088_frame01_slice_4.h5 -train_slices/patient088_frame01_slice_5.h5 -train_slices/patient088_frame01_slice_6.h5 -train_slices/patient088_frame01_slice_7.h5 -train_slices/patient088_frame01_slice_8.h5 -train_slices/patient088_frame01_slice_9.h5 -train_slices/patient088_frame12_slice_0.h5 -train_slices/patient088_frame12_slice_1.h5 -train_slices/patient088_frame12_slice_10.h5 -train_slices/patient088_frame12_slice_11.h5 -train_slices/patient088_frame12_slice_12.h5 -train_slices/patient088_frame12_slice_13.h5 -train_slices/patient088_frame12_slice_14.h5 -train_slices/patient088_frame12_slice_15.h5 -train_slices/patient088_frame12_slice_2.h5 -train_slices/patient088_frame12_slice_3.h5 -train_slices/patient088_frame12_slice_4.h5 -train_slices/patient088_frame12_slice_5.h5 -train_slices/patient088_frame12_slice_6.h5 -train_slices/patient088_frame12_slice_7.h5 -train_slices/patient088_frame12_slice_8.h5 -train_slices/patient088_frame12_slice_9.h5 -train_slices/patient090_frame11_slice_0.h5 -train_slices/patient090_frame11_slice_1.h5 -train_slices/patient090_frame11_slice_2.h5 -train_slices/patient090_frame11_slice_3.h5 -train_slices/patient090_frame11_slice_4.h5 -train_slices/patient090_frame11_slice_5.h5 -train_slices/patient090_frame11_slice_6.h5 -train_slices/patient091_frame01_slice_0.h5 -train_slices/patient091_frame01_slice_1.h5 -train_slices/patient091_frame01_slice_2.h5 -train_slices/patient091_frame01_slice_3.h5 -train_slices/patient091_frame01_slice_4.h5 -train_slices/patient091_frame01_slice_5.h5 -train_slices/patient091_frame01_slice_6.h5 -train_slices/patient091_frame01_slice_7.h5 -train_slices/patient091_frame09_slice_0.h5 -train_slices/patient091_frame09_slice_1.h5 -train_slices/patient091_frame09_slice_2.h5 -train_slices/patient091_frame09_slice_3.h5 -train_slices/patient091_frame09_slice_4.h5 -train_slices/patient091_frame09_slice_5.h5 -train_slices/patient091_frame09_slice_6.h5 -train_slices/patient091_frame09_slice_7.h5 -train_slices/patient092_frame01_slice_0.h5 -train_slices/patient092_frame01_slice_1.h5 -train_slices/patient092_frame01_slice_10.h5 -train_slices/patient092_frame01_slice_11.h5 -train_slices/patient092_frame01_slice_12.h5 -train_slices/patient092_frame01_slice_13.h5 -train_slices/patient092_frame01_slice_14.h5 -train_slices/patient092_frame01_slice_2.h5 -train_slices/patient092_frame01_slice_3.h5 -train_slices/patient092_frame01_slice_4.h5 -train_slices/patient092_frame01_slice_5.h5 -train_slices/patient092_frame01_slice_6.h5 -train_slices/patient092_frame01_slice_7.h5 -train_slices/patient092_frame01_slice_8.h5 -train_slices/patient092_frame01_slice_9.h5 -train_slices/patient092_frame06_slice_0.h5 -train_slices/patient092_frame06_slice_1.h5 -train_slices/patient092_frame06_slice_10.h5 -train_slices/patient092_frame06_slice_11.h5 -train_slices/patient092_frame06_slice_12.h5 -train_slices/patient092_frame06_slice_13.h5 -train_slices/patient092_frame06_slice_14.h5 -train_slices/patient092_frame06_slice_2.h5 -train_slices/patient092_frame06_slice_3.h5 -train_slices/patient092_frame06_slice_4.h5 -train_slices/patient092_frame06_slice_5.h5 -train_slices/patient092_frame06_slice_6.h5 -train_slices/patient092_frame06_slice_7.h5 -train_slices/patient092_frame06_slice_8.h5 -train_slices/patient092_frame06_slice_9.h5 -train_slices/patient093_frame14_slice_0.h5 -train_slices/patient093_frame14_slice_1.h5 -train_slices/patient093_frame14_slice_2.h5 -train_slices/patient093_frame14_slice_3.h5 -train_slices/patient093_frame14_slice_4.h5 -train_slices/patient093_frame14_slice_5.h5 -train_slices/patient093_frame14_slice_6.h5 -train_slices/patient093_frame14_slice_7.h5 -train_slices/patient093_frame14_slice_8.h5 -train_slices/patient093_frame14_slice_9.h5 -train_slices/patient095_frame01_slice_0.h5 -train_slices/patient095_frame01_slice_1.h5 -train_slices/patient095_frame01_slice_10.h5 -train_slices/patient095_frame01_slice_11.h5 -train_slices/patient095_frame01_slice_12.h5 -train_slices/patient095_frame01_slice_13.h5 -train_slices/patient095_frame01_slice_2.h5 -train_slices/patient095_frame01_slice_3.h5 -train_slices/patient095_frame01_slice_4.h5 -train_slices/patient095_frame01_slice_5.h5 -train_slices/patient095_frame01_slice_6.h5 -train_slices/patient095_frame01_slice_7.h5 -train_slices/patient095_frame01_slice_8.h5 -train_slices/patient095_frame01_slice_9.h5 -train_slices/patient095_frame12_slice_0.h5 -train_slices/patient095_frame12_slice_1.h5 -train_slices/patient095_frame12_slice_10.h5 -train_slices/patient095_frame12_slice_11.h5 -train_slices/patient095_frame12_slice_12.h5 -train_slices/patient095_frame12_slice_13.h5 -train_slices/patient095_frame12_slice_2.h5 -train_slices/patient095_frame12_slice_3.h5 -train_slices/patient095_frame12_slice_4.h5 -train_slices/patient095_frame12_slice_5.h5 -train_slices/patient095_frame12_slice_6.h5 -train_slices/patient095_frame12_slice_7.h5 -train_slices/patient095_frame12_slice_8.h5 -train_slices/patient095_frame12_slice_9.h5 -train_slices/patient096_frame08_slice_0.h5 -train_slices/patient096_frame08_slice_1.h5 -train_slices/patient096_frame08_slice_10.h5 -train_slices/patient096_frame08_slice_11.h5 -train_slices/patient096_frame08_slice_12.h5 -train_slices/patient096_frame08_slice_13.h5 -train_slices/patient096_frame08_slice_14.h5 -train_slices/patient096_frame08_slice_15.h5 -train_slices/patient096_frame08_slice_16.h5 -train_slices/patient096_frame08_slice_17.h5 -train_slices/patient096_frame08_slice_2.h5 -train_slices/patient096_frame08_slice_3.h5 -train_slices/patient096_frame08_slice_4.h5 -train_slices/patient096_frame08_slice_5.h5 -train_slices/patient096_frame08_slice_6.h5 -train_slices/patient096_frame08_slice_7.h5 -train_slices/patient096_frame08_slice_8.h5 -train_slices/patient096_frame08_slice_9.h5 -train_slices/patient097_frame01_slice_0.h5 -train_slices/patient097_frame01_slice_1.h5 -train_slices/patient097_frame01_slice_2.h5 -train_slices/patient097_frame01_slice_3.h5 -train_slices/patient097_frame01_slice_4.h5 -train_slices/patient097_frame01_slice_5.h5 -train_slices/patient097_frame01_slice_6.h5 -train_slices/patient097_frame01_slice_7.h5 -train_slices/patient097_frame11_slice_0.h5 -train_slices/patient097_frame11_slice_1.h5 -train_slices/patient097_frame11_slice_2.h5 -train_slices/patient097_frame11_slice_3.h5 -train_slices/patient097_frame11_slice_4.h5 -train_slices/patient097_frame11_slice_5.h5 -train_slices/patient097_frame11_slice_6.h5 -train_slices/patient097_frame11_slice_7.h5 -train_slices/patient099_frame01_slice_0.h5 -train_slices/patient099_frame01_slice_1.h5 -train_slices/patient099_frame01_slice_10.h5 -train_slices/patient099_frame01_slice_11.h5 -train_slices/patient099_frame01_slice_12.h5 -train_slices/patient099_frame01_slice_13.h5 -train_slices/patient099_frame01_slice_14.h5 -train_slices/patient099_frame01_slice_15.h5 -train_slices/patient099_frame01_slice_2.h5 -train_slices/patient099_frame01_slice_3.h5 -train_slices/patient099_frame01_slice_4.h5 -train_slices/patient099_frame01_slice_5.h5 -train_slices/patient099_frame01_slice_6.h5 -train_slices/patient099_frame01_slice_7.h5 -train_slices/patient099_frame01_slice_8.h5 -train_slices/patient099_frame01_slice_9.h5 -train_slices/patient099_frame09_slice_0.h5 -train_slices/patient099_frame09_slice_1.h5 -train_slices/patient099_frame09_slice_10.h5 -train_slices/patient099_frame09_slice_11.h5 -train_slices/patient099_frame09_slice_12.h5 -train_slices/patient099_frame09_slice_13.h5 -train_slices/patient099_frame09_slice_14.h5 -train_slices/patient099_frame09_slice_15.h5 -train_slices/patient099_frame09_slice_2.h5 -train_slices/patient099_frame09_slice_3.h5 -train_slices/patient099_frame09_slice_4.h5 -train_slices/patient099_frame09_slice_5.h5 -train_slices/patient099_frame09_slice_6.h5 -train_slices/patient099_frame09_slice_7.h5 -train_slices/patient099_frame09_slice_8.h5 -train_slices/patient099_frame09_slice_9.h5 -train_slices/patient100_frame01_slice_0.h5 -train_slices/patient100_frame01_slice_1.h5 -train_slices/patient100_frame01_slice_2.h5 -train_slices/patient100_frame01_slice_3.h5 -train_slices/patient100_frame01_slice_4.h5 -train_slices/patient100_frame01_slice_5.h5 -train_slices/patient100_frame01_slice_6.h5 -train_slices/patient100_frame01_slice_7.h5 -train_slices/patient100_frame13_slice_0.h5 -train_slices/patient100_frame13_slice_1.h5 -train_slices/patient100_frame13_slice_2.h5 -train_slices/patient100_frame13_slice_3.h5 -train_slices/patient100_frame13_slice_4.h5 -train_slices/patient100_frame13_slice_5.h5 -train_slices/patient100_frame13_slice_6.h5 -train_slices/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/train.txt b/data/ACDC2017/ACDC_for2D/train.txt deleted file mode 100644 index 63d2dff..0000000 --- a/data/ACDC2017/ACDC_for2D/train.txt +++ /dev/null @@ -1,1356 +0,0 @@ -train_slices/patient001_frame01_slice_0.h5 -train_slices/patient001_frame01_slice_1.h5 -train_slices/patient001_frame01_slice_2.h5 -train_slices/patient001_frame01_slice_3.h5 -train_slices/patient001_frame01_slice_4.h5 -train_slices/patient001_frame01_slice_5.h5 -train_slices/patient001_frame01_slice_6.h5 -train_slices/patient001_frame01_slice_7.h5 -train_slices/patient001_frame01_slice_8.h5 -train_slices/patient001_frame01_slice_9.h5 -train_slices/patient001_frame12_slice_0.h5 -train_slices/patient001_frame12_slice_1.h5 -train_slices/patient001_frame12_slice_2.h5 -train_slices/patient001_frame12_slice_3.h5 -train_slices/patient001_frame12_slice_4.h5 -train_slices/patient001_frame12_slice_5.h5 -train_slices/patient001_frame12_slice_6.h5 -train_slices/patient001_frame12_slice_7.h5 -train_slices/patient001_frame12_slice_8.h5 -train_slices/patient001_frame12_slice_9.h5 -train_slices/patient002_frame01_slice_0.h5 -train_slices/patient002_frame01_slice_1.h5 -train_slices/patient002_frame01_slice_2.h5 -train_slices/patient002_frame01_slice_3.h5 -train_slices/patient002_frame01_slice_4.h5 -train_slices/patient002_frame01_slice_5.h5 -train_slices/patient002_frame01_slice_6.h5 -train_slices/patient002_frame01_slice_7.h5 -train_slices/patient002_frame01_slice_8.h5 -train_slices/patient002_frame01_slice_9.h5 -train_slices/patient002_frame12_slice_0.h5 -train_slices/patient002_frame12_slice_1.h5 -train_slices/patient002_frame12_slice_2.h5 -train_slices/patient002_frame12_slice_3.h5 -train_slices/patient002_frame12_slice_4.h5 -train_slices/patient002_frame12_slice_5.h5 -train_slices/patient002_frame12_slice_6.h5 -train_slices/patient002_frame12_slice_7.h5 -train_slices/patient002_frame12_slice_8.h5 -train_slices/patient002_frame12_slice_9.h5 -train_slices/patient003_frame01_slice_0.h5 -train_slices/patient003_frame01_slice_1.h5 -train_slices/patient003_frame01_slice_2.h5 -train_slices/patient003_frame01_slice_3.h5 -train_slices/patient003_frame01_slice_4.h5 -train_slices/patient003_frame01_slice_5.h5 -train_slices/patient003_frame01_slice_6.h5 -train_slices/patient003_frame01_slice_7.h5 -train_slices/patient003_frame01_slice_8.h5 -train_slices/patient003_frame01_slice_9.h5 -train_slices/patient003_frame15_slice_0.h5 -train_slices/patient003_frame15_slice_1.h5 -train_slices/patient003_frame15_slice_2.h5 -train_slices/patient003_frame15_slice_3.h5 -train_slices/patient003_frame15_slice_4.h5 -train_slices/patient003_frame15_slice_5.h5 -train_slices/patient003_frame15_slice_6.h5 -train_slices/patient003_frame15_slice_7.h5 -train_slices/patient003_frame15_slice_8.h5 -train_slices/patient003_frame15_slice_9.h5 -train_slices/patient004_frame01_slice_0.h5 -train_slices/patient004_frame01_slice_1.h5 -train_slices/patient004_frame01_slice_2.h5 -train_slices/patient004_frame01_slice_3.h5 -train_slices/patient004_frame01_slice_4.h5 -train_slices/patient004_frame01_slice_5.h5 -train_slices/patient004_frame01_slice_6.h5 -train_slices/patient004_frame01_slice_7.h5 -train_slices/patient004_frame01_slice_8.h5 -train_slices/patient004_frame01_slice_9.h5 -train_slices/patient005_frame01_slice_0.h5 -train_slices/patient005_frame01_slice_1.h5 -train_slices/patient005_frame01_slice_2.h5 -train_slices/patient005_frame01_slice_3.h5 -train_slices/patient005_frame01_slice_4.h5 -train_slices/patient005_frame01_slice_5.h5 -train_slices/patient005_frame01_slice_6.h5 -train_slices/patient005_frame01_slice_7.h5 -train_slices/patient005_frame01_slice_8.h5 -train_slices/patient005_frame01_slice_9.h5 -train_slices/patient005_frame13_slice_0.h5 -train_slices/patient005_frame13_slice_1.h5 -train_slices/patient005_frame13_slice_2.h5 -train_slices/patient005_frame13_slice_3.h5 -train_slices/patient005_frame13_slice_4.h5 -train_slices/patient005_frame13_slice_5.h5 -train_slices/patient005_frame13_slice_6.h5 -train_slices/patient005_frame13_slice_7.h5 -train_slices/patient005_frame13_slice_8.h5 -train_slices/patient005_frame13_slice_9.h5 -train_slices/patient006_frame16_slice_0.h5 -train_slices/patient006_frame16_slice_1.h5 -train_slices/patient006_frame16_slice_10.h5 -train_slices/patient006_frame16_slice_2.h5 -train_slices/patient006_frame16_slice_3.h5 -train_slices/patient006_frame16_slice_4.h5 -train_slices/patient006_frame16_slice_5.h5 -train_slices/patient006_frame16_slice_6.h5 -train_slices/patient006_frame16_slice_7.h5 -train_slices/patient006_frame16_slice_8.h5 -train_slices/patient006_frame16_slice_9.h5 -train_slices/patient007_frame01_slice_0.h5 -train_slices/patient007_frame01_slice_1.h5 -train_slices/patient007_frame01_slice_2.h5 -train_slices/patient007_frame01_slice_3.h5 -train_slices/patient007_frame01_slice_4.h5 -train_slices/patient007_frame01_slice_5.h5 -train_slices/patient007_frame01_slice_6.h5 -train_slices/patient007_frame01_slice_7.h5 -train_slices/patient007_frame01_slice_8.h5 -train_slices/patient007_frame01_slice_9.h5 -train_slices/patient007_frame07_slice_0.h5 -train_slices/patient007_frame07_slice_1.h5 -train_slices/patient007_frame07_slice_2.h5 -train_slices/patient007_frame07_slice_3.h5 -train_slices/patient007_frame07_slice_4.h5 -train_slices/patient007_frame07_slice_5.h5 -train_slices/patient007_frame07_slice_6.h5 -train_slices/patient007_frame07_slice_7.h5 -train_slices/patient007_frame07_slice_8.h5 -train_slices/patient007_frame07_slice_9.h5 -train_slices/patient008_frame13_slice_0.h5 -train_slices/patient008_frame13_slice_1.h5 -train_slices/patient008_frame13_slice_2.h5 -train_slices/patient008_frame13_slice_3.h5 -train_slices/patient008_frame13_slice_4.h5 -train_slices/patient008_frame13_slice_5.h5 -train_slices/patient008_frame13_slice_6.h5 -train_slices/patient008_frame13_slice_7.h5 -train_slices/patient008_frame13_slice_8.h5 -train_slices/patient008_frame13_slice_9.h5 -train_slices/patient009_frame01_slice_0.h5 -train_slices/patient009_frame01_slice_1.h5 -train_slices/patient009_frame01_slice_2.h5 -train_slices/patient009_frame01_slice_3.h5 -train_slices/patient009_frame01_slice_4.h5 -train_slices/patient009_frame01_slice_5.h5 -train_slices/patient009_frame01_slice_6.h5 -train_slices/patient009_frame01_slice_7.h5 -train_slices/patient009_frame01_slice_8.h5 -train_slices/patient009_frame01_slice_9.h5 -train_slices/patient010_frame01_slice_0.h5 -train_slices/patient010_frame01_slice_1.h5 -train_slices/patient010_frame01_slice_2.h5 -train_slices/patient010_frame01_slice_3.h5 -train_slices/patient010_frame01_slice_4.h5 -train_slices/patient010_frame01_slice_5.h5 -train_slices/patient010_frame01_slice_6.h5 -train_slices/patient010_frame01_slice_7.h5 -train_slices/patient010_frame01_slice_8.h5 -train_slices/patient010_frame01_slice_9.h5 -train_slices/patient010_frame13_slice_0.h5 -train_slices/patient010_frame13_slice_1.h5 -train_slices/patient010_frame13_slice_2.h5 -train_slices/patient010_frame13_slice_3.h5 -train_slices/patient010_frame13_slice_4.h5 -train_slices/patient010_frame13_slice_5.h5 -train_slices/patient010_frame13_slice_6.h5 -train_slices/patient010_frame13_slice_7.h5 -train_slices/patient010_frame13_slice_8.h5 -train_slices/patient010_frame13_slice_9.h5 -train_slices/patient011_frame01_slice_0.h5 -train_slices/patient011_frame01_slice_1.h5 -train_slices/patient011_frame01_slice_2.h5 -train_slices/patient011_frame01_slice_3.h5 -train_slices/patient011_frame01_slice_4.h5 -train_slices/patient011_frame01_slice_5.h5 -train_slices/patient011_frame01_slice_6.h5 -train_slices/patient011_frame01_slice_7.h5 -train_slices/patient011_frame01_slice_8.h5 -train_slices/patient011_frame08_slice_0.h5 -train_slices/patient011_frame08_slice_1.h5 -train_slices/patient011_frame08_slice_2.h5 -train_slices/patient011_frame08_slice_3.h5 -train_slices/patient011_frame08_slice_4.h5 -train_slices/patient011_frame08_slice_5.h5 -train_slices/patient011_frame08_slice_6.h5 -train_slices/patient011_frame08_slice_7.h5 -train_slices/patient011_frame08_slice_8.h5 -train_slices/patient012_frame01_slice_0.h5 -train_slices/patient012_frame01_slice_1.h5 -train_slices/patient012_frame01_slice_2.h5 -train_slices/patient012_frame01_slice_3.h5 -train_slices/patient012_frame01_slice_4.h5 -train_slices/patient012_frame01_slice_5.h5 -train_slices/patient012_frame01_slice_6.h5 -train_slices/patient012_frame01_slice_7.h5 -train_slices/patient012_frame01_slice_8.h5 -train_slices/patient012_frame01_slice_9.h5 -train_slices/patient013_frame01_slice_0.h5 -train_slices/patient013_frame01_slice_1.h5 -train_slices/patient013_frame01_slice_2.h5 -train_slices/patient013_frame01_slice_3.h5 -train_slices/patient013_frame01_slice_4.h5 -train_slices/patient013_frame01_slice_5.h5 -train_slices/patient013_frame01_slice_6.h5 -train_slices/patient013_frame01_slice_7.h5 -train_slices/patient013_frame01_slice_8.h5 -train_slices/patient013_frame01_slice_9.h5 -train_slices/patient014_frame13_slice_0.h5 -train_slices/patient014_frame13_slice_1.h5 -train_slices/patient014_frame13_slice_2.h5 -train_slices/patient014_frame13_slice_3.h5 -train_slices/patient014_frame13_slice_4.h5 -train_slices/patient014_frame13_slice_5.h5 -train_slices/patient014_frame13_slice_6.h5 -train_slices/patient014_frame13_slice_7.h5 -train_slices/patient014_frame13_slice_8.h5 -train_slices/patient014_frame13_slice_9.h5 -train_slices/patient015_frame10_slice_0.h5 -train_slices/patient015_frame10_slice_1.h5 -train_slices/patient015_frame10_slice_2.h5 -train_slices/patient015_frame10_slice_3.h5 -train_slices/patient015_frame10_slice_4.h5 -train_slices/patient015_frame10_slice_5.h5 -train_slices/patient015_frame10_slice_6.h5 -train_slices/patient015_frame10_slice_7.h5 -train_slices/patient015_frame10_slice_8.h5 -train_slices/patient016_frame12_slice_0.h5 -train_slices/patient016_frame12_slice_1.h5 -train_slices/patient016_frame12_slice_2.h5 -train_slices/patient016_frame12_slice_3.h5 -train_slices/patient016_frame12_slice_4.h5 -train_slices/patient016_frame12_slice_5.h5 -train_slices/patient016_frame12_slice_6.h5 -train_slices/patient016_frame12_slice_7.h5 -train_slices/patient016_frame12_slice_8.h5 -train_slices/patient016_frame12_slice_9.h5 -train_slices/patient017_frame01_slice_0.h5 -train_slices/patient017_frame01_slice_1.h5 -train_slices/patient017_frame01_slice_2.h5 -train_slices/patient017_frame01_slice_3.h5 -train_slices/patient017_frame01_slice_4.h5 -train_slices/patient017_frame01_slice_5.h5 -train_slices/patient017_frame01_slice_6.h5 -train_slices/patient017_frame01_slice_7.h5 -train_slices/patient017_frame01_slice_8.h5 -train_slices/patient017_frame09_slice_0.h5 -train_slices/patient017_frame09_slice_1.h5 -train_slices/patient017_frame09_slice_2.h5 -train_slices/patient017_frame09_slice_3.h5 -train_slices/patient017_frame09_slice_4.h5 -train_slices/patient017_frame09_slice_5.h5 -train_slices/patient017_frame09_slice_6.h5 -train_slices/patient017_frame09_slice_7.h5 -train_slices/patient017_frame09_slice_8.h5 -train_slices/patient018_frame01_slice_0.h5 -train_slices/patient018_frame01_slice_1.h5 -train_slices/patient018_frame01_slice_2.h5 -train_slices/patient018_frame01_slice_3.h5 -train_slices/patient018_frame01_slice_4.h5 -train_slices/patient018_frame01_slice_5.h5 -train_slices/patient018_frame01_slice_6.h5 -train_slices/patient018_frame01_slice_7.h5 -train_slices/patient018_frame10_slice_0.h5 -train_slices/patient018_frame10_slice_1.h5 -train_slices/patient018_frame10_slice_2.h5 -train_slices/patient018_frame10_slice_3.h5 -train_slices/patient018_frame10_slice_4.h5 -train_slices/patient018_frame10_slice_5.h5 -train_slices/patient018_frame10_slice_6.h5 -train_slices/patient018_frame10_slice_7.h5 -train_slices/patient019_frame11_slice_0.h5 -train_slices/patient019_frame11_slice_1.h5 -train_slices/patient019_frame11_slice_10.h5 -train_slices/patient019_frame11_slice_2.h5 -train_slices/patient019_frame11_slice_3.h5 -train_slices/patient019_frame11_slice_4.h5 -train_slices/patient019_frame11_slice_5.h5 -train_slices/patient019_frame11_slice_6.h5 -train_slices/patient019_frame11_slice_7.h5 -train_slices/patient019_frame11_slice_8.h5 -train_slices/patient019_frame11_slice_9.h5 -train_slices/patient020_frame01_slice_0.h5 -train_slices/patient020_frame01_slice_1.h5 -train_slices/patient020_frame01_slice_2.h5 -train_slices/patient020_frame01_slice_3.h5 -train_slices/patient020_frame01_slice_4.h5 -train_slices/patient020_frame01_slice_5.h5 -train_slices/patient020_frame01_slice_6.h5 -train_slices/patient020_frame01_slice_7.h5 -train_slices/patient021_frame01_slice_0.h5 -train_slices/patient021_frame01_slice_1.h5 -train_slices/patient021_frame01_slice_2.h5 -train_slices/patient021_frame01_slice_3.h5 -train_slices/patient021_frame01_slice_4.h5 -train_slices/patient021_frame01_slice_5.h5 -train_slices/patient021_frame01_slice_6.h5 -train_slices/patient021_frame01_slice_7.h5 -train_slices/patient021_frame01_slice_8.h5 -train_slices/patient021_frame01_slice_9.h5 -train_slices/patient021_frame13_slice_0.h5 -train_slices/patient021_frame13_slice_1.h5 -train_slices/patient021_frame13_slice_2.h5 -train_slices/patient021_frame13_slice_3.h5 -train_slices/patient021_frame13_slice_4.h5 -train_slices/patient021_frame13_slice_5.h5 -train_slices/patient021_frame13_slice_6.h5 -train_slices/patient021_frame13_slice_7.h5 -train_slices/patient021_frame13_slice_8.h5 -train_slices/patient021_frame13_slice_9.h5 -train_slices/patient022_frame01_slice_0.h5 -train_slices/patient022_frame01_slice_1.h5 -train_slices/patient022_frame01_slice_2.h5 -train_slices/patient022_frame01_slice_3.h5 -train_slices/patient022_frame01_slice_4.h5 -train_slices/patient022_frame01_slice_5.h5 -train_slices/patient022_frame01_slice_6.h5 -train_slices/patient022_frame11_slice_0.h5 -train_slices/patient022_frame11_slice_1.h5 -train_slices/patient022_frame11_slice_2.h5 -train_slices/patient022_frame11_slice_3.h5 -train_slices/patient022_frame11_slice_4.h5 -train_slices/patient022_frame11_slice_5.h5 -train_slices/patient022_frame11_slice_6.h5 -train_slices/patient023_frame01_slice_0.h5 -train_slices/patient023_frame01_slice_1.h5 -train_slices/patient023_frame01_slice_2.h5 -train_slices/patient023_frame01_slice_3.h5 -train_slices/patient023_frame01_slice_4.h5 -train_slices/patient023_frame01_slice_5.h5 -train_slices/patient023_frame01_slice_6.h5 -train_slices/patient023_frame01_slice_7.h5 -train_slices/patient023_frame01_slice_8.h5 -train_slices/patient024_frame09_slice_0.h5 -train_slices/patient024_frame09_slice_1.h5 -train_slices/patient024_frame09_slice_2.h5 -train_slices/patient024_frame09_slice_3.h5 -train_slices/patient024_frame09_slice_4.h5 -train_slices/patient024_frame09_slice_5.h5 -train_slices/patient024_frame09_slice_6.h5 -train_slices/patient024_frame09_slice_7.h5 -train_slices/patient025_frame01_slice_0.h5 -train_slices/patient025_frame01_slice_1.h5 -train_slices/patient025_frame01_slice_2.h5 -train_slices/patient025_frame01_slice_3.h5 -train_slices/patient025_frame01_slice_4.h5 -train_slices/patient025_frame01_slice_5.h5 -train_slices/patient025_frame01_slice_6.h5 -train_slices/patient025_frame01_slice_7.h5 -train_slices/patient025_frame01_slice_8.h5 -train_slices/patient026_frame01_slice_0.h5 -train_slices/patient026_frame01_slice_1.h5 -train_slices/patient026_frame01_slice_2.h5 -train_slices/patient026_frame01_slice_3.h5 -train_slices/patient026_frame01_slice_4.h5 -train_slices/patient026_frame01_slice_5.h5 -train_slices/patient026_frame01_slice_6.h5 -train_slices/patient026_frame01_slice_7.h5 -train_slices/patient026_frame01_slice_8.h5 -train_slices/patient026_frame01_slice_9.h5 -train_slices/patient026_frame12_slice_0.h5 -train_slices/patient026_frame12_slice_1.h5 -train_slices/patient026_frame12_slice_2.h5 -train_slices/patient026_frame12_slice_3.h5 -train_slices/patient026_frame12_slice_4.h5 -train_slices/patient026_frame12_slice_5.h5 -train_slices/patient026_frame12_slice_6.h5 -train_slices/patient026_frame12_slice_7.h5 -train_slices/patient026_frame12_slice_8.h5 -train_slices/patient026_frame12_slice_9.h5 -train_slices/patient027_frame01_slice_0.h5 -train_slices/patient027_frame01_slice_1.h5 -train_slices/patient027_frame01_slice_2.h5 -train_slices/patient027_frame01_slice_3.h5 -train_slices/patient027_frame01_slice_4.h5 -train_slices/patient027_frame01_slice_5.h5 -train_slices/patient027_frame01_slice_6.h5 -train_slices/patient027_frame01_slice_7.h5 -train_slices/patient027_frame01_slice_8.h5 -train_slices/patient027_frame01_slice_9.h5 -train_slices/patient027_frame11_slice_0.h5 -train_slices/patient027_frame11_slice_1.h5 -train_slices/patient027_frame11_slice_2.h5 -train_slices/patient027_frame11_slice_3.h5 -train_slices/patient027_frame11_slice_4.h5 -train_slices/patient027_frame11_slice_5.h5 -train_slices/patient027_frame11_slice_6.h5 -train_slices/patient027_frame11_slice_7.h5 -train_slices/patient027_frame11_slice_8.h5 -train_slices/patient027_frame11_slice_9.h5 -train_slices/patient028_frame01_slice_0.h5 -train_slices/patient028_frame01_slice_1.h5 -train_slices/patient028_frame01_slice_2.h5 -train_slices/patient028_frame01_slice_3.h5 -train_slices/patient028_frame01_slice_4.h5 -train_slices/patient028_frame01_slice_5.h5 -train_slices/patient028_frame01_slice_6.h5 -train_slices/patient028_frame01_slice_7.h5 -train_slices/patient028_frame01_slice_8.h5 -train_slices/patient028_frame01_slice_9.h5 -train_slices/patient028_frame09_slice_0.h5 -train_slices/patient028_frame09_slice_1.h5 -train_slices/patient028_frame09_slice_2.h5 -train_slices/patient028_frame09_slice_3.h5 -train_slices/patient028_frame09_slice_4.h5 -train_slices/patient028_frame09_slice_5.h5 -train_slices/patient028_frame09_slice_6.h5 -train_slices/patient028_frame09_slice_7.h5 -train_slices/patient028_frame09_slice_8.h5 -train_slices/patient028_frame09_slice_9.h5 -train_slices/patient029_frame12_slice_0.h5 -train_slices/patient029_frame12_slice_1.h5 -train_slices/patient029_frame12_slice_10.h5 -train_slices/patient029_frame12_slice_2.h5 -train_slices/patient029_frame12_slice_3.h5 -train_slices/patient029_frame12_slice_4.h5 -train_slices/patient029_frame12_slice_5.h5 -train_slices/patient029_frame12_slice_6.h5 -train_slices/patient029_frame12_slice_7.h5 -train_slices/patient029_frame12_slice_8.h5 -train_slices/patient029_frame12_slice_9.h5 -train_slices/patient030_frame12_slice_0.h5 -train_slices/patient030_frame12_slice_1.h5 -train_slices/patient030_frame12_slice_2.h5 -train_slices/patient030_frame12_slice_3.h5 -train_slices/patient030_frame12_slice_4.h5 -train_slices/patient030_frame12_slice_5.h5 -train_slices/patient030_frame12_slice_6.h5 -train_slices/patient030_frame12_slice_7.h5 -train_slices/patient030_frame12_slice_8.h5 -train_slices/patient030_frame12_slice_9.h5 -train_slices/patient031_frame01_slice_0.h5 -train_slices/patient031_frame01_slice_1.h5 -train_slices/patient031_frame01_slice_2.h5 -train_slices/patient031_frame01_slice_3.h5 -train_slices/patient031_frame01_slice_4.h5 -train_slices/patient031_frame01_slice_5.h5 -train_slices/patient031_frame01_slice_6.h5 -train_slices/patient031_frame01_slice_7.h5 -train_slices/patient031_frame01_slice_8.h5 -train_slices/patient031_frame01_slice_9.h5 -train_slices/patient032_frame12_slice_0.h5 -train_slices/patient032_frame12_slice_1.h5 -train_slices/patient032_frame12_slice_2.h5 -train_slices/patient032_frame12_slice_3.h5 -train_slices/patient032_frame12_slice_4.h5 -train_slices/patient032_frame12_slice_5.h5 -train_slices/patient032_frame12_slice_6.h5 -train_slices/patient032_frame12_slice_7.h5 -train_slices/patient032_frame12_slice_8.h5 -train_slices/patient032_frame12_slice_9.h5 -train_slices/patient033_frame01_slice_0.h5 -train_slices/patient033_frame01_slice_1.h5 -train_slices/patient033_frame01_slice_2.h5 -train_slices/patient033_frame01_slice_3.h5 -train_slices/patient033_frame01_slice_4.h5 -train_slices/patient033_frame01_slice_5.h5 -train_slices/patient033_frame01_slice_6.h5 -train_slices/patient033_frame01_slice_7.h5 -train_slices/patient033_frame01_slice_8.h5 -train_slices/patient033_frame01_slice_9.h5 -train_slices/patient033_frame14_slice_0.h5 -train_slices/patient033_frame14_slice_1.h5 -train_slices/patient033_frame14_slice_2.h5 -train_slices/patient033_frame14_slice_3.h5 -train_slices/patient033_frame14_slice_4.h5 -train_slices/patient033_frame14_slice_5.h5 -train_slices/patient033_frame14_slice_6.h5 -train_slices/patient033_frame14_slice_7.h5 -train_slices/patient033_frame14_slice_8.h5 -train_slices/patient033_frame14_slice_9.h5 -train_slices/patient034_frame01_slice_0.h5 -train_slices/patient034_frame01_slice_1.h5 -train_slices/patient034_frame01_slice_2.h5 -train_slices/patient034_frame01_slice_3.h5 -train_slices/patient034_frame01_slice_4.h5 -train_slices/patient034_frame01_slice_5.h5 -train_slices/patient034_frame01_slice_6.h5 -train_slices/patient034_frame01_slice_7.h5 -train_slices/patient034_frame01_slice_8.h5 -train_slices/patient034_frame01_slice_9.h5 -train_slices/patient035_frame01_slice_0.h5 -train_slices/patient035_frame01_slice_1.h5 -train_slices/patient035_frame01_slice_10.h5 -train_slices/patient035_frame01_slice_11.h5 -train_slices/patient035_frame01_slice_12.h5 -train_slices/patient035_frame01_slice_2.h5 -train_slices/patient035_frame01_slice_3.h5 -train_slices/patient035_frame01_slice_4.h5 -train_slices/patient035_frame01_slice_5.h5 -train_slices/patient035_frame01_slice_6.h5 -train_slices/patient035_frame01_slice_7.h5 -train_slices/patient035_frame01_slice_8.h5 -train_slices/patient035_frame01_slice_9.h5 -train_slices/patient035_frame11_slice_0.h5 -train_slices/patient035_frame11_slice_1.h5 -train_slices/patient035_frame11_slice_10.h5 -train_slices/patient035_frame11_slice_11.h5 -train_slices/patient035_frame11_slice_12.h5 -train_slices/patient035_frame11_slice_2.h5 -train_slices/patient035_frame11_slice_3.h5 -train_slices/patient035_frame11_slice_4.h5 -train_slices/patient035_frame11_slice_5.h5 -train_slices/patient035_frame11_slice_6.h5 -train_slices/patient035_frame11_slice_7.h5 -train_slices/patient035_frame11_slice_8.h5 -train_slices/patient035_frame11_slice_9.h5 -train_slices/patient036_frame12_slice_0.h5 -train_slices/patient036_frame12_slice_1.h5 -train_slices/patient036_frame12_slice_2.h5 -train_slices/patient036_frame12_slice_3.h5 -train_slices/patient036_frame12_slice_4.h5 -train_slices/patient036_frame12_slice_5.h5 -train_slices/patient036_frame12_slice_6.h5 -train_slices/patient036_frame12_slice_7.h5 -train_slices/patient037_frame01_slice_0.h5 -train_slices/patient037_frame01_slice_1.h5 -train_slices/patient037_frame01_slice_2.h5 -train_slices/patient037_frame01_slice_3.h5 -train_slices/patient037_frame01_slice_4.h5 -train_slices/patient037_frame01_slice_5.h5 -train_slices/patient037_frame01_slice_6.h5 -train_slices/patient037_frame12_slice_0.h5 -train_slices/patient037_frame12_slice_1.h5 -train_slices/patient037_frame12_slice_2.h5 -train_slices/patient037_frame12_slice_3.h5 -train_slices/patient037_frame12_slice_4.h5 -train_slices/patient037_frame12_slice_5.h5 -train_slices/patient037_frame12_slice_6.h5 -train_slices/patient038_frame01_slice_0.h5 -train_slices/patient038_frame01_slice_1.h5 -train_slices/patient038_frame01_slice_2.h5 -train_slices/patient038_frame01_slice_3.h5 -train_slices/patient038_frame01_slice_4.h5 -train_slices/patient038_frame01_slice_5.h5 -train_slices/patient038_frame01_slice_6.h5 -train_slices/patient038_frame01_slice_7.h5 -train_slices/patient039_frame01_slice_0.h5 -train_slices/patient039_frame01_slice_1.h5 -train_slices/patient039_frame01_slice_2.h5 -train_slices/patient039_frame01_slice_3.h5 -train_slices/patient039_frame01_slice_4.h5 -train_slices/patient039_frame01_slice_5.h5 -train_slices/patient039_frame01_slice_6.h5 -train_slices/patient039_frame01_slice_7.h5 -train_slices/patient039_frame01_slice_8.h5 -train_slices/patient039_frame10_slice_0.h5 -train_slices/patient039_frame10_slice_1.h5 -train_slices/patient039_frame10_slice_2.h5 -train_slices/patient039_frame10_slice_3.h5 -train_slices/patient039_frame10_slice_4.h5 -train_slices/patient039_frame10_slice_5.h5 -train_slices/patient039_frame10_slice_6.h5 -train_slices/patient039_frame10_slice_7.h5 -train_slices/patient039_frame10_slice_8.h5 -train_slices/patient040_frame01_slice_0.h5 -train_slices/patient040_frame01_slice_1.h5 -train_slices/patient040_frame01_slice_2.h5 -train_slices/patient040_frame01_slice_3.h5 -train_slices/patient040_frame01_slice_4.h5 -train_slices/patient040_frame01_slice_5.h5 -train_slices/patient040_frame01_slice_6.h5 -train_slices/patient040_frame01_slice_7.h5 -train_slices/patient040_frame01_slice_8.h5 -train_slices/patient040_frame01_slice_9.h5 -train_slices/patient041_frame01_slice_0.h5 -train_slices/patient041_frame01_slice_1.h5 -train_slices/patient041_frame01_slice_2.h5 -train_slices/patient041_frame01_slice_3.h5 -train_slices/patient041_frame01_slice_4.h5 -train_slices/patient041_frame01_slice_5.h5 -train_slices/patient041_frame11_slice_0.h5 -train_slices/patient041_frame11_slice_1.h5 -train_slices/patient041_frame11_slice_2.h5 -train_slices/patient041_frame11_slice_3.h5 -train_slices/patient041_frame11_slice_4.h5 -train_slices/patient041_frame11_slice_5.h5 -train_slices/patient042_frame01_slice_0.h5 -train_slices/patient042_frame01_slice_1.h5 -train_slices/patient042_frame01_slice_2.h5 -train_slices/patient042_frame01_slice_3.h5 -train_slices/patient042_frame01_slice_4.h5 -train_slices/patient042_frame01_slice_5.h5 -train_slices/patient042_frame01_slice_6.h5 -train_slices/patient042_frame01_slice_7.h5 -train_slices/patient042_frame01_slice_8.h5 -train_slices/patient042_frame16_slice_0.h5 -train_slices/patient042_frame16_slice_1.h5 -train_slices/patient042_frame16_slice_2.h5 -train_slices/patient042_frame16_slice_3.h5 -train_slices/patient042_frame16_slice_4.h5 -train_slices/patient042_frame16_slice_5.h5 -train_slices/patient042_frame16_slice_6.h5 -train_slices/patient042_frame16_slice_7.h5 -train_slices/patient042_frame16_slice_8.h5 -train_slices/patient043_frame01_slice_0.h5 -train_slices/patient043_frame01_slice_1.h5 -train_slices/patient043_frame01_slice_10.h5 -train_slices/patient043_frame01_slice_11.h5 -train_slices/patient043_frame01_slice_2.h5 -train_slices/patient043_frame01_slice_3.h5 -train_slices/patient043_frame01_slice_4.h5 -train_slices/patient043_frame01_slice_5.h5 -train_slices/patient043_frame01_slice_6.h5 -train_slices/patient043_frame01_slice_7.h5 -train_slices/patient043_frame01_slice_8.h5 -train_slices/patient043_frame01_slice_9.h5 -train_slices/patient043_frame07_slice_0.h5 -train_slices/patient043_frame07_slice_1.h5 -train_slices/patient043_frame07_slice_10.h5 -train_slices/patient043_frame07_slice_11.h5 -train_slices/patient043_frame07_slice_2.h5 -train_slices/patient043_frame07_slice_3.h5 -train_slices/patient043_frame07_slice_4.h5 -train_slices/patient043_frame07_slice_5.h5 -train_slices/patient043_frame07_slice_6.h5 -train_slices/patient043_frame07_slice_7.h5 -train_slices/patient043_frame07_slice_8.h5 -train_slices/patient043_frame07_slice_9.h5 -train_slices/patient044_frame01_slice_0.h5 -train_slices/patient044_frame01_slice_1.h5 -train_slices/patient044_frame01_slice_2.h5 -train_slices/patient044_frame01_slice_3.h5 -train_slices/patient044_frame01_slice_4.h5 -train_slices/patient044_frame01_slice_5.h5 -train_slices/patient044_frame01_slice_6.h5 -train_slices/patient044_frame01_slice_7.h5 -train_slices/patient044_frame01_slice_8.h5 -train_slices/patient044_frame11_slice_0.h5 -train_slices/patient044_frame11_slice_1.h5 -train_slices/patient044_frame11_slice_2.h5 -train_slices/patient044_frame11_slice_3.h5 -train_slices/patient044_frame11_slice_4.h5 -train_slices/patient044_frame11_slice_5.h5 -train_slices/patient044_frame11_slice_6.h5 -train_slices/patient044_frame11_slice_7.h5 -train_slices/patient044_frame11_slice_8.h5 -train_slices/patient045_frame01_slice_0.h5 -train_slices/patient045_frame01_slice_1.h5 -train_slices/patient045_frame01_slice_2.h5 -train_slices/patient045_frame01_slice_3.h5 -train_slices/patient045_frame01_slice_4.h5 -train_slices/patient045_frame01_slice_5.h5 -train_slices/patient045_frame01_slice_6.h5 -train_slices/patient045_frame01_slice_7.h5 -train_slices/patient046_frame01_slice_0.h5 -train_slices/patient046_frame01_slice_1.h5 -train_slices/patient046_frame01_slice_2.h5 -train_slices/patient046_frame01_slice_3.h5 -train_slices/patient046_frame01_slice_4.h5 -train_slices/patient046_frame01_slice_5.h5 -train_slices/patient046_frame01_slice_6.h5 -train_slices/patient046_frame01_slice_7.h5 -train_slices/patient046_frame01_slice_8.h5 -train_slices/patient046_frame10_slice_0.h5 -train_slices/patient046_frame10_slice_1.h5 -train_slices/patient046_frame10_slice_2.h5 -train_slices/patient046_frame10_slice_3.h5 -train_slices/patient046_frame10_slice_4.h5 -train_slices/patient046_frame10_slice_5.h5 -train_slices/patient046_frame10_slice_6.h5 -train_slices/patient046_frame10_slice_7.h5 -train_slices/patient046_frame10_slice_8.h5 -train_slices/patient047_frame01_slice_0.h5 -train_slices/patient047_frame01_slice_1.h5 -train_slices/patient047_frame01_slice_2.h5 -train_slices/patient047_frame01_slice_3.h5 -train_slices/patient047_frame01_slice_4.h5 -train_slices/patient047_frame01_slice_5.h5 -train_slices/patient047_frame01_slice_6.h5 -train_slices/patient047_frame01_slice_7.h5 -train_slices/patient047_frame01_slice_8.h5 -train_slices/patient048_frame01_slice_0.h5 -train_slices/patient048_frame01_slice_1.h5 -train_slices/patient048_frame01_slice_2.h5 -train_slices/patient048_frame01_slice_3.h5 -train_slices/patient048_frame01_slice_4.h5 -train_slices/patient048_frame01_slice_5.h5 -train_slices/patient048_frame01_slice_6.h5 -train_slices/patient048_frame01_slice_7.h5 -train_slices/patient049_frame01_slice_0.h5 -train_slices/patient049_frame01_slice_1.h5 -train_slices/patient049_frame01_slice_2.h5 -train_slices/patient049_frame01_slice_3.h5 -train_slices/patient049_frame01_slice_4.h5 -train_slices/patient049_frame01_slice_5.h5 -train_slices/patient049_frame01_slice_6.h5 -train_slices/patient049_frame11_slice_0.h5 -train_slices/patient049_frame11_slice_1.h5 -train_slices/patient049_frame11_slice_2.h5 -train_slices/patient049_frame11_slice_3.h5 -train_slices/patient049_frame11_slice_4.h5 -train_slices/patient049_frame11_slice_5.h5 -train_slices/patient049_frame11_slice_6.h5 -train_slices/patient050_frame01_slice_0.h5 -train_slices/patient050_frame01_slice_1.h5 -train_slices/patient050_frame01_slice_2.h5 -train_slices/patient050_frame01_slice_3.h5 -train_slices/patient050_frame01_slice_4.h5 -train_slices/patient050_frame01_slice_5.h5 -train_slices/patient050_frame01_slice_6.h5 -train_slices/patient050_frame01_slice_7.h5 -train_slices/patient050_frame01_slice_8.h5 -train_slices/patient050_frame01_slice_9.h5 -train_slices/patient050_frame12_slice_0.h5 -train_slices/patient050_frame12_slice_1.h5 -train_slices/patient050_frame12_slice_2.h5 -train_slices/patient050_frame12_slice_3.h5 -train_slices/patient050_frame12_slice_4.h5 -train_slices/patient050_frame12_slice_5.h5 -train_slices/patient050_frame12_slice_6.h5 -train_slices/patient050_frame12_slice_7.h5 -train_slices/patient050_frame12_slice_8.h5 -train_slices/patient050_frame12_slice_9.h5 -train_slices/patient051_frame01_slice_0.h5 -train_slices/patient051_frame01_slice_1.h5 -train_slices/patient051_frame01_slice_2.h5 -train_slices/patient051_frame01_slice_3.h5 -train_slices/patient051_frame01_slice_4.h5 -train_slices/patient051_frame01_slice_5.h5 -train_slices/patient051_frame01_slice_6.h5 -train_slices/patient051_frame01_slice_7.h5 -train_slices/patient051_frame01_slice_8.h5 -train_slices/patient051_frame01_slice_9.h5 -train_slices/patient051_frame11_slice_0.h5 -train_slices/patient051_frame11_slice_1.h5 -train_slices/patient051_frame11_slice_2.h5 -train_slices/patient051_frame11_slice_3.h5 -train_slices/patient051_frame11_slice_4.h5 -train_slices/patient051_frame11_slice_5.h5 -train_slices/patient051_frame11_slice_6.h5 -train_slices/patient051_frame11_slice_7.h5 -train_slices/patient051_frame11_slice_8.h5 -train_slices/patient051_frame11_slice_9.h5 -train_slices/patient052_frame01_slice_0.h5 -train_slices/patient052_frame01_slice_1.h5 -train_slices/patient052_frame01_slice_2.h5 -train_slices/patient052_frame01_slice_3.h5 -train_slices/patient052_frame01_slice_4.h5 -train_slices/patient052_frame01_slice_5.h5 -train_slices/patient052_frame01_slice_6.h5 -train_slices/patient052_frame01_slice_7.h5 -train_slices/patient052_frame09_slice_0.h5 -train_slices/patient052_frame09_slice_1.h5 -train_slices/patient052_frame09_slice_2.h5 -train_slices/patient052_frame09_slice_3.h5 -train_slices/patient052_frame09_slice_4.h5 -train_slices/patient052_frame09_slice_5.h5 -train_slices/patient052_frame09_slice_6.h5 -train_slices/patient052_frame09_slice_7.h5 -train_slices/patient053_frame12_slice_0.h5 -train_slices/patient053_frame12_slice_1.h5 -train_slices/patient053_frame12_slice_2.h5 -train_slices/patient053_frame12_slice_3.h5 -train_slices/patient053_frame12_slice_4.h5 -train_slices/patient053_frame12_slice_5.h5 -train_slices/patient053_frame12_slice_6.h5 -train_slices/patient054_frame01_slice_0.h5 -train_slices/patient054_frame01_slice_1.h5 -train_slices/patient054_frame01_slice_2.h5 -train_slices/patient054_frame01_slice_3.h5 -train_slices/patient054_frame01_slice_4.h5 -train_slices/patient054_frame01_slice_5.h5 -train_slices/patient054_frame01_slice_6.h5 -train_slices/patient054_frame01_slice_7.h5 -train_slices/patient054_frame12_slice_0.h5 -train_slices/patient054_frame12_slice_1.h5 -train_slices/patient054_frame12_slice_2.h5 -train_slices/patient054_frame12_slice_3.h5 -train_slices/patient054_frame12_slice_4.h5 -train_slices/patient054_frame12_slice_5.h5 -train_slices/patient054_frame12_slice_6.h5 -train_slices/patient054_frame12_slice_7.h5 -train_slices/patient055_frame10_slice_0.h5 -train_slices/patient055_frame10_slice_1.h5 -train_slices/patient055_frame10_slice_2.h5 -train_slices/patient055_frame10_slice_3.h5 -train_slices/patient055_frame10_slice_4.h5 -train_slices/patient055_frame10_slice_5.h5 -train_slices/patient055_frame10_slice_6.h5 -train_slices/patient055_frame10_slice_7.h5 -train_slices/patient055_frame10_slice_8.h5 -train_slices/patient056_frame01_slice_0.h5 -train_slices/patient056_frame01_slice_1.h5 -train_slices/patient056_frame01_slice_2.h5 -train_slices/patient056_frame01_slice_3.h5 -train_slices/patient056_frame01_slice_4.h5 -train_slices/patient056_frame01_slice_5.h5 -train_slices/patient056_frame01_slice_6.h5 -train_slices/patient056_frame01_slice_7.h5 -train_slices/patient056_frame01_slice_8.h5 -train_slices/patient056_frame12_slice_0.h5 -train_slices/patient056_frame12_slice_1.h5 -train_slices/patient056_frame12_slice_2.h5 -train_slices/patient056_frame12_slice_3.h5 -train_slices/patient056_frame12_slice_4.h5 -train_slices/patient056_frame12_slice_5.h5 -train_slices/patient056_frame12_slice_6.h5 -train_slices/patient056_frame12_slice_7.h5 -train_slices/patient056_frame12_slice_8.h5 -train_slices/patient057_frame01_slice_0.h5 -train_slices/patient057_frame01_slice_1.h5 -train_slices/patient057_frame01_slice_2.h5 -train_slices/patient057_frame01_slice_3.h5 -train_slices/patient057_frame01_slice_4.h5 -train_slices/patient057_frame01_slice_5.h5 -train_slices/patient057_frame01_slice_6.h5 -train_slices/patient057_frame01_slice_7.h5 -train_slices/patient058_frame14_slice_0.h5 -train_slices/patient058_frame14_slice_1.h5 -train_slices/patient058_frame14_slice_2.h5 -train_slices/patient058_frame14_slice_3.h5 -train_slices/patient058_frame14_slice_4.h5 -train_slices/patient058_frame14_slice_5.h5 -train_slices/patient058_frame14_slice_6.h5 -train_slices/patient058_frame14_slice_7.h5 -train_slices/patient058_frame14_slice_8.h5 -train_slices/patient059_frame01_slice_0.h5 -train_slices/patient059_frame01_slice_1.h5 -train_slices/patient059_frame01_slice_2.h5 -train_slices/patient059_frame01_slice_3.h5 -train_slices/patient059_frame01_slice_4.h5 -train_slices/patient059_frame01_slice_5.h5 -train_slices/patient059_frame01_slice_6.h5 -train_slices/patient059_frame01_slice_7.h5 -train_slices/patient059_frame01_slice_8.h5 -train_slices/patient059_frame09_slice_0.h5 -train_slices/patient059_frame09_slice_1.h5 -train_slices/patient059_frame09_slice_2.h5 -train_slices/patient059_frame09_slice_3.h5 -train_slices/patient059_frame09_slice_4.h5 -train_slices/patient059_frame09_slice_5.h5 -train_slices/patient059_frame09_slice_6.h5 -train_slices/patient059_frame09_slice_7.h5 -train_slices/patient059_frame09_slice_8.h5 -train_slices/patient060_frame14_slice_0.h5 -train_slices/patient060_frame14_slice_1.h5 -train_slices/patient060_frame14_slice_2.h5 -train_slices/patient060_frame14_slice_3.h5 -train_slices/patient060_frame14_slice_4.h5 -train_slices/patient060_frame14_slice_5.h5 -train_slices/patient060_frame14_slice_6.h5 -train_slices/patient060_frame14_slice_7.h5 -train_slices/patient060_frame14_slice_8.h5 -train_slices/patient061_frame01_slice_0.h5 -train_slices/patient061_frame01_slice_1.h5 -train_slices/patient061_frame01_slice_2.h5 -train_slices/patient061_frame01_slice_3.h5 -train_slices/patient061_frame01_slice_4.h5 -train_slices/patient061_frame01_slice_5.h5 -train_slices/patient061_frame01_slice_6.h5 -train_slices/patient061_frame01_slice_7.h5 -train_slices/patient061_frame01_slice_8.h5 -train_slices/patient061_frame10_slice_0.h5 -train_slices/patient061_frame10_slice_1.h5 -train_slices/patient061_frame10_slice_2.h5 -train_slices/patient061_frame10_slice_3.h5 -train_slices/patient061_frame10_slice_4.h5 -train_slices/patient061_frame10_slice_5.h5 -train_slices/patient061_frame10_slice_6.h5 -train_slices/patient061_frame10_slice_7.h5 -train_slices/patient061_frame10_slice_8.h5 -train_slices/patient062_frame01_slice_0.h5 -train_slices/patient062_frame01_slice_1.h5 -train_slices/patient062_frame01_slice_2.h5 -train_slices/patient062_frame01_slice_3.h5 -train_slices/patient062_frame01_slice_4.h5 -train_slices/patient062_frame01_slice_5.h5 -train_slices/patient062_frame01_slice_6.h5 -train_slices/patient062_frame01_slice_7.h5 -train_slices/patient062_frame01_slice_8.h5 -train_slices/patient062_frame01_slice_9.h5 -train_slices/patient062_frame09_slice_0.h5 -train_slices/patient062_frame09_slice_1.h5 -train_slices/patient062_frame09_slice_2.h5 -train_slices/patient062_frame09_slice_3.h5 -train_slices/patient062_frame09_slice_4.h5 -train_slices/patient062_frame09_slice_5.h5 -train_slices/patient062_frame09_slice_6.h5 -train_slices/patient062_frame09_slice_7.h5 -train_slices/patient062_frame09_slice_8.h5 -train_slices/patient062_frame09_slice_9.h5 -train_slices/patient063_frame16_slice_0.h5 -train_slices/patient063_frame16_slice_1.h5 -train_slices/patient063_frame16_slice_2.h5 -train_slices/patient063_frame16_slice_3.h5 -train_slices/patient063_frame16_slice_4.h5 -train_slices/patient063_frame16_slice_5.h5 -train_slices/patient063_frame16_slice_6.h5 -train_slices/patient063_frame16_slice_7.h5 -train_slices/patient064_frame01_slice_0.h5 -train_slices/patient064_frame01_slice_1.h5 -train_slices/patient064_frame01_slice_2.h5 -train_slices/patient064_frame01_slice_3.h5 -train_slices/patient064_frame01_slice_4.h5 -train_slices/patient064_frame01_slice_5.h5 -train_slices/patient064_frame01_slice_6.h5 -train_slices/patient064_frame01_slice_7.h5 -train_slices/patient064_frame01_slice_8.h5 -train_slices/patient064_frame01_slice_9.h5 -train_slices/patient066_frame01_slice_0.h5 -train_slices/patient066_frame01_slice_1.h5 -train_slices/patient066_frame01_slice_2.h5 -train_slices/patient066_frame01_slice_3.h5 -train_slices/patient066_frame01_slice_4.h5 -train_slices/patient066_frame01_slice_5.h5 -train_slices/patient066_frame01_slice_6.h5 -train_slices/patient066_frame01_slice_7.h5 -train_slices/patient066_frame01_slice_8.h5 -train_slices/patient067_frame01_slice_0.h5 -train_slices/patient067_frame01_slice_1.h5 -train_slices/patient067_frame01_slice_2.h5 -train_slices/patient067_frame01_slice_3.h5 -train_slices/patient067_frame01_slice_4.h5 -train_slices/patient067_frame01_slice_5.h5 -train_slices/patient067_frame01_slice_6.h5 -train_slices/patient067_frame01_slice_7.h5 -train_slices/patient067_frame01_slice_8.h5 -train_slices/patient067_frame01_slice_9.h5 -train_slices/patient067_frame10_slice_0.h5 -train_slices/patient067_frame10_slice_1.h5 -train_slices/patient067_frame10_slice_2.h5 -train_slices/patient067_frame10_slice_3.h5 -train_slices/patient067_frame10_slice_4.h5 -train_slices/patient067_frame10_slice_5.h5 -train_slices/patient067_frame10_slice_6.h5 -train_slices/patient067_frame10_slice_7.h5 -train_slices/patient067_frame10_slice_8.h5 -train_slices/patient067_frame10_slice_9.h5 -train_slices/patient068_frame01_slice_0.h5 -train_slices/patient068_frame01_slice_1.h5 -train_slices/patient068_frame01_slice_2.h5 -train_slices/patient068_frame01_slice_3.h5 -train_slices/patient068_frame01_slice_4.h5 -train_slices/patient068_frame01_slice_5.h5 -train_slices/patient068_frame01_slice_6.h5 -train_slices/patient069_frame01_slice_0.h5 -train_slices/patient069_frame01_slice_1.h5 -train_slices/patient069_frame01_slice_2.h5 -train_slices/patient069_frame01_slice_3.h5 -train_slices/patient069_frame01_slice_4.h5 -train_slices/patient069_frame01_slice_5.h5 -train_slices/patient069_frame01_slice_6.h5 -train_slices/patient070_frame01_slice_0.h5 -train_slices/patient070_frame01_slice_1.h5 -train_slices/patient070_frame01_slice_2.h5 -train_slices/patient070_frame01_slice_3.h5 -train_slices/patient070_frame01_slice_4.h5 -train_slices/patient070_frame01_slice_5.h5 -train_slices/patient071_frame09_slice_0.h5 -train_slices/patient071_frame09_slice_1.h5 -train_slices/patient071_frame09_slice_2.h5 -train_slices/patient071_frame09_slice_3.h5 -train_slices/patient071_frame09_slice_4.h5 -train_slices/patient071_frame09_slice_5.h5 -train_slices/patient071_frame09_slice_6.h5 -train_slices/patient071_frame09_slice_7.h5 -train_slices/patient071_frame09_slice_8.h5 -train_slices/patient071_frame09_slice_9.h5 -train_slices/patient072_frame01_slice_0.h5 -train_slices/patient072_frame01_slice_1.h5 -train_slices/patient072_frame01_slice_2.h5 -train_slices/patient072_frame01_slice_3.h5 -train_slices/patient072_frame01_slice_4.h5 -train_slices/patient072_frame01_slice_5.h5 -train_slices/patient072_frame01_slice_6.h5 -train_slices/patient072_frame01_slice_7.h5 -train_slices/patient073_frame10_slice_0.h5 -train_slices/patient073_frame10_slice_1.h5 -train_slices/patient073_frame10_slice_2.h5 -train_slices/patient073_frame10_slice_3.h5 -train_slices/patient073_frame10_slice_4.h5 -train_slices/patient073_frame10_slice_5.h5 -train_slices/patient073_frame10_slice_6.h5 -train_slices/patient074_frame12_slice_0.h5 -train_slices/patient074_frame12_slice_1.h5 -train_slices/patient074_frame12_slice_2.h5 -train_slices/patient074_frame12_slice_3.h5 -train_slices/patient074_frame12_slice_4.h5 -train_slices/patient074_frame12_slice_5.h5 -train_slices/patient074_frame12_slice_6.h5 -train_slices/patient074_frame12_slice_7.h5 -train_slices/patient075_frame01_slice_0.h5 -train_slices/patient075_frame01_slice_1.h5 -train_slices/patient075_frame01_slice_10.h5 -train_slices/patient075_frame01_slice_11.h5 -train_slices/patient075_frame01_slice_12.h5 -train_slices/patient075_frame01_slice_13.h5 -train_slices/patient075_frame01_slice_2.h5 -train_slices/patient075_frame01_slice_3.h5 -train_slices/patient075_frame01_slice_4.h5 -train_slices/patient075_frame01_slice_5.h5 -train_slices/patient075_frame01_slice_6.h5 -train_slices/patient075_frame01_slice_7.h5 -train_slices/patient075_frame01_slice_8.h5 -train_slices/patient075_frame01_slice_9.h5 -train_slices/patient076_frame12_slice_0.h5 -train_slices/patient076_frame12_slice_1.h5 -train_slices/patient076_frame12_slice_2.h5 -train_slices/patient076_frame12_slice_3.h5 -train_slices/patient076_frame12_slice_4.h5 -train_slices/patient076_frame12_slice_5.h5 -train_slices/patient076_frame12_slice_6.h5 -train_slices/patient076_frame12_slice_7.h5 -train_slices/patient077_frame09_slice_0.h5 -train_slices/patient077_frame09_slice_1.h5 -train_slices/patient077_frame09_slice_2.h5 -train_slices/patient077_frame09_slice_3.h5 -train_slices/patient077_frame09_slice_4.h5 -train_slices/patient077_frame09_slice_5.h5 -train_slices/patient077_frame09_slice_6.h5 -train_slices/patient077_frame09_slice_7.h5 -train_slices/patient078_frame01_slice_0.h5 -train_slices/patient078_frame01_slice_1.h5 -train_slices/patient078_frame01_slice_2.h5 -train_slices/patient078_frame01_slice_3.h5 -train_slices/patient078_frame01_slice_4.h5 -train_slices/patient078_frame01_slice_5.h5 -train_slices/patient078_frame01_slice_6.h5 -train_slices/patient078_frame01_slice_7.h5 -train_slices/patient078_frame09_slice_0.h5 -train_slices/patient078_frame09_slice_1.h5 -train_slices/patient078_frame09_slice_2.h5 -train_slices/patient078_frame09_slice_3.h5 -train_slices/patient078_frame09_slice_4.h5 -train_slices/patient078_frame09_slice_5.h5 -train_slices/patient078_frame09_slice_6.h5 -train_slices/patient078_frame09_slice_7.h5 -train_slices/patient079_frame01_slice_0.h5 -train_slices/patient079_frame01_slice_1.h5 -train_slices/patient079_frame01_slice_2.h5 -train_slices/patient079_frame01_slice_3.h5 -train_slices/patient079_frame01_slice_4.h5 -train_slices/patient079_frame01_slice_5.h5 -train_slices/patient079_frame01_slice_6.h5 -train_slices/patient079_frame01_slice_7.h5 -train_slices/patient079_frame01_slice_8.h5 -train_slices/patient079_frame11_slice_0.h5 -train_slices/patient079_frame11_slice_1.h5 -train_slices/patient079_frame11_slice_2.h5 -train_slices/patient079_frame11_slice_3.h5 -train_slices/patient079_frame11_slice_4.h5 -train_slices/patient079_frame11_slice_5.h5 -train_slices/patient079_frame11_slice_6.h5 -train_slices/patient079_frame11_slice_7.h5 -train_slices/patient079_frame11_slice_8.h5 -train_slices/patient080_frame01_slice_0.h5 -train_slices/patient080_frame01_slice_1.h5 -train_slices/patient080_frame01_slice_2.h5 -train_slices/patient080_frame01_slice_3.h5 -train_slices/patient080_frame01_slice_4.h5 -train_slices/patient080_frame01_slice_5.h5 -train_slices/patient080_frame10_slice_0.h5 -train_slices/patient080_frame10_slice_1.h5 -train_slices/patient080_frame10_slice_2.h5 -train_slices/patient080_frame10_slice_3.h5 -train_slices/patient080_frame10_slice_4.h5 -train_slices/patient080_frame10_slice_5.h5 -train_slices/patient081_frame07_slice_0.h5 -train_slices/patient081_frame07_slice_1.h5 -train_slices/patient081_frame07_slice_10.h5 -train_slices/patient081_frame07_slice_11.h5 -train_slices/patient081_frame07_slice_12.h5 -train_slices/patient081_frame07_slice_13.h5 -train_slices/patient081_frame07_slice_14.h5 -train_slices/patient081_frame07_slice_15.h5 -train_slices/patient081_frame07_slice_16.h5 -train_slices/patient081_frame07_slice_2.h5 -train_slices/patient081_frame07_slice_3.h5 -train_slices/patient081_frame07_slice_4.h5 -train_slices/patient081_frame07_slice_5.h5 -train_slices/patient081_frame07_slice_6.h5 -train_slices/patient081_frame07_slice_7.h5 -train_slices/patient081_frame07_slice_8.h5 -train_slices/patient081_frame07_slice_9.h5 -train_slices/patient082_frame01_slice_0.h5 -train_slices/patient082_frame01_slice_1.h5 -train_slices/patient082_frame01_slice_10.h5 -train_slices/patient082_frame01_slice_11.h5 -train_slices/patient082_frame01_slice_12.h5 -train_slices/patient082_frame01_slice_13.h5 -train_slices/patient082_frame01_slice_14.h5 -train_slices/patient082_frame01_slice_15.h5 -train_slices/patient082_frame01_slice_2.h5 -train_slices/patient082_frame01_slice_3.h5 -train_slices/patient082_frame01_slice_4.h5 -train_slices/patient082_frame01_slice_5.h5 -train_slices/patient082_frame01_slice_6.h5 -train_slices/patient082_frame01_slice_7.h5 -train_slices/patient082_frame01_slice_8.h5 -train_slices/patient082_frame01_slice_9.h5 -train_slices/patient082_frame07_slice_0.h5 -train_slices/patient082_frame07_slice_1.h5 -train_slices/patient082_frame07_slice_10.h5 -train_slices/patient082_frame07_slice_11.h5 -train_slices/patient082_frame07_slice_12.h5 -train_slices/patient082_frame07_slice_13.h5 -train_slices/patient082_frame07_slice_14.h5 -train_slices/patient082_frame07_slice_15.h5 -train_slices/patient082_frame07_slice_2.h5 -train_slices/patient082_frame07_slice_3.h5 -train_slices/patient082_frame07_slice_4.h5 -train_slices/patient082_frame07_slice_5.h5 -train_slices/patient082_frame07_slice_6.h5 -train_slices/patient082_frame07_slice_7.h5 -train_slices/patient082_frame07_slice_8.h5 -train_slices/patient082_frame07_slice_9.h5 -train_slices/patient083_frame01_slice_0.h5 -train_slices/patient083_frame01_slice_1.h5 -train_slices/patient083_frame01_slice_2.h5 -train_slices/patient083_frame01_slice_3.h5 -train_slices/patient083_frame01_slice_4.h5 -train_slices/patient083_frame01_slice_5.h5 -train_slices/patient084_frame01_slice_0.h5 -train_slices/patient084_frame01_slice_1.h5 -train_slices/patient084_frame01_slice_10.h5 -train_slices/patient084_frame01_slice_11.h5 -train_slices/patient084_frame01_slice_2.h5 -train_slices/patient084_frame01_slice_3.h5 -train_slices/patient084_frame01_slice_4.h5 -train_slices/patient084_frame01_slice_5.h5 -train_slices/patient084_frame01_slice_6.h5 -train_slices/patient084_frame01_slice_7.h5 -train_slices/patient084_frame01_slice_8.h5 -train_slices/patient084_frame01_slice_9.h5 -train_slices/patient084_frame10_slice_0.h5 -train_slices/patient084_frame10_slice_1.h5 -train_slices/patient084_frame10_slice_10.h5 -train_slices/patient084_frame10_slice_11.h5 -train_slices/patient084_frame10_slice_2.h5 -train_slices/patient084_frame10_slice_3.h5 -train_slices/patient084_frame10_slice_4.h5 -train_slices/patient084_frame10_slice_5.h5 -train_slices/patient084_frame10_slice_6.h5 -train_slices/patient084_frame10_slice_7.h5 -train_slices/patient084_frame10_slice_8.h5 -train_slices/patient084_frame10_slice_9.h5 -train_slices/patient085_frame01_slice_0.h5 -train_slices/patient085_frame01_slice_1.h5 -train_slices/patient085_frame01_slice_10.h5 -train_slices/patient085_frame01_slice_11.h5 -train_slices/patient085_frame01_slice_12.h5 -train_slices/patient085_frame01_slice_13.h5 -train_slices/patient085_frame01_slice_14.h5 -train_slices/patient085_frame01_slice_2.h5 -train_slices/patient085_frame01_slice_3.h5 -train_slices/patient085_frame01_slice_4.h5 -train_slices/patient085_frame01_slice_5.h5 -train_slices/patient085_frame01_slice_6.h5 -train_slices/patient085_frame01_slice_7.h5 -train_slices/patient085_frame01_slice_8.h5 -train_slices/patient085_frame01_slice_9.h5 -train_slices/patient087_frame01_slice_0.h5 -train_slices/patient087_frame01_slice_1.h5 -train_slices/patient087_frame01_slice_2.h5 -train_slices/patient087_frame01_slice_3.h5 -train_slices/patient087_frame01_slice_4.h5 -train_slices/patient087_frame01_slice_5.h5 -train_slices/patient087_frame01_slice_6.h5 -train_slices/patient087_frame01_slice_7.h5 -train_slices/patient088_frame01_slice_0.h5 -train_slices/patient088_frame01_slice_1.h5 -train_slices/patient088_frame01_slice_10.h5 -train_slices/patient088_frame01_slice_11.h5 -train_slices/patient088_frame01_slice_12.h5 -train_slices/patient088_frame01_slice_13.h5 -train_slices/patient088_frame01_slice_14.h5 -train_slices/patient088_frame01_slice_15.h5 -train_slices/patient088_frame01_slice_2.h5 -train_slices/patient088_frame01_slice_3.h5 -train_slices/patient088_frame01_slice_4.h5 -train_slices/patient088_frame01_slice_5.h5 -train_slices/patient088_frame01_slice_6.h5 -train_slices/patient088_frame01_slice_7.h5 -train_slices/patient088_frame01_slice_8.h5 -train_slices/patient088_frame01_slice_9.h5 -train_slices/patient088_frame12_slice_0.h5 -train_slices/patient088_frame12_slice_1.h5 -train_slices/patient088_frame12_slice_10.h5 -train_slices/patient088_frame12_slice_11.h5 -train_slices/patient088_frame12_slice_12.h5 -train_slices/patient088_frame12_slice_13.h5 -train_slices/patient088_frame12_slice_14.h5 -train_slices/patient088_frame12_slice_15.h5 -train_slices/patient088_frame12_slice_2.h5 -train_slices/patient088_frame12_slice_3.h5 -train_slices/patient088_frame12_slice_4.h5 -train_slices/patient088_frame12_slice_5.h5 -train_slices/patient088_frame12_slice_6.h5 -train_slices/patient088_frame12_slice_7.h5 -train_slices/patient088_frame12_slice_8.h5 -train_slices/patient088_frame12_slice_9.h5 -train_slices/patient090_frame11_slice_0.h5 -train_slices/patient090_frame11_slice_1.h5 -train_slices/patient090_frame11_slice_2.h5 -train_slices/patient090_frame11_slice_3.h5 -train_slices/patient090_frame11_slice_4.h5 -train_slices/patient090_frame11_slice_5.h5 -train_slices/patient090_frame11_slice_6.h5 -train_slices/patient091_frame01_slice_0.h5 -train_slices/patient091_frame01_slice_1.h5 -train_slices/patient091_frame01_slice_2.h5 -train_slices/patient091_frame01_slice_3.h5 -train_slices/patient091_frame01_slice_4.h5 -train_slices/patient091_frame01_slice_5.h5 -train_slices/patient091_frame01_slice_6.h5 -train_slices/patient091_frame01_slice_7.h5 -train_slices/patient091_frame09_slice_0.h5 -train_slices/patient091_frame09_slice_1.h5 -train_slices/patient091_frame09_slice_2.h5 -train_slices/patient091_frame09_slice_3.h5 -train_slices/patient091_frame09_slice_4.h5 -train_slices/patient091_frame09_slice_5.h5 -train_slices/patient091_frame09_slice_6.h5 -train_slices/patient091_frame09_slice_7.h5 -train_slices/patient092_frame01_slice_0.h5 -train_slices/patient092_frame01_slice_1.h5 -train_slices/patient092_frame01_slice_10.h5 -train_slices/patient092_frame01_slice_11.h5 -train_slices/patient092_frame01_slice_12.h5 -train_slices/patient092_frame01_slice_13.h5 -train_slices/patient092_frame01_slice_14.h5 -train_slices/patient092_frame01_slice_2.h5 -train_slices/patient092_frame01_slice_3.h5 -train_slices/patient092_frame01_slice_4.h5 -train_slices/patient092_frame01_slice_5.h5 -train_slices/patient092_frame01_slice_6.h5 -train_slices/patient092_frame01_slice_7.h5 -train_slices/patient092_frame01_slice_8.h5 -train_slices/patient092_frame01_slice_9.h5 -train_slices/patient092_frame06_slice_0.h5 -train_slices/patient092_frame06_slice_1.h5 -train_slices/patient092_frame06_slice_10.h5 -train_slices/patient092_frame06_slice_11.h5 -train_slices/patient092_frame06_slice_12.h5 -train_slices/patient092_frame06_slice_13.h5 -train_slices/patient092_frame06_slice_14.h5 -train_slices/patient092_frame06_slice_2.h5 -train_slices/patient092_frame06_slice_3.h5 -train_slices/patient092_frame06_slice_4.h5 -train_slices/patient092_frame06_slice_5.h5 -train_slices/patient092_frame06_slice_6.h5 -train_slices/patient092_frame06_slice_7.h5 -train_slices/patient092_frame06_slice_8.h5 -train_slices/patient092_frame06_slice_9.h5 -train_slices/patient093_frame14_slice_0.h5 -train_slices/patient093_frame14_slice_1.h5 -train_slices/patient093_frame14_slice_2.h5 -train_slices/patient093_frame14_slice_3.h5 -train_slices/patient093_frame14_slice_4.h5 -train_slices/patient093_frame14_slice_5.h5 -train_slices/patient093_frame14_slice_6.h5 -train_slices/patient093_frame14_slice_7.h5 -train_slices/patient093_frame14_slice_8.h5 -train_slices/patient093_frame14_slice_9.h5 -train_slices/patient095_frame01_slice_0.h5 -train_slices/patient095_frame01_slice_1.h5 -train_slices/patient095_frame01_slice_10.h5 -train_slices/patient095_frame01_slice_11.h5 -train_slices/patient095_frame01_slice_12.h5 -train_slices/patient095_frame01_slice_13.h5 -train_slices/patient095_frame01_slice_2.h5 -train_slices/patient095_frame01_slice_3.h5 -train_slices/patient095_frame01_slice_4.h5 -train_slices/patient095_frame01_slice_5.h5 -train_slices/patient095_frame01_slice_6.h5 -train_slices/patient095_frame01_slice_7.h5 -train_slices/patient095_frame01_slice_8.h5 -train_slices/patient095_frame01_slice_9.h5 -train_slices/patient095_frame12_slice_0.h5 -train_slices/patient095_frame12_slice_1.h5 -train_slices/patient095_frame12_slice_10.h5 -train_slices/patient095_frame12_slice_11.h5 -train_slices/patient095_frame12_slice_12.h5 -train_slices/patient095_frame12_slice_13.h5 -train_slices/patient095_frame12_slice_2.h5 -train_slices/patient095_frame12_slice_3.h5 -train_slices/patient095_frame12_slice_4.h5 -train_slices/patient095_frame12_slice_5.h5 -train_slices/patient095_frame12_slice_6.h5 -train_slices/patient095_frame12_slice_7.h5 -train_slices/patient095_frame12_slice_8.h5 -train_slices/patient095_frame12_slice_9.h5 -train_slices/patient096_frame08_slice_0.h5 -train_slices/patient096_frame08_slice_1.h5 -train_slices/patient096_frame08_slice_10.h5 -train_slices/patient096_frame08_slice_11.h5 -train_slices/patient096_frame08_slice_12.h5 -train_slices/patient096_frame08_slice_13.h5 -train_slices/patient096_frame08_slice_14.h5 -train_slices/patient096_frame08_slice_15.h5 -train_slices/patient096_frame08_slice_16.h5 -train_slices/patient096_frame08_slice_17.h5 -train_slices/patient096_frame08_slice_2.h5 -train_slices/patient096_frame08_slice_3.h5 -train_slices/patient096_frame08_slice_4.h5 -train_slices/patient096_frame08_slice_5.h5 -train_slices/patient096_frame08_slice_6.h5 -train_slices/patient096_frame08_slice_7.h5 -train_slices/patient096_frame08_slice_8.h5 -train_slices/patient096_frame08_slice_9.h5 -train_slices/patient097_frame01_slice_0.h5 -train_slices/patient097_frame01_slice_1.h5 -train_slices/patient097_frame01_slice_2.h5 -train_slices/patient097_frame01_slice_3.h5 -train_slices/patient097_frame01_slice_4.h5 -train_slices/patient097_frame01_slice_5.h5 -train_slices/patient097_frame01_slice_6.h5 -train_slices/patient097_frame01_slice_7.h5 -train_slices/patient097_frame11_slice_0.h5 -train_slices/patient097_frame11_slice_1.h5 -train_slices/patient097_frame11_slice_2.h5 -train_slices/patient097_frame11_slice_3.h5 -train_slices/patient097_frame11_slice_4.h5 -train_slices/patient097_frame11_slice_5.h5 -train_slices/patient097_frame11_slice_6.h5 -train_slices/patient097_frame11_slice_7.h5 -train_slices/patient099_frame01_slice_0.h5 -train_slices/patient099_frame01_slice_1.h5 -train_slices/patient099_frame01_slice_10.h5 -train_slices/patient099_frame01_slice_11.h5 -train_slices/patient099_frame01_slice_12.h5 -train_slices/patient099_frame01_slice_13.h5 -train_slices/patient099_frame01_slice_14.h5 -train_slices/patient099_frame01_slice_15.h5 -train_slices/patient099_frame01_slice_2.h5 -train_slices/patient099_frame01_slice_3.h5 -train_slices/patient099_frame01_slice_4.h5 -train_slices/patient099_frame01_slice_5.h5 -train_slices/patient099_frame01_slice_6.h5 -train_slices/patient099_frame01_slice_7.h5 -train_slices/patient099_frame01_slice_8.h5 -train_slices/patient099_frame01_slice_9.h5 -train_slices/patient099_frame09_slice_0.h5 -train_slices/patient099_frame09_slice_1.h5 -train_slices/patient099_frame09_slice_10.h5 -train_slices/patient099_frame09_slice_11.h5 -train_slices/patient099_frame09_slice_12.h5 -train_slices/patient099_frame09_slice_13.h5 -train_slices/patient099_frame09_slice_14.h5 -train_slices/patient099_frame09_slice_15.h5 -train_slices/patient099_frame09_slice_2.h5 -train_slices/patient099_frame09_slice_3.h5 -train_slices/patient099_frame09_slice_4.h5 -train_slices/patient099_frame09_slice_5.h5 -train_slices/patient099_frame09_slice_6.h5 -train_slices/patient099_frame09_slice_7.h5 -train_slices/patient099_frame09_slice_8.h5 -train_slices/patient099_frame09_slice_9.h5 -train_slices/patient100_frame01_slice_0.h5 -train_slices/patient100_frame01_slice_1.h5 -train_slices/patient100_frame01_slice_2.h5 -train_slices/patient100_frame01_slice_3.h5 -train_slices/patient100_frame01_slice_4.h5 -train_slices/patient100_frame01_slice_5.h5 -train_slices/patient100_frame01_slice_6.h5 -train_slices/patient100_frame01_slice_7.h5 -train_slices/patient100_frame13_slice_0.h5 -train_slices/patient100_frame13_slice_1.h5 -train_slices/patient100_frame13_slice_2.h5 -train_slices/patient100_frame13_slice_3.h5 -train_slices/patient100_frame13_slice_4.h5 -train_slices/patient100_frame13_slice_5.h5 -train_slices/patient100_frame13_slice_6.h5 -train_slices/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/train_stage2.csv b/data/ACDC2017/ACDC_for2D/train_stage2.csv deleted file mode 100644 index 538e869..0000000 --- a/data/ACDC2017/ACDC_for2D/train_stage2.csv +++ /dev/null @@ -1,1357 +0,0 @@ -image -train_slices_stage2/patient001_frame01_slice_0.h5 -train_slices_stage2/patient001_frame01_slice_1.h5 -train_slices_stage2/patient001_frame01_slice_2.h5 -train_slices_stage2/patient001_frame01_slice_3.h5 -train_slices_stage2/patient001_frame01_slice_4.h5 -train_slices_stage2/patient001_frame01_slice_5.h5 -train_slices_stage2/patient001_frame01_slice_6.h5 -train_slices_stage2/patient001_frame01_slice_7.h5 -train_slices_stage2/patient001_frame01_slice_8.h5 -train_slices_stage2/patient001_frame01_slice_9.h5 -train_slices_stage2/patient001_frame12_slice_0.h5 -train_slices_stage2/patient001_frame12_slice_1.h5 -train_slices_stage2/patient001_frame12_slice_2.h5 -train_slices_stage2/patient001_frame12_slice_3.h5 -train_slices_stage2/patient001_frame12_slice_4.h5 -train_slices_stage2/patient001_frame12_slice_5.h5 -train_slices_stage2/patient001_frame12_slice_6.h5 -train_slices_stage2/patient001_frame12_slice_7.h5 -train_slices_stage2/patient001_frame12_slice_8.h5 -train_slices_stage2/patient001_frame12_slice_9.h5 -train_slices_stage2/patient002_frame01_slice_0.h5 -train_slices_stage2/patient002_frame01_slice_1.h5 -train_slices_stage2/patient002_frame01_slice_2.h5 -train_slices_stage2/patient002_frame01_slice_3.h5 -train_slices_stage2/patient002_frame01_slice_4.h5 -train_slices_stage2/patient002_frame01_slice_5.h5 -train_slices_stage2/patient002_frame01_slice_6.h5 -train_slices_stage2/patient002_frame01_slice_7.h5 -train_slices_stage2/patient002_frame01_slice_8.h5 -train_slices_stage2/patient002_frame01_slice_9.h5 -train_slices_stage2/patient002_frame12_slice_0.h5 -train_slices_stage2/patient002_frame12_slice_1.h5 -train_slices_stage2/patient002_frame12_slice_2.h5 -train_slices_stage2/patient002_frame12_slice_3.h5 -train_slices_stage2/patient002_frame12_slice_4.h5 -train_slices_stage2/patient002_frame12_slice_5.h5 -train_slices_stage2/patient002_frame12_slice_6.h5 -train_slices_stage2/patient002_frame12_slice_7.h5 -train_slices_stage2/patient002_frame12_slice_8.h5 -train_slices_stage2/patient002_frame12_slice_9.h5 -train_slices_stage2/patient003_frame01_slice_0.h5 -train_slices_stage2/patient003_frame01_slice_1.h5 -train_slices_stage2/patient003_frame01_slice_2.h5 -train_slices_stage2/patient003_frame01_slice_3.h5 -train_slices_stage2/patient003_frame01_slice_4.h5 -train_slices_stage2/patient003_frame01_slice_5.h5 -train_slices_stage2/patient003_frame01_slice_6.h5 -train_slices_stage2/patient003_frame01_slice_7.h5 -train_slices_stage2/patient003_frame01_slice_8.h5 -train_slices_stage2/patient003_frame01_slice_9.h5 -train_slices_stage2/patient003_frame15_slice_0.h5 -train_slices_stage2/patient003_frame15_slice_1.h5 -train_slices_stage2/patient003_frame15_slice_2.h5 -train_slices_stage2/patient003_frame15_slice_3.h5 -train_slices_stage2/patient003_frame15_slice_4.h5 -train_slices_stage2/patient003_frame15_slice_5.h5 -train_slices_stage2/patient003_frame15_slice_6.h5 -train_slices_stage2/patient003_frame15_slice_7.h5 -train_slices_stage2/patient003_frame15_slice_8.h5 -train_slices_stage2/patient003_frame15_slice_9.h5 -train_slices_stage2/patient004_frame01_slice_0.h5 -train_slices_stage2/patient004_frame01_slice_1.h5 -train_slices_stage2/patient004_frame01_slice_2.h5 -train_slices_stage2/patient004_frame01_slice_3.h5 -train_slices_stage2/patient004_frame01_slice_4.h5 -train_slices_stage2/patient004_frame01_slice_5.h5 -train_slices_stage2/patient004_frame01_slice_6.h5 -train_slices_stage2/patient004_frame01_slice_7.h5 -train_slices_stage2/patient004_frame01_slice_8.h5 -train_slices_stage2/patient004_frame01_slice_9.h5 -train_slices_stage2/patient005_frame01_slice_0.h5 -train_slices_stage2/patient005_frame01_slice_1.h5 -train_slices_stage2/patient005_frame01_slice_2.h5 -train_slices_stage2/patient005_frame01_slice_3.h5 -train_slices_stage2/patient005_frame01_slice_4.h5 -train_slices_stage2/patient005_frame01_slice_5.h5 -train_slices_stage2/patient005_frame01_slice_6.h5 -train_slices_stage2/patient005_frame01_slice_7.h5 -train_slices_stage2/patient005_frame01_slice_8.h5 -train_slices_stage2/patient005_frame01_slice_9.h5 -train_slices_stage2/patient005_frame13_slice_0.h5 -train_slices_stage2/patient005_frame13_slice_1.h5 -train_slices_stage2/patient005_frame13_slice_2.h5 -train_slices_stage2/patient005_frame13_slice_3.h5 -train_slices_stage2/patient005_frame13_slice_4.h5 -train_slices_stage2/patient005_frame13_slice_5.h5 -train_slices_stage2/patient005_frame13_slice_6.h5 -train_slices_stage2/patient005_frame13_slice_7.h5 -train_slices_stage2/patient005_frame13_slice_8.h5 -train_slices_stage2/patient005_frame13_slice_9.h5 -train_slices_stage2/patient006_frame16_slice_0.h5 -train_slices_stage2/patient006_frame16_slice_1.h5 -train_slices_stage2/patient006_frame16_slice_10.h5 -train_slices_stage2/patient006_frame16_slice_2.h5 -train_slices_stage2/patient006_frame16_slice_3.h5 -train_slices_stage2/patient006_frame16_slice_4.h5 -train_slices_stage2/patient006_frame16_slice_5.h5 -train_slices_stage2/patient006_frame16_slice_6.h5 -train_slices_stage2/patient006_frame16_slice_7.h5 -train_slices_stage2/patient006_frame16_slice_8.h5 -train_slices_stage2/patient006_frame16_slice_9.h5 -train_slices_stage2/patient007_frame01_slice_0.h5 -train_slices_stage2/patient007_frame01_slice_1.h5 -train_slices_stage2/patient007_frame01_slice_2.h5 -train_slices_stage2/patient007_frame01_slice_3.h5 -train_slices_stage2/patient007_frame01_slice_4.h5 -train_slices_stage2/patient007_frame01_slice_5.h5 -train_slices_stage2/patient007_frame01_slice_6.h5 -train_slices_stage2/patient007_frame01_slice_7.h5 -train_slices_stage2/patient007_frame01_slice_8.h5 -train_slices_stage2/patient007_frame01_slice_9.h5 -train_slices_stage2/patient007_frame07_slice_0.h5 -train_slices_stage2/patient007_frame07_slice_1.h5 -train_slices_stage2/patient007_frame07_slice_2.h5 -train_slices_stage2/patient007_frame07_slice_3.h5 -train_slices_stage2/patient007_frame07_slice_4.h5 -train_slices_stage2/patient007_frame07_slice_5.h5 -train_slices_stage2/patient007_frame07_slice_6.h5 -train_slices_stage2/patient007_frame07_slice_7.h5 -train_slices_stage2/patient007_frame07_slice_8.h5 -train_slices_stage2/patient007_frame07_slice_9.h5 -train_slices_stage2/patient008_frame13_slice_0.h5 -train_slices_stage2/patient008_frame13_slice_1.h5 -train_slices_stage2/patient008_frame13_slice_2.h5 -train_slices_stage2/patient008_frame13_slice_3.h5 -train_slices_stage2/patient008_frame13_slice_4.h5 -train_slices_stage2/patient008_frame13_slice_5.h5 -train_slices_stage2/patient008_frame13_slice_6.h5 -train_slices_stage2/patient008_frame13_slice_7.h5 -train_slices_stage2/patient008_frame13_slice_8.h5 -train_slices_stage2/patient008_frame13_slice_9.h5 -train_slices_stage2/patient009_frame01_slice_0.h5 -train_slices_stage2/patient009_frame01_slice_1.h5 -train_slices_stage2/patient009_frame01_slice_2.h5 -train_slices_stage2/patient009_frame01_slice_3.h5 -train_slices_stage2/patient009_frame01_slice_4.h5 -train_slices_stage2/patient009_frame01_slice_5.h5 -train_slices_stage2/patient009_frame01_slice_6.h5 -train_slices_stage2/patient009_frame01_slice_7.h5 -train_slices_stage2/patient009_frame01_slice_8.h5 -train_slices_stage2/patient009_frame01_slice_9.h5 -train_slices_stage2/patient010_frame01_slice_0.h5 -train_slices_stage2/patient010_frame01_slice_1.h5 -train_slices_stage2/patient010_frame01_slice_2.h5 -train_slices_stage2/patient010_frame01_slice_3.h5 -train_slices_stage2/patient010_frame01_slice_4.h5 -train_slices_stage2/patient010_frame01_slice_5.h5 -train_slices_stage2/patient010_frame01_slice_6.h5 -train_slices_stage2/patient010_frame01_slice_7.h5 -train_slices_stage2/patient010_frame01_slice_8.h5 -train_slices_stage2/patient010_frame01_slice_9.h5 -train_slices_stage2/patient010_frame13_slice_0.h5 -train_slices_stage2/patient010_frame13_slice_1.h5 -train_slices_stage2/patient010_frame13_slice_2.h5 -train_slices_stage2/patient010_frame13_slice_3.h5 -train_slices_stage2/patient010_frame13_slice_4.h5 -train_slices_stage2/patient010_frame13_slice_5.h5 -train_slices_stage2/patient010_frame13_slice_6.h5 -train_slices_stage2/patient010_frame13_slice_7.h5 -train_slices_stage2/patient010_frame13_slice_8.h5 -train_slices_stage2/patient010_frame13_slice_9.h5 -train_slices_stage2/patient011_frame01_slice_0.h5 -train_slices_stage2/patient011_frame01_slice_1.h5 -train_slices_stage2/patient011_frame01_slice_2.h5 -train_slices_stage2/patient011_frame01_slice_3.h5 -train_slices_stage2/patient011_frame01_slice_4.h5 -train_slices_stage2/patient011_frame01_slice_5.h5 -train_slices_stage2/patient011_frame01_slice_6.h5 -train_slices_stage2/patient011_frame01_slice_7.h5 -train_slices_stage2/patient011_frame01_slice_8.h5 -train_slices_stage2/patient011_frame08_slice_0.h5 -train_slices_stage2/patient011_frame08_slice_1.h5 -train_slices_stage2/patient011_frame08_slice_2.h5 -train_slices_stage2/patient011_frame08_slice_3.h5 -train_slices_stage2/patient011_frame08_slice_4.h5 -train_slices_stage2/patient011_frame08_slice_5.h5 -train_slices_stage2/patient011_frame08_slice_6.h5 -train_slices_stage2/patient011_frame08_slice_7.h5 -train_slices_stage2/patient011_frame08_slice_8.h5 -train_slices_stage2/patient012_frame01_slice_0.h5 -train_slices_stage2/patient012_frame01_slice_1.h5 -train_slices_stage2/patient012_frame01_slice_2.h5 -train_slices_stage2/patient012_frame01_slice_3.h5 -train_slices_stage2/patient012_frame01_slice_4.h5 -train_slices_stage2/patient012_frame01_slice_5.h5 -train_slices_stage2/patient012_frame01_slice_6.h5 -train_slices_stage2/patient012_frame01_slice_7.h5 -train_slices_stage2/patient012_frame01_slice_8.h5 -train_slices_stage2/patient012_frame01_slice_9.h5 -train_slices_stage2/patient013_frame01_slice_0.h5 -train_slices_stage2/patient013_frame01_slice_1.h5 -train_slices_stage2/patient013_frame01_slice_2.h5 -train_slices_stage2/patient013_frame01_slice_3.h5 -train_slices_stage2/patient013_frame01_slice_4.h5 -train_slices_stage2/patient013_frame01_slice_5.h5 -train_slices_stage2/patient013_frame01_slice_6.h5 -train_slices_stage2/patient013_frame01_slice_7.h5 -train_slices_stage2/patient013_frame01_slice_8.h5 -train_slices_stage2/patient013_frame01_slice_9.h5 -train_slices_stage2/patient014_frame13_slice_0.h5 -train_slices_stage2/patient014_frame13_slice_1.h5 -train_slices_stage2/patient014_frame13_slice_2.h5 -train_slices_stage2/patient014_frame13_slice_3.h5 -train_slices_stage2/patient014_frame13_slice_4.h5 -train_slices_stage2/patient014_frame13_slice_5.h5 -train_slices_stage2/patient014_frame13_slice_6.h5 -train_slices_stage2/patient014_frame13_slice_7.h5 -train_slices_stage2/patient014_frame13_slice_8.h5 -train_slices_stage2/patient014_frame13_slice_9.h5 -train_slices_stage2/patient015_frame10_slice_0.h5 -train_slices_stage2/patient015_frame10_slice_1.h5 -train_slices_stage2/patient015_frame10_slice_2.h5 -train_slices_stage2/patient015_frame10_slice_3.h5 -train_slices_stage2/patient015_frame10_slice_4.h5 -train_slices_stage2/patient015_frame10_slice_5.h5 -train_slices_stage2/patient015_frame10_slice_6.h5 -train_slices_stage2/patient015_frame10_slice_7.h5 -train_slices_stage2/patient015_frame10_slice_8.h5 -train_slices_stage2/patient016_frame12_slice_0.h5 -train_slices_stage2/patient016_frame12_slice_1.h5 -train_slices_stage2/patient016_frame12_slice_2.h5 -train_slices_stage2/patient016_frame12_slice_3.h5 -train_slices_stage2/patient016_frame12_slice_4.h5 -train_slices_stage2/patient016_frame12_slice_5.h5 -train_slices_stage2/patient016_frame12_slice_6.h5 -train_slices_stage2/patient016_frame12_slice_7.h5 -train_slices_stage2/patient016_frame12_slice_8.h5 -train_slices_stage2/patient016_frame12_slice_9.h5 -train_slices_stage2/patient017_frame01_slice_0.h5 -train_slices_stage2/patient017_frame01_slice_1.h5 -train_slices_stage2/patient017_frame01_slice_2.h5 -train_slices_stage2/patient017_frame01_slice_3.h5 -train_slices_stage2/patient017_frame01_slice_4.h5 -train_slices_stage2/patient017_frame01_slice_5.h5 -train_slices_stage2/patient017_frame01_slice_6.h5 -train_slices_stage2/patient017_frame01_slice_7.h5 -train_slices_stage2/patient017_frame01_slice_8.h5 -train_slices_stage2/patient017_frame09_slice_0.h5 -train_slices_stage2/patient017_frame09_slice_1.h5 -train_slices_stage2/patient017_frame09_slice_2.h5 -train_slices_stage2/patient017_frame09_slice_3.h5 -train_slices_stage2/patient017_frame09_slice_4.h5 -train_slices_stage2/patient017_frame09_slice_5.h5 -train_slices_stage2/patient017_frame09_slice_6.h5 -train_slices_stage2/patient017_frame09_slice_7.h5 -train_slices_stage2/patient017_frame09_slice_8.h5 -train_slices_stage2/patient018_frame01_slice_0.h5 -train_slices_stage2/patient018_frame01_slice_1.h5 -train_slices_stage2/patient018_frame01_slice_2.h5 -train_slices_stage2/patient018_frame01_slice_3.h5 -train_slices_stage2/patient018_frame01_slice_4.h5 -train_slices_stage2/patient018_frame01_slice_5.h5 -train_slices_stage2/patient018_frame01_slice_6.h5 -train_slices_stage2/patient018_frame01_slice_7.h5 -train_slices_stage2/patient018_frame10_slice_0.h5 -train_slices_stage2/patient018_frame10_slice_1.h5 -train_slices_stage2/patient018_frame10_slice_2.h5 -train_slices_stage2/patient018_frame10_slice_3.h5 -train_slices_stage2/patient018_frame10_slice_4.h5 -train_slices_stage2/patient018_frame10_slice_5.h5 -train_slices_stage2/patient018_frame10_slice_6.h5 -train_slices_stage2/patient018_frame10_slice_7.h5 -train_slices_stage2/patient019_frame11_slice_0.h5 -train_slices_stage2/patient019_frame11_slice_1.h5 -train_slices_stage2/patient019_frame11_slice_10.h5 -train_slices_stage2/patient019_frame11_slice_2.h5 -train_slices_stage2/patient019_frame11_slice_3.h5 -train_slices_stage2/patient019_frame11_slice_4.h5 -train_slices_stage2/patient019_frame11_slice_5.h5 -train_slices_stage2/patient019_frame11_slice_6.h5 -train_slices_stage2/patient019_frame11_slice_7.h5 -train_slices_stage2/patient019_frame11_slice_8.h5 -train_slices_stage2/patient019_frame11_slice_9.h5 -train_slices_stage2/patient020_frame01_slice_0.h5 -train_slices_stage2/patient020_frame01_slice_1.h5 -train_slices_stage2/patient020_frame01_slice_2.h5 -train_slices_stage2/patient020_frame01_slice_3.h5 -train_slices_stage2/patient020_frame01_slice_4.h5 -train_slices_stage2/patient020_frame01_slice_5.h5 -train_slices_stage2/patient020_frame01_slice_6.h5 -train_slices_stage2/patient020_frame01_slice_7.h5 -train_slices_stage2/patient021_frame01_slice_0.h5 -train_slices_stage2/patient021_frame01_slice_1.h5 -train_slices_stage2/patient021_frame01_slice_2.h5 -train_slices_stage2/patient021_frame01_slice_3.h5 -train_slices_stage2/patient021_frame01_slice_4.h5 -train_slices_stage2/patient021_frame01_slice_5.h5 -train_slices_stage2/patient021_frame01_slice_6.h5 -train_slices_stage2/patient021_frame01_slice_7.h5 -train_slices_stage2/patient021_frame01_slice_8.h5 -train_slices_stage2/patient021_frame01_slice_9.h5 -train_slices_stage2/patient021_frame13_slice_0.h5 -train_slices_stage2/patient021_frame13_slice_1.h5 -train_slices_stage2/patient021_frame13_slice_2.h5 -train_slices_stage2/patient021_frame13_slice_3.h5 -train_slices_stage2/patient021_frame13_slice_4.h5 -train_slices_stage2/patient021_frame13_slice_5.h5 -train_slices_stage2/patient021_frame13_slice_6.h5 -train_slices_stage2/patient021_frame13_slice_7.h5 -train_slices_stage2/patient021_frame13_slice_8.h5 -train_slices_stage2/patient021_frame13_slice_9.h5 -train_slices_stage2/patient022_frame01_slice_0.h5 -train_slices_stage2/patient022_frame01_slice_1.h5 -train_slices_stage2/patient022_frame01_slice_2.h5 -train_slices_stage2/patient022_frame01_slice_3.h5 -train_slices_stage2/patient022_frame01_slice_4.h5 -train_slices_stage2/patient022_frame01_slice_5.h5 -train_slices_stage2/patient022_frame01_slice_6.h5 -train_slices_stage2/patient022_frame11_slice_0.h5 -train_slices_stage2/patient022_frame11_slice_1.h5 -train_slices_stage2/patient022_frame11_slice_2.h5 -train_slices_stage2/patient022_frame11_slice_3.h5 -train_slices_stage2/patient022_frame11_slice_4.h5 -train_slices_stage2/patient022_frame11_slice_5.h5 -train_slices_stage2/patient022_frame11_slice_6.h5 -train_slices_stage2/patient023_frame01_slice_0.h5 -train_slices_stage2/patient023_frame01_slice_1.h5 -train_slices_stage2/patient023_frame01_slice_2.h5 -train_slices_stage2/patient023_frame01_slice_3.h5 -train_slices_stage2/patient023_frame01_slice_4.h5 -train_slices_stage2/patient023_frame01_slice_5.h5 -train_slices_stage2/patient023_frame01_slice_6.h5 -train_slices_stage2/patient023_frame01_slice_7.h5 -train_slices_stage2/patient023_frame01_slice_8.h5 -train_slices_stage2/patient024_frame09_slice_0.h5 -train_slices_stage2/patient024_frame09_slice_1.h5 -train_slices_stage2/patient024_frame09_slice_2.h5 -train_slices_stage2/patient024_frame09_slice_3.h5 -train_slices_stage2/patient024_frame09_slice_4.h5 -train_slices_stage2/patient024_frame09_slice_5.h5 -train_slices_stage2/patient024_frame09_slice_6.h5 -train_slices_stage2/patient024_frame09_slice_7.h5 -train_slices_stage2/patient025_frame01_slice_0.h5 -train_slices_stage2/patient025_frame01_slice_1.h5 -train_slices_stage2/patient025_frame01_slice_2.h5 -train_slices_stage2/patient025_frame01_slice_3.h5 -train_slices_stage2/patient025_frame01_slice_4.h5 -train_slices_stage2/patient025_frame01_slice_5.h5 -train_slices_stage2/patient025_frame01_slice_6.h5 -train_slices_stage2/patient025_frame01_slice_7.h5 -train_slices_stage2/patient025_frame01_slice_8.h5 -train_slices_stage2/patient026_frame01_slice_0.h5 -train_slices_stage2/patient026_frame01_slice_1.h5 -train_slices_stage2/patient026_frame01_slice_2.h5 -train_slices_stage2/patient026_frame01_slice_3.h5 -train_slices_stage2/patient026_frame01_slice_4.h5 -train_slices_stage2/patient026_frame01_slice_5.h5 -train_slices_stage2/patient026_frame01_slice_6.h5 -train_slices_stage2/patient026_frame01_slice_7.h5 -train_slices_stage2/patient026_frame01_slice_8.h5 -train_slices_stage2/patient026_frame01_slice_9.h5 -train_slices_stage2/patient026_frame12_slice_0.h5 -train_slices_stage2/patient026_frame12_slice_1.h5 -train_slices_stage2/patient026_frame12_slice_2.h5 -train_slices_stage2/patient026_frame12_slice_3.h5 -train_slices_stage2/patient026_frame12_slice_4.h5 -train_slices_stage2/patient026_frame12_slice_5.h5 -train_slices_stage2/patient026_frame12_slice_6.h5 -train_slices_stage2/patient026_frame12_slice_7.h5 -train_slices_stage2/patient026_frame12_slice_8.h5 -train_slices_stage2/patient026_frame12_slice_9.h5 -train_slices_stage2/patient027_frame01_slice_0.h5 -train_slices_stage2/patient027_frame01_slice_1.h5 -train_slices_stage2/patient027_frame01_slice_2.h5 -train_slices_stage2/patient027_frame01_slice_3.h5 -train_slices_stage2/patient027_frame01_slice_4.h5 -train_slices_stage2/patient027_frame01_slice_5.h5 -train_slices_stage2/patient027_frame01_slice_6.h5 -train_slices_stage2/patient027_frame01_slice_7.h5 -train_slices_stage2/patient027_frame01_slice_8.h5 -train_slices_stage2/patient027_frame01_slice_9.h5 -train_slices_stage2/patient027_frame11_slice_0.h5 -train_slices_stage2/patient027_frame11_slice_1.h5 -train_slices_stage2/patient027_frame11_slice_2.h5 -train_slices_stage2/patient027_frame11_slice_3.h5 -train_slices_stage2/patient027_frame11_slice_4.h5 -train_slices_stage2/patient027_frame11_slice_5.h5 -train_slices_stage2/patient027_frame11_slice_6.h5 -train_slices_stage2/patient027_frame11_slice_7.h5 -train_slices_stage2/patient027_frame11_slice_8.h5 -train_slices_stage2/patient027_frame11_slice_9.h5 -train_slices_stage2/patient028_frame01_slice_0.h5 -train_slices_stage2/patient028_frame01_slice_1.h5 -train_slices_stage2/patient028_frame01_slice_2.h5 -train_slices_stage2/patient028_frame01_slice_3.h5 -train_slices_stage2/patient028_frame01_slice_4.h5 -train_slices_stage2/patient028_frame01_slice_5.h5 -train_slices_stage2/patient028_frame01_slice_6.h5 -train_slices_stage2/patient028_frame01_slice_7.h5 -train_slices_stage2/patient028_frame01_slice_8.h5 -train_slices_stage2/patient028_frame01_slice_9.h5 -train_slices_stage2/patient028_frame09_slice_0.h5 -train_slices_stage2/patient028_frame09_slice_1.h5 -train_slices_stage2/patient028_frame09_slice_2.h5 -train_slices_stage2/patient028_frame09_slice_3.h5 -train_slices_stage2/patient028_frame09_slice_4.h5 -train_slices_stage2/patient028_frame09_slice_5.h5 -train_slices_stage2/patient028_frame09_slice_6.h5 -train_slices_stage2/patient028_frame09_slice_7.h5 -train_slices_stage2/patient028_frame09_slice_8.h5 -train_slices_stage2/patient028_frame09_slice_9.h5 -train_slices_stage2/patient029_frame12_slice_0.h5 -train_slices_stage2/patient029_frame12_slice_1.h5 -train_slices_stage2/patient029_frame12_slice_10.h5 -train_slices_stage2/patient029_frame12_slice_2.h5 -train_slices_stage2/patient029_frame12_slice_3.h5 -train_slices_stage2/patient029_frame12_slice_4.h5 -train_slices_stage2/patient029_frame12_slice_5.h5 -train_slices_stage2/patient029_frame12_slice_6.h5 -train_slices_stage2/patient029_frame12_slice_7.h5 -train_slices_stage2/patient029_frame12_slice_8.h5 -train_slices_stage2/patient029_frame12_slice_9.h5 -train_slices_stage2/patient030_frame12_slice_0.h5 -train_slices_stage2/patient030_frame12_slice_1.h5 -train_slices_stage2/patient030_frame12_slice_2.h5 -train_slices_stage2/patient030_frame12_slice_3.h5 -train_slices_stage2/patient030_frame12_slice_4.h5 -train_slices_stage2/patient030_frame12_slice_5.h5 -train_slices_stage2/patient030_frame12_slice_6.h5 -train_slices_stage2/patient030_frame12_slice_7.h5 -train_slices_stage2/patient030_frame12_slice_8.h5 -train_slices_stage2/patient030_frame12_slice_9.h5 -train_slices_stage2/patient031_frame01_slice_0.h5 -train_slices_stage2/patient031_frame01_slice_1.h5 -train_slices_stage2/patient031_frame01_slice_2.h5 -train_slices_stage2/patient031_frame01_slice_3.h5 -train_slices_stage2/patient031_frame01_slice_4.h5 -train_slices_stage2/patient031_frame01_slice_5.h5 -train_slices_stage2/patient031_frame01_slice_6.h5 -train_slices_stage2/patient031_frame01_slice_7.h5 -train_slices_stage2/patient031_frame01_slice_8.h5 -train_slices_stage2/patient031_frame01_slice_9.h5 -train_slices_stage2/patient032_frame12_slice_0.h5 -train_slices_stage2/patient032_frame12_slice_1.h5 -train_slices_stage2/patient032_frame12_slice_2.h5 -train_slices_stage2/patient032_frame12_slice_3.h5 -train_slices_stage2/patient032_frame12_slice_4.h5 -train_slices_stage2/patient032_frame12_slice_5.h5 -train_slices_stage2/patient032_frame12_slice_6.h5 -train_slices_stage2/patient032_frame12_slice_7.h5 -train_slices_stage2/patient032_frame12_slice_8.h5 -train_slices_stage2/patient032_frame12_slice_9.h5 -train_slices_stage2/patient033_frame01_slice_0.h5 -train_slices_stage2/patient033_frame01_slice_1.h5 -train_slices_stage2/patient033_frame01_slice_2.h5 -train_slices_stage2/patient033_frame01_slice_3.h5 -train_slices_stage2/patient033_frame01_slice_4.h5 -train_slices_stage2/patient033_frame01_slice_5.h5 -train_slices_stage2/patient033_frame01_slice_6.h5 -train_slices_stage2/patient033_frame01_slice_7.h5 -train_slices_stage2/patient033_frame01_slice_8.h5 -train_slices_stage2/patient033_frame01_slice_9.h5 -train_slices_stage2/patient033_frame14_slice_0.h5 -train_slices_stage2/patient033_frame14_slice_1.h5 -train_slices_stage2/patient033_frame14_slice_2.h5 -train_slices_stage2/patient033_frame14_slice_3.h5 -train_slices_stage2/patient033_frame14_slice_4.h5 -train_slices_stage2/patient033_frame14_slice_5.h5 -train_slices_stage2/patient033_frame14_slice_6.h5 -train_slices_stage2/patient033_frame14_slice_7.h5 -train_slices_stage2/patient033_frame14_slice_8.h5 -train_slices_stage2/patient033_frame14_slice_9.h5 -train_slices_stage2/patient034_frame01_slice_0.h5 -train_slices_stage2/patient034_frame01_slice_1.h5 -train_slices_stage2/patient034_frame01_slice_2.h5 -train_slices_stage2/patient034_frame01_slice_3.h5 -train_slices_stage2/patient034_frame01_slice_4.h5 -train_slices_stage2/patient034_frame01_slice_5.h5 -train_slices_stage2/patient034_frame01_slice_6.h5 -train_slices_stage2/patient034_frame01_slice_7.h5 -train_slices_stage2/patient034_frame01_slice_8.h5 -train_slices_stage2/patient034_frame01_slice_9.h5 -train_slices_stage2/patient035_frame01_slice_0.h5 -train_slices_stage2/patient035_frame01_slice_1.h5 -train_slices_stage2/patient035_frame01_slice_10.h5 -train_slices_stage2/patient035_frame01_slice_11.h5 -train_slices_stage2/patient035_frame01_slice_12.h5 -train_slices_stage2/patient035_frame01_slice_2.h5 -train_slices_stage2/patient035_frame01_slice_3.h5 -train_slices_stage2/patient035_frame01_slice_4.h5 -train_slices_stage2/patient035_frame01_slice_5.h5 -train_slices_stage2/patient035_frame01_slice_6.h5 -train_slices_stage2/patient035_frame01_slice_7.h5 -train_slices_stage2/patient035_frame01_slice_8.h5 -train_slices_stage2/patient035_frame01_slice_9.h5 -train_slices_stage2/patient035_frame11_slice_0.h5 -train_slices_stage2/patient035_frame11_slice_1.h5 -train_slices_stage2/patient035_frame11_slice_10.h5 -train_slices_stage2/patient035_frame11_slice_11.h5 -train_slices_stage2/patient035_frame11_slice_12.h5 -train_slices_stage2/patient035_frame11_slice_2.h5 -train_slices_stage2/patient035_frame11_slice_3.h5 -train_slices_stage2/patient035_frame11_slice_4.h5 -train_slices_stage2/patient035_frame11_slice_5.h5 -train_slices_stage2/patient035_frame11_slice_6.h5 -train_slices_stage2/patient035_frame11_slice_7.h5 -train_slices_stage2/patient035_frame11_slice_8.h5 -train_slices_stage2/patient035_frame11_slice_9.h5 -train_slices_stage2/patient036_frame12_slice_0.h5 -train_slices_stage2/patient036_frame12_slice_1.h5 -train_slices_stage2/patient036_frame12_slice_2.h5 -train_slices_stage2/patient036_frame12_slice_3.h5 -train_slices_stage2/patient036_frame12_slice_4.h5 -train_slices_stage2/patient036_frame12_slice_5.h5 -train_slices_stage2/patient036_frame12_slice_6.h5 -train_slices_stage2/patient036_frame12_slice_7.h5 -train_slices_stage2/patient037_frame01_slice_0.h5 -train_slices_stage2/patient037_frame01_slice_1.h5 -train_slices_stage2/patient037_frame01_slice_2.h5 -train_slices_stage2/patient037_frame01_slice_3.h5 -train_slices_stage2/patient037_frame01_slice_4.h5 -train_slices_stage2/patient037_frame01_slice_5.h5 -train_slices_stage2/patient037_frame01_slice_6.h5 -train_slices_stage2/patient037_frame12_slice_0.h5 -train_slices_stage2/patient037_frame12_slice_1.h5 -train_slices_stage2/patient037_frame12_slice_2.h5 -train_slices_stage2/patient037_frame12_slice_3.h5 -train_slices_stage2/patient037_frame12_slice_4.h5 -train_slices_stage2/patient037_frame12_slice_5.h5 -train_slices_stage2/patient037_frame12_slice_6.h5 -train_slices_stage2/patient038_frame01_slice_0.h5 -train_slices_stage2/patient038_frame01_slice_1.h5 -train_slices_stage2/patient038_frame01_slice_2.h5 -train_slices_stage2/patient038_frame01_slice_3.h5 -train_slices_stage2/patient038_frame01_slice_4.h5 -train_slices_stage2/patient038_frame01_slice_5.h5 -train_slices_stage2/patient038_frame01_slice_6.h5 -train_slices_stage2/patient038_frame01_slice_7.h5 -train_slices_stage2/patient039_frame01_slice_0.h5 -train_slices_stage2/patient039_frame01_slice_1.h5 -train_slices_stage2/patient039_frame01_slice_2.h5 -train_slices_stage2/patient039_frame01_slice_3.h5 -train_slices_stage2/patient039_frame01_slice_4.h5 -train_slices_stage2/patient039_frame01_slice_5.h5 -train_slices_stage2/patient039_frame01_slice_6.h5 -train_slices_stage2/patient039_frame01_slice_7.h5 -train_slices_stage2/patient039_frame01_slice_8.h5 -train_slices_stage2/patient039_frame10_slice_0.h5 -train_slices_stage2/patient039_frame10_slice_1.h5 -train_slices_stage2/patient039_frame10_slice_2.h5 -train_slices_stage2/patient039_frame10_slice_3.h5 -train_slices_stage2/patient039_frame10_slice_4.h5 -train_slices_stage2/patient039_frame10_slice_5.h5 -train_slices_stage2/patient039_frame10_slice_6.h5 -train_slices_stage2/patient039_frame10_slice_7.h5 -train_slices_stage2/patient039_frame10_slice_8.h5 -train_slices_stage2/patient040_frame01_slice_0.h5 -train_slices_stage2/patient040_frame01_slice_1.h5 -train_slices_stage2/patient040_frame01_slice_2.h5 -train_slices_stage2/patient040_frame01_slice_3.h5 -train_slices_stage2/patient040_frame01_slice_4.h5 -train_slices_stage2/patient040_frame01_slice_5.h5 -train_slices_stage2/patient040_frame01_slice_6.h5 -train_slices_stage2/patient040_frame01_slice_7.h5 -train_slices_stage2/patient040_frame01_slice_8.h5 -train_slices_stage2/patient040_frame01_slice_9.h5 -train_slices_stage2/patient041_frame01_slice_0.h5 -train_slices_stage2/patient041_frame01_slice_1.h5 -train_slices_stage2/patient041_frame01_slice_2.h5 -train_slices_stage2/patient041_frame01_slice_3.h5 -train_slices_stage2/patient041_frame01_slice_4.h5 -train_slices_stage2/patient041_frame01_slice_5.h5 -train_slices_stage2/patient041_frame11_slice_0.h5 -train_slices_stage2/patient041_frame11_slice_1.h5 -train_slices_stage2/patient041_frame11_slice_2.h5 -train_slices_stage2/patient041_frame11_slice_3.h5 -train_slices_stage2/patient041_frame11_slice_4.h5 -train_slices_stage2/patient041_frame11_slice_5.h5 -train_slices_stage2/patient042_frame01_slice_0.h5 -train_slices_stage2/patient042_frame01_slice_1.h5 -train_slices_stage2/patient042_frame01_slice_2.h5 -train_slices_stage2/patient042_frame01_slice_3.h5 -train_slices_stage2/patient042_frame01_slice_4.h5 -train_slices_stage2/patient042_frame01_slice_5.h5 -train_slices_stage2/patient042_frame01_slice_6.h5 -train_slices_stage2/patient042_frame01_slice_7.h5 -train_slices_stage2/patient042_frame01_slice_8.h5 -train_slices_stage2/patient042_frame16_slice_0.h5 -train_slices_stage2/patient042_frame16_slice_1.h5 -train_slices_stage2/patient042_frame16_slice_2.h5 -train_slices_stage2/patient042_frame16_slice_3.h5 -train_slices_stage2/patient042_frame16_slice_4.h5 -train_slices_stage2/patient042_frame16_slice_5.h5 -train_slices_stage2/patient042_frame16_slice_6.h5 -train_slices_stage2/patient042_frame16_slice_7.h5 -train_slices_stage2/patient042_frame16_slice_8.h5 -train_slices_stage2/patient043_frame01_slice_0.h5 -train_slices_stage2/patient043_frame01_slice_1.h5 -train_slices_stage2/patient043_frame01_slice_10.h5 -train_slices_stage2/patient043_frame01_slice_11.h5 -train_slices_stage2/patient043_frame01_slice_2.h5 -train_slices_stage2/patient043_frame01_slice_3.h5 -train_slices_stage2/patient043_frame01_slice_4.h5 -train_slices_stage2/patient043_frame01_slice_5.h5 -train_slices_stage2/patient043_frame01_slice_6.h5 -train_slices_stage2/patient043_frame01_slice_7.h5 -train_slices_stage2/patient043_frame01_slice_8.h5 -train_slices_stage2/patient043_frame01_slice_9.h5 -train_slices_stage2/patient043_frame07_slice_0.h5 -train_slices_stage2/patient043_frame07_slice_1.h5 -train_slices_stage2/patient043_frame07_slice_10.h5 -train_slices_stage2/patient043_frame07_slice_11.h5 -train_slices_stage2/patient043_frame07_slice_2.h5 -train_slices_stage2/patient043_frame07_slice_3.h5 -train_slices_stage2/patient043_frame07_slice_4.h5 -train_slices_stage2/patient043_frame07_slice_5.h5 -train_slices_stage2/patient043_frame07_slice_6.h5 -train_slices_stage2/patient043_frame07_slice_7.h5 -train_slices_stage2/patient043_frame07_slice_8.h5 -train_slices_stage2/patient043_frame07_slice_9.h5 -train_slices_stage2/patient044_frame01_slice_0.h5 -train_slices_stage2/patient044_frame01_slice_1.h5 -train_slices_stage2/patient044_frame01_slice_2.h5 -train_slices_stage2/patient044_frame01_slice_3.h5 -train_slices_stage2/patient044_frame01_slice_4.h5 -train_slices_stage2/patient044_frame01_slice_5.h5 -train_slices_stage2/patient044_frame01_slice_6.h5 -train_slices_stage2/patient044_frame01_slice_7.h5 -train_slices_stage2/patient044_frame01_slice_8.h5 -train_slices_stage2/patient044_frame11_slice_0.h5 -train_slices_stage2/patient044_frame11_slice_1.h5 -train_slices_stage2/patient044_frame11_slice_2.h5 -train_slices_stage2/patient044_frame11_slice_3.h5 -train_slices_stage2/patient044_frame11_slice_4.h5 -train_slices_stage2/patient044_frame11_slice_5.h5 -train_slices_stage2/patient044_frame11_slice_6.h5 -train_slices_stage2/patient044_frame11_slice_7.h5 -train_slices_stage2/patient044_frame11_slice_8.h5 -train_slices_stage2/patient045_frame01_slice_0.h5 -train_slices_stage2/patient045_frame01_slice_1.h5 -train_slices_stage2/patient045_frame01_slice_2.h5 -train_slices_stage2/patient045_frame01_slice_3.h5 -train_slices_stage2/patient045_frame01_slice_4.h5 -train_slices_stage2/patient045_frame01_slice_5.h5 -train_slices_stage2/patient045_frame01_slice_6.h5 -train_slices_stage2/patient045_frame01_slice_7.h5 -train_slices_stage2/patient046_frame01_slice_0.h5 -train_slices_stage2/patient046_frame01_slice_1.h5 -train_slices_stage2/patient046_frame01_slice_2.h5 -train_slices_stage2/patient046_frame01_slice_3.h5 -train_slices_stage2/patient046_frame01_slice_4.h5 -train_slices_stage2/patient046_frame01_slice_5.h5 -train_slices_stage2/patient046_frame01_slice_6.h5 -train_slices_stage2/patient046_frame01_slice_7.h5 -train_slices_stage2/patient046_frame01_slice_8.h5 -train_slices_stage2/patient046_frame10_slice_0.h5 -train_slices_stage2/patient046_frame10_slice_1.h5 -train_slices_stage2/patient046_frame10_slice_2.h5 -train_slices_stage2/patient046_frame10_slice_3.h5 -train_slices_stage2/patient046_frame10_slice_4.h5 -train_slices_stage2/patient046_frame10_slice_5.h5 -train_slices_stage2/patient046_frame10_slice_6.h5 -train_slices_stage2/patient046_frame10_slice_7.h5 -train_slices_stage2/patient046_frame10_slice_8.h5 -train_slices_stage2/patient047_frame01_slice_0.h5 -train_slices_stage2/patient047_frame01_slice_1.h5 -train_slices_stage2/patient047_frame01_slice_2.h5 -train_slices_stage2/patient047_frame01_slice_3.h5 -train_slices_stage2/patient047_frame01_slice_4.h5 -train_slices_stage2/patient047_frame01_slice_5.h5 -train_slices_stage2/patient047_frame01_slice_6.h5 -train_slices_stage2/patient047_frame01_slice_7.h5 -train_slices_stage2/patient047_frame01_slice_8.h5 -train_slices_stage2/patient048_frame01_slice_0.h5 -train_slices_stage2/patient048_frame01_slice_1.h5 -train_slices_stage2/patient048_frame01_slice_2.h5 -train_slices_stage2/patient048_frame01_slice_3.h5 -train_slices_stage2/patient048_frame01_slice_4.h5 -train_slices_stage2/patient048_frame01_slice_5.h5 -train_slices_stage2/patient048_frame01_slice_6.h5 -train_slices_stage2/patient048_frame01_slice_7.h5 -train_slices_stage2/patient049_frame01_slice_0.h5 -train_slices_stage2/patient049_frame01_slice_1.h5 -train_slices_stage2/patient049_frame01_slice_2.h5 -train_slices_stage2/patient049_frame01_slice_3.h5 -train_slices_stage2/patient049_frame01_slice_4.h5 -train_slices_stage2/patient049_frame01_slice_5.h5 -train_slices_stage2/patient049_frame01_slice_6.h5 -train_slices_stage2/patient049_frame11_slice_0.h5 -train_slices_stage2/patient049_frame11_slice_1.h5 -train_slices_stage2/patient049_frame11_slice_2.h5 -train_slices_stage2/patient049_frame11_slice_3.h5 -train_slices_stage2/patient049_frame11_slice_4.h5 -train_slices_stage2/patient049_frame11_slice_5.h5 -train_slices_stage2/patient049_frame11_slice_6.h5 -train_slices_stage2/patient050_frame01_slice_0.h5 -train_slices_stage2/patient050_frame01_slice_1.h5 -train_slices_stage2/patient050_frame01_slice_2.h5 -train_slices_stage2/patient050_frame01_slice_3.h5 -train_slices_stage2/patient050_frame01_slice_4.h5 -train_slices_stage2/patient050_frame01_slice_5.h5 -train_slices_stage2/patient050_frame01_slice_6.h5 -train_slices_stage2/patient050_frame01_slice_7.h5 -train_slices_stage2/patient050_frame01_slice_8.h5 -train_slices_stage2/patient050_frame01_slice_9.h5 -train_slices_stage2/patient050_frame12_slice_0.h5 -train_slices_stage2/patient050_frame12_slice_1.h5 -train_slices_stage2/patient050_frame12_slice_2.h5 -train_slices_stage2/patient050_frame12_slice_3.h5 -train_slices_stage2/patient050_frame12_slice_4.h5 -train_slices_stage2/patient050_frame12_slice_5.h5 -train_slices_stage2/patient050_frame12_slice_6.h5 -train_slices_stage2/patient050_frame12_slice_7.h5 -train_slices_stage2/patient050_frame12_slice_8.h5 -train_slices_stage2/patient050_frame12_slice_9.h5 -train_slices_stage2/patient051_frame01_slice_0.h5 -train_slices_stage2/patient051_frame01_slice_1.h5 -train_slices_stage2/patient051_frame01_slice_2.h5 -train_slices_stage2/patient051_frame01_slice_3.h5 -train_slices_stage2/patient051_frame01_slice_4.h5 -train_slices_stage2/patient051_frame01_slice_5.h5 -train_slices_stage2/patient051_frame01_slice_6.h5 -train_slices_stage2/patient051_frame01_slice_7.h5 -train_slices_stage2/patient051_frame01_slice_8.h5 -train_slices_stage2/patient051_frame01_slice_9.h5 -train_slices_stage2/patient051_frame11_slice_0.h5 -train_slices_stage2/patient051_frame11_slice_1.h5 -train_slices_stage2/patient051_frame11_slice_2.h5 -train_slices_stage2/patient051_frame11_slice_3.h5 -train_slices_stage2/patient051_frame11_slice_4.h5 -train_slices_stage2/patient051_frame11_slice_5.h5 -train_slices_stage2/patient051_frame11_slice_6.h5 -train_slices_stage2/patient051_frame11_slice_7.h5 -train_slices_stage2/patient051_frame11_slice_8.h5 -train_slices_stage2/patient051_frame11_slice_9.h5 -train_slices_stage2/patient052_frame01_slice_0.h5 -train_slices_stage2/patient052_frame01_slice_1.h5 -train_slices_stage2/patient052_frame01_slice_2.h5 -train_slices_stage2/patient052_frame01_slice_3.h5 -train_slices_stage2/patient052_frame01_slice_4.h5 -train_slices_stage2/patient052_frame01_slice_5.h5 -train_slices_stage2/patient052_frame01_slice_6.h5 -train_slices_stage2/patient052_frame01_slice_7.h5 -train_slices_stage2/patient052_frame09_slice_0.h5 -train_slices_stage2/patient052_frame09_slice_1.h5 -train_slices_stage2/patient052_frame09_slice_2.h5 -train_slices_stage2/patient052_frame09_slice_3.h5 -train_slices_stage2/patient052_frame09_slice_4.h5 -train_slices_stage2/patient052_frame09_slice_5.h5 -train_slices_stage2/patient052_frame09_slice_6.h5 -train_slices_stage2/patient052_frame09_slice_7.h5 -train_slices_stage2/patient053_frame12_slice_0.h5 -train_slices_stage2/patient053_frame12_slice_1.h5 -train_slices_stage2/patient053_frame12_slice_2.h5 -train_slices_stage2/patient053_frame12_slice_3.h5 -train_slices_stage2/patient053_frame12_slice_4.h5 -train_slices_stage2/patient053_frame12_slice_5.h5 -train_slices_stage2/patient053_frame12_slice_6.h5 -train_slices_stage2/patient054_frame01_slice_0.h5 -train_slices_stage2/patient054_frame01_slice_1.h5 -train_slices_stage2/patient054_frame01_slice_2.h5 -train_slices_stage2/patient054_frame01_slice_3.h5 -train_slices_stage2/patient054_frame01_slice_4.h5 -train_slices_stage2/patient054_frame01_slice_5.h5 -train_slices_stage2/patient054_frame01_slice_6.h5 -train_slices_stage2/patient054_frame01_slice_7.h5 -train_slices_stage2/patient054_frame12_slice_0.h5 -train_slices_stage2/patient054_frame12_slice_1.h5 -train_slices_stage2/patient054_frame12_slice_2.h5 -train_slices_stage2/patient054_frame12_slice_3.h5 -train_slices_stage2/patient054_frame12_slice_4.h5 -train_slices_stage2/patient054_frame12_slice_5.h5 -train_slices_stage2/patient054_frame12_slice_6.h5 -train_slices_stage2/patient054_frame12_slice_7.h5 -train_slices_stage2/patient055_frame10_slice_0.h5 -train_slices_stage2/patient055_frame10_slice_1.h5 -train_slices_stage2/patient055_frame10_slice_2.h5 -train_slices_stage2/patient055_frame10_slice_3.h5 -train_slices_stage2/patient055_frame10_slice_4.h5 -train_slices_stage2/patient055_frame10_slice_5.h5 -train_slices_stage2/patient055_frame10_slice_6.h5 -train_slices_stage2/patient055_frame10_slice_7.h5 -train_slices_stage2/patient055_frame10_slice_8.h5 -train_slices_stage2/patient056_frame01_slice_0.h5 -train_slices_stage2/patient056_frame01_slice_1.h5 -train_slices_stage2/patient056_frame01_slice_2.h5 -train_slices_stage2/patient056_frame01_slice_3.h5 -train_slices_stage2/patient056_frame01_slice_4.h5 -train_slices_stage2/patient056_frame01_slice_5.h5 -train_slices_stage2/patient056_frame01_slice_6.h5 -train_slices_stage2/patient056_frame01_slice_7.h5 -train_slices_stage2/patient056_frame01_slice_8.h5 -train_slices_stage2/patient056_frame12_slice_0.h5 -train_slices_stage2/patient056_frame12_slice_1.h5 -train_slices_stage2/patient056_frame12_slice_2.h5 -train_slices_stage2/patient056_frame12_slice_3.h5 -train_slices_stage2/patient056_frame12_slice_4.h5 -train_slices_stage2/patient056_frame12_slice_5.h5 -train_slices_stage2/patient056_frame12_slice_6.h5 -train_slices_stage2/patient056_frame12_slice_7.h5 -train_slices_stage2/patient056_frame12_slice_8.h5 -train_slices_stage2/patient057_frame01_slice_0.h5 -train_slices_stage2/patient057_frame01_slice_1.h5 -train_slices_stage2/patient057_frame01_slice_2.h5 -train_slices_stage2/patient057_frame01_slice_3.h5 -train_slices_stage2/patient057_frame01_slice_4.h5 -train_slices_stage2/patient057_frame01_slice_5.h5 -train_slices_stage2/patient057_frame01_slice_6.h5 -train_slices_stage2/patient057_frame01_slice_7.h5 -train_slices_stage2/patient058_frame14_slice_0.h5 -train_slices_stage2/patient058_frame14_slice_1.h5 -train_slices_stage2/patient058_frame14_slice_2.h5 -train_slices_stage2/patient058_frame14_slice_3.h5 -train_slices_stage2/patient058_frame14_slice_4.h5 -train_slices_stage2/patient058_frame14_slice_5.h5 -train_slices_stage2/patient058_frame14_slice_6.h5 -train_slices_stage2/patient058_frame14_slice_7.h5 -train_slices_stage2/patient058_frame14_slice_8.h5 -train_slices_stage2/patient059_frame01_slice_0.h5 -train_slices_stage2/patient059_frame01_slice_1.h5 -train_slices_stage2/patient059_frame01_slice_2.h5 -train_slices_stage2/patient059_frame01_slice_3.h5 -train_slices_stage2/patient059_frame01_slice_4.h5 -train_slices_stage2/patient059_frame01_slice_5.h5 -train_slices_stage2/patient059_frame01_slice_6.h5 -train_slices_stage2/patient059_frame01_slice_7.h5 -train_slices_stage2/patient059_frame01_slice_8.h5 -train_slices_stage2/patient059_frame09_slice_0.h5 -train_slices_stage2/patient059_frame09_slice_1.h5 -train_slices_stage2/patient059_frame09_slice_2.h5 -train_slices_stage2/patient059_frame09_slice_3.h5 -train_slices_stage2/patient059_frame09_slice_4.h5 -train_slices_stage2/patient059_frame09_slice_5.h5 -train_slices_stage2/patient059_frame09_slice_6.h5 -train_slices_stage2/patient059_frame09_slice_7.h5 -train_slices_stage2/patient059_frame09_slice_8.h5 -train_slices_stage2/patient060_frame14_slice_0.h5 -train_slices_stage2/patient060_frame14_slice_1.h5 -train_slices_stage2/patient060_frame14_slice_2.h5 -train_slices_stage2/patient060_frame14_slice_3.h5 -train_slices_stage2/patient060_frame14_slice_4.h5 -train_slices_stage2/patient060_frame14_slice_5.h5 -train_slices_stage2/patient060_frame14_slice_6.h5 -train_slices_stage2/patient060_frame14_slice_7.h5 -train_slices_stage2/patient060_frame14_slice_8.h5 -train_slices_stage2/patient061_frame01_slice_0.h5 -train_slices_stage2/patient061_frame01_slice_1.h5 -train_slices_stage2/patient061_frame01_slice_2.h5 -train_slices_stage2/patient061_frame01_slice_3.h5 -train_slices_stage2/patient061_frame01_slice_4.h5 -train_slices_stage2/patient061_frame01_slice_5.h5 -train_slices_stage2/patient061_frame01_slice_6.h5 -train_slices_stage2/patient061_frame01_slice_7.h5 -train_slices_stage2/patient061_frame01_slice_8.h5 -train_slices_stage2/patient061_frame10_slice_0.h5 -train_slices_stage2/patient061_frame10_slice_1.h5 -train_slices_stage2/patient061_frame10_slice_2.h5 -train_slices_stage2/patient061_frame10_slice_3.h5 -train_slices_stage2/patient061_frame10_slice_4.h5 -train_slices_stage2/patient061_frame10_slice_5.h5 -train_slices_stage2/patient061_frame10_slice_6.h5 -train_slices_stage2/patient061_frame10_slice_7.h5 -train_slices_stage2/patient061_frame10_slice_8.h5 -train_slices_stage2/patient062_frame01_slice_0.h5 -train_slices_stage2/patient062_frame01_slice_1.h5 -train_slices_stage2/patient062_frame01_slice_2.h5 -train_slices_stage2/patient062_frame01_slice_3.h5 -train_slices_stage2/patient062_frame01_slice_4.h5 -train_slices_stage2/patient062_frame01_slice_5.h5 -train_slices_stage2/patient062_frame01_slice_6.h5 -train_slices_stage2/patient062_frame01_slice_7.h5 -train_slices_stage2/patient062_frame01_slice_8.h5 -train_slices_stage2/patient062_frame01_slice_9.h5 -train_slices_stage2/patient062_frame09_slice_0.h5 -train_slices_stage2/patient062_frame09_slice_1.h5 -train_slices_stage2/patient062_frame09_slice_2.h5 -train_slices_stage2/patient062_frame09_slice_3.h5 -train_slices_stage2/patient062_frame09_slice_4.h5 -train_slices_stage2/patient062_frame09_slice_5.h5 -train_slices_stage2/patient062_frame09_slice_6.h5 -train_slices_stage2/patient062_frame09_slice_7.h5 -train_slices_stage2/patient062_frame09_slice_8.h5 -train_slices_stage2/patient062_frame09_slice_9.h5 -train_slices_stage2/patient063_frame16_slice_0.h5 -train_slices_stage2/patient063_frame16_slice_1.h5 -train_slices_stage2/patient063_frame16_slice_2.h5 -train_slices_stage2/patient063_frame16_slice_3.h5 -train_slices_stage2/patient063_frame16_slice_4.h5 -train_slices_stage2/patient063_frame16_slice_5.h5 -train_slices_stage2/patient063_frame16_slice_6.h5 -train_slices_stage2/patient063_frame16_slice_7.h5 -train_slices_stage2/patient064_frame01_slice_0.h5 -train_slices_stage2/patient064_frame01_slice_1.h5 -train_slices_stage2/patient064_frame01_slice_2.h5 -train_slices_stage2/patient064_frame01_slice_3.h5 -train_slices_stage2/patient064_frame01_slice_4.h5 -train_slices_stage2/patient064_frame01_slice_5.h5 -train_slices_stage2/patient064_frame01_slice_6.h5 -train_slices_stage2/patient064_frame01_slice_7.h5 -train_slices_stage2/patient064_frame01_slice_8.h5 -train_slices_stage2/patient064_frame01_slice_9.h5 -train_slices_stage2/patient066_frame01_slice_0.h5 -train_slices_stage2/patient066_frame01_slice_1.h5 -train_slices_stage2/patient066_frame01_slice_2.h5 -train_slices_stage2/patient066_frame01_slice_3.h5 -train_slices_stage2/patient066_frame01_slice_4.h5 -train_slices_stage2/patient066_frame01_slice_5.h5 -train_slices_stage2/patient066_frame01_slice_6.h5 -train_slices_stage2/patient066_frame01_slice_7.h5 -train_slices_stage2/patient066_frame01_slice_8.h5 -train_slices_stage2/patient067_frame01_slice_0.h5 -train_slices_stage2/patient067_frame01_slice_1.h5 -train_slices_stage2/patient067_frame01_slice_2.h5 -train_slices_stage2/patient067_frame01_slice_3.h5 -train_slices_stage2/patient067_frame01_slice_4.h5 -train_slices_stage2/patient067_frame01_slice_5.h5 -train_slices_stage2/patient067_frame01_slice_6.h5 -train_slices_stage2/patient067_frame01_slice_7.h5 -train_slices_stage2/patient067_frame01_slice_8.h5 -train_slices_stage2/patient067_frame01_slice_9.h5 -train_slices_stage2/patient067_frame10_slice_0.h5 -train_slices_stage2/patient067_frame10_slice_1.h5 -train_slices_stage2/patient067_frame10_slice_2.h5 -train_slices_stage2/patient067_frame10_slice_3.h5 -train_slices_stage2/patient067_frame10_slice_4.h5 -train_slices_stage2/patient067_frame10_slice_5.h5 -train_slices_stage2/patient067_frame10_slice_6.h5 -train_slices_stage2/patient067_frame10_slice_7.h5 -train_slices_stage2/patient067_frame10_slice_8.h5 -train_slices_stage2/patient067_frame10_slice_9.h5 -train_slices_stage2/patient068_frame01_slice_0.h5 -train_slices_stage2/patient068_frame01_slice_1.h5 -train_slices_stage2/patient068_frame01_slice_2.h5 -train_slices_stage2/patient068_frame01_slice_3.h5 -train_slices_stage2/patient068_frame01_slice_4.h5 -train_slices_stage2/patient068_frame01_slice_5.h5 -train_slices_stage2/patient068_frame01_slice_6.h5 -train_slices_stage2/patient069_frame01_slice_0.h5 -train_slices_stage2/patient069_frame01_slice_1.h5 -train_slices_stage2/patient069_frame01_slice_2.h5 -train_slices_stage2/patient069_frame01_slice_3.h5 -train_slices_stage2/patient069_frame01_slice_4.h5 -train_slices_stage2/patient069_frame01_slice_5.h5 -train_slices_stage2/patient069_frame01_slice_6.h5 -train_slices_stage2/patient070_frame01_slice_0.h5 -train_slices_stage2/patient070_frame01_slice_1.h5 -train_slices_stage2/patient070_frame01_slice_2.h5 -train_slices_stage2/patient070_frame01_slice_3.h5 -train_slices_stage2/patient070_frame01_slice_4.h5 -train_slices_stage2/patient070_frame01_slice_5.h5 -train_slices_stage2/patient071_frame09_slice_0.h5 -train_slices_stage2/patient071_frame09_slice_1.h5 -train_slices_stage2/patient071_frame09_slice_2.h5 -train_slices_stage2/patient071_frame09_slice_3.h5 -train_slices_stage2/patient071_frame09_slice_4.h5 -train_slices_stage2/patient071_frame09_slice_5.h5 -train_slices_stage2/patient071_frame09_slice_6.h5 -train_slices_stage2/patient071_frame09_slice_7.h5 -train_slices_stage2/patient071_frame09_slice_8.h5 -train_slices_stage2/patient071_frame09_slice_9.h5 -train_slices_stage2/patient072_frame01_slice_0.h5 -train_slices_stage2/patient072_frame01_slice_1.h5 -train_slices_stage2/patient072_frame01_slice_2.h5 -train_slices_stage2/patient072_frame01_slice_3.h5 -train_slices_stage2/patient072_frame01_slice_4.h5 -train_slices_stage2/patient072_frame01_slice_5.h5 -train_slices_stage2/patient072_frame01_slice_6.h5 -train_slices_stage2/patient072_frame01_slice_7.h5 -train_slices_stage2/patient073_frame10_slice_0.h5 -train_slices_stage2/patient073_frame10_slice_1.h5 -train_slices_stage2/patient073_frame10_slice_2.h5 -train_slices_stage2/patient073_frame10_slice_3.h5 -train_slices_stage2/patient073_frame10_slice_4.h5 -train_slices_stage2/patient073_frame10_slice_5.h5 -train_slices_stage2/patient073_frame10_slice_6.h5 -train_slices_stage2/patient074_frame12_slice_0.h5 -train_slices_stage2/patient074_frame12_slice_1.h5 -train_slices_stage2/patient074_frame12_slice_2.h5 -train_slices_stage2/patient074_frame12_slice_3.h5 -train_slices_stage2/patient074_frame12_slice_4.h5 -train_slices_stage2/patient074_frame12_slice_5.h5 -train_slices_stage2/patient074_frame12_slice_6.h5 -train_slices_stage2/patient074_frame12_slice_7.h5 -train_slices_stage2/patient075_frame01_slice_0.h5 -train_slices_stage2/patient075_frame01_slice_1.h5 -train_slices_stage2/patient075_frame01_slice_10.h5 -train_slices_stage2/patient075_frame01_slice_11.h5 -train_slices_stage2/patient075_frame01_slice_12.h5 -train_slices_stage2/patient075_frame01_slice_13.h5 -train_slices_stage2/patient075_frame01_slice_2.h5 -train_slices_stage2/patient075_frame01_slice_3.h5 -train_slices_stage2/patient075_frame01_slice_4.h5 -train_slices_stage2/patient075_frame01_slice_5.h5 -train_slices_stage2/patient075_frame01_slice_6.h5 -train_slices_stage2/patient075_frame01_slice_7.h5 -train_slices_stage2/patient075_frame01_slice_8.h5 -train_slices_stage2/patient075_frame01_slice_9.h5 -train_slices_stage2/patient076_frame12_slice_0.h5 -train_slices_stage2/patient076_frame12_slice_1.h5 -train_slices_stage2/patient076_frame12_slice_2.h5 -train_slices_stage2/patient076_frame12_slice_3.h5 -train_slices_stage2/patient076_frame12_slice_4.h5 -train_slices_stage2/patient076_frame12_slice_5.h5 -train_slices_stage2/patient076_frame12_slice_6.h5 -train_slices_stage2/patient076_frame12_slice_7.h5 -train_slices_stage2/patient077_frame09_slice_0.h5 -train_slices_stage2/patient077_frame09_slice_1.h5 -train_slices_stage2/patient077_frame09_slice_2.h5 -train_slices_stage2/patient077_frame09_slice_3.h5 -train_slices_stage2/patient077_frame09_slice_4.h5 -train_slices_stage2/patient077_frame09_slice_5.h5 -train_slices_stage2/patient077_frame09_slice_6.h5 -train_slices_stage2/patient077_frame09_slice_7.h5 -train_slices_stage2/patient078_frame01_slice_0.h5 -train_slices_stage2/patient078_frame01_slice_1.h5 -train_slices_stage2/patient078_frame01_slice_2.h5 -train_slices_stage2/patient078_frame01_slice_3.h5 -train_slices_stage2/patient078_frame01_slice_4.h5 -train_slices_stage2/patient078_frame01_slice_5.h5 -train_slices_stage2/patient078_frame01_slice_6.h5 -train_slices_stage2/patient078_frame01_slice_7.h5 -train_slices_stage2/patient078_frame09_slice_0.h5 -train_slices_stage2/patient078_frame09_slice_1.h5 -train_slices_stage2/patient078_frame09_slice_2.h5 -train_slices_stage2/patient078_frame09_slice_3.h5 -train_slices_stage2/patient078_frame09_slice_4.h5 -train_slices_stage2/patient078_frame09_slice_5.h5 -train_slices_stage2/patient078_frame09_slice_6.h5 -train_slices_stage2/patient078_frame09_slice_7.h5 -train_slices_stage2/patient079_frame01_slice_0.h5 -train_slices_stage2/patient079_frame01_slice_1.h5 -train_slices_stage2/patient079_frame01_slice_2.h5 -train_slices_stage2/patient079_frame01_slice_3.h5 -train_slices_stage2/patient079_frame01_slice_4.h5 -train_slices_stage2/patient079_frame01_slice_5.h5 -train_slices_stage2/patient079_frame01_slice_6.h5 -train_slices_stage2/patient079_frame01_slice_7.h5 -train_slices_stage2/patient079_frame01_slice_8.h5 -train_slices_stage2/patient079_frame11_slice_0.h5 -train_slices_stage2/patient079_frame11_slice_1.h5 -train_slices_stage2/patient079_frame11_slice_2.h5 -train_slices_stage2/patient079_frame11_slice_3.h5 -train_slices_stage2/patient079_frame11_slice_4.h5 -train_slices_stage2/patient079_frame11_slice_5.h5 -train_slices_stage2/patient079_frame11_slice_6.h5 -train_slices_stage2/patient079_frame11_slice_7.h5 -train_slices_stage2/patient079_frame11_slice_8.h5 -train_slices_stage2/patient080_frame01_slice_0.h5 -train_slices_stage2/patient080_frame01_slice_1.h5 -train_slices_stage2/patient080_frame01_slice_2.h5 -train_slices_stage2/patient080_frame01_slice_3.h5 -train_slices_stage2/patient080_frame01_slice_4.h5 -train_slices_stage2/patient080_frame01_slice_5.h5 -train_slices_stage2/patient080_frame10_slice_0.h5 -train_slices_stage2/patient080_frame10_slice_1.h5 -train_slices_stage2/patient080_frame10_slice_2.h5 -train_slices_stage2/patient080_frame10_slice_3.h5 -train_slices_stage2/patient080_frame10_slice_4.h5 -train_slices_stage2/patient080_frame10_slice_5.h5 -train_slices_stage2/patient081_frame07_slice_0.h5 -train_slices_stage2/patient081_frame07_slice_1.h5 -train_slices_stage2/patient081_frame07_slice_10.h5 -train_slices_stage2/patient081_frame07_slice_11.h5 -train_slices_stage2/patient081_frame07_slice_12.h5 -train_slices_stage2/patient081_frame07_slice_13.h5 -train_slices_stage2/patient081_frame07_slice_14.h5 -train_slices_stage2/patient081_frame07_slice_15.h5 -train_slices_stage2/patient081_frame07_slice_16.h5 -train_slices_stage2/patient081_frame07_slice_2.h5 -train_slices_stage2/patient081_frame07_slice_3.h5 -train_slices_stage2/patient081_frame07_slice_4.h5 -train_slices_stage2/patient081_frame07_slice_5.h5 -train_slices_stage2/patient081_frame07_slice_6.h5 -train_slices_stage2/patient081_frame07_slice_7.h5 -train_slices_stage2/patient081_frame07_slice_8.h5 -train_slices_stage2/patient081_frame07_slice_9.h5 -train_slices_stage2/patient082_frame01_slice_0.h5 -train_slices_stage2/patient082_frame01_slice_1.h5 -train_slices_stage2/patient082_frame01_slice_10.h5 -train_slices_stage2/patient082_frame01_slice_11.h5 -train_slices_stage2/patient082_frame01_slice_12.h5 -train_slices_stage2/patient082_frame01_slice_13.h5 -train_slices_stage2/patient082_frame01_slice_14.h5 -train_slices_stage2/patient082_frame01_slice_15.h5 -train_slices_stage2/patient082_frame01_slice_2.h5 -train_slices_stage2/patient082_frame01_slice_3.h5 -train_slices_stage2/patient082_frame01_slice_4.h5 -train_slices_stage2/patient082_frame01_slice_5.h5 -train_slices_stage2/patient082_frame01_slice_6.h5 -train_slices_stage2/patient082_frame01_slice_7.h5 -train_slices_stage2/patient082_frame01_slice_8.h5 -train_slices_stage2/patient082_frame01_slice_9.h5 -train_slices_stage2/patient082_frame07_slice_0.h5 -train_slices_stage2/patient082_frame07_slice_1.h5 -train_slices_stage2/patient082_frame07_slice_10.h5 -train_slices_stage2/patient082_frame07_slice_11.h5 -train_slices_stage2/patient082_frame07_slice_12.h5 -train_slices_stage2/patient082_frame07_slice_13.h5 -train_slices_stage2/patient082_frame07_slice_14.h5 -train_slices_stage2/patient082_frame07_slice_15.h5 -train_slices_stage2/patient082_frame07_slice_2.h5 -train_slices_stage2/patient082_frame07_slice_3.h5 -train_slices_stage2/patient082_frame07_slice_4.h5 -train_slices_stage2/patient082_frame07_slice_5.h5 -train_slices_stage2/patient082_frame07_slice_6.h5 -train_slices_stage2/patient082_frame07_slice_7.h5 -train_slices_stage2/patient082_frame07_slice_8.h5 -train_slices_stage2/patient082_frame07_slice_9.h5 -train_slices_stage2/patient083_frame01_slice_0.h5 -train_slices_stage2/patient083_frame01_slice_1.h5 -train_slices_stage2/patient083_frame01_slice_2.h5 -train_slices_stage2/patient083_frame01_slice_3.h5 -train_slices_stage2/patient083_frame01_slice_4.h5 -train_slices_stage2/patient083_frame01_slice_5.h5 -train_slices_stage2/patient084_frame01_slice_0.h5 -train_slices_stage2/patient084_frame01_slice_1.h5 -train_slices_stage2/patient084_frame01_slice_10.h5 -train_slices_stage2/patient084_frame01_slice_11.h5 -train_slices_stage2/patient084_frame01_slice_2.h5 -train_slices_stage2/patient084_frame01_slice_3.h5 -train_slices_stage2/patient084_frame01_slice_4.h5 -train_slices_stage2/patient084_frame01_slice_5.h5 -train_slices_stage2/patient084_frame01_slice_6.h5 -train_slices_stage2/patient084_frame01_slice_7.h5 -train_slices_stage2/patient084_frame01_slice_8.h5 -train_slices_stage2/patient084_frame01_slice_9.h5 -train_slices_stage2/patient084_frame10_slice_0.h5 -train_slices_stage2/patient084_frame10_slice_1.h5 -train_slices_stage2/patient084_frame10_slice_10.h5 -train_slices_stage2/patient084_frame10_slice_11.h5 -train_slices_stage2/patient084_frame10_slice_2.h5 -train_slices_stage2/patient084_frame10_slice_3.h5 -train_slices_stage2/patient084_frame10_slice_4.h5 -train_slices_stage2/patient084_frame10_slice_5.h5 -train_slices_stage2/patient084_frame10_slice_6.h5 -train_slices_stage2/patient084_frame10_slice_7.h5 -train_slices_stage2/patient084_frame10_slice_8.h5 -train_slices_stage2/patient084_frame10_slice_9.h5 -train_slices_stage2/patient085_frame01_slice_0.h5 -train_slices_stage2/patient085_frame01_slice_1.h5 -train_slices_stage2/patient085_frame01_slice_10.h5 -train_slices_stage2/patient085_frame01_slice_11.h5 -train_slices_stage2/patient085_frame01_slice_12.h5 -train_slices_stage2/patient085_frame01_slice_13.h5 -train_slices_stage2/patient085_frame01_slice_14.h5 -train_slices_stage2/patient085_frame01_slice_2.h5 -train_slices_stage2/patient085_frame01_slice_3.h5 -train_slices_stage2/patient085_frame01_slice_4.h5 -train_slices_stage2/patient085_frame01_slice_5.h5 -train_slices_stage2/patient085_frame01_slice_6.h5 -train_slices_stage2/patient085_frame01_slice_7.h5 -train_slices_stage2/patient085_frame01_slice_8.h5 -train_slices_stage2/patient085_frame01_slice_9.h5 -train_slices_stage2/patient087_frame01_slice_0.h5 -train_slices_stage2/patient087_frame01_slice_1.h5 -train_slices_stage2/patient087_frame01_slice_2.h5 -train_slices_stage2/patient087_frame01_slice_3.h5 -train_slices_stage2/patient087_frame01_slice_4.h5 -train_slices_stage2/patient087_frame01_slice_5.h5 -train_slices_stage2/patient087_frame01_slice_6.h5 -train_slices_stage2/patient087_frame01_slice_7.h5 -train_slices_stage2/patient088_frame01_slice_0.h5 -train_slices_stage2/patient088_frame01_slice_1.h5 -train_slices_stage2/patient088_frame01_slice_10.h5 -train_slices_stage2/patient088_frame01_slice_11.h5 -train_slices_stage2/patient088_frame01_slice_12.h5 -train_slices_stage2/patient088_frame01_slice_13.h5 -train_slices_stage2/patient088_frame01_slice_14.h5 -train_slices_stage2/patient088_frame01_slice_15.h5 -train_slices_stage2/patient088_frame01_slice_2.h5 -train_slices_stage2/patient088_frame01_slice_3.h5 -train_slices_stage2/patient088_frame01_slice_4.h5 -train_slices_stage2/patient088_frame01_slice_5.h5 -train_slices_stage2/patient088_frame01_slice_6.h5 -train_slices_stage2/patient088_frame01_slice_7.h5 -train_slices_stage2/patient088_frame01_slice_8.h5 -train_slices_stage2/patient088_frame01_slice_9.h5 -train_slices_stage2/patient088_frame12_slice_0.h5 -train_slices_stage2/patient088_frame12_slice_1.h5 -train_slices_stage2/patient088_frame12_slice_10.h5 -train_slices_stage2/patient088_frame12_slice_11.h5 -train_slices_stage2/patient088_frame12_slice_12.h5 -train_slices_stage2/patient088_frame12_slice_13.h5 -train_slices_stage2/patient088_frame12_slice_14.h5 -train_slices_stage2/patient088_frame12_slice_15.h5 -train_slices_stage2/patient088_frame12_slice_2.h5 -train_slices_stage2/patient088_frame12_slice_3.h5 -train_slices_stage2/patient088_frame12_slice_4.h5 -train_slices_stage2/patient088_frame12_slice_5.h5 -train_slices_stage2/patient088_frame12_slice_6.h5 -train_slices_stage2/patient088_frame12_slice_7.h5 -train_slices_stage2/patient088_frame12_slice_8.h5 -train_slices_stage2/patient088_frame12_slice_9.h5 -train_slices_stage2/patient090_frame11_slice_0.h5 -train_slices_stage2/patient090_frame11_slice_1.h5 -train_slices_stage2/patient090_frame11_slice_2.h5 -train_slices_stage2/patient090_frame11_slice_3.h5 -train_slices_stage2/patient090_frame11_slice_4.h5 -train_slices_stage2/patient090_frame11_slice_5.h5 -train_slices_stage2/patient090_frame11_slice_6.h5 -train_slices_stage2/patient091_frame01_slice_0.h5 -train_slices_stage2/patient091_frame01_slice_1.h5 -train_slices_stage2/patient091_frame01_slice_2.h5 -train_slices_stage2/patient091_frame01_slice_3.h5 -train_slices_stage2/patient091_frame01_slice_4.h5 -train_slices_stage2/patient091_frame01_slice_5.h5 -train_slices_stage2/patient091_frame01_slice_6.h5 -train_slices_stage2/patient091_frame01_slice_7.h5 -train_slices_stage2/patient091_frame09_slice_0.h5 -train_slices_stage2/patient091_frame09_slice_1.h5 -train_slices_stage2/patient091_frame09_slice_2.h5 -train_slices_stage2/patient091_frame09_slice_3.h5 -train_slices_stage2/patient091_frame09_slice_4.h5 -train_slices_stage2/patient091_frame09_slice_5.h5 -train_slices_stage2/patient091_frame09_slice_6.h5 -train_slices_stage2/patient091_frame09_slice_7.h5 -train_slices_stage2/patient092_frame01_slice_0.h5 -train_slices_stage2/patient092_frame01_slice_1.h5 -train_slices_stage2/patient092_frame01_slice_10.h5 -train_slices_stage2/patient092_frame01_slice_11.h5 -train_slices_stage2/patient092_frame01_slice_12.h5 -train_slices_stage2/patient092_frame01_slice_13.h5 -train_slices_stage2/patient092_frame01_slice_14.h5 -train_slices_stage2/patient092_frame01_slice_2.h5 -train_slices_stage2/patient092_frame01_slice_3.h5 -train_slices_stage2/patient092_frame01_slice_4.h5 -train_slices_stage2/patient092_frame01_slice_5.h5 -train_slices_stage2/patient092_frame01_slice_6.h5 -train_slices_stage2/patient092_frame01_slice_7.h5 -train_slices_stage2/patient092_frame01_slice_8.h5 -train_slices_stage2/patient092_frame01_slice_9.h5 -train_slices_stage2/patient092_frame06_slice_0.h5 -train_slices_stage2/patient092_frame06_slice_1.h5 -train_slices_stage2/patient092_frame06_slice_10.h5 -train_slices_stage2/patient092_frame06_slice_11.h5 -train_slices_stage2/patient092_frame06_slice_12.h5 -train_slices_stage2/patient092_frame06_slice_13.h5 -train_slices_stage2/patient092_frame06_slice_14.h5 -train_slices_stage2/patient092_frame06_slice_2.h5 -train_slices_stage2/patient092_frame06_slice_3.h5 -train_slices_stage2/patient092_frame06_slice_4.h5 -train_slices_stage2/patient092_frame06_slice_5.h5 -train_slices_stage2/patient092_frame06_slice_6.h5 -train_slices_stage2/patient092_frame06_slice_7.h5 -train_slices_stage2/patient092_frame06_slice_8.h5 -train_slices_stage2/patient092_frame06_slice_9.h5 -train_slices_stage2/patient093_frame14_slice_0.h5 -train_slices_stage2/patient093_frame14_slice_1.h5 -train_slices_stage2/patient093_frame14_slice_2.h5 -train_slices_stage2/patient093_frame14_slice_3.h5 -train_slices_stage2/patient093_frame14_slice_4.h5 -train_slices_stage2/patient093_frame14_slice_5.h5 -train_slices_stage2/patient093_frame14_slice_6.h5 -train_slices_stage2/patient093_frame14_slice_7.h5 -train_slices_stage2/patient093_frame14_slice_8.h5 -train_slices_stage2/patient093_frame14_slice_9.h5 -train_slices_stage2/patient095_frame01_slice_0.h5 -train_slices_stage2/patient095_frame01_slice_1.h5 -train_slices_stage2/patient095_frame01_slice_10.h5 -train_slices_stage2/patient095_frame01_slice_11.h5 -train_slices_stage2/patient095_frame01_slice_12.h5 -train_slices_stage2/patient095_frame01_slice_13.h5 -train_slices_stage2/patient095_frame01_slice_2.h5 -train_slices_stage2/patient095_frame01_slice_3.h5 -train_slices_stage2/patient095_frame01_slice_4.h5 -train_slices_stage2/patient095_frame01_slice_5.h5 -train_slices_stage2/patient095_frame01_slice_6.h5 -train_slices_stage2/patient095_frame01_slice_7.h5 -train_slices_stage2/patient095_frame01_slice_8.h5 -train_slices_stage2/patient095_frame01_slice_9.h5 -train_slices_stage2/patient095_frame12_slice_0.h5 -train_slices_stage2/patient095_frame12_slice_1.h5 -train_slices_stage2/patient095_frame12_slice_10.h5 -train_slices_stage2/patient095_frame12_slice_11.h5 -train_slices_stage2/patient095_frame12_slice_12.h5 -train_slices_stage2/patient095_frame12_slice_13.h5 -train_slices_stage2/patient095_frame12_slice_2.h5 -train_slices_stage2/patient095_frame12_slice_3.h5 -train_slices_stage2/patient095_frame12_slice_4.h5 -train_slices_stage2/patient095_frame12_slice_5.h5 -train_slices_stage2/patient095_frame12_slice_6.h5 -train_slices_stage2/patient095_frame12_slice_7.h5 -train_slices_stage2/patient095_frame12_slice_8.h5 -train_slices_stage2/patient095_frame12_slice_9.h5 -train_slices_stage2/patient096_frame08_slice_0.h5 -train_slices_stage2/patient096_frame08_slice_1.h5 -train_slices_stage2/patient096_frame08_slice_10.h5 -train_slices_stage2/patient096_frame08_slice_11.h5 -train_slices_stage2/patient096_frame08_slice_12.h5 -train_slices_stage2/patient096_frame08_slice_13.h5 -train_slices_stage2/patient096_frame08_slice_14.h5 -train_slices_stage2/patient096_frame08_slice_15.h5 -train_slices_stage2/patient096_frame08_slice_16.h5 -train_slices_stage2/patient096_frame08_slice_17.h5 -train_slices_stage2/patient096_frame08_slice_2.h5 -train_slices_stage2/patient096_frame08_slice_3.h5 -train_slices_stage2/patient096_frame08_slice_4.h5 -train_slices_stage2/patient096_frame08_slice_5.h5 -train_slices_stage2/patient096_frame08_slice_6.h5 -train_slices_stage2/patient096_frame08_slice_7.h5 -train_slices_stage2/patient096_frame08_slice_8.h5 -train_slices_stage2/patient096_frame08_slice_9.h5 -train_slices_stage2/patient097_frame01_slice_0.h5 -train_slices_stage2/patient097_frame01_slice_1.h5 -train_slices_stage2/patient097_frame01_slice_2.h5 -train_slices_stage2/patient097_frame01_slice_3.h5 -train_slices_stage2/patient097_frame01_slice_4.h5 -train_slices_stage2/patient097_frame01_slice_5.h5 -train_slices_stage2/patient097_frame01_slice_6.h5 -train_slices_stage2/patient097_frame01_slice_7.h5 -train_slices_stage2/patient097_frame11_slice_0.h5 -train_slices_stage2/patient097_frame11_slice_1.h5 -train_slices_stage2/patient097_frame11_slice_2.h5 -train_slices_stage2/patient097_frame11_slice_3.h5 -train_slices_stage2/patient097_frame11_slice_4.h5 -train_slices_stage2/patient097_frame11_slice_5.h5 -train_slices_stage2/patient097_frame11_slice_6.h5 -train_slices_stage2/patient097_frame11_slice_7.h5 -train_slices_stage2/patient099_frame01_slice_0.h5 -train_slices_stage2/patient099_frame01_slice_1.h5 -train_slices_stage2/patient099_frame01_slice_10.h5 -train_slices_stage2/patient099_frame01_slice_11.h5 -train_slices_stage2/patient099_frame01_slice_12.h5 -train_slices_stage2/patient099_frame01_slice_13.h5 -train_slices_stage2/patient099_frame01_slice_14.h5 -train_slices_stage2/patient099_frame01_slice_15.h5 -train_slices_stage2/patient099_frame01_slice_2.h5 -train_slices_stage2/patient099_frame01_slice_3.h5 -train_slices_stage2/patient099_frame01_slice_4.h5 -train_slices_stage2/patient099_frame01_slice_5.h5 -train_slices_stage2/patient099_frame01_slice_6.h5 -train_slices_stage2/patient099_frame01_slice_7.h5 -train_slices_stage2/patient099_frame01_slice_8.h5 -train_slices_stage2/patient099_frame01_slice_9.h5 -train_slices_stage2/patient099_frame09_slice_0.h5 -train_slices_stage2/patient099_frame09_slice_1.h5 -train_slices_stage2/patient099_frame09_slice_10.h5 -train_slices_stage2/patient099_frame09_slice_11.h5 -train_slices_stage2/patient099_frame09_slice_12.h5 -train_slices_stage2/patient099_frame09_slice_13.h5 -train_slices_stage2/patient099_frame09_slice_14.h5 -train_slices_stage2/patient099_frame09_slice_15.h5 -train_slices_stage2/patient099_frame09_slice_2.h5 -train_slices_stage2/patient099_frame09_slice_3.h5 -train_slices_stage2/patient099_frame09_slice_4.h5 -train_slices_stage2/patient099_frame09_slice_5.h5 -train_slices_stage2/patient099_frame09_slice_6.h5 -train_slices_stage2/patient099_frame09_slice_7.h5 -train_slices_stage2/patient099_frame09_slice_8.h5 -train_slices_stage2/patient099_frame09_slice_9.h5 -train_slices_stage2/patient100_frame01_slice_0.h5 -train_slices_stage2/patient100_frame01_slice_1.h5 -train_slices_stage2/patient100_frame01_slice_2.h5 -train_slices_stage2/patient100_frame01_slice_3.h5 -train_slices_stage2/patient100_frame01_slice_4.h5 -train_slices_stage2/patient100_frame01_slice_5.h5 -train_slices_stage2/patient100_frame01_slice_6.h5 -train_slices_stage2/patient100_frame01_slice_7.h5 -train_slices_stage2/patient100_frame13_slice_0.h5 -train_slices_stage2/patient100_frame13_slice_1.h5 -train_slices_stage2/patient100_frame13_slice_2.h5 -train_slices_stage2/patient100_frame13_slice_3.h5 -train_slices_stage2/patient100_frame13_slice_4.h5 -train_slices_stage2/patient100_frame13_slice_5.h5 -train_slices_stage2/patient100_frame13_slice_6.h5 -train_slices_stage2/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/trainrless2.txt b/data/ACDC2017/ACDC_for2D/trainrless2.txt deleted file mode 100644 index c23a47b..0000000 --- a/data/ACDC2017/ACDC_for2D/trainrless2.txt +++ /dev/null @@ -1,1356 +0,0 @@ -trainrless2_slices/patient001_frame01_slice_0.h5 -trainrless2_slices/patient001_frame01_slice_1.h5 -trainrless2_slices/patient001_frame01_slice_2.h5 -trainrless2_slices/patient001_frame01_slice_3.h5 -trainrless2_slices/patient001_frame01_slice_4.h5 -trainrless2_slices/patient001_frame01_slice_5.h5 -trainrless2_slices/patient001_frame01_slice_6.h5 -trainrless2_slices/patient001_frame01_slice_7.h5 -trainrless2_slices/patient001_frame01_slice_8.h5 -trainrless2_slices/patient001_frame01_slice_9.h5 -trainrless2_slices/patient001_frame12_slice_0.h5 -trainrless2_slices/patient001_frame12_slice_1.h5 -trainrless2_slices/patient001_frame12_slice_2.h5 -trainrless2_slices/patient001_frame12_slice_3.h5 -trainrless2_slices/patient001_frame12_slice_4.h5 -trainrless2_slices/patient001_frame12_slice_5.h5 -trainrless2_slices/patient001_frame12_slice_6.h5 -trainrless2_slices/patient001_frame12_slice_7.h5 -trainrless2_slices/patient001_frame12_slice_8.h5 -trainrless2_slices/patient001_frame12_slice_9.h5 -trainrless2_slices/patient002_frame01_slice_0.h5 -trainrless2_slices/patient002_frame01_slice_1.h5 -trainrless2_slices/patient002_frame01_slice_2.h5 -trainrless2_slices/patient002_frame01_slice_3.h5 -trainrless2_slices/patient002_frame01_slice_4.h5 -trainrless2_slices/patient002_frame01_slice_5.h5 -trainrless2_slices/patient002_frame01_slice_6.h5 -trainrless2_slices/patient002_frame01_slice_7.h5 -trainrless2_slices/patient002_frame01_slice_8.h5 -trainrless2_slices/patient002_frame01_slice_9.h5 -trainrless2_slices/patient002_frame12_slice_0.h5 -trainrless2_slices/patient002_frame12_slice_1.h5 -trainrless2_slices/patient002_frame12_slice_2.h5 -trainrless2_slices/patient002_frame12_slice_3.h5 -trainrless2_slices/patient002_frame12_slice_4.h5 -trainrless2_slices/patient002_frame12_slice_5.h5 -trainrless2_slices/patient002_frame12_slice_6.h5 -trainrless2_slices/patient002_frame12_slice_7.h5 -trainrless2_slices/patient002_frame12_slice_8.h5 -trainrless2_slices/patient002_frame12_slice_9.h5 -trainrless2_slices/patient003_frame01_slice_0.h5 -trainrless2_slices/patient003_frame01_slice_1.h5 -trainrless2_slices/patient003_frame01_slice_2.h5 -trainrless2_slices/patient003_frame01_slice_3.h5 -trainrless2_slices/patient003_frame01_slice_4.h5 -trainrless2_slices/patient003_frame01_slice_5.h5 -trainrless2_slices/patient003_frame01_slice_6.h5 -trainrless2_slices/patient003_frame01_slice_7.h5 -trainrless2_slices/patient003_frame01_slice_8.h5 -trainrless2_slices/patient003_frame01_slice_9.h5 -trainrless2_slices/patient003_frame15_slice_0.h5 -trainrless2_slices/patient003_frame15_slice_1.h5 -trainrless2_slices/patient003_frame15_slice_2.h5 -trainrless2_slices/patient003_frame15_slice_3.h5 -trainrless2_slices/patient003_frame15_slice_4.h5 -trainrless2_slices/patient003_frame15_slice_5.h5 -trainrless2_slices/patient003_frame15_slice_6.h5 -trainrless2_slices/patient003_frame15_slice_7.h5 -trainrless2_slices/patient003_frame15_slice_8.h5 -trainrless2_slices/patient003_frame15_slice_9.h5 -trainrless2_slices/patient004_frame01_slice_0.h5 -trainrless2_slices/patient004_frame01_slice_1.h5 -trainrless2_slices/patient004_frame01_slice_2.h5 -trainrless2_slices/patient004_frame01_slice_3.h5 -trainrless2_slices/patient004_frame01_slice_4.h5 -trainrless2_slices/patient004_frame01_slice_5.h5 -trainrless2_slices/patient004_frame01_slice_6.h5 -trainrless2_slices/patient004_frame01_slice_7.h5 -trainrless2_slices/patient004_frame01_slice_8.h5 -trainrless2_slices/patient004_frame01_slice_9.h5 -trainrless2_slices/patient005_frame01_slice_0.h5 -trainrless2_slices/patient005_frame01_slice_1.h5 -trainrless2_slices/patient005_frame01_slice_2.h5 -trainrless2_slices/patient005_frame01_slice_3.h5 -trainrless2_slices/patient005_frame01_slice_4.h5 -trainrless2_slices/patient005_frame01_slice_5.h5 -trainrless2_slices/patient005_frame01_slice_6.h5 -trainrless2_slices/patient005_frame01_slice_7.h5 -trainrless2_slices/patient005_frame01_slice_8.h5 -trainrless2_slices/patient005_frame01_slice_9.h5 -trainrless2_slices/patient005_frame13_slice_0.h5 -trainrless2_slices/patient005_frame13_slice_1.h5 -trainrless2_slices/patient005_frame13_slice_2.h5 -trainrless2_slices/patient005_frame13_slice_3.h5 -trainrless2_slices/patient005_frame13_slice_4.h5 -trainrless2_slices/patient005_frame13_slice_5.h5 -trainrless2_slices/patient005_frame13_slice_6.h5 -trainrless2_slices/patient005_frame13_slice_7.h5 -trainrless2_slices/patient005_frame13_slice_8.h5 -trainrless2_slices/patient005_frame13_slice_9.h5 -trainrless2_slices/patient006_frame16_slice_0.h5 -trainrless2_slices/patient006_frame16_slice_1.h5 -trainrless2_slices/patient006_frame16_slice_10.h5 -trainrless2_slices/patient006_frame16_slice_2.h5 -trainrless2_slices/patient006_frame16_slice_3.h5 -trainrless2_slices/patient006_frame16_slice_4.h5 -trainrless2_slices/patient006_frame16_slice_5.h5 -trainrless2_slices/patient006_frame16_slice_6.h5 -trainrless2_slices/patient006_frame16_slice_7.h5 -trainrless2_slices/patient006_frame16_slice_8.h5 -trainrless2_slices/patient006_frame16_slice_9.h5 -trainrless2_slices/patient007_frame01_slice_0.h5 -trainrless2_slices/patient007_frame01_slice_1.h5 -trainrless2_slices/patient007_frame01_slice_2.h5 -trainrless2_slices/patient007_frame01_slice_3.h5 -trainrless2_slices/patient007_frame01_slice_4.h5 -trainrless2_slices/patient007_frame01_slice_5.h5 -trainrless2_slices/patient007_frame01_slice_6.h5 -trainrless2_slices/patient007_frame01_slice_7.h5 -trainrless2_slices/patient007_frame01_slice_8.h5 -trainrless2_slices/patient007_frame01_slice_9.h5 -trainrless2_slices/patient007_frame07_slice_0.h5 -trainrless2_slices/patient007_frame07_slice_1.h5 -trainrless2_slices/patient007_frame07_slice_2.h5 -trainrless2_slices/patient007_frame07_slice_3.h5 -trainrless2_slices/patient007_frame07_slice_4.h5 -trainrless2_slices/patient007_frame07_slice_5.h5 -trainrless2_slices/patient007_frame07_slice_6.h5 -trainrless2_slices/patient007_frame07_slice_7.h5 -trainrless2_slices/patient007_frame07_slice_8.h5 -trainrless2_slices/patient007_frame07_slice_9.h5 -trainrless2_slices/patient008_frame13_slice_0.h5 -trainrless2_slices/patient008_frame13_slice_1.h5 -trainrless2_slices/patient008_frame13_slice_2.h5 -trainrless2_slices/patient008_frame13_slice_3.h5 -trainrless2_slices/patient008_frame13_slice_4.h5 -trainrless2_slices/patient008_frame13_slice_5.h5 -trainrless2_slices/patient008_frame13_slice_6.h5 -trainrless2_slices/patient008_frame13_slice_7.h5 -trainrless2_slices/patient008_frame13_slice_8.h5 -trainrless2_slices/patient008_frame13_slice_9.h5 -trainrless2_slices/patient009_frame01_slice_0.h5 -trainrless2_slices/patient009_frame01_slice_1.h5 -trainrless2_slices/patient009_frame01_slice_2.h5 -trainrless2_slices/patient009_frame01_slice_3.h5 -trainrless2_slices/patient009_frame01_slice_4.h5 -trainrless2_slices/patient009_frame01_slice_5.h5 -trainrless2_slices/patient009_frame01_slice_6.h5 -trainrless2_slices/patient009_frame01_slice_7.h5 -trainrless2_slices/patient009_frame01_slice_8.h5 -trainrless2_slices/patient009_frame01_slice_9.h5 -trainrless2_slices/patient010_frame01_slice_0.h5 -trainrless2_slices/patient010_frame01_slice_1.h5 -trainrless2_slices/patient010_frame01_slice_2.h5 -trainrless2_slices/patient010_frame01_slice_3.h5 -trainrless2_slices/patient010_frame01_slice_4.h5 -trainrless2_slices/patient010_frame01_slice_5.h5 -trainrless2_slices/patient010_frame01_slice_6.h5 -trainrless2_slices/patient010_frame01_slice_7.h5 -trainrless2_slices/patient010_frame01_slice_8.h5 -trainrless2_slices/patient010_frame01_slice_9.h5 -trainrless2_slices/patient010_frame13_slice_0.h5 -trainrless2_slices/patient010_frame13_slice_1.h5 -trainrless2_slices/patient010_frame13_slice_2.h5 -trainrless2_slices/patient010_frame13_slice_3.h5 -trainrless2_slices/patient010_frame13_slice_4.h5 -trainrless2_slices/patient010_frame13_slice_5.h5 -trainrless2_slices/patient010_frame13_slice_6.h5 -trainrless2_slices/patient010_frame13_slice_7.h5 -trainrless2_slices/patient010_frame13_slice_8.h5 -trainrless2_slices/patient010_frame13_slice_9.h5 -trainrless2_slices/patient011_frame01_slice_0.h5 -trainrless2_slices/patient011_frame01_slice_1.h5 -trainrless2_slices/patient011_frame01_slice_2.h5 -trainrless2_slices/patient011_frame01_slice_3.h5 -trainrless2_slices/patient011_frame01_slice_4.h5 -trainrless2_slices/patient011_frame01_slice_5.h5 -trainrless2_slices/patient011_frame01_slice_6.h5 -trainrless2_slices/patient011_frame01_slice_7.h5 -trainrless2_slices/patient011_frame01_slice_8.h5 -trainrless2_slices/patient011_frame08_slice_0.h5 -trainrless2_slices/patient011_frame08_slice_1.h5 -trainrless2_slices/patient011_frame08_slice_2.h5 -trainrless2_slices/patient011_frame08_slice_3.h5 -trainrless2_slices/patient011_frame08_slice_4.h5 -trainrless2_slices/patient011_frame08_slice_5.h5 -trainrless2_slices/patient011_frame08_slice_6.h5 -trainrless2_slices/patient011_frame08_slice_7.h5 -trainrless2_slices/patient011_frame08_slice_8.h5 -trainrless2_slices/patient012_frame01_slice_0.h5 -trainrless2_slices/patient012_frame01_slice_1.h5 -trainrless2_slices/patient012_frame01_slice_2.h5 -trainrless2_slices/patient012_frame01_slice_3.h5 -trainrless2_slices/patient012_frame01_slice_4.h5 -trainrless2_slices/patient012_frame01_slice_5.h5 -trainrless2_slices/patient012_frame01_slice_6.h5 -trainrless2_slices/patient012_frame01_slice_7.h5 -trainrless2_slices/patient012_frame01_slice_8.h5 -trainrless2_slices/patient012_frame01_slice_9.h5 -trainrless2_slices/patient013_frame01_slice_0.h5 -trainrless2_slices/patient013_frame01_slice_1.h5 -trainrless2_slices/patient013_frame01_slice_2.h5 -trainrless2_slices/patient013_frame01_slice_3.h5 -trainrless2_slices/patient013_frame01_slice_4.h5 -trainrless2_slices/patient013_frame01_slice_5.h5 -trainrless2_slices/patient013_frame01_slice_6.h5 -trainrless2_slices/patient013_frame01_slice_7.h5 -trainrless2_slices/patient013_frame01_slice_8.h5 -trainrless2_slices/patient013_frame01_slice_9.h5 -trainrless2_slices/patient014_frame13_slice_0.h5 -trainrless2_slices/patient014_frame13_slice_1.h5 -trainrless2_slices/patient014_frame13_slice_2.h5 -trainrless2_slices/patient014_frame13_slice_3.h5 -trainrless2_slices/patient014_frame13_slice_4.h5 -trainrless2_slices/patient014_frame13_slice_5.h5 -trainrless2_slices/patient014_frame13_slice_6.h5 -trainrless2_slices/patient014_frame13_slice_7.h5 -trainrless2_slices/patient014_frame13_slice_8.h5 -trainrless2_slices/patient014_frame13_slice_9.h5 -trainrless2_slices/patient015_frame10_slice_0.h5 -trainrless2_slices/patient015_frame10_slice_1.h5 -trainrless2_slices/patient015_frame10_slice_2.h5 -trainrless2_slices/patient015_frame10_slice_3.h5 -trainrless2_slices/patient015_frame10_slice_4.h5 -trainrless2_slices/patient015_frame10_slice_5.h5 -trainrless2_slices/patient015_frame10_slice_6.h5 -trainrless2_slices/patient015_frame10_slice_7.h5 -trainrless2_slices/patient015_frame10_slice_8.h5 -trainrless2_slices/patient016_frame12_slice_0.h5 -trainrless2_slices/patient016_frame12_slice_1.h5 -trainrless2_slices/patient016_frame12_slice_2.h5 -trainrless2_slices/patient016_frame12_slice_3.h5 -trainrless2_slices/patient016_frame12_slice_4.h5 -trainrless2_slices/patient016_frame12_slice_5.h5 -trainrless2_slices/patient016_frame12_slice_6.h5 -trainrless2_slices/patient016_frame12_slice_7.h5 -trainrless2_slices/patient016_frame12_slice_8.h5 -trainrless2_slices/patient016_frame12_slice_9.h5 -trainrless2_slices/patient017_frame01_slice_0.h5 -trainrless2_slices/patient017_frame01_slice_1.h5 -trainrless2_slices/patient017_frame01_slice_2.h5 -trainrless2_slices/patient017_frame01_slice_3.h5 -trainrless2_slices/patient017_frame01_slice_4.h5 -trainrless2_slices/patient017_frame01_slice_5.h5 -trainrless2_slices/patient017_frame01_slice_6.h5 -trainrless2_slices/patient017_frame01_slice_7.h5 -trainrless2_slices/patient017_frame01_slice_8.h5 -trainrless2_slices/patient017_frame09_slice_0.h5 -trainrless2_slices/patient017_frame09_slice_1.h5 -trainrless2_slices/patient017_frame09_slice_2.h5 -trainrless2_slices/patient017_frame09_slice_3.h5 -trainrless2_slices/patient017_frame09_slice_4.h5 -trainrless2_slices/patient017_frame09_slice_5.h5 -trainrless2_slices/patient017_frame09_slice_6.h5 -trainrless2_slices/patient017_frame09_slice_7.h5 -trainrless2_slices/patient017_frame09_slice_8.h5 -trainrless2_slices/patient018_frame01_slice_0.h5 -trainrless2_slices/patient018_frame01_slice_1.h5 -trainrless2_slices/patient018_frame01_slice_2.h5 -trainrless2_slices/patient018_frame01_slice_3.h5 -trainrless2_slices/patient018_frame01_slice_4.h5 -trainrless2_slices/patient018_frame01_slice_5.h5 -trainrless2_slices/patient018_frame01_slice_6.h5 -trainrless2_slices/patient018_frame01_slice_7.h5 -trainrless2_slices/patient018_frame10_slice_0.h5 -trainrless2_slices/patient018_frame10_slice_1.h5 -trainrless2_slices/patient018_frame10_slice_2.h5 -trainrless2_slices/patient018_frame10_slice_3.h5 -trainrless2_slices/patient018_frame10_slice_4.h5 -trainrless2_slices/patient018_frame10_slice_5.h5 -trainrless2_slices/patient018_frame10_slice_6.h5 -trainrless2_slices/patient018_frame10_slice_7.h5 -trainrless2_slices/patient019_frame11_slice_0.h5 -trainrless2_slices/patient019_frame11_slice_1.h5 -trainrless2_slices/patient019_frame11_slice_10.h5 -trainrless2_slices/patient019_frame11_slice_2.h5 -trainrless2_slices/patient019_frame11_slice_3.h5 -trainrless2_slices/patient019_frame11_slice_4.h5 -trainrless2_slices/patient019_frame11_slice_5.h5 -trainrless2_slices/patient019_frame11_slice_6.h5 -trainrless2_slices/patient019_frame11_slice_7.h5 -trainrless2_slices/patient019_frame11_slice_8.h5 -trainrless2_slices/patient019_frame11_slice_9.h5 -trainrless2_slices/patient020_frame01_slice_0.h5 -trainrless2_slices/patient020_frame01_slice_1.h5 -trainrless2_slices/patient020_frame01_slice_2.h5 -trainrless2_slices/patient020_frame01_slice_3.h5 -trainrless2_slices/patient020_frame01_slice_4.h5 -trainrless2_slices/patient020_frame01_slice_5.h5 -trainrless2_slices/patient020_frame01_slice_6.h5 -trainrless2_slices/patient020_frame01_slice_7.h5 -trainrless2_slices/patient021_frame01_slice_0.h5 -trainrless2_slices/patient021_frame01_slice_1.h5 -trainrless2_slices/patient021_frame01_slice_2.h5 -trainrless2_slices/patient021_frame01_slice_3.h5 -trainrless2_slices/patient021_frame01_slice_4.h5 -trainrless2_slices/patient021_frame01_slice_5.h5 -trainrless2_slices/patient021_frame01_slice_6.h5 -trainrless2_slices/patient021_frame01_slice_7.h5 -trainrless2_slices/patient021_frame01_slice_8.h5 -trainrless2_slices/patient021_frame01_slice_9.h5 -trainrless2_slices/patient021_frame13_slice_0.h5 -trainrless2_slices/patient021_frame13_slice_1.h5 -trainrless2_slices/patient021_frame13_slice_2.h5 -trainrless2_slices/patient021_frame13_slice_3.h5 -trainrless2_slices/patient021_frame13_slice_4.h5 -trainrless2_slices/patient021_frame13_slice_5.h5 -trainrless2_slices/patient021_frame13_slice_6.h5 -trainrless2_slices/patient021_frame13_slice_7.h5 -trainrless2_slices/patient021_frame13_slice_8.h5 -trainrless2_slices/patient021_frame13_slice_9.h5 -trainrless2_slices/patient022_frame01_slice_0.h5 -trainrless2_slices/patient022_frame01_slice_1.h5 -trainrless2_slices/patient022_frame01_slice_2.h5 -trainrless2_slices/patient022_frame01_slice_3.h5 -trainrless2_slices/patient022_frame01_slice_4.h5 -trainrless2_slices/patient022_frame01_slice_5.h5 -trainrless2_slices/patient022_frame01_slice_6.h5 -trainrless2_slices/patient022_frame11_slice_0.h5 -trainrless2_slices/patient022_frame11_slice_1.h5 -trainrless2_slices/patient022_frame11_slice_2.h5 -trainrless2_slices/patient022_frame11_slice_3.h5 -trainrless2_slices/patient022_frame11_slice_4.h5 -trainrless2_slices/patient022_frame11_slice_5.h5 -trainrless2_slices/patient022_frame11_slice_6.h5 -trainrless2_slices/patient023_frame01_slice_0.h5 -trainrless2_slices/patient023_frame01_slice_1.h5 -trainrless2_slices/patient023_frame01_slice_2.h5 -trainrless2_slices/patient023_frame01_slice_3.h5 -trainrless2_slices/patient023_frame01_slice_4.h5 -trainrless2_slices/patient023_frame01_slice_5.h5 -trainrless2_slices/patient023_frame01_slice_6.h5 -trainrless2_slices/patient023_frame01_slice_7.h5 -trainrless2_slices/patient023_frame01_slice_8.h5 -trainrless2_slices/patient024_frame09_slice_0.h5 -trainrless2_slices/patient024_frame09_slice_1.h5 -trainrless2_slices/patient024_frame09_slice_2.h5 -trainrless2_slices/patient024_frame09_slice_3.h5 -trainrless2_slices/patient024_frame09_slice_4.h5 -trainrless2_slices/patient024_frame09_slice_5.h5 -trainrless2_slices/patient024_frame09_slice_6.h5 -trainrless2_slices/patient024_frame09_slice_7.h5 -trainrless2_slices/patient025_frame01_slice_0.h5 -trainrless2_slices/patient025_frame01_slice_1.h5 -trainrless2_slices/patient025_frame01_slice_2.h5 -trainrless2_slices/patient025_frame01_slice_3.h5 -trainrless2_slices/patient025_frame01_slice_4.h5 -trainrless2_slices/patient025_frame01_slice_5.h5 -trainrless2_slices/patient025_frame01_slice_6.h5 -trainrless2_slices/patient025_frame01_slice_7.h5 -trainrless2_slices/patient025_frame01_slice_8.h5 -trainrless2_slices/patient026_frame01_slice_0.h5 -trainrless2_slices/patient026_frame01_slice_1.h5 -trainrless2_slices/patient026_frame01_slice_2.h5 -trainrless2_slices/patient026_frame01_slice_3.h5 -trainrless2_slices/patient026_frame01_slice_4.h5 -trainrless2_slices/patient026_frame01_slice_5.h5 -trainrless2_slices/patient026_frame01_slice_6.h5 -trainrless2_slices/patient026_frame01_slice_7.h5 -trainrless2_slices/patient026_frame01_slice_8.h5 -trainrless2_slices/patient026_frame01_slice_9.h5 -trainrless2_slices/patient026_frame12_slice_0.h5 -trainrless2_slices/patient026_frame12_slice_1.h5 -trainrless2_slices/patient026_frame12_slice_2.h5 -trainrless2_slices/patient026_frame12_slice_3.h5 -trainrless2_slices/patient026_frame12_slice_4.h5 -trainrless2_slices/patient026_frame12_slice_5.h5 -trainrless2_slices/patient026_frame12_slice_6.h5 -trainrless2_slices/patient026_frame12_slice_7.h5 -trainrless2_slices/patient026_frame12_slice_8.h5 -trainrless2_slices/patient026_frame12_slice_9.h5 -trainrless2_slices/patient027_frame01_slice_0.h5 -trainrless2_slices/patient027_frame01_slice_1.h5 -trainrless2_slices/patient027_frame01_slice_2.h5 -trainrless2_slices/patient027_frame01_slice_3.h5 -trainrless2_slices/patient027_frame01_slice_4.h5 -trainrless2_slices/patient027_frame01_slice_5.h5 -trainrless2_slices/patient027_frame01_slice_6.h5 -trainrless2_slices/patient027_frame01_slice_7.h5 -trainrless2_slices/patient027_frame01_slice_8.h5 -trainrless2_slices/patient027_frame01_slice_9.h5 -trainrless2_slices/patient027_frame11_slice_0.h5 -trainrless2_slices/patient027_frame11_slice_1.h5 -trainrless2_slices/patient027_frame11_slice_2.h5 -trainrless2_slices/patient027_frame11_slice_3.h5 -trainrless2_slices/patient027_frame11_slice_4.h5 -trainrless2_slices/patient027_frame11_slice_5.h5 -trainrless2_slices/patient027_frame11_slice_6.h5 -trainrless2_slices/patient027_frame11_slice_7.h5 -trainrless2_slices/patient027_frame11_slice_8.h5 -trainrless2_slices/patient027_frame11_slice_9.h5 -trainrless2_slices/patient028_frame01_slice_0.h5 -trainrless2_slices/patient028_frame01_slice_1.h5 -trainrless2_slices/patient028_frame01_slice_2.h5 -trainrless2_slices/patient028_frame01_slice_3.h5 -trainrless2_slices/patient028_frame01_slice_4.h5 -trainrless2_slices/patient028_frame01_slice_5.h5 -trainrless2_slices/patient028_frame01_slice_6.h5 -trainrless2_slices/patient028_frame01_slice_7.h5 -trainrless2_slices/patient028_frame01_slice_8.h5 -trainrless2_slices/patient028_frame01_slice_9.h5 -trainrless2_slices/patient028_frame09_slice_0.h5 -trainrless2_slices/patient028_frame09_slice_1.h5 -trainrless2_slices/patient028_frame09_slice_2.h5 -trainrless2_slices/patient028_frame09_slice_3.h5 -trainrless2_slices/patient028_frame09_slice_4.h5 -trainrless2_slices/patient028_frame09_slice_5.h5 -trainrless2_slices/patient028_frame09_slice_6.h5 -trainrless2_slices/patient028_frame09_slice_7.h5 -trainrless2_slices/patient028_frame09_slice_8.h5 -trainrless2_slices/patient028_frame09_slice_9.h5 -trainrless2_slices/patient029_frame12_slice_0.h5 -trainrless2_slices/patient029_frame12_slice_1.h5 -trainrless2_slices/patient029_frame12_slice_10.h5 -trainrless2_slices/patient029_frame12_slice_2.h5 -trainrless2_slices/patient029_frame12_slice_3.h5 -trainrless2_slices/patient029_frame12_slice_4.h5 -trainrless2_slices/patient029_frame12_slice_5.h5 -trainrless2_slices/patient029_frame12_slice_6.h5 -trainrless2_slices/patient029_frame12_slice_7.h5 -trainrless2_slices/patient029_frame12_slice_8.h5 -trainrless2_slices/patient029_frame12_slice_9.h5 -trainrless2_slices/patient030_frame12_slice_0.h5 -trainrless2_slices/patient030_frame12_slice_1.h5 -trainrless2_slices/patient030_frame12_slice_2.h5 -trainrless2_slices/patient030_frame12_slice_3.h5 -trainrless2_slices/patient030_frame12_slice_4.h5 -trainrless2_slices/patient030_frame12_slice_5.h5 -trainrless2_slices/patient030_frame12_slice_6.h5 -trainrless2_slices/patient030_frame12_slice_7.h5 -trainrless2_slices/patient030_frame12_slice_8.h5 -trainrless2_slices/patient030_frame12_slice_9.h5 -trainrless2_slices/patient031_frame01_slice_0.h5 -trainrless2_slices/patient031_frame01_slice_1.h5 -trainrless2_slices/patient031_frame01_slice_2.h5 -trainrless2_slices/patient031_frame01_slice_3.h5 -trainrless2_slices/patient031_frame01_slice_4.h5 -trainrless2_slices/patient031_frame01_slice_5.h5 -trainrless2_slices/patient031_frame01_slice_6.h5 -trainrless2_slices/patient031_frame01_slice_7.h5 -trainrless2_slices/patient031_frame01_slice_8.h5 -trainrless2_slices/patient031_frame01_slice_9.h5 -trainrless2_slices/patient032_frame12_slice_0.h5 -trainrless2_slices/patient032_frame12_slice_1.h5 -trainrless2_slices/patient032_frame12_slice_2.h5 -trainrless2_slices/patient032_frame12_slice_3.h5 -trainrless2_slices/patient032_frame12_slice_4.h5 -trainrless2_slices/patient032_frame12_slice_5.h5 -trainrless2_slices/patient032_frame12_slice_6.h5 -trainrless2_slices/patient032_frame12_slice_7.h5 -trainrless2_slices/patient032_frame12_slice_8.h5 -trainrless2_slices/patient032_frame12_slice_9.h5 -trainrless2_slices/patient033_frame01_slice_0.h5 -trainrless2_slices/patient033_frame01_slice_1.h5 -trainrless2_slices/patient033_frame01_slice_2.h5 -trainrless2_slices/patient033_frame01_slice_3.h5 -trainrless2_slices/patient033_frame01_slice_4.h5 -trainrless2_slices/patient033_frame01_slice_5.h5 -trainrless2_slices/patient033_frame01_slice_6.h5 -trainrless2_slices/patient033_frame01_slice_7.h5 -trainrless2_slices/patient033_frame01_slice_8.h5 -trainrless2_slices/patient033_frame01_slice_9.h5 -trainrless2_slices/patient033_frame14_slice_0.h5 -trainrless2_slices/patient033_frame14_slice_1.h5 -trainrless2_slices/patient033_frame14_slice_2.h5 -trainrless2_slices/patient033_frame14_slice_3.h5 -trainrless2_slices/patient033_frame14_slice_4.h5 -trainrless2_slices/patient033_frame14_slice_5.h5 -trainrless2_slices/patient033_frame14_slice_6.h5 -trainrless2_slices/patient033_frame14_slice_7.h5 -trainrless2_slices/patient033_frame14_slice_8.h5 -trainrless2_slices/patient033_frame14_slice_9.h5 -trainrless2_slices/patient034_frame01_slice_0.h5 -trainrless2_slices/patient034_frame01_slice_1.h5 -trainrless2_slices/patient034_frame01_slice_2.h5 -trainrless2_slices/patient034_frame01_slice_3.h5 -trainrless2_slices/patient034_frame01_slice_4.h5 -trainrless2_slices/patient034_frame01_slice_5.h5 -trainrless2_slices/patient034_frame01_slice_6.h5 -trainrless2_slices/patient034_frame01_slice_7.h5 -trainrless2_slices/patient034_frame01_slice_8.h5 -trainrless2_slices/patient034_frame01_slice_9.h5 -trainrless2_slices/patient035_frame01_slice_0.h5 -trainrless2_slices/patient035_frame01_slice_1.h5 -trainrless2_slices/patient035_frame01_slice_10.h5 -trainrless2_slices/patient035_frame01_slice_11.h5 -trainrless2_slices/patient035_frame01_slice_12.h5 -trainrless2_slices/patient035_frame01_slice_2.h5 -trainrless2_slices/patient035_frame01_slice_3.h5 -trainrless2_slices/patient035_frame01_slice_4.h5 -trainrless2_slices/patient035_frame01_slice_5.h5 -trainrless2_slices/patient035_frame01_slice_6.h5 -trainrless2_slices/patient035_frame01_slice_7.h5 -trainrless2_slices/patient035_frame01_slice_8.h5 -trainrless2_slices/patient035_frame01_slice_9.h5 -trainrless2_slices/patient035_frame11_slice_0.h5 -trainrless2_slices/patient035_frame11_slice_1.h5 -trainrless2_slices/patient035_frame11_slice_10.h5 -trainrless2_slices/patient035_frame11_slice_11.h5 -trainrless2_slices/patient035_frame11_slice_12.h5 -trainrless2_slices/patient035_frame11_slice_2.h5 -trainrless2_slices/patient035_frame11_slice_3.h5 -trainrless2_slices/patient035_frame11_slice_4.h5 -trainrless2_slices/patient035_frame11_slice_5.h5 -trainrless2_slices/patient035_frame11_slice_6.h5 -trainrless2_slices/patient035_frame11_slice_7.h5 -trainrless2_slices/patient035_frame11_slice_8.h5 -trainrless2_slices/patient035_frame11_slice_9.h5 -trainrless2_slices/patient036_frame12_slice_0.h5 -trainrless2_slices/patient036_frame12_slice_1.h5 -trainrless2_slices/patient036_frame12_slice_2.h5 -trainrless2_slices/patient036_frame12_slice_3.h5 -trainrless2_slices/patient036_frame12_slice_4.h5 -trainrless2_slices/patient036_frame12_slice_5.h5 -trainrless2_slices/patient036_frame12_slice_6.h5 -trainrless2_slices/patient036_frame12_slice_7.h5 -trainrless2_slices/patient037_frame01_slice_0.h5 -trainrless2_slices/patient037_frame01_slice_1.h5 -trainrless2_slices/patient037_frame01_slice_2.h5 -trainrless2_slices/patient037_frame01_slice_3.h5 -trainrless2_slices/patient037_frame01_slice_4.h5 -trainrless2_slices/patient037_frame01_slice_5.h5 -trainrless2_slices/patient037_frame01_slice_6.h5 -trainrless2_slices/patient037_frame12_slice_0.h5 -trainrless2_slices/patient037_frame12_slice_1.h5 -trainrless2_slices/patient037_frame12_slice_2.h5 -trainrless2_slices/patient037_frame12_slice_3.h5 -trainrless2_slices/patient037_frame12_slice_4.h5 -trainrless2_slices/patient037_frame12_slice_5.h5 -trainrless2_slices/patient037_frame12_slice_6.h5 -trainrless2_slices/patient038_frame01_slice_0.h5 -trainrless2_slices/patient038_frame01_slice_1.h5 -trainrless2_slices/patient038_frame01_slice_2.h5 -trainrless2_slices/patient038_frame01_slice_3.h5 -trainrless2_slices/patient038_frame01_slice_4.h5 -trainrless2_slices/patient038_frame01_slice_5.h5 -trainrless2_slices/patient038_frame01_slice_6.h5 -trainrless2_slices/patient038_frame01_slice_7.h5 -trainrless2_slices/patient039_frame01_slice_0.h5 -trainrless2_slices/patient039_frame01_slice_1.h5 -trainrless2_slices/patient039_frame01_slice_2.h5 -trainrless2_slices/patient039_frame01_slice_3.h5 -trainrless2_slices/patient039_frame01_slice_4.h5 -trainrless2_slices/patient039_frame01_slice_5.h5 -trainrless2_slices/patient039_frame01_slice_6.h5 -trainrless2_slices/patient039_frame01_slice_7.h5 -trainrless2_slices/patient039_frame01_slice_8.h5 -trainrless2_slices/patient039_frame10_slice_0.h5 -trainrless2_slices/patient039_frame10_slice_1.h5 -trainrless2_slices/patient039_frame10_slice_2.h5 -trainrless2_slices/patient039_frame10_slice_3.h5 -trainrless2_slices/patient039_frame10_slice_4.h5 -trainrless2_slices/patient039_frame10_slice_5.h5 -trainrless2_slices/patient039_frame10_slice_6.h5 -trainrless2_slices/patient039_frame10_slice_7.h5 -trainrless2_slices/patient039_frame10_slice_8.h5 -trainrless2_slices/patient040_frame01_slice_0.h5 -trainrless2_slices/patient040_frame01_slice_1.h5 -trainrless2_slices/patient040_frame01_slice_2.h5 -trainrless2_slices/patient040_frame01_slice_3.h5 -trainrless2_slices/patient040_frame01_slice_4.h5 -trainrless2_slices/patient040_frame01_slice_5.h5 -trainrless2_slices/patient040_frame01_slice_6.h5 -trainrless2_slices/patient040_frame01_slice_7.h5 -trainrless2_slices/patient040_frame01_slice_8.h5 -trainrless2_slices/patient040_frame01_slice_9.h5 -trainrless2_slices/patient041_frame01_slice_0.h5 -trainrless2_slices/patient041_frame01_slice_1.h5 -trainrless2_slices/patient041_frame01_slice_2.h5 -trainrless2_slices/patient041_frame01_slice_3.h5 -trainrless2_slices/patient041_frame01_slice_4.h5 -trainrless2_slices/patient041_frame01_slice_5.h5 -trainrless2_slices/patient041_frame11_slice_0.h5 -trainrless2_slices/patient041_frame11_slice_1.h5 -trainrless2_slices/patient041_frame11_slice_2.h5 -trainrless2_slices/patient041_frame11_slice_3.h5 -trainrless2_slices/patient041_frame11_slice_4.h5 -trainrless2_slices/patient041_frame11_slice_5.h5 -trainrless2_slices/patient042_frame01_slice_0.h5 -trainrless2_slices/patient042_frame01_slice_1.h5 -trainrless2_slices/patient042_frame01_slice_2.h5 -trainrless2_slices/patient042_frame01_slice_3.h5 -trainrless2_slices/patient042_frame01_slice_4.h5 -trainrless2_slices/patient042_frame01_slice_5.h5 -trainrless2_slices/patient042_frame01_slice_6.h5 -trainrless2_slices/patient042_frame01_slice_7.h5 -trainrless2_slices/patient042_frame01_slice_8.h5 -trainrless2_slices/patient042_frame16_slice_0.h5 -trainrless2_slices/patient042_frame16_slice_1.h5 -trainrless2_slices/patient042_frame16_slice_2.h5 -trainrless2_slices/patient042_frame16_slice_3.h5 -trainrless2_slices/patient042_frame16_slice_4.h5 -trainrless2_slices/patient042_frame16_slice_5.h5 -trainrless2_slices/patient042_frame16_slice_6.h5 -trainrless2_slices/patient042_frame16_slice_7.h5 -trainrless2_slices/patient042_frame16_slice_8.h5 -trainrless2_slices/patient043_frame01_slice_0.h5 -trainrless2_slices/patient043_frame01_slice_1.h5 -trainrless2_slices/patient043_frame01_slice_10.h5 -trainrless2_slices/patient043_frame01_slice_11.h5 -trainrless2_slices/patient043_frame01_slice_2.h5 -trainrless2_slices/patient043_frame01_slice_3.h5 -trainrless2_slices/patient043_frame01_slice_4.h5 -trainrless2_slices/patient043_frame01_slice_5.h5 -trainrless2_slices/patient043_frame01_slice_6.h5 -trainrless2_slices/patient043_frame01_slice_7.h5 -trainrless2_slices/patient043_frame01_slice_8.h5 -trainrless2_slices/patient043_frame01_slice_9.h5 -trainrless2_slices/patient043_frame07_slice_0.h5 -trainrless2_slices/patient043_frame07_slice_1.h5 -trainrless2_slices/patient043_frame07_slice_10.h5 -trainrless2_slices/patient043_frame07_slice_11.h5 -trainrless2_slices/patient043_frame07_slice_2.h5 -trainrless2_slices/patient043_frame07_slice_3.h5 -trainrless2_slices/patient043_frame07_slice_4.h5 -trainrless2_slices/patient043_frame07_slice_5.h5 -trainrless2_slices/patient043_frame07_slice_6.h5 -trainrless2_slices/patient043_frame07_slice_7.h5 -trainrless2_slices/patient043_frame07_slice_8.h5 -trainrless2_slices/patient043_frame07_slice_9.h5 -trainrless2_slices/patient044_frame01_slice_0.h5 -trainrless2_slices/patient044_frame01_slice_1.h5 -trainrless2_slices/patient044_frame01_slice_2.h5 -trainrless2_slices/patient044_frame01_slice_3.h5 -trainrless2_slices/patient044_frame01_slice_4.h5 -trainrless2_slices/patient044_frame01_slice_5.h5 -trainrless2_slices/patient044_frame01_slice_6.h5 -trainrless2_slices/patient044_frame01_slice_7.h5 -trainrless2_slices/patient044_frame01_slice_8.h5 -trainrless2_slices/patient044_frame11_slice_0.h5 -trainrless2_slices/patient044_frame11_slice_1.h5 -trainrless2_slices/patient044_frame11_slice_2.h5 -trainrless2_slices/patient044_frame11_slice_3.h5 -trainrless2_slices/patient044_frame11_slice_4.h5 -trainrless2_slices/patient044_frame11_slice_5.h5 -trainrless2_slices/patient044_frame11_slice_6.h5 -trainrless2_slices/patient044_frame11_slice_7.h5 -trainrless2_slices/patient044_frame11_slice_8.h5 -trainrless2_slices/patient045_frame01_slice_0.h5 -trainrless2_slices/patient045_frame01_slice_1.h5 -trainrless2_slices/patient045_frame01_slice_2.h5 -trainrless2_slices/patient045_frame01_slice_3.h5 -trainrless2_slices/patient045_frame01_slice_4.h5 -trainrless2_slices/patient045_frame01_slice_5.h5 -trainrless2_slices/patient045_frame01_slice_6.h5 -trainrless2_slices/patient045_frame01_slice_7.h5 -trainrless2_slices/patient046_frame01_slice_0.h5 -trainrless2_slices/patient046_frame01_slice_1.h5 -trainrless2_slices/patient046_frame01_slice_2.h5 -trainrless2_slices/patient046_frame01_slice_3.h5 -trainrless2_slices/patient046_frame01_slice_4.h5 -trainrless2_slices/patient046_frame01_slice_5.h5 -trainrless2_slices/patient046_frame01_slice_6.h5 -trainrless2_slices/patient046_frame01_slice_7.h5 -trainrless2_slices/patient046_frame01_slice_8.h5 -trainrless2_slices/patient046_frame10_slice_0.h5 -trainrless2_slices/patient046_frame10_slice_1.h5 -trainrless2_slices/patient046_frame10_slice_2.h5 -trainrless2_slices/patient046_frame10_slice_3.h5 -trainrless2_slices/patient046_frame10_slice_4.h5 -trainrless2_slices/patient046_frame10_slice_5.h5 -trainrless2_slices/patient046_frame10_slice_6.h5 -trainrless2_slices/patient046_frame10_slice_7.h5 -trainrless2_slices/patient046_frame10_slice_8.h5 -trainrless2_slices/patient047_frame01_slice_0.h5 -trainrless2_slices/patient047_frame01_slice_1.h5 -trainrless2_slices/patient047_frame01_slice_2.h5 -trainrless2_slices/patient047_frame01_slice_3.h5 -trainrless2_slices/patient047_frame01_slice_4.h5 -trainrless2_slices/patient047_frame01_slice_5.h5 -trainrless2_slices/patient047_frame01_slice_6.h5 -trainrless2_slices/patient047_frame01_slice_7.h5 -trainrless2_slices/patient047_frame01_slice_8.h5 -trainrless2_slices/patient048_frame01_slice_0.h5 -trainrless2_slices/patient048_frame01_slice_1.h5 -trainrless2_slices/patient048_frame01_slice_2.h5 -trainrless2_slices/patient048_frame01_slice_3.h5 -trainrless2_slices/patient048_frame01_slice_4.h5 -trainrless2_slices/patient048_frame01_slice_5.h5 -trainrless2_slices/patient048_frame01_slice_6.h5 -trainrless2_slices/patient048_frame01_slice_7.h5 -trainrless2_slices/patient049_frame01_slice_0.h5 -trainrless2_slices/patient049_frame01_slice_1.h5 -trainrless2_slices/patient049_frame01_slice_2.h5 -trainrless2_slices/patient049_frame01_slice_3.h5 -trainrless2_slices/patient049_frame01_slice_4.h5 -trainrless2_slices/patient049_frame01_slice_5.h5 -trainrless2_slices/patient049_frame01_slice_6.h5 -trainrless2_slices/patient049_frame11_slice_0.h5 -trainrless2_slices/patient049_frame11_slice_1.h5 -trainrless2_slices/patient049_frame11_slice_2.h5 -trainrless2_slices/patient049_frame11_slice_3.h5 -trainrless2_slices/patient049_frame11_slice_4.h5 -trainrless2_slices/patient049_frame11_slice_5.h5 -trainrless2_slices/patient049_frame11_slice_6.h5 -trainrless2_slices/patient050_frame01_slice_0.h5 -trainrless2_slices/patient050_frame01_slice_1.h5 -trainrless2_slices/patient050_frame01_slice_2.h5 -trainrless2_slices/patient050_frame01_slice_3.h5 -trainrless2_slices/patient050_frame01_slice_4.h5 -trainrless2_slices/patient050_frame01_slice_5.h5 -trainrless2_slices/patient050_frame01_slice_6.h5 -trainrless2_slices/patient050_frame01_slice_7.h5 -trainrless2_slices/patient050_frame01_slice_8.h5 -trainrless2_slices/patient050_frame01_slice_9.h5 -trainrless2_slices/patient050_frame12_slice_0.h5 -trainrless2_slices/patient050_frame12_slice_1.h5 -trainrless2_slices/patient050_frame12_slice_2.h5 -trainrless2_slices/patient050_frame12_slice_3.h5 -trainrless2_slices/patient050_frame12_slice_4.h5 -trainrless2_slices/patient050_frame12_slice_5.h5 -trainrless2_slices/patient050_frame12_slice_6.h5 -trainrless2_slices/patient050_frame12_slice_7.h5 -trainrless2_slices/patient050_frame12_slice_8.h5 -trainrless2_slices/patient050_frame12_slice_9.h5 -trainrless2_slices/patient051_frame01_slice_0.h5 -trainrless2_slices/patient051_frame01_slice_1.h5 -trainrless2_slices/patient051_frame01_slice_2.h5 -trainrless2_slices/patient051_frame01_slice_3.h5 -trainrless2_slices/patient051_frame01_slice_4.h5 -trainrless2_slices/patient051_frame01_slice_5.h5 -trainrless2_slices/patient051_frame01_slice_6.h5 -trainrless2_slices/patient051_frame01_slice_7.h5 -trainrless2_slices/patient051_frame01_slice_8.h5 -trainrless2_slices/patient051_frame01_slice_9.h5 -trainrless2_slices/patient051_frame11_slice_0.h5 -trainrless2_slices/patient051_frame11_slice_1.h5 -trainrless2_slices/patient051_frame11_slice_2.h5 -trainrless2_slices/patient051_frame11_slice_3.h5 -trainrless2_slices/patient051_frame11_slice_4.h5 -trainrless2_slices/patient051_frame11_slice_5.h5 -trainrless2_slices/patient051_frame11_slice_6.h5 -trainrless2_slices/patient051_frame11_slice_7.h5 -trainrless2_slices/patient051_frame11_slice_8.h5 -trainrless2_slices/patient051_frame11_slice_9.h5 -trainrless2_slices/patient052_frame01_slice_0.h5 -trainrless2_slices/patient052_frame01_slice_1.h5 -trainrless2_slices/patient052_frame01_slice_2.h5 -trainrless2_slices/patient052_frame01_slice_3.h5 -trainrless2_slices/patient052_frame01_slice_4.h5 -trainrless2_slices/patient052_frame01_slice_5.h5 -trainrless2_slices/patient052_frame01_slice_6.h5 -trainrless2_slices/patient052_frame01_slice_7.h5 -trainrless2_slices/patient052_frame09_slice_0.h5 -trainrless2_slices/patient052_frame09_slice_1.h5 -trainrless2_slices/patient052_frame09_slice_2.h5 -trainrless2_slices/patient052_frame09_slice_3.h5 -trainrless2_slices/patient052_frame09_slice_4.h5 -trainrless2_slices/patient052_frame09_slice_5.h5 -trainrless2_slices/patient052_frame09_slice_6.h5 -trainrless2_slices/patient052_frame09_slice_7.h5 -trainrless2_slices/patient053_frame12_slice_0.h5 -trainrless2_slices/patient053_frame12_slice_1.h5 -trainrless2_slices/patient053_frame12_slice_2.h5 -trainrless2_slices/patient053_frame12_slice_3.h5 -trainrless2_slices/patient053_frame12_slice_4.h5 -trainrless2_slices/patient053_frame12_slice_5.h5 -trainrless2_slices/patient053_frame12_slice_6.h5 -trainrless2_slices/patient054_frame01_slice_0.h5 -trainrless2_slices/patient054_frame01_slice_1.h5 -trainrless2_slices/patient054_frame01_slice_2.h5 -trainrless2_slices/patient054_frame01_slice_3.h5 -trainrless2_slices/patient054_frame01_slice_4.h5 -trainrless2_slices/patient054_frame01_slice_5.h5 -trainrless2_slices/patient054_frame01_slice_6.h5 -trainrless2_slices/patient054_frame01_slice_7.h5 -trainrless2_slices/patient054_frame12_slice_0.h5 -trainrless2_slices/patient054_frame12_slice_1.h5 -trainrless2_slices/patient054_frame12_slice_2.h5 -trainrless2_slices/patient054_frame12_slice_3.h5 -trainrless2_slices/patient054_frame12_slice_4.h5 -trainrless2_slices/patient054_frame12_slice_5.h5 -trainrless2_slices/patient054_frame12_slice_6.h5 -trainrless2_slices/patient054_frame12_slice_7.h5 -trainrless2_slices/patient055_frame10_slice_0.h5 -trainrless2_slices/patient055_frame10_slice_1.h5 -trainrless2_slices/patient055_frame10_slice_2.h5 -trainrless2_slices/patient055_frame10_slice_3.h5 -trainrless2_slices/patient055_frame10_slice_4.h5 -trainrless2_slices/patient055_frame10_slice_5.h5 -trainrless2_slices/patient055_frame10_slice_6.h5 -trainrless2_slices/patient055_frame10_slice_7.h5 -trainrless2_slices/patient055_frame10_slice_8.h5 -trainrless2_slices/patient056_frame01_slice_0.h5 -trainrless2_slices/patient056_frame01_slice_1.h5 -trainrless2_slices/patient056_frame01_slice_2.h5 -trainrless2_slices/patient056_frame01_slice_3.h5 -trainrless2_slices/patient056_frame01_slice_4.h5 -trainrless2_slices/patient056_frame01_slice_5.h5 -trainrless2_slices/patient056_frame01_slice_6.h5 -trainrless2_slices/patient056_frame01_slice_7.h5 -trainrless2_slices/patient056_frame01_slice_8.h5 -trainrless2_slices/patient056_frame12_slice_0.h5 -trainrless2_slices/patient056_frame12_slice_1.h5 -trainrless2_slices/patient056_frame12_slice_2.h5 -trainrless2_slices/patient056_frame12_slice_3.h5 -trainrless2_slices/patient056_frame12_slice_4.h5 -trainrless2_slices/patient056_frame12_slice_5.h5 -trainrless2_slices/patient056_frame12_slice_6.h5 -trainrless2_slices/patient056_frame12_slice_7.h5 -trainrless2_slices/patient056_frame12_slice_8.h5 -trainrless2_slices/patient057_frame01_slice_0.h5 -trainrless2_slices/patient057_frame01_slice_1.h5 -trainrless2_slices/patient057_frame01_slice_2.h5 -trainrless2_slices/patient057_frame01_slice_3.h5 -trainrless2_slices/patient057_frame01_slice_4.h5 -trainrless2_slices/patient057_frame01_slice_5.h5 -trainrless2_slices/patient057_frame01_slice_6.h5 -trainrless2_slices/patient057_frame01_slice_7.h5 -trainrless2_slices/patient058_frame14_slice_0.h5 -trainrless2_slices/patient058_frame14_slice_1.h5 -trainrless2_slices/patient058_frame14_slice_2.h5 -trainrless2_slices/patient058_frame14_slice_3.h5 -trainrless2_slices/patient058_frame14_slice_4.h5 -trainrless2_slices/patient058_frame14_slice_5.h5 -trainrless2_slices/patient058_frame14_slice_6.h5 -trainrless2_slices/patient058_frame14_slice_7.h5 -trainrless2_slices/patient058_frame14_slice_8.h5 -trainrless2_slices/patient059_frame01_slice_0.h5 -trainrless2_slices/patient059_frame01_slice_1.h5 -trainrless2_slices/patient059_frame01_slice_2.h5 -trainrless2_slices/patient059_frame01_slice_3.h5 -trainrless2_slices/patient059_frame01_slice_4.h5 -trainrless2_slices/patient059_frame01_slice_5.h5 -trainrless2_slices/patient059_frame01_slice_6.h5 -trainrless2_slices/patient059_frame01_slice_7.h5 -trainrless2_slices/patient059_frame01_slice_8.h5 -trainrless2_slices/patient059_frame09_slice_0.h5 -trainrless2_slices/patient059_frame09_slice_1.h5 -trainrless2_slices/patient059_frame09_slice_2.h5 -trainrless2_slices/patient059_frame09_slice_3.h5 -trainrless2_slices/patient059_frame09_slice_4.h5 -trainrless2_slices/patient059_frame09_slice_5.h5 -trainrless2_slices/patient059_frame09_slice_6.h5 -trainrless2_slices/patient059_frame09_slice_7.h5 -trainrless2_slices/patient059_frame09_slice_8.h5 -trainrless2_slices/patient060_frame14_slice_0.h5 -trainrless2_slices/patient060_frame14_slice_1.h5 -trainrless2_slices/patient060_frame14_slice_2.h5 -trainrless2_slices/patient060_frame14_slice_3.h5 -trainrless2_slices/patient060_frame14_slice_4.h5 -trainrless2_slices/patient060_frame14_slice_5.h5 -trainrless2_slices/patient060_frame14_slice_6.h5 -trainrless2_slices/patient060_frame14_slice_7.h5 -trainrless2_slices/patient060_frame14_slice_8.h5 -trainrless2_slices/patient061_frame01_slice_0.h5 -trainrless2_slices/patient061_frame01_slice_1.h5 -trainrless2_slices/patient061_frame01_slice_2.h5 -trainrless2_slices/patient061_frame01_slice_3.h5 -trainrless2_slices/patient061_frame01_slice_4.h5 -trainrless2_slices/patient061_frame01_slice_5.h5 -trainrless2_slices/patient061_frame01_slice_6.h5 -trainrless2_slices/patient061_frame01_slice_7.h5 -trainrless2_slices/patient061_frame01_slice_8.h5 -trainrless2_slices/patient061_frame10_slice_0.h5 -trainrless2_slices/patient061_frame10_slice_1.h5 -trainrless2_slices/patient061_frame10_slice_2.h5 -trainrless2_slices/patient061_frame10_slice_3.h5 -trainrless2_slices/patient061_frame10_slice_4.h5 -trainrless2_slices/patient061_frame10_slice_5.h5 -trainrless2_slices/patient061_frame10_slice_6.h5 -trainrless2_slices/patient061_frame10_slice_7.h5 -trainrless2_slices/patient061_frame10_slice_8.h5 -trainrless2_slices/patient062_frame01_slice_0.h5 -trainrless2_slices/patient062_frame01_slice_1.h5 -trainrless2_slices/patient062_frame01_slice_2.h5 -trainrless2_slices/patient062_frame01_slice_3.h5 -trainrless2_slices/patient062_frame01_slice_4.h5 -trainrless2_slices/patient062_frame01_slice_5.h5 -trainrless2_slices/patient062_frame01_slice_6.h5 -trainrless2_slices/patient062_frame01_slice_7.h5 -trainrless2_slices/patient062_frame01_slice_8.h5 -trainrless2_slices/patient062_frame01_slice_9.h5 -trainrless2_slices/patient062_frame09_slice_0.h5 -trainrless2_slices/patient062_frame09_slice_1.h5 -trainrless2_slices/patient062_frame09_slice_2.h5 -trainrless2_slices/patient062_frame09_slice_3.h5 -trainrless2_slices/patient062_frame09_slice_4.h5 -trainrless2_slices/patient062_frame09_slice_5.h5 -trainrless2_slices/patient062_frame09_slice_6.h5 -trainrless2_slices/patient062_frame09_slice_7.h5 -trainrless2_slices/patient062_frame09_slice_8.h5 -trainrless2_slices/patient062_frame09_slice_9.h5 -trainrless2_slices/patient063_frame16_slice_0.h5 -trainrless2_slices/patient063_frame16_slice_1.h5 -trainrless2_slices/patient063_frame16_slice_2.h5 -trainrless2_slices/patient063_frame16_slice_3.h5 -trainrless2_slices/patient063_frame16_slice_4.h5 -trainrless2_slices/patient063_frame16_slice_5.h5 -trainrless2_slices/patient063_frame16_slice_6.h5 -trainrless2_slices/patient063_frame16_slice_7.h5 -trainrless2_slices/patient064_frame01_slice_0.h5 -trainrless2_slices/patient064_frame01_slice_1.h5 -trainrless2_slices/patient064_frame01_slice_2.h5 -trainrless2_slices/patient064_frame01_slice_3.h5 -trainrless2_slices/patient064_frame01_slice_4.h5 -trainrless2_slices/patient064_frame01_slice_5.h5 -trainrless2_slices/patient064_frame01_slice_6.h5 -trainrless2_slices/patient064_frame01_slice_7.h5 -trainrless2_slices/patient064_frame01_slice_8.h5 -trainrless2_slices/patient064_frame01_slice_9.h5 -trainrless2_slices/patient066_frame01_slice_0.h5 -trainrless2_slices/patient066_frame01_slice_1.h5 -trainrless2_slices/patient066_frame01_slice_2.h5 -trainrless2_slices/patient066_frame01_slice_3.h5 -trainrless2_slices/patient066_frame01_slice_4.h5 -trainrless2_slices/patient066_frame01_slice_5.h5 -trainrless2_slices/patient066_frame01_slice_6.h5 -trainrless2_slices/patient066_frame01_slice_7.h5 -trainrless2_slices/patient066_frame01_slice_8.h5 -trainrless2_slices/patient067_frame01_slice_0.h5 -trainrless2_slices/patient067_frame01_slice_1.h5 -trainrless2_slices/patient067_frame01_slice_2.h5 -trainrless2_slices/patient067_frame01_slice_3.h5 -trainrless2_slices/patient067_frame01_slice_4.h5 -trainrless2_slices/patient067_frame01_slice_5.h5 -trainrless2_slices/patient067_frame01_slice_6.h5 -trainrless2_slices/patient067_frame01_slice_7.h5 -trainrless2_slices/patient067_frame01_slice_8.h5 -trainrless2_slices/patient067_frame01_slice_9.h5 -trainrless2_slices/patient067_frame10_slice_0.h5 -trainrless2_slices/patient067_frame10_slice_1.h5 -trainrless2_slices/patient067_frame10_slice_2.h5 -trainrless2_slices/patient067_frame10_slice_3.h5 -trainrless2_slices/patient067_frame10_slice_4.h5 -trainrless2_slices/patient067_frame10_slice_5.h5 -trainrless2_slices/patient067_frame10_slice_6.h5 -trainrless2_slices/patient067_frame10_slice_7.h5 -trainrless2_slices/patient067_frame10_slice_8.h5 -trainrless2_slices/patient067_frame10_slice_9.h5 -trainrless2_slices/patient068_frame01_slice_0.h5 -trainrless2_slices/patient068_frame01_slice_1.h5 -trainrless2_slices/patient068_frame01_slice_2.h5 -trainrless2_slices/patient068_frame01_slice_3.h5 -trainrless2_slices/patient068_frame01_slice_4.h5 -trainrless2_slices/patient068_frame01_slice_5.h5 -trainrless2_slices/patient068_frame01_slice_6.h5 -trainrless2_slices/patient069_frame01_slice_0.h5 -trainrless2_slices/patient069_frame01_slice_1.h5 -trainrless2_slices/patient069_frame01_slice_2.h5 -trainrless2_slices/patient069_frame01_slice_3.h5 -trainrless2_slices/patient069_frame01_slice_4.h5 -trainrless2_slices/patient069_frame01_slice_5.h5 -trainrless2_slices/patient069_frame01_slice_6.h5 -trainrless2_slices/patient070_frame01_slice_0.h5 -trainrless2_slices/patient070_frame01_slice_1.h5 -trainrless2_slices/patient070_frame01_slice_2.h5 -trainrless2_slices/patient070_frame01_slice_3.h5 -trainrless2_slices/patient070_frame01_slice_4.h5 -trainrless2_slices/patient070_frame01_slice_5.h5 -trainrless2_slices/patient071_frame09_slice_0.h5 -trainrless2_slices/patient071_frame09_slice_1.h5 -trainrless2_slices/patient071_frame09_slice_2.h5 -trainrless2_slices/patient071_frame09_slice_3.h5 -trainrless2_slices/patient071_frame09_slice_4.h5 -trainrless2_slices/patient071_frame09_slice_5.h5 -trainrless2_slices/patient071_frame09_slice_6.h5 -trainrless2_slices/patient071_frame09_slice_7.h5 -trainrless2_slices/patient071_frame09_slice_8.h5 -trainrless2_slices/patient071_frame09_slice_9.h5 -trainrless2_slices/patient072_frame01_slice_0.h5 -trainrless2_slices/patient072_frame01_slice_1.h5 -trainrless2_slices/patient072_frame01_slice_2.h5 -trainrless2_slices/patient072_frame01_slice_3.h5 -trainrless2_slices/patient072_frame01_slice_4.h5 -trainrless2_slices/patient072_frame01_slice_5.h5 -trainrless2_slices/patient072_frame01_slice_6.h5 -trainrless2_slices/patient072_frame01_slice_7.h5 -trainrless2_slices/patient073_frame10_slice_0.h5 -trainrless2_slices/patient073_frame10_slice_1.h5 -trainrless2_slices/patient073_frame10_slice_2.h5 -trainrless2_slices/patient073_frame10_slice_3.h5 -trainrless2_slices/patient073_frame10_slice_4.h5 -trainrless2_slices/patient073_frame10_slice_5.h5 -trainrless2_slices/patient073_frame10_slice_6.h5 -trainrless2_slices/patient074_frame12_slice_0.h5 -trainrless2_slices/patient074_frame12_slice_1.h5 -trainrless2_slices/patient074_frame12_slice_2.h5 -trainrless2_slices/patient074_frame12_slice_3.h5 -trainrless2_slices/patient074_frame12_slice_4.h5 -trainrless2_slices/patient074_frame12_slice_5.h5 -trainrless2_slices/patient074_frame12_slice_6.h5 -trainrless2_slices/patient074_frame12_slice_7.h5 -trainrless2_slices/patient075_frame01_slice_0.h5 -trainrless2_slices/patient075_frame01_slice_1.h5 -trainrless2_slices/patient075_frame01_slice_10.h5 -trainrless2_slices/patient075_frame01_slice_11.h5 -trainrless2_slices/patient075_frame01_slice_12.h5 -trainrless2_slices/patient075_frame01_slice_13.h5 -trainrless2_slices/patient075_frame01_slice_2.h5 -trainrless2_slices/patient075_frame01_slice_3.h5 -trainrless2_slices/patient075_frame01_slice_4.h5 -trainrless2_slices/patient075_frame01_slice_5.h5 -trainrless2_slices/patient075_frame01_slice_6.h5 -trainrless2_slices/patient075_frame01_slice_7.h5 -trainrless2_slices/patient075_frame01_slice_8.h5 -trainrless2_slices/patient075_frame01_slice_9.h5 -trainrless2_slices/patient076_frame12_slice_0.h5 -trainrless2_slices/patient076_frame12_slice_1.h5 -trainrless2_slices/patient076_frame12_slice_2.h5 -trainrless2_slices/patient076_frame12_slice_3.h5 -trainrless2_slices/patient076_frame12_slice_4.h5 -trainrless2_slices/patient076_frame12_slice_5.h5 -trainrless2_slices/patient076_frame12_slice_6.h5 -trainrless2_slices/patient076_frame12_slice_7.h5 -trainrless2_slices/patient077_frame09_slice_0.h5 -trainrless2_slices/patient077_frame09_slice_1.h5 -trainrless2_slices/patient077_frame09_slice_2.h5 -trainrless2_slices/patient077_frame09_slice_3.h5 -trainrless2_slices/patient077_frame09_slice_4.h5 -trainrless2_slices/patient077_frame09_slice_5.h5 -trainrless2_slices/patient077_frame09_slice_6.h5 -trainrless2_slices/patient077_frame09_slice_7.h5 -trainrless2_slices/patient078_frame01_slice_0.h5 -trainrless2_slices/patient078_frame01_slice_1.h5 -trainrless2_slices/patient078_frame01_slice_2.h5 -trainrless2_slices/patient078_frame01_slice_3.h5 -trainrless2_slices/patient078_frame01_slice_4.h5 -trainrless2_slices/patient078_frame01_slice_5.h5 -trainrless2_slices/patient078_frame01_slice_6.h5 -trainrless2_slices/patient078_frame01_slice_7.h5 -trainrless2_slices/patient078_frame09_slice_0.h5 -trainrless2_slices/patient078_frame09_slice_1.h5 -trainrless2_slices/patient078_frame09_slice_2.h5 -trainrless2_slices/patient078_frame09_slice_3.h5 -trainrless2_slices/patient078_frame09_slice_4.h5 -trainrless2_slices/patient078_frame09_slice_5.h5 -trainrless2_slices/patient078_frame09_slice_6.h5 -trainrless2_slices/patient078_frame09_slice_7.h5 -trainrless2_slices/patient079_frame01_slice_0.h5 -trainrless2_slices/patient079_frame01_slice_1.h5 -trainrless2_slices/patient079_frame01_slice_2.h5 -trainrless2_slices/patient079_frame01_slice_3.h5 -trainrless2_slices/patient079_frame01_slice_4.h5 -trainrless2_slices/patient079_frame01_slice_5.h5 -trainrless2_slices/patient079_frame01_slice_6.h5 -trainrless2_slices/patient079_frame01_slice_7.h5 -trainrless2_slices/patient079_frame01_slice_8.h5 -trainrless2_slices/patient079_frame11_slice_0.h5 -trainrless2_slices/patient079_frame11_slice_1.h5 -trainrless2_slices/patient079_frame11_slice_2.h5 -trainrless2_slices/patient079_frame11_slice_3.h5 -trainrless2_slices/patient079_frame11_slice_4.h5 -trainrless2_slices/patient079_frame11_slice_5.h5 -trainrless2_slices/patient079_frame11_slice_6.h5 -trainrless2_slices/patient079_frame11_slice_7.h5 -trainrless2_slices/patient079_frame11_slice_8.h5 -trainrless2_slices/patient080_frame01_slice_0.h5 -trainrless2_slices/patient080_frame01_slice_1.h5 -trainrless2_slices/patient080_frame01_slice_2.h5 -trainrless2_slices/patient080_frame01_slice_3.h5 -trainrless2_slices/patient080_frame01_slice_4.h5 -trainrless2_slices/patient080_frame01_slice_5.h5 -trainrless2_slices/patient080_frame10_slice_0.h5 -trainrless2_slices/patient080_frame10_slice_1.h5 -trainrless2_slices/patient080_frame10_slice_2.h5 -trainrless2_slices/patient080_frame10_slice_3.h5 -trainrless2_slices/patient080_frame10_slice_4.h5 -trainrless2_slices/patient080_frame10_slice_5.h5 -trainrless2_slices/patient081_frame07_slice_0.h5 -trainrless2_slices/patient081_frame07_slice_1.h5 -trainrless2_slices/patient081_frame07_slice_10.h5 -trainrless2_slices/patient081_frame07_slice_11.h5 -trainrless2_slices/patient081_frame07_slice_12.h5 -trainrless2_slices/patient081_frame07_slice_13.h5 -trainrless2_slices/patient081_frame07_slice_14.h5 -trainrless2_slices/patient081_frame07_slice_15.h5 -trainrless2_slices/patient081_frame07_slice_16.h5 -trainrless2_slices/patient081_frame07_slice_2.h5 -trainrless2_slices/patient081_frame07_slice_3.h5 -trainrless2_slices/patient081_frame07_slice_4.h5 -trainrless2_slices/patient081_frame07_slice_5.h5 -trainrless2_slices/patient081_frame07_slice_6.h5 -trainrless2_slices/patient081_frame07_slice_7.h5 -trainrless2_slices/patient081_frame07_slice_8.h5 -trainrless2_slices/patient081_frame07_slice_9.h5 -trainrless2_slices/patient082_frame01_slice_0.h5 -trainrless2_slices/patient082_frame01_slice_1.h5 -trainrless2_slices/patient082_frame01_slice_10.h5 -trainrless2_slices/patient082_frame01_slice_11.h5 -trainrless2_slices/patient082_frame01_slice_12.h5 -trainrless2_slices/patient082_frame01_slice_13.h5 -trainrless2_slices/patient082_frame01_slice_14.h5 -trainrless2_slices/patient082_frame01_slice_15.h5 -trainrless2_slices/patient082_frame01_slice_2.h5 -trainrless2_slices/patient082_frame01_slice_3.h5 -trainrless2_slices/patient082_frame01_slice_4.h5 -trainrless2_slices/patient082_frame01_slice_5.h5 -trainrless2_slices/patient082_frame01_slice_6.h5 -trainrless2_slices/patient082_frame01_slice_7.h5 -trainrless2_slices/patient082_frame01_slice_8.h5 -trainrless2_slices/patient082_frame01_slice_9.h5 -trainrless2_slices/patient082_frame07_slice_0.h5 -trainrless2_slices/patient082_frame07_slice_1.h5 -trainrless2_slices/patient082_frame07_slice_10.h5 -trainrless2_slices/patient082_frame07_slice_11.h5 -trainrless2_slices/patient082_frame07_slice_12.h5 -trainrless2_slices/patient082_frame07_slice_13.h5 -trainrless2_slices/patient082_frame07_slice_14.h5 -trainrless2_slices/patient082_frame07_slice_15.h5 -trainrless2_slices/patient082_frame07_slice_2.h5 -trainrless2_slices/patient082_frame07_slice_3.h5 -trainrless2_slices/patient082_frame07_slice_4.h5 -trainrless2_slices/patient082_frame07_slice_5.h5 -trainrless2_slices/patient082_frame07_slice_6.h5 -trainrless2_slices/patient082_frame07_slice_7.h5 -trainrless2_slices/patient082_frame07_slice_8.h5 -trainrless2_slices/patient082_frame07_slice_9.h5 -trainrless2_slices/patient083_frame01_slice_0.h5 -trainrless2_slices/patient083_frame01_slice_1.h5 -trainrless2_slices/patient083_frame01_slice_2.h5 -trainrless2_slices/patient083_frame01_slice_3.h5 -trainrless2_slices/patient083_frame01_slice_4.h5 -trainrless2_slices/patient083_frame01_slice_5.h5 -trainrless2_slices/patient084_frame01_slice_0.h5 -trainrless2_slices/patient084_frame01_slice_1.h5 -trainrless2_slices/patient084_frame01_slice_10.h5 -trainrless2_slices/patient084_frame01_slice_11.h5 -trainrless2_slices/patient084_frame01_slice_2.h5 -trainrless2_slices/patient084_frame01_slice_3.h5 -trainrless2_slices/patient084_frame01_slice_4.h5 -trainrless2_slices/patient084_frame01_slice_5.h5 -trainrless2_slices/patient084_frame01_slice_6.h5 -trainrless2_slices/patient084_frame01_slice_7.h5 -trainrless2_slices/patient084_frame01_slice_8.h5 -trainrless2_slices/patient084_frame01_slice_9.h5 -trainrless2_slices/patient084_frame10_slice_0.h5 -trainrless2_slices/patient084_frame10_slice_1.h5 -trainrless2_slices/patient084_frame10_slice_10.h5 -trainrless2_slices/patient084_frame10_slice_11.h5 -trainrless2_slices/patient084_frame10_slice_2.h5 -trainrless2_slices/patient084_frame10_slice_3.h5 -trainrless2_slices/patient084_frame10_slice_4.h5 -trainrless2_slices/patient084_frame10_slice_5.h5 -trainrless2_slices/patient084_frame10_slice_6.h5 -trainrless2_slices/patient084_frame10_slice_7.h5 -trainrless2_slices/patient084_frame10_slice_8.h5 -trainrless2_slices/patient084_frame10_slice_9.h5 -trainrless2_slices/patient085_frame01_slice_0.h5 -trainrless2_slices/patient085_frame01_slice_1.h5 -trainrless2_slices/patient085_frame01_slice_10.h5 -trainrless2_slices/patient085_frame01_slice_11.h5 -trainrless2_slices/patient085_frame01_slice_12.h5 -trainrless2_slices/patient085_frame01_slice_13.h5 -trainrless2_slices/patient085_frame01_slice_14.h5 -trainrless2_slices/patient085_frame01_slice_2.h5 -trainrless2_slices/patient085_frame01_slice_3.h5 -trainrless2_slices/patient085_frame01_slice_4.h5 -trainrless2_slices/patient085_frame01_slice_5.h5 -trainrless2_slices/patient085_frame01_slice_6.h5 -trainrless2_slices/patient085_frame01_slice_7.h5 -trainrless2_slices/patient085_frame01_slice_8.h5 -trainrless2_slices/patient085_frame01_slice_9.h5 -trainrless2_slices/patient087_frame01_slice_0.h5 -trainrless2_slices/patient087_frame01_slice_1.h5 -trainrless2_slices/patient087_frame01_slice_2.h5 -trainrless2_slices/patient087_frame01_slice_3.h5 -trainrless2_slices/patient087_frame01_slice_4.h5 -trainrless2_slices/patient087_frame01_slice_5.h5 -trainrless2_slices/patient087_frame01_slice_6.h5 -trainrless2_slices/patient087_frame01_slice_7.h5 -trainrless2_slices/patient088_frame01_slice_0.h5 -trainrless2_slices/patient088_frame01_slice_1.h5 -trainrless2_slices/patient088_frame01_slice_10.h5 -trainrless2_slices/patient088_frame01_slice_11.h5 -trainrless2_slices/patient088_frame01_slice_12.h5 -trainrless2_slices/patient088_frame01_slice_13.h5 -trainrless2_slices/patient088_frame01_slice_14.h5 -trainrless2_slices/patient088_frame01_slice_15.h5 -trainrless2_slices/patient088_frame01_slice_2.h5 -trainrless2_slices/patient088_frame01_slice_3.h5 -trainrless2_slices/patient088_frame01_slice_4.h5 -trainrless2_slices/patient088_frame01_slice_5.h5 -trainrless2_slices/patient088_frame01_slice_6.h5 -trainrless2_slices/patient088_frame01_slice_7.h5 -trainrless2_slices/patient088_frame01_slice_8.h5 -trainrless2_slices/patient088_frame01_slice_9.h5 -trainrless2_slices/patient088_frame12_slice_0.h5 -trainrless2_slices/patient088_frame12_slice_1.h5 -trainrless2_slices/patient088_frame12_slice_10.h5 -trainrless2_slices/patient088_frame12_slice_11.h5 -trainrless2_slices/patient088_frame12_slice_12.h5 -trainrless2_slices/patient088_frame12_slice_13.h5 -trainrless2_slices/patient088_frame12_slice_14.h5 -trainrless2_slices/patient088_frame12_slice_15.h5 -trainrless2_slices/patient088_frame12_slice_2.h5 -trainrless2_slices/patient088_frame12_slice_3.h5 -trainrless2_slices/patient088_frame12_slice_4.h5 -trainrless2_slices/patient088_frame12_slice_5.h5 -trainrless2_slices/patient088_frame12_slice_6.h5 -trainrless2_slices/patient088_frame12_slice_7.h5 -trainrless2_slices/patient088_frame12_slice_8.h5 -trainrless2_slices/patient088_frame12_slice_9.h5 -trainrless2_slices/patient090_frame11_slice_0.h5 -trainrless2_slices/patient090_frame11_slice_1.h5 -trainrless2_slices/patient090_frame11_slice_2.h5 -trainrless2_slices/patient090_frame11_slice_3.h5 -trainrless2_slices/patient090_frame11_slice_4.h5 -trainrless2_slices/patient090_frame11_slice_5.h5 -trainrless2_slices/patient090_frame11_slice_6.h5 -trainrless2_slices/patient091_frame01_slice_0.h5 -trainrless2_slices/patient091_frame01_slice_1.h5 -trainrless2_slices/patient091_frame01_slice_2.h5 -trainrless2_slices/patient091_frame01_slice_3.h5 -trainrless2_slices/patient091_frame01_slice_4.h5 -trainrless2_slices/patient091_frame01_slice_5.h5 -trainrless2_slices/patient091_frame01_slice_6.h5 -trainrless2_slices/patient091_frame01_slice_7.h5 -trainrless2_slices/patient091_frame09_slice_0.h5 -trainrless2_slices/patient091_frame09_slice_1.h5 -trainrless2_slices/patient091_frame09_slice_2.h5 -trainrless2_slices/patient091_frame09_slice_3.h5 -trainrless2_slices/patient091_frame09_slice_4.h5 -trainrless2_slices/patient091_frame09_slice_5.h5 -trainrless2_slices/patient091_frame09_slice_6.h5 -trainrless2_slices/patient091_frame09_slice_7.h5 -trainrless2_slices/patient092_frame01_slice_0.h5 -trainrless2_slices/patient092_frame01_slice_1.h5 -trainrless2_slices/patient092_frame01_slice_10.h5 -trainrless2_slices/patient092_frame01_slice_11.h5 -trainrless2_slices/patient092_frame01_slice_12.h5 -trainrless2_slices/patient092_frame01_slice_13.h5 -trainrless2_slices/patient092_frame01_slice_14.h5 -trainrless2_slices/patient092_frame01_slice_2.h5 -trainrless2_slices/patient092_frame01_slice_3.h5 -trainrless2_slices/patient092_frame01_slice_4.h5 -trainrless2_slices/patient092_frame01_slice_5.h5 -trainrless2_slices/patient092_frame01_slice_6.h5 -trainrless2_slices/patient092_frame01_slice_7.h5 -trainrless2_slices/patient092_frame01_slice_8.h5 -trainrless2_slices/patient092_frame01_slice_9.h5 -trainrless2_slices/patient092_frame06_slice_0.h5 -trainrless2_slices/patient092_frame06_slice_1.h5 -trainrless2_slices/patient092_frame06_slice_10.h5 -trainrless2_slices/patient092_frame06_slice_11.h5 -trainrless2_slices/patient092_frame06_slice_12.h5 -trainrless2_slices/patient092_frame06_slice_13.h5 -trainrless2_slices/patient092_frame06_slice_14.h5 -trainrless2_slices/patient092_frame06_slice_2.h5 -trainrless2_slices/patient092_frame06_slice_3.h5 -trainrless2_slices/patient092_frame06_slice_4.h5 -trainrless2_slices/patient092_frame06_slice_5.h5 -trainrless2_slices/patient092_frame06_slice_6.h5 -trainrless2_slices/patient092_frame06_slice_7.h5 -trainrless2_slices/patient092_frame06_slice_8.h5 -trainrless2_slices/patient092_frame06_slice_9.h5 -trainrless2_slices/patient093_frame14_slice_0.h5 -trainrless2_slices/patient093_frame14_slice_1.h5 -trainrless2_slices/patient093_frame14_slice_2.h5 -trainrless2_slices/patient093_frame14_slice_3.h5 -trainrless2_slices/patient093_frame14_slice_4.h5 -trainrless2_slices/patient093_frame14_slice_5.h5 -trainrless2_slices/patient093_frame14_slice_6.h5 -trainrless2_slices/patient093_frame14_slice_7.h5 -trainrless2_slices/patient093_frame14_slice_8.h5 -trainrless2_slices/patient093_frame14_slice_9.h5 -trainrless2_slices/patient095_frame01_slice_0.h5 -trainrless2_slices/patient095_frame01_slice_1.h5 -trainrless2_slices/patient095_frame01_slice_10.h5 -trainrless2_slices/patient095_frame01_slice_11.h5 -trainrless2_slices/patient095_frame01_slice_12.h5 -trainrless2_slices/patient095_frame01_slice_13.h5 -trainrless2_slices/patient095_frame01_slice_2.h5 -trainrless2_slices/patient095_frame01_slice_3.h5 -trainrless2_slices/patient095_frame01_slice_4.h5 -trainrless2_slices/patient095_frame01_slice_5.h5 -trainrless2_slices/patient095_frame01_slice_6.h5 -trainrless2_slices/patient095_frame01_slice_7.h5 -trainrless2_slices/patient095_frame01_slice_8.h5 -trainrless2_slices/patient095_frame01_slice_9.h5 -trainrless2_slices/patient095_frame12_slice_0.h5 -trainrless2_slices/patient095_frame12_slice_1.h5 -trainrless2_slices/patient095_frame12_slice_10.h5 -trainrless2_slices/patient095_frame12_slice_11.h5 -trainrless2_slices/patient095_frame12_slice_12.h5 -trainrless2_slices/patient095_frame12_slice_13.h5 -trainrless2_slices/patient095_frame12_slice_2.h5 -trainrless2_slices/patient095_frame12_slice_3.h5 -trainrless2_slices/patient095_frame12_slice_4.h5 -trainrless2_slices/patient095_frame12_slice_5.h5 -trainrless2_slices/patient095_frame12_slice_6.h5 -trainrless2_slices/patient095_frame12_slice_7.h5 -trainrless2_slices/patient095_frame12_slice_8.h5 -trainrless2_slices/patient095_frame12_slice_9.h5 -trainrless2_slices/patient096_frame08_slice_0.h5 -trainrless2_slices/patient096_frame08_slice_1.h5 -trainrless2_slices/patient096_frame08_slice_10.h5 -trainrless2_slices/patient096_frame08_slice_11.h5 -trainrless2_slices/patient096_frame08_slice_12.h5 -trainrless2_slices/patient096_frame08_slice_13.h5 -trainrless2_slices/patient096_frame08_slice_14.h5 -trainrless2_slices/patient096_frame08_slice_15.h5 -trainrless2_slices/patient096_frame08_slice_16.h5 -trainrless2_slices/patient096_frame08_slice_17.h5 -trainrless2_slices/patient096_frame08_slice_2.h5 -trainrless2_slices/patient096_frame08_slice_3.h5 -trainrless2_slices/patient096_frame08_slice_4.h5 -trainrless2_slices/patient096_frame08_slice_5.h5 -trainrless2_slices/patient096_frame08_slice_6.h5 -trainrless2_slices/patient096_frame08_slice_7.h5 -trainrless2_slices/patient096_frame08_slice_8.h5 -trainrless2_slices/patient096_frame08_slice_9.h5 -trainrless2_slices/patient097_frame01_slice_0.h5 -trainrless2_slices/patient097_frame01_slice_1.h5 -trainrless2_slices/patient097_frame01_slice_2.h5 -trainrless2_slices/patient097_frame01_slice_3.h5 -trainrless2_slices/patient097_frame01_slice_4.h5 -trainrless2_slices/patient097_frame01_slice_5.h5 -trainrless2_slices/patient097_frame01_slice_6.h5 -trainrless2_slices/patient097_frame01_slice_7.h5 -trainrless2_slices/patient097_frame11_slice_0.h5 -trainrless2_slices/patient097_frame11_slice_1.h5 -trainrless2_slices/patient097_frame11_slice_2.h5 -trainrless2_slices/patient097_frame11_slice_3.h5 -trainrless2_slices/patient097_frame11_slice_4.h5 -trainrless2_slices/patient097_frame11_slice_5.h5 -trainrless2_slices/patient097_frame11_slice_6.h5 -trainrless2_slices/patient097_frame11_slice_7.h5 -trainrless2_slices/patient099_frame01_slice_0.h5 -trainrless2_slices/patient099_frame01_slice_1.h5 -trainrless2_slices/patient099_frame01_slice_10.h5 -trainrless2_slices/patient099_frame01_slice_11.h5 -trainrless2_slices/patient099_frame01_slice_12.h5 -trainrless2_slices/patient099_frame01_slice_13.h5 -trainrless2_slices/patient099_frame01_slice_14.h5 -trainrless2_slices/patient099_frame01_slice_15.h5 -trainrless2_slices/patient099_frame01_slice_2.h5 -trainrless2_slices/patient099_frame01_slice_3.h5 -trainrless2_slices/patient099_frame01_slice_4.h5 -trainrless2_slices/patient099_frame01_slice_5.h5 -trainrless2_slices/patient099_frame01_slice_6.h5 -trainrless2_slices/patient099_frame01_slice_7.h5 -trainrless2_slices/patient099_frame01_slice_8.h5 -trainrless2_slices/patient099_frame01_slice_9.h5 -trainrless2_slices/patient099_frame09_slice_0.h5 -trainrless2_slices/patient099_frame09_slice_1.h5 -trainrless2_slices/patient099_frame09_slice_10.h5 -trainrless2_slices/patient099_frame09_slice_11.h5 -trainrless2_slices/patient099_frame09_slice_12.h5 -trainrless2_slices/patient099_frame09_slice_13.h5 -trainrless2_slices/patient099_frame09_slice_14.h5 -trainrless2_slices/patient099_frame09_slice_15.h5 -trainrless2_slices/patient099_frame09_slice_2.h5 -trainrless2_slices/patient099_frame09_slice_3.h5 -trainrless2_slices/patient099_frame09_slice_4.h5 -trainrless2_slices/patient099_frame09_slice_5.h5 -trainrless2_slices/patient099_frame09_slice_6.h5 -trainrless2_slices/patient099_frame09_slice_7.h5 -trainrless2_slices/patient099_frame09_slice_8.h5 -trainrless2_slices/patient099_frame09_slice_9.h5 -trainrless2_slices/patient100_frame01_slice_0.h5 -trainrless2_slices/patient100_frame01_slice_1.h5 -trainrless2_slices/patient100_frame01_slice_2.h5 -trainrless2_slices/patient100_frame01_slice_3.h5 -trainrless2_slices/patient100_frame01_slice_4.h5 -trainrless2_slices/patient100_frame01_slice_5.h5 -trainrless2_slices/patient100_frame01_slice_6.h5 -trainrless2_slices/patient100_frame01_slice_7.h5 -trainrless2_slices/patient100_frame13_slice_0.h5 -trainrless2_slices/patient100_frame13_slice_1.h5 -trainrless2_slices/patient100_frame13_slice_2.h5 -trainrless2_slices/patient100_frame13_slice_3.h5 -trainrless2_slices/patient100_frame13_slice_4.h5 -trainrless2_slices/patient100_frame13_slice_5.h5 -trainrless2_slices/patient100_frame13_slice_6.h5 -trainrless2_slices/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/trainrlessd16.txt b/data/ACDC2017/ACDC_for2D/trainrlessd16.txt deleted file mode 100644 index b862b5e..0000000 --- a/data/ACDC2017/ACDC_for2D/trainrlessd16.txt +++ /dev/null @@ -1,1356 +0,0 @@ -trainrlessd16_slices/patient001_frame01_slice_0.h5 -trainrlessd16_slices/patient001_frame01_slice_1.h5 -trainrlessd16_slices/patient001_frame01_slice_2.h5 -trainrlessd16_slices/patient001_frame01_slice_3.h5 -trainrlessd16_slices/patient001_frame01_slice_4.h5 -trainrlessd16_slices/patient001_frame01_slice_5.h5 -trainrlessd16_slices/patient001_frame01_slice_6.h5 -trainrlessd16_slices/patient001_frame01_slice_7.h5 -trainrlessd16_slices/patient001_frame01_slice_8.h5 -trainrlessd16_slices/patient001_frame01_slice_9.h5 -trainrlessd16_slices/patient001_frame12_slice_0.h5 -trainrlessd16_slices/patient001_frame12_slice_1.h5 -trainrlessd16_slices/patient001_frame12_slice_2.h5 -trainrlessd16_slices/patient001_frame12_slice_3.h5 -trainrlessd16_slices/patient001_frame12_slice_4.h5 -trainrlessd16_slices/patient001_frame12_slice_5.h5 -trainrlessd16_slices/patient001_frame12_slice_6.h5 -trainrlessd16_slices/patient001_frame12_slice_7.h5 -trainrlessd16_slices/patient001_frame12_slice_8.h5 -trainrlessd16_slices/patient001_frame12_slice_9.h5 -trainrlessd16_slices/patient002_frame01_slice_0.h5 -trainrlessd16_slices/patient002_frame01_slice_1.h5 -trainrlessd16_slices/patient002_frame01_slice_2.h5 -trainrlessd16_slices/patient002_frame01_slice_3.h5 -trainrlessd16_slices/patient002_frame01_slice_4.h5 -trainrlessd16_slices/patient002_frame01_slice_5.h5 -trainrlessd16_slices/patient002_frame01_slice_6.h5 -trainrlessd16_slices/patient002_frame01_slice_7.h5 -trainrlessd16_slices/patient002_frame01_slice_8.h5 -trainrlessd16_slices/patient002_frame01_slice_9.h5 -trainrlessd16_slices/patient002_frame12_slice_0.h5 -trainrlessd16_slices/patient002_frame12_slice_1.h5 -trainrlessd16_slices/patient002_frame12_slice_2.h5 -trainrlessd16_slices/patient002_frame12_slice_3.h5 -trainrlessd16_slices/patient002_frame12_slice_4.h5 -trainrlessd16_slices/patient002_frame12_slice_5.h5 -trainrlessd16_slices/patient002_frame12_slice_6.h5 -trainrlessd16_slices/patient002_frame12_slice_7.h5 -trainrlessd16_slices/patient002_frame12_slice_8.h5 -trainrlessd16_slices/patient002_frame12_slice_9.h5 -trainrlessd16_slices/patient003_frame01_slice_0.h5 -trainrlessd16_slices/patient003_frame01_slice_1.h5 -trainrlessd16_slices/patient003_frame01_slice_2.h5 -trainrlessd16_slices/patient003_frame01_slice_3.h5 -trainrlessd16_slices/patient003_frame01_slice_4.h5 -trainrlessd16_slices/patient003_frame01_slice_5.h5 -trainrlessd16_slices/patient003_frame01_slice_6.h5 -trainrlessd16_slices/patient003_frame01_slice_7.h5 -trainrlessd16_slices/patient003_frame01_slice_8.h5 -trainrlessd16_slices/patient003_frame01_slice_9.h5 -trainrlessd16_slices/patient003_frame15_slice_0.h5 -trainrlessd16_slices/patient003_frame15_slice_1.h5 -trainrlessd16_slices/patient003_frame15_slice_2.h5 -trainrlessd16_slices/patient003_frame15_slice_3.h5 -trainrlessd16_slices/patient003_frame15_slice_4.h5 -trainrlessd16_slices/patient003_frame15_slice_5.h5 -trainrlessd16_slices/patient003_frame15_slice_6.h5 -trainrlessd16_slices/patient003_frame15_slice_7.h5 -trainrlessd16_slices/patient003_frame15_slice_8.h5 -trainrlessd16_slices/patient003_frame15_slice_9.h5 -trainrlessd16_slices/patient004_frame01_slice_0.h5 -trainrlessd16_slices/patient004_frame01_slice_1.h5 -trainrlessd16_slices/patient004_frame01_slice_2.h5 -trainrlessd16_slices/patient004_frame01_slice_3.h5 -trainrlessd16_slices/patient004_frame01_slice_4.h5 -trainrlessd16_slices/patient004_frame01_slice_5.h5 -trainrlessd16_slices/patient004_frame01_slice_6.h5 -trainrlessd16_slices/patient004_frame01_slice_7.h5 -trainrlessd16_slices/patient004_frame01_slice_8.h5 -trainrlessd16_slices/patient004_frame01_slice_9.h5 -trainrlessd16_slices/patient005_frame01_slice_0.h5 -trainrlessd16_slices/patient005_frame01_slice_1.h5 -trainrlessd16_slices/patient005_frame01_slice_2.h5 -trainrlessd16_slices/patient005_frame01_slice_3.h5 -trainrlessd16_slices/patient005_frame01_slice_4.h5 -trainrlessd16_slices/patient005_frame01_slice_5.h5 -trainrlessd16_slices/patient005_frame01_slice_6.h5 -trainrlessd16_slices/patient005_frame01_slice_7.h5 -trainrlessd16_slices/patient005_frame01_slice_8.h5 -trainrlessd16_slices/patient005_frame01_slice_9.h5 -trainrlessd16_slices/patient005_frame13_slice_0.h5 -trainrlessd16_slices/patient005_frame13_slice_1.h5 -trainrlessd16_slices/patient005_frame13_slice_2.h5 -trainrlessd16_slices/patient005_frame13_slice_3.h5 -trainrlessd16_slices/patient005_frame13_slice_4.h5 -trainrlessd16_slices/patient005_frame13_slice_5.h5 -trainrlessd16_slices/patient005_frame13_slice_6.h5 -trainrlessd16_slices/patient005_frame13_slice_7.h5 -trainrlessd16_slices/patient005_frame13_slice_8.h5 -trainrlessd16_slices/patient005_frame13_slice_9.h5 -trainrlessd16_slices/patient006_frame16_slice_0.h5 -trainrlessd16_slices/patient006_frame16_slice_1.h5 -trainrlessd16_slices/patient006_frame16_slice_10.h5 -trainrlessd16_slices/patient006_frame16_slice_2.h5 -trainrlessd16_slices/patient006_frame16_slice_3.h5 -trainrlessd16_slices/patient006_frame16_slice_4.h5 -trainrlessd16_slices/patient006_frame16_slice_5.h5 -trainrlessd16_slices/patient006_frame16_slice_6.h5 -trainrlessd16_slices/patient006_frame16_slice_7.h5 -trainrlessd16_slices/patient006_frame16_slice_8.h5 -trainrlessd16_slices/patient006_frame16_slice_9.h5 -trainrlessd16_slices/patient007_frame01_slice_0.h5 -trainrlessd16_slices/patient007_frame01_slice_1.h5 -trainrlessd16_slices/patient007_frame01_slice_2.h5 -trainrlessd16_slices/patient007_frame01_slice_3.h5 -trainrlessd16_slices/patient007_frame01_slice_4.h5 -trainrlessd16_slices/patient007_frame01_slice_5.h5 -trainrlessd16_slices/patient007_frame01_slice_6.h5 -trainrlessd16_slices/patient007_frame01_slice_7.h5 -trainrlessd16_slices/patient007_frame01_slice_8.h5 -trainrlessd16_slices/patient007_frame01_slice_9.h5 -trainrlessd16_slices/patient007_frame07_slice_0.h5 -trainrlessd16_slices/patient007_frame07_slice_1.h5 -trainrlessd16_slices/patient007_frame07_slice_2.h5 -trainrlessd16_slices/patient007_frame07_slice_3.h5 -trainrlessd16_slices/patient007_frame07_slice_4.h5 -trainrlessd16_slices/patient007_frame07_slice_5.h5 -trainrlessd16_slices/patient007_frame07_slice_6.h5 -trainrlessd16_slices/patient007_frame07_slice_7.h5 -trainrlessd16_slices/patient007_frame07_slice_8.h5 -trainrlessd16_slices/patient007_frame07_slice_9.h5 -trainrlessd16_slices/patient008_frame13_slice_0.h5 -trainrlessd16_slices/patient008_frame13_slice_1.h5 -trainrlessd16_slices/patient008_frame13_slice_2.h5 -trainrlessd16_slices/patient008_frame13_slice_3.h5 -trainrlessd16_slices/patient008_frame13_slice_4.h5 -trainrlessd16_slices/patient008_frame13_slice_5.h5 -trainrlessd16_slices/patient008_frame13_slice_6.h5 -trainrlessd16_slices/patient008_frame13_slice_7.h5 -trainrlessd16_slices/patient008_frame13_slice_8.h5 -trainrlessd16_slices/patient008_frame13_slice_9.h5 -trainrlessd16_slices/patient009_frame01_slice_0.h5 -trainrlessd16_slices/patient009_frame01_slice_1.h5 -trainrlessd16_slices/patient009_frame01_slice_2.h5 -trainrlessd16_slices/patient009_frame01_slice_3.h5 -trainrlessd16_slices/patient009_frame01_slice_4.h5 -trainrlessd16_slices/patient009_frame01_slice_5.h5 -trainrlessd16_slices/patient009_frame01_slice_6.h5 -trainrlessd16_slices/patient009_frame01_slice_7.h5 -trainrlessd16_slices/patient009_frame01_slice_8.h5 -trainrlessd16_slices/patient009_frame01_slice_9.h5 -trainrlessd16_slices/patient010_frame01_slice_0.h5 -trainrlessd16_slices/patient010_frame01_slice_1.h5 -trainrlessd16_slices/patient010_frame01_slice_2.h5 -trainrlessd16_slices/patient010_frame01_slice_3.h5 -trainrlessd16_slices/patient010_frame01_slice_4.h5 -trainrlessd16_slices/patient010_frame01_slice_5.h5 -trainrlessd16_slices/patient010_frame01_slice_6.h5 -trainrlessd16_slices/patient010_frame01_slice_7.h5 -trainrlessd16_slices/patient010_frame01_slice_8.h5 -trainrlessd16_slices/patient010_frame01_slice_9.h5 -trainrlessd16_slices/patient010_frame13_slice_0.h5 -trainrlessd16_slices/patient010_frame13_slice_1.h5 -trainrlessd16_slices/patient010_frame13_slice_2.h5 -trainrlessd16_slices/patient010_frame13_slice_3.h5 -trainrlessd16_slices/patient010_frame13_slice_4.h5 -trainrlessd16_slices/patient010_frame13_slice_5.h5 -trainrlessd16_slices/patient010_frame13_slice_6.h5 -trainrlessd16_slices/patient010_frame13_slice_7.h5 -trainrlessd16_slices/patient010_frame13_slice_8.h5 -trainrlessd16_slices/patient010_frame13_slice_9.h5 -trainrlessd16_slices/patient011_frame01_slice_0.h5 -trainrlessd16_slices/patient011_frame01_slice_1.h5 -trainrlessd16_slices/patient011_frame01_slice_2.h5 -trainrlessd16_slices/patient011_frame01_slice_3.h5 -trainrlessd16_slices/patient011_frame01_slice_4.h5 -trainrlessd16_slices/patient011_frame01_slice_5.h5 -trainrlessd16_slices/patient011_frame01_slice_6.h5 -trainrlessd16_slices/patient011_frame01_slice_7.h5 -trainrlessd16_slices/patient011_frame01_slice_8.h5 -trainrlessd16_slices/patient011_frame08_slice_0.h5 -trainrlessd16_slices/patient011_frame08_slice_1.h5 -trainrlessd16_slices/patient011_frame08_slice_2.h5 -trainrlessd16_slices/patient011_frame08_slice_3.h5 -trainrlessd16_slices/patient011_frame08_slice_4.h5 -trainrlessd16_slices/patient011_frame08_slice_5.h5 -trainrlessd16_slices/patient011_frame08_slice_6.h5 -trainrlessd16_slices/patient011_frame08_slice_7.h5 -trainrlessd16_slices/patient011_frame08_slice_8.h5 -trainrlessd16_slices/patient012_frame01_slice_0.h5 -trainrlessd16_slices/patient012_frame01_slice_1.h5 -trainrlessd16_slices/patient012_frame01_slice_2.h5 -trainrlessd16_slices/patient012_frame01_slice_3.h5 -trainrlessd16_slices/patient012_frame01_slice_4.h5 -trainrlessd16_slices/patient012_frame01_slice_5.h5 -trainrlessd16_slices/patient012_frame01_slice_6.h5 -trainrlessd16_slices/patient012_frame01_slice_7.h5 -trainrlessd16_slices/patient012_frame01_slice_8.h5 -trainrlessd16_slices/patient012_frame01_slice_9.h5 -trainrlessd16_slices/patient013_frame01_slice_0.h5 -trainrlessd16_slices/patient013_frame01_slice_1.h5 -trainrlessd16_slices/patient013_frame01_slice_2.h5 -trainrlessd16_slices/patient013_frame01_slice_3.h5 -trainrlessd16_slices/patient013_frame01_slice_4.h5 -trainrlessd16_slices/patient013_frame01_slice_5.h5 -trainrlessd16_slices/patient013_frame01_slice_6.h5 -trainrlessd16_slices/patient013_frame01_slice_7.h5 -trainrlessd16_slices/patient013_frame01_slice_8.h5 -trainrlessd16_slices/patient013_frame01_slice_9.h5 -trainrlessd16_slices/patient014_frame13_slice_0.h5 -trainrlessd16_slices/patient014_frame13_slice_1.h5 -trainrlessd16_slices/patient014_frame13_slice_2.h5 -trainrlessd16_slices/patient014_frame13_slice_3.h5 -trainrlessd16_slices/patient014_frame13_slice_4.h5 -trainrlessd16_slices/patient014_frame13_slice_5.h5 -trainrlessd16_slices/patient014_frame13_slice_6.h5 -trainrlessd16_slices/patient014_frame13_slice_7.h5 -trainrlessd16_slices/patient014_frame13_slice_8.h5 -trainrlessd16_slices/patient014_frame13_slice_9.h5 -trainrlessd16_slices/patient015_frame10_slice_0.h5 -trainrlessd16_slices/patient015_frame10_slice_1.h5 -trainrlessd16_slices/patient015_frame10_slice_2.h5 -trainrlessd16_slices/patient015_frame10_slice_3.h5 -trainrlessd16_slices/patient015_frame10_slice_4.h5 -trainrlessd16_slices/patient015_frame10_slice_5.h5 -trainrlessd16_slices/patient015_frame10_slice_6.h5 -trainrlessd16_slices/patient015_frame10_slice_7.h5 -trainrlessd16_slices/patient015_frame10_slice_8.h5 -trainrlessd16_slices/patient016_frame12_slice_0.h5 -trainrlessd16_slices/patient016_frame12_slice_1.h5 -trainrlessd16_slices/patient016_frame12_slice_2.h5 -trainrlessd16_slices/patient016_frame12_slice_3.h5 -trainrlessd16_slices/patient016_frame12_slice_4.h5 -trainrlessd16_slices/patient016_frame12_slice_5.h5 -trainrlessd16_slices/patient016_frame12_slice_6.h5 -trainrlessd16_slices/patient016_frame12_slice_7.h5 -trainrlessd16_slices/patient016_frame12_slice_8.h5 -trainrlessd16_slices/patient016_frame12_slice_9.h5 -trainrlessd16_slices/patient017_frame01_slice_0.h5 -trainrlessd16_slices/patient017_frame01_slice_1.h5 -trainrlessd16_slices/patient017_frame01_slice_2.h5 -trainrlessd16_slices/patient017_frame01_slice_3.h5 -trainrlessd16_slices/patient017_frame01_slice_4.h5 -trainrlessd16_slices/patient017_frame01_slice_5.h5 -trainrlessd16_slices/patient017_frame01_slice_6.h5 -trainrlessd16_slices/patient017_frame01_slice_7.h5 -trainrlessd16_slices/patient017_frame01_slice_8.h5 -trainrlessd16_slices/patient017_frame09_slice_0.h5 -trainrlessd16_slices/patient017_frame09_slice_1.h5 -trainrlessd16_slices/patient017_frame09_slice_2.h5 -trainrlessd16_slices/patient017_frame09_slice_3.h5 -trainrlessd16_slices/patient017_frame09_slice_4.h5 -trainrlessd16_slices/patient017_frame09_slice_5.h5 -trainrlessd16_slices/patient017_frame09_slice_6.h5 -trainrlessd16_slices/patient017_frame09_slice_7.h5 -trainrlessd16_slices/patient017_frame09_slice_8.h5 -trainrlessd16_slices/patient018_frame01_slice_0.h5 -trainrlessd16_slices/patient018_frame01_slice_1.h5 -trainrlessd16_slices/patient018_frame01_slice_2.h5 -trainrlessd16_slices/patient018_frame01_slice_3.h5 -trainrlessd16_slices/patient018_frame01_slice_4.h5 -trainrlessd16_slices/patient018_frame01_slice_5.h5 -trainrlessd16_slices/patient018_frame01_slice_6.h5 -trainrlessd16_slices/patient018_frame01_slice_7.h5 -trainrlessd16_slices/patient018_frame10_slice_0.h5 -trainrlessd16_slices/patient018_frame10_slice_1.h5 -trainrlessd16_slices/patient018_frame10_slice_2.h5 -trainrlessd16_slices/patient018_frame10_slice_3.h5 -trainrlessd16_slices/patient018_frame10_slice_4.h5 -trainrlessd16_slices/patient018_frame10_slice_5.h5 -trainrlessd16_slices/patient018_frame10_slice_6.h5 -trainrlessd16_slices/patient018_frame10_slice_7.h5 -trainrlessd16_slices/patient019_frame11_slice_0.h5 -trainrlessd16_slices/patient019_frame11_slice_1.h5 -trainrlessd16_slices/patient019_frame11_slice_10.h5 -trainrlessd16_slices/patient019_frame11_slice_2.h5 -trainrlessd16_slices/patient019_frame11_slice_3.h5 -trainrlessd16_slices/patient019_frame11_slice_4.h5 -trainrlessd16_slices/patient019_frame11_slice_5.h5 -trainrlessd16_slices/patient019_frame11_slice_6.h5 -trainrlessd16_slices/patient019_frame11_slice_7.h5 -trainrlessd16_slices/patient019_frame11_slice_8.h5 -trainrlessd16_slices/patient019_frame11_slice_9.h5 -trainrlessd16_slices/patient020_frame01_slice_0.h5 -trainrlessd16_slices/patient020_frame01_slice_1.h5 -trainrlessd16_slices/patient020_frame01_slice_2.h5 -trainrlessd16_slices/patient020_frame01_slice_3.h5 -trainrlessd16_slices/patient020_frame01_slice_4.h5 -trainrlessd16_slices/patient020_frame01_slice_5.h5 -trainrlessd16_slices/patient020_frame01_slice_6.h5 -trainrlessd16_slices/patient020_frame01_slice_7.h5 -trainrlessd16_slices/patient021_frame01_slice_0.h5 -trainrlessd16_slices/patient021_frame01_slice_1.h5 -trainrlessd16_slices/patient021_frame01_slice_2.h5 -trainrlessd16_slices/patient021_frame01_slice_3.h5 -trainrlessd16_slices/patient021_frame01_slice_4.h5 -trainrlessd16_slices/patient021_frame01_slice_5.h5 -trainrlessd16_slices/patient021_frame01_slice_6.h5 -trainrlessd16_slices/patient021_frame01_slice_7.h5 -trainrlessd16_slices/patient021_frame01_slice_8.h5 -trainrlessd16_slices/patient021_frame01_slice_9.h5 -trainrlessd16_slices/patient021_frame13_slice_0.h5 -trainrlessd16_slices/patient021_frame13_slice_1.h5 -trainrlessd16_slices/patient021_frame13_slice_2.h5 -trainrlessd16_slices/patient021_frame13_slice_3.h5 -trainrlessd16_slices/patient021_frame13_slice_4.h5 -trainrlessd16_slices/patient021_frame13_slice_5.h5 -trainrlessd16_slices/patient021_frame13_slice_6.h5 -trainrlessd16_slices/patient021_frame13_slice_7.h5 -trainrlessd16_slices/patient021_frame13_slice_8.h5 -trainrlessd16_slices/patient021_frame13_slice_9.h5 -trainrlessd16_slices/patient022_frame01_slice_0.h5 -trainrlessd16_slices/patient022_frame01_slice_1.h5 -trainrlessd16_slices/patient022_frame01_slice_2.h5 -trainrlessd16_slices/patient022_frame01_slice_3.h5 -trainrlessd16_slices/patient022_frame01_slice_4.h5 -trainrlessd16_slices/patient022_frame01_slice_5.h5 -trainrlessd16_slices/patient022_frame01_slice_6.h5 -trainrlessd16_slices/patient022_frame11_slice_0.h5 -trainrlessd16_slices/patient022_frame11_slice_1.h5 -trainrlessd16_slices/patient022_frame11_slice_2.h5 -trainrlessd16_slices/patient022_frame11_slice_3.h5 -trainrlessd16_slices/patient022_frame11_slice_4.h5 -trainrlessd16_slices/patient022_frame11_slice_5.h5 -trainrlessd16_slices/patient022_frame11_slice_6.h5 -trainrlessd16_slices/patient023_frame01_slice_0.h5 -trainrlessd16_slices/patient023_frame01_slice_1.h5 -trainrlessd16_slices/patient023_frame01_slice_2.h5 -trainrlessd16_slices/patient023_frame01_slice_3.h5 -trainrlessd16_slices/patient023_frame01_slice_4.h5 -trainrlessd16_slices/patient023_frame01_slice_5.h5 -trainrlessd16_slices/patient023_frame01_slice_6.h5 -trainrlessd16_slices/patient023_frame01_slice_7.h5 -trainrlessd16_slices/patient023_frame01_slice_8.h5 -trainrlessd16_slices/patient024_frame09_slice_0.h5 -trainrlessd16_slices/patient024_frame09_slice_1.h5 -trainrlessd16_slices/patient024_frame09_slice_2.h5 -trainrlessd16_slices/patient024_frame09_slice_3.h5 -trainrlessd16_slices/patient024_frame09_slice_4.h5 -trainrlessd16_slices/patient024_frame09_slice_5.h5 -trainrlessd16_slices/patient024_frame09_slice_6.h5 -trainrlessd16_slices/patient024_frame09_slice_7.h5 -trainrlessd16_slices/patient025_frame01_slice_0.h5 -trainrlessd16_slices/patient025_frame01_slice_1.h5 -trainrlessd16_slices/patient025_frame01_slice_2.h5 -trainrlessd16_slices/patient025_frame01_slice_3.h5 -trainrlessd16_slices/patient025_frame01_slice_4.h5 -trainrlessd16_slices/patient025_frame01_slice_5.h5 -trainrlessd16_slices/patient025_frame01_slice_6.h5 -trainrlessd16_slices/patient025_frame01_slice_7.h5 -trainrlessd16_slices/patient025_frame01_slice_8.h5 -trainrlessd16_slices/patient026_frame01_slice_0.h5 -trainrlessd16_slices/patient026_frame01_slice_1.h5 -trainrlessd16_slices/patient026_frame01_slice_2.h5 -trainrlessd16_slices/patient026_frame01_slice_3.h5 -trainrlessd16_slices/patient026_frame01_slice_4.h5 -trainrlessd16_slices/patient026_frame01_slice_5.h5 -trainrlessd16_slices/patient026_frame01_slice_6.h5 -trainrlessd16_slices/patient026_frame01_slice_7.h5 -trainrlessd16_slices/patient026_frame01_slice_8.h5 -trainrlessd16_slices/patient026_frame01_slice_9.h5 -trainrlessd16_slices/patient026_frame12_slice_0.h5 -trainrlessd16_slices/patient026_frame12_slice_1.h5 -trainrlessd16_slices/patient026_frame12_slice_2.h5 -trainrlessd16_slices/patient026_frame12_slice_3.h5 -trainrlessd16_slices/patient026_frame12_slice_4.h5 -trainrlessd16_slices/patient026_frame12_slice_5.h5 -trainrlessd16_slices/patient026_frame12_slice_6.h5 -trainrlessd16_slices/patient026_frame12_slice_7.h5 -trainrlessd16_slices/patient026_frame12_slice_8.h5 -trainrlessd16_slices/patient026_frame12_slice_9.h5 -trainrlessd16_slices/patient027_frame01_slice_0.h5 -trainrlessd16_slices/patient027_frame01_slice_1.h5 -trainrlessd16_slices/patient027_frame01_slice_2.h5 -trainrlessd16_slices/patient027_frame01_slice_3.h5 -trainrlessd16_slices/patient027_frame01_slice_4.h5 -trainrlessd16_slices/patient027_frame01_slice_5.h5 -trainrlessd16_slices/patient027_frame01_slice_6.h5 -trainrlessd16_slices/patient027_frame01_slice_7.h5 -trainrlessd16_slices/patient027_frame01_slice_8.h5 -trainrlessd16_slices/patient027_frame01_slice_9.h5 -trainrlessd16_slices/patient027_frame11_slice_0.h5 -trainrlessd16_slices/patient027_frame11_slice_1.h5 -trainrlessd16_slices/patient027_frame11_slice_2.h5 -trainrlessd16_slices/patient027_frame11_slice_3.h5 -trainrlessd16_slices/patient027_frame11_slice_4.h5 -trainrlessd16_slices/patient027_frame11_slice_5.h5 -trainrlessd16_slices/patient027_frame11_slice_6.h5 -trainrlessd16_slices/patient027_frame11_slice_7.h5 -trainrlessd16_slices/patient027_frame11_slice_8.h5 -trainrlessd16_slices/patient027_frame11_slice_9.h5 -trainrlessd16_slices/patient028_frame01_slice_0.h5 -trainrlessd16_slices/patient028_frame01_slice_1.h5 -trainrlessd16_slices/patient028_frame01_slice_2.h5 -trainrlessd16_slices/patient028_frame01_slice_3.h5 -trainrlessd16_slices/patient028_frame01_slice_4.h5 -trainrlessd16_slices/patient028_frame01_slice_5.h5 -trainrlessd16_slices/patient028_frame01_slice_6.h5 -trainrlessd16_slices/patient028_frame01_slice_7.h5 -trainrlessd16_slices/patient028_frame01_slice_8.h5 -trainrlessd16_slices/patient028_frame01_slice_9.h5 -trainrlessd16_slices/patient028_frame09_slice_0.h5 -trainrlessd16_slices/patient028_frame09_slice_1.h5 -trainrlessd16_slices/patient028_frame09_slice_2.h5 -trainrlessd16_slices/patient028_frame09_slice_3.h5 -trainrlessd16_slices/patient028_frame09_slice_4.h5 -trainrlessd16_slices/patient028_frame09_slice_5.h5 -trainrlessd16_slices/patient028_frame09_slice_6.h5 -trainrlessd16_slices/patient028_frame09_slice_7.h5 -trainrlessd16_slices/patient028_frame09_slice_8.h5 -trainrlessd16_slices/patient028_frame09_slice_9.h5 -trainrlessd16_slices/patient029_frame12_slice_0.h5 -trainrlessd16_slices/patient029_frame12_slice_1.h5 -trainrlessd16_slices/patient029_frame12_slice_10.h5 -trainrlessd16_slices/patient029_frame12_slice_2.h5 -trainrlessd16_slices/patient029_frame12_slice_3.h5 -trainrlessd16_slices/patient029_frame12_slice_4.h5 -trainrlessd16_slices/patient029_frame12_slice_5.h5 -trainrlessd16_slices/patient029_frame12_slice_6.h5 -trainrlessd16_slices/patient029_frame12_slice_7.h5 -trainrlessd16_slices/patient029_frame12_slice_8.h5 -trainrlessd16_slices/patient029_frame12_slice_9.h5 -trainrlessd16_slices/patient030_frame12_slice_0.h5 -trainrlessd16_slices/patient030_frame12_slice_1.h5 -trainrlessd16_slices/patient030_frame12_slice_2.h5 -trainrlessd16_slices/patient030_frame12_slice_3.h5 -trainrlessd16_slices/patient030_frame12_slice_4.h5 -trainrlessd16_slices/patient030_frame12_slice_5.h5 -trainrlessd16_slices/patient030_frame12_slice_6.h5 -trainrlessd16_slices/patient030_frame12_slice_7.h5 -trainrlessd16_slices/patient030_frame12_slice_8.h5 -trainrlessd16_slices/patient030_frame12_slice_9.h5 -trainrlessd16_slices/patient031_frame01_slice_0.h5 -trainrlessd16_slices/patient031_frame01_slice_1.h5 -trainrlessd16_slices/patient031_frame01_slice_2.h5 -trainrlessd16_slices/patient031_frame01_slice_3.h5 -trainrlessd16_slices/patient031_frame01_slice_4.h5 -trainrlessd16_slices/patient031_frame01_slice_5.h5 -trainrlessd16_slices/patient031_frame01_slice_6.h5 -trainrlessd16_slices/patient031_frame01_slice_7.h5 -trainrlessd16_slices/patient031_frame01_slice_8.h5 -trainrlessd16_slices/patient031_frame01_slice_9.h5 -trainrlessd16_slices/patient032_frame12_slice_0.h5 -trainrlessd16_slices/patient032_frame12_slice_1.h5 -trainrlessd16_slices/patient032_frame12_slice_2.h5 -trainrlessd16_slices/patient032_frame12_slice_3.h5 -trainrlessd16_slices/patient032_frame12_slice_4.h5 -trainrlessd16_slices/patient032_frame12_slice_5.h5 -trainrlessd16_slices/patient032_frame12_slice_6.h5 -trainrlessd16_slices/patient032_frame12_slice_7.h5 -trainrlessd16_slices/patient032_frame12_slice_8.h5 -trainrlessd16_slices/patient032_frame12_slice_9.h5 -trainrlessd16_slices/patient033_frame01_slice_0.h5 -trainrlessd16_slices/patient033_frame01_slice_1.h5 -trainrlessd16_slices/patient033_frame01_slice_2.h5 -trainrlessd16_slices/patient033_frame01_slice_3.h5 -trainrlessd16_slices/patient033_frame01_slice_4.h5 -trainrlessd16_slices/patient033_frame01_slice_5.h5 -trainrlessd16_slices/patient033_frame01_slice_6.h5 -trainrlessd16_slices/patient033_frame01_slice_7.h5 -trainrlessd16_slices/patient033_frame01_slice_8.h5 -trainrlessd16_slices/patient033_frame01_slice_9.h5 -trainrlessd16_slices/patient033_frame14_slice_0.h5 -trainrlessd16_slices/patient033_frame14_slice_1.h5 -trainrlessd16_slices/patient033_frame14_slice_2.h5 -trainrlessd16_slices/patient033_frame14_slice_3.h5 -trainrlessd16_slices/patient033_frame14_slice_4.h5 -trainrlessd16_slices/patient033_frame14_slice_5.h5 -trainrlessd16_slices/patient033_frame14_slice_6.h5 -trainrlessd16_slices/patient033_frame14_slice_7.h5 -trainrlessd16_slices/patient033_frame14_slice_8.h5 -trainrlessd16_slices/patient033_frame14_slice_9.h5 -trainrlessd16_slices/patient034_frame01_slice_0.h5 -trainrlessd16_slices/patient034_frame01_slice_1.h5 -trainrlessd16_slices/patient034_frame01_slice_2.h5 -trainrlessd16_slices/patient034_frame01_slice_3.h5 -trainrlessd16_slices/patient034_frame01_slice_4.h5 -trainrlessd16_slices/patient034_frame01_slice_5.h5 -trainrlessd16_slices/patient034_frame01_slice_6.h5 -trainrlessd16_slices/patient034_frame01_slice_7.h5 -trainrlessd16_slices/patient034_frame01_slice_8.h5 -trainrlessd16_slices/patient034_frame01_slice_9.h5 -trainrlessd16_slices/patient035_frame01_slice_0.h5 -trainrlessd16_slices/patient035_frame01_slice_1.h5 -trainrlessd16_slices/patient035_frame01_slice_10.h5 -trainrlessd16_slices/patient035_frame01_slice_11.h5 -trainrlessd16_slices/patient035_frame01_slice_12.h5 -trainrlessd16_slices/patient035_frame01_slice_2.h5 -trainrlessd16_slices/patient035_frame01_slice_3.h5 -trainrlessd16_slices/patient035_frame01_slice_4.h5 -trainrlessd16_slices/patient035_frame01_slice_5.h5 -trainrlessd16_slices/patient035_frame01_slice_6.h5 -trainrlessd16_slices/patient035_frame01_slice_7.h5 -trainrlessd16_slices/patient035_frame01_slice_8.h5 -trainrlessd16_slices/patient035_frame01_slice_9.h5 -trainrlessd16_slices/patient035_frame11_slice_0.h5 -trainrlessd16_slices/patient035_frame11_slice_1.h5 -trainrlessd16_slices/patient035_frame11_slice_10.h5 -trainrlessd16_slices/patient035_frame11_slice_11.h5 -trainrlessd16_slices/patient035_frame11_slice_12.h5 -trainrlessd16_slices/patient035_frame11_slice_2.h5 -trainrlessd16_slices/patient035_frame11_slice_3.h5 -trainrlessd16_slices/patient035_frame11_slice_4.h5 -trainrlessd16_slices/patient035_frame11_slice_5.h5 -trainrlessd16_slices/patient035_frame11_slice_6.h5 -trainrlessd16_slices/patient035_frame11_slice_7.h5 -trainrlessd16_slices/patient035_frame11_slice_8.h5 -trainrlessd16_slices/patient035_frame11_slice_9.h5 -trainrlessd16_slices/patient036_frame12_slice_0.h5 -trainrlessd16_slices/patient036_frame12_slice_1.h5 -trainrlessd16_slices/patient036_frame12_slice_2.h5 -trainrlessd16_slices/patient036_frame12_slice_3.h5 -trainrlessd16_slices/patient036_frame12_slice_4.h5 -trainrlessd16_slices/patient036_frame12_slice_5.h5 -trainrlessd16_slices/patient036_frame12_slice_6.h5 -trainrlessd16_slices/patient036_frame12_slice_7.h5 -trainrlessd16_slices/patient037_frame01_slice_0.h5 -trainrlessd16_slices/patient037_frame01_slice_1.h5 -trainrlessd16_slices/patient037_frame01_slice_2.h5 -trainrlessd16_slices/patient037_frame01_slice_3.h5 -trainrlessd16_slices/patient037_frame01_slice_4.h5 -trainrlessd16_slices/patient037_frame01_slice_5.h5 -trainrlessd16_slices/patient037_frame01_slice_6.h5 -trainrlessd16_slices/patient037_frame12_slice_0.h5 -trainrlessd16_slices/patient037_frame12_slice_1.h5 -trainrlessd16_slices/patient037_frame12_slice_2.h5 -trainrlessd16_slices/patient037_frame12_slice_3.h5 -trainrlessd16_slices/patient037_frame12_slice_4.h5 -trainrlessd16_slices/patient037_frame12_slice_5.h5 -trainrlessd16_slices/patient037_frame12_slice_6.h5 -trainrlessd16_slices/patient038_frame01_slice_0.h5 -trainrlessd16_slices/patient038_frame01_slice_1.h5 -trainrlessd16_slices/patient038_frame01_slice_2.h5 -trainrlessd16_slices/patient038_frame01_slice_3.h5 -trainrlessd16_slices/patient038_frame01_slice_4.h5 -trainrlessd16_slices/patient038_frame01_slice_5.h5 -trainrlessd16_slices/patient038_frame01_slice_6.h5 -trainrlessd16_slices/patient038_frame01_slice_7.h5 -trainrlessd16_slices/patient039_frame01_slice_0.h5 -trainrlessd16_slices/patient039_frame01_slice_1.h5 -trainrlessd16_slices/patient039_frame01_slice_2.h5 -trainrlessd16_slices/patient039_frame01_slice_3.h5 -trainrlessd16_slices/patient039_frame01_slice_4.h5 -trainrlessd16_slices/patient039_frame01_slice_5.h5 -trainrlessd16_slices/patient039_frame01_slice_6.h5 -trainrlessd16_slices/patient039_frame01_slice_7.h5 -trainrlessd16_slices/patient039_frame01_slice_8.h5 -trainrlessd16_slices/patient039_frame10_slice_0.h5 -trainrlessd16_slices/patient039_frame10_slice_1.h5 -trainrlessd16_slices/patient039_frame10_slice_2.h5 -trainrlessd16_slices/patient039_frame10_slice_3.h5 -trainrlessd16_slices/patient039_frame10_slice_4.h5 -trainrlessd16_slices/patient039_frame10_slice_5.h5 -trainrlessd16_slices/patient039_frame10_slice_6.h5 -trainrlessd16_slices/patient039_frame10_slice_7.h5 -trainrlessd16_slices/patient039_frame10_slice_8.h5 -trainrlessd16_slices/patient040_frame01_slice_0.h5 -trainrlessd16_slices/patient040_frame01_slice_1.h5 -trainrlessd16_slices/patient040_frame01_slice_2.h5 -trainrlessd16_slices/patient040_frame01_slice_3.h5 -trainrlessd16_slices/patient040_frame01_slice_4.h5 -trainrlessd16_slices/patient040_frame01_slice_5.h5 -trainrlessd16_slices/patient040_frame01_slice_6.h5 -trainrlessd16_slices/patient040_frame01_slice_7.h5 -trainrlessd16_slices/patient040_frame01_slice_8.h5 -trainrlessd16_slices/patient040_frame01_slice_9.h5 -trainrlessd16_slices/patient041_frame01_slice_0.h5 -trainrlessd16_slices/patient041_frame01_slice_1.h5 -trainrlessd16_slices/patient041_frame01_slice_2.h5 -trainrlessd16_slices/patient041_frame01_slice_3.h5 -trainrlessd16_slices/patient041_frame01_slice_4.h5 -trainrlessd16_slices/patient041_frame01_slice_5.h5 -trainrlessd16_slices/patient041_frame11_slice_0.h5 -trainrlessd16_slices/patient041_frame11_slice_1.h5 -trainrlessd16_slices/patient041_frame11_slice_2.h5 -trainrlessd16_slices/patient041_frame11_slice_3.h5 -trainrlessd16_slices/patient041_frame11_slice_4.h5 -trainrlessd16_slices/patient041_frame11_slice_5.h5 -trainrlessd16_slices/patient042_frame01_slice_0.h5 -trainrlessd16_slices/patient042_frame01_slice_1.h5 -trainrlessd16_slices/patient042_frame01_slice_2.h5 -trainrlessd16_slices/patient042_frame01_slice_3.h5 -trainrlessd16_slices/patient042_frame01_slice_4.h5 -trainrlessd16_slices/patient042_frame01_slice_5.h5 -trainrlessd16_slices/patient042_frame01_slice_6.h5 -trainrlessd16_slices/patient042_frame01_slice_7.h5 -trainrlessd16_slices/patient042_frame01_slice_8.h5 -trainrlessd16_slices/patient042_frame16_slice_0.h5 -trainrlessd16_slices/patient042_frame16_slice_1.h5 -trainrlessd16_slices/patient042_frame16_slice_2.h5 -trainrlessd16_slices/patient042_frame16_slice_3.h5 -trainrlessd16_slices/patient042_frame16_slice_4.h5 -trainrlessd16_slices/patient042_frame16_slice_5.h5 -trainrlessd16_slices/patient042_frame16_slice_6.h5 -trainrlessd16_slices/patient042_frame16_slice_7.h5 -trainrlessd16_slices/patient042_frame16_slice_8.h5 -trainrlessd16_slices/patient043_frame01_slice_0.h5 -trainrlessd16_slices/patient043_frame01_slice_1.h5 -trainrlessd16_slices/patient043_frame01_slice_10.h5 -trainrlessd16_slices/patient043_frame01_slice_11.h5 -trainrlessd16_slices/patient043_frame01_slice_2.h5 -trainrlessd16_slices/patient043_frame01_slice_3.h5 -trainrlessd16_slices/patient043_frame01_slice_4.h5 -trainrlessd16_slices/patient043_frame01_slice_5.h5 -trainrlessd16_slices/patient043_frame01_slice_6.h5 -trainrlessd16_slices/patient043_frame01_slice_7.h5 -trainrlessd16_slices/patient043_frame01_slice_8.h5 -trainrlessd16_slices/patient043_frame01_slice_9.h5 -trainrlessd16_slices/patient043_frame07_slice_0.h5 -trainrlessd16_slices/patient043_frame07_slice_1.h5 -trainrlessd16_slices/patient043_frame07_slice_10.h5 -trainrlessd16_slices/patient043_frame07_slice_11.h5 -trainrlessd16_slices/patient043_frame07_slice_2.h5 -trainrlessd16_slices/patient043_frame07_slice_3.h5 -trainrlessd16_slices/patient043_frame07_slice_4.h5 -trainrlessd16_slices/patient043_frame07_slice_5.h5 -trainrlessd16_slices/patient043_frame07_slice_6.h5 -trainrlessd16_slices/patient043_frame07_slice_7.h5 -trainrlessd16_slices/patient043_frame07_slice_8.h5 -trainrlessd16_slices/patient043_frame07_slice_9.h5 -trainrlessd16_slices/patient044_frame01_slice_0.h5 -trainrlessd16_slices/patient044_frame01_slice_1.h5 -trainrlessd16_slices/patient044_frame01_slice_2.h5 -trainrlessd16_slices/patient044_frame01_slice_3.h5 -trainrlessd16_slices/patient044_frame01_slice_4.h5 -trainrlessd16_slices/patient044_frame01_slice_5.h5 -trainrlessd16_slices/patient044_frame01_slice_6.h5 -trainrlessd16_slices/patient044_frame01_slice_7.h5 -trainrlessd16_slices/patient044_frame01_slice_8.h5 -trainrlessd16_slices/patient044_frame11_slice_0.h5 -trainrlessd16_slices/patient044_frame11_slice_1.h5 -trainrlessd16_slices/patient044_frame11_slice_2.h5 -trainrlessd16_slices/patient044_frame11_slice_3.h5 -trainrlessd16_slices/patient044_frame11_slice_4.h5 -trainrlessd16_slices/patient044_frame11_slice_5.h5 -trainrlessd16_slices/patient044_frame11_slice_6.h5 -trainrlessd16_slices/patient044_frame11_slice_7.h5 -trainrlessd16_slices/patient044_frame11_slice_8.h5 -trainrlessd16_slices/patient045_frame01_slice_0.h5 -trainrlessd16_slices/patient045_frame01_slice_1.h5 -trainrlessd16_slices/patient045_frame01_slice_2.h5 -trainrlessd16_slices/patient045_frame01_slice_3.h5 -trainrlessd16_slices/patient045_frame01_slice_4.h5 -trainrlessd16_slices/patient045_frame01_slice_5.h5 -trainrlessd16_slices/patient045_frame01_slice_6.h5 -trainrlessd16_slices/patient045_frame01_slice_7.h5 -trainrlessd16_slices/patient046_frame01_slice_0.h5 -trainrlessd16_slices/patient046_frame01_slice_1.h5 -trainrlessd16_slices/patient046_frame01_slice_2.h5 -trainrlessd16_slices/patient046_frame01_slice_3.h5 -trainrlessd16_slices/patient046_frame01_slice_4.h5 -trainrlessd16_slices/patient046_frame01_slice_5.h5 -trainrlessd16_slices/patient046_frame01_slice_6.h5 -trainrlessd16_slices/patient046_frame01_slice_7.h5 -trainrlessd16_slices/patient046_frame01_slice_8.h5 -trainrlessd16_slices/patient046_frame10_slice_0.h5 -trainrlessd16_slices/patient046_frame10_slice_1.h5 -trainrlessd16_slices/patient046_frame10_slice_2.h5 -trainrlessd16_slices/patient046_frame10_slice_3.h5 -trainrlessd16_slices/patient046_frame10_slice_4.h5 -trainrlessd16_slices/patient046_frame10_slice_5.h5 -trainrlessd16_slices/patient046_frame10_slice_6.h5 -trainrlessd16_slices/patient046_frame10_slice_7.h5 -trainrlessd16_slices/patient046_frame10_slice_8.h5 -trainrlessd16_slices/patient047_frame01_slice_0.h5 -trainrlessd16_slices/patient047_frame01_slice_1.h5 -trainrlessd16_slices/patient047_frame01_slice_2.h5 -trainrlessd16_slices/patient047_frame01_slice_3.h5 -trainrlessd16_slices/patient047_frame01_slice_4.h5 -trainrlessd16_slices/patient047_frame01_slice_5.h5 -trainrlessd16_slices/patient047_frame01_slice_6.h5 -trainrlessd16_slices/patient047_frame01_slice_7.h5 -trainrlessd16_slices/patient047_frame01_slice_8.h5 -trainrlessd16_slices/patient048_frame01_slice_0.h5 -trainrlessd16_slices/patient048_frame01_slice_1.h5 -trainrlessd16_slices/patient048_frame01_slice_2.h5 -trainrlessd16_slices/patient048_frame01_slice_3.h5 -trainrlessd16_slices/patient048_frame01_slice_4.h5 -trainrlessd16_slices/patient048_frame01_slice_5.h5 -trainrlessd16_slices/patient048_frame01_slice_6.h5 -trainrlessd16_slices/patient048_frame01_slice_7.h5 -trainrlessd16_slices/patient049_frame01_slice_0.h5 -trainrlessd16_slices/patient049_frame01_slice_1.h5 -trainrlessd16_slices/patient049_frame01_slice_2.h5 -trainrlessd16_slices/patient049_frame01_slice_3.h5 -trainrlessd16_slices/patient049_frame01_slice_4.h5 -trainrlessd16_slices/patient049_frame01_slice_5.h5 -trainrlessd16_slices/patient049_frame01_slice_6.h5 -trainrlessd16_slices/patient049_frame11_slice_0.h5 -trainrlessd16_slices/patient049_frame11_slice_1.h5 -trainrlessd16_slices/patient049_frame11_slice_2.h5 -trainrlessd16_slices/patient049_frame11_slice_3.h5 -trainrlessd16_slices/patient049_frame11_slice_4.h5 -trainrlessd16_slices/patient049_frame11_slice_5.h5 -trainrlessd16_slices/patient049_frame11_slice_6.h5 -trainrlessd16_slices/patient050_frame01_slice_0.h5 -trainrlessd16_slices/patient050_frame01_slice_1.h5 -trainrlessd16_slices/patient050_frame01_slice_2.h5 -trainrlessd16_slices/patient050_frame01_slice_3.h5 -trainrlessd16_slices/patient050_frame01_slice_4.h5 -trainrlessd16_slices/patient050_frame01_slice_5.h5 -trainrlessd16_slices/patient050_frame01_slice_6.h5 -trainrlessd16_slices/patient050_frame01_slice_7.h5 -trainrlessd16_slices/patient050_frame01_slice_8.h5 -trainrlessd16_slices/patient050_frame01_slice_9.h5 -trainrlessd16_slices/patient050_frame12_slice_0.h5 -trainrlessd16_slices/patient050_frame12_slice_1.h5 -trainrlessd16_slices/patient050_frame12_slice_2.h5 -trainrlessd16_slices/patient050_frame12_slice_3.h5 -trainrlessd16_slices/patient050_frame12_slice_4.h5 -trainrlessd16_slices/patient050_frame12_slice_5.h5 -trainrlessd16_slices/patient050_frame12_slice_6.h5 -trainrlessd16_slices/patient050_frame12_slice_7.h5 -trainrlessd16_slices/patient050_frame12_slice_8.h5 -trainrlessd16_slices/patient050_frame12_slice_9.h5 -trainrlessd16_slices/patient051_frame01_slice_0.h5 -trainrlessd16_slices/patient051_frame01_slice_1.h5 -trainrlessd16_slices/patient051_frame01_slice_2.h5 -trainrlessd16_slices/patient051_frame01_slice_3.h5 -trainrlessd16_slices/patient051_frame01_slice_4.h5 -trainrlessd16_slices/patient051_frame01_slice_5.h5 -trainrlessd16_slices/patient051_frame01_slice_6.h5 -trainrlessd16_slices/patient051_frame01_slice_7.h5 -trainrlessd16_slices/patient051_frame01_slice_8.h5 -trainrlessd16_slices/patient051_frame01_slice_9.h5 -trainrlessd16_slices/patient051_frame11_slice_0.h5 -trainrlessd16_slices/patient051_frame11_slice_1.h5 -trainrlessd16_slices/patient051_frame11_slice_2.h5 -trainrlessd16_slices/patient051_frame11_slice_3.h5 -trainrlessd16_slices/patient051_frame11_slice_4.h5 -trainrlessd16_slices/patient051_frame11_slice_5.h5 -trainrlessd16_slices/patient051_frame11_slice_6.h5 -trainrlessd16_slices/patient051_frame11_slice_7.h5 -trainrlessd16_slices/patient051_frame11_slice_8.h5 -trainrlessd16_slices/patient051_frame11_slice_9.h5 -trainrlessd16_slices/patient052_frame01_slice_0.h5 -trainrlessd16_slices/patient052_frame01_slice_1.h5 -trainrlessd16_slices/patient052_frame01_slice_2.h5 -trainrlessd16_slices/patient052_frame01_slice_3.h5 -trainrlessd16_slices/patient052_frame01_slice_4.h5 -trainrlessd16_slices/patient052_frame01_slice_5.h5 -trainrlessd16_slices/patient052_frame01_slice_6.h5 -trainrlessd16_slices/patient052_frame01_slice_7.h5 -trainrlessd16_slices/patient052_frame09_slice_0.h5 -trainrlessd16_slices/patient052_frame09_slice_1.h5 -trainrlessd16_slices/patient052_frame09_slice_2.h5 -trainrlessd16_slices/patient052_frame09_slice_3.h5 -trainrlessd16_slices/patient052_frame09_slice_4.h5 -trainrlessd16_slices/patient052_frame09_slice_5.h5 -trainrlessd16_slices/patient052_frame09_slice_6.h5 -trainrlessd16_slices/patient052_frame09_slice_7.h5 -trainrlessd16_slices/patient053_frame12_slice_0.h5 -trainrlessd16_slices/patient053_frame12_slice_1.h5 -trainrlessd16_slices/patient053_frame12_slice_2.h5 -trainrlessd16_slices/patient053_frame12_slice_3.h5 -trainrlessd16_slices/patient053_frame12_slice_4.h5 -trainrlessd16_slices/patient053_frame12_slice_5.h5 -trainrlessd16_slices/patient053_frame12_slice_6.h5 -trainrlessd16_slices/patient054_frame01_slice_0.h5 -trainrlessd16_slices/patient054_frame01_slice_1.h5 -trainrlessd16_slices/patient054_frame01_slice_2.h5 -trainrlessd16_slices/patient054_frame01_slice_3.h5 -trainrlessd16_slices/patient054_frame01_slice_4.h5 -trainrlessd16_slices/patient054_frame01_slice_5.h5 -trainrlessd16_slices/patient054_frame01_slice_6.h5 -trainrlessd16_slices/patient054_frame01_slice_7.h5 -trainrlessd16_slices/patient054_frame12_slice_0.h5 -trainrlessd16_slices/patient054_frame12_slice_1.h5 -trainrlessd16_slices/patient054_frame12_slice_2.h5 -trainrlessd16_slices/patient054_frame12_slice_3.h5 -trainrlessd16_slices/patient054_frame12_slice_4.h5 -trainrlessd16_slices/patient054_frame12_slice_5.h5 -trainrlessd16_slices/patient054_frame12_slice_6.h5 -trainrlessd16_slices/patient054_frame12_slice_7.h5 -trainrlessd16_slices/patient055_frame10_slice_0.h5 -trainrlessd16_slices/patient055_frame10_slice_1.h5 -trainrlessd16_slices/patient055_frame10_slice_2.h5 -trainrlessd16_slices/patient055_frame10_slice_3.h5 -trainrlessd16_slices/patient055_frame10_slice_4.h5 -trainrlessd16_slices/patient055_frame10_slice_5.h5 -trainrlessd16_slices/patient055_frame10_slice_6.h5 -trainrlessd16_slices/patient055_frame10_slice_7.h5 -trainrlessd16_slices/patient055_frame10_slice_8.h5 -trainrlessd16_slices/patient056_frame01_slice_0.h5 -trainrlessd16_slices/patient056_frame01_slice_1.h5 -trainrlessd16_slices/patient056_frame01_slice_2.h5 -trainrlessd16_slices/patient056_frame01_slice_3.h5 -trainrlessd16_slices/patient056_frame01_slice_4.h5 -trainrlessd16_slices/patient056_frame01_slice_5.h5 -trainrlessd16_slices/patient056_frame01_slice_6.h5 -trainrlessd16_slices/patient056_frame01_slice_7.h5 -trainrlessd16_slices/patient056_frame01_slice_8.h5 -trainrlessd16_slices/patient056_frame12_slice_0.h5 -trainrlessd16_slices/patient056_frame12_slice_1.h5 -trainrlessd16_slices/patient056_frame12_slice_2.h5 -trainrlessd16_slices/patient056_frame12_slice_3.h5 -trainrlessd16_slices/patient056_frame12_slice_4.h5 -trainrlessd16_slices/patient056_frame12_slice_5.h5 -trainrlessd16_slices/patient056_frame12_slice_6.h5 -trainrlessd16_slices/patient056_frame12_slice_7.h5 -trainrlessd16_slices/patient056_frame12_slice_8.h5 -trainrlessd16_slices/patient057_frame01_slice_0.h5 -trainrlessd16_slices/patient057_frame01_slice_1.h5 -trainrlessd16_slices/patient057_frame01_slice_2.h5 -trainrlessd16_slices/patient057_frame01_slice_3.h5 -trainrlessd16_slices/patient057_frame01_slice_4.h5 -trainrlessd16_slices/patient057_frame01_slice_5.h5 -trainrlessd16_slices/patient057_frame01_slice_6.h5 -trainrlessd16_slices/patient057_frame01_slice_7.h5 -trainrlessd16_slices/patient058_frame14_slice_0.h5 -trainrlessd16_slices/patient058_frame14_slice_1.h5 -trainrlessd16_slices/patient058_frame14_slice_2.h5 -trainrlessd16_slices/patient058_frame14_slice_3.h5 -trainrlessd16_slices/patient058_frame14_slice_4.h5 -trainrlessd16_slices/patient058_frame14_slice_5.h5 -trainrlessd16_slices/patient058_frame14_slice_6.h5 -trainrlessd16_slices/patient058_frame14_slice_7.h5 -trainrlessd16_slices/patient058_frame14_slice_8.h5 -trainrlessd16_slices/patient059_frame01_slice_0.h5 -trainrlessd16_slices/patient059_frame01_slice_1.h5 -trainrlessd16_slices/patient059_frame01_slice_2.h5 -trainrlessd16_slices/patient059_frame01_slice_3.h5 -trainrlessd16_slices/patient059_frame01_slice_4.h5 -trainrlessd16_slices/patient059_frame01_slice_5.h5 -trainrlessd16_slices/patient059_frame01_slice_6.h5 -trainrlessd16_slices/patient059_frame01_slice_7.h5 -trainrlessd16_slices/patient059_frame01_slice_8.h5 -trainrlessd16_slices/patient059_frame09_slice_0.h5 -trainrlessd16_slices/patient059_frame09_slice_1.h5 -trainrlessd16_slices/patient059_frame09_slice_2.h5 -trainrlessd16_slices/patient059_frame09_slice_3.h5 -trainrlessd16_slices/patient059_frame09_slice_4.h5 -trainrlessd16_slices/patient059_frame09_slice_5.h5 -trainrlessd16_slices/patient059_frame09_slice_6.h5 -trainrlessd16_slices/patient059_frame09_slice_7.h5 -trainrlessd16_slices/patient059_frame09_slice_8.h5 -trainrlessd16_slices/patient060_frame14_slice_0.h5 -trainrlessd16_slices/patient060_frame14_slice_1.h5 -trainrlessd16_slices/patient060_frame14_slice_2.h5 -trainrlessd16_slices/patient060_frame14_slice_3.h5 -trainrlessd16_slices/patient060_frame14_slice_4.h5 -trainrlessd16_slices/patient060_frame14_slice_5.h5 -trainrlessd16_slices/patient060_frame14_slice_6.h5 -trainrlessd16_slices/patient060_frame14_slice_7.h5 -trainrlessd16_slices/patient060_frame14_slice_8.h5 -trainrlessd16_slices/patient061_frame01_slice_0.h5 -trainrlessd16_slices/patient061_frame01_slice_1.h5 -trainrlessd16_slices/patient061_frame01_slice_2.h5 -trainrlessd16_slices/patient061_frame01_slice_3.h5 -trainrlessd16_slices/patient061_frame01_slice_4.h5 -trainrlessd16_slices/patient061_frame01_slice_5.h5 -trainrlessd16_slices/patient061_frame01_slice_6.h5 -trainrlessd16_slices/patient061_frame01_slice_7.h5 -trainrlessd16_slices/patient061_frame01_slice_8.h5 -trainrlessd16_slices/patient061_frame10_slice_0.h5 -trainrlessd16_slices/patient061_frame10_slice_1.h5 -trainrlessd16_slices/patient061_frame10_slice_2.h5 -trainrlessd16_slices/patient061_frame10_slice_3.h5 -trainrlessd16_slices/patient061_frame10_slice_4.h5 -trainrlessd16_slices/patient061_frame10_slice_5.h5 -trainrlessd16_slices/patient061_frame10_slice_6.h5 -trainrlessd16_slices/patient061_frame10_slice_7.h5 -trainrlessd16_slices/patient061_frame10_slice_8.h5 -trainrlessd16_slices/patient062_frame01_slice_0.h5 -trainrlessd16_slices/patient062_frame01_slice_1.h5 -trainrlessd16_slices/patient062_frame01_slice_2.h5 -trainrlessd16_slices/patient062_frame01_slice_3.h5 -trainrlessd16_slices/patient062_frame01_slice_4.h5 -trainrlessd16_slices/patient062_frame01_slice_5.h5 -trainrlessd16_slices/patient062_frame01_slice_6.h5 -trainrlessd16_slices/patient062_frame01_slice_7.h5 -trainrlessd16_slices/patient062_frame01_slice_8.h5 -trainrlessd16_slices/patient062_frame01_slice_9.h5 -trainrlessd16_slices/patient062_frame09_slice_0.h5 -trainrlessd16_slices/patient062_frame09_slice_1.h5 -trainrlessd16_slices/patient062_frame09_slice_2.h5 -trainrlessd16_slices/patient062_frame09_slice_3.h5 -trainrlessd16_slices/patient062_frame09_slice_4.h5 -trainrlessd16_slices/patient062_frame09_slice_5.h5 -trainrlessd16_slices/patient062_frame09_slice_6.h5 -trainrlessd16_slices/patient062_frame09_slice_7.h5 -trainrlessd16_slices/patient062_frame09_slice_8.h5 -trainrlessd16_slices/patient062_frame09_slice_9.h5 -trainrlessd16_slices/patient063_frame16_slice_0.h5 -trainrlessd16_slices/patient063_frame16_slice_1.h5 -trainrlessd16_slices/patient063_frame16_slice_2.h5 -trainrlessd16_slices/patient063_frame16_slice_3.h5 -trainrlessd16_slices/patient063_frame16_slice_4.h5 -trainrlessd16_slices/patient063_frame16_slice_5.h5 -trainrlessd16_slices/patient063_frame16_slice_6.h5 -trainrlessd16_slices/patient063_frame16_slice_7.h5 -trainrlessd16_slices/patient064_frame01_slice_0.h5 -trainrlessd16_slices/patient064_frame01_slice_1.h5 -trainrlessd16_slices/patient064_frame01_slice_2.h5 -trainrlessd16_slices/patient064_frame01_slice_3.h5 -trainrlessd16_slices/patient064_frame01_slice_4.h5 -trainrlessd16_slices/patient064_frame01_slice_5.h5 -trainrlessd16_slices/patient064_frame01_slice_6.h5 -trainrlessd16_slices/patient064_frame01_slice_7.h5 -trainrlessd16_slices/patient064_frame01_slice_8.h5 -trainrlessd16_slices/patient064_frame01_slice_9.h5 -trainrlessd16_slices/patient066_frame01_slice_0.h5 -trainrlessd16_slices/patient066_frame01_slice_1.h5 -trainrlessd16_slices/patient066_frame01_slice_2.h5 -trainrlessd16_slices/patient066_frame01_slice_3.h5 -trainrlessd16_slices/patient066_frame01_slice_4.h5 -trainrlessd16_slices/patient066_frame01_slice_5.h5 -trainrlessd16_slices/patient066_frame01_slice_6.h5 -trainrlessd16_slices/patient066_frame01_slice_7.h5 -trainrlessd16_slices/patient066_frame01_slice_8.h5 -trainrlessd16_slices/patient067_frame01_slice_0.h5 -trainrlessd16_slices/patient067_frame01_slice_1.h5 -trainrlessd16_slices/patient067_frame01_slice_2.h5 -trainrlessd16_slices/patient067_frame01_slice_3.h5 -trainrlessd16_slices/patient067_frame01_slice_4.h5 -trainrlessd16_slices/patient067_frame01_slice_5.h5 -trainrlessd16_slices/patient067_frame01_slice_6.h5 -trainrlessd16_slices/patient067_frame01_slice_7.h5 -trainrlessd16_slices/patient067_frame01_slice_8.h5 -trainrlessd16_slices/patient067_frame01_slice_9.h5 -trainrlessd16_slices/patient067_frame10_slice_0.h5 -trainrlessd16_slices/patient067_frame10_slice_1.h5 -trainrlessd16_slices/patient067_frame10_slice_2.h5 -trainrlessd16_slices/patient067_frame10_slice_3.h5 -trainrlessd16_slices/patient067_frame10_slice_4.h5 -trainrlessd16_slices/patient067_frame10_slice_5.h5 -trainrlessd16_slices/patient067_frame10_slice_6.h5 -trainrlessd16_slices/patient067_frame10_slice_7.h5 -trainrlessd16_slices/patient067_frame10_slice_8.h5 -trainrlessd16_slices/patient067_frame10_slice_9.h5 -trainrlessd16_slices/patient068_frame01_slice_0.h5 -trainrlessd16_slices/patient068_frame01_slice_1.h5 -trainrlessd16_slices/patient068_frame01_slice_2.h5 -trainrlessd16_slices/patient068_frame01_slice_3.h5 -trainrlessd16_slices/patient068_frame01_slice_4.h5 -trainrlessd16_slices/patient068_frame01_slice_5.h5 -trainrlessd16_slices/patient068_frame01_slice_6.h5 -trainrlessd16_slices/patient069_frame01_slice_0.h5 -trainrlessd16_slices/patient069_frame01_slice_1.h5 -trainrlessd16_slices/patient069_frame01_slice_2.h5 -trainrlessd16_slices/patient069_frame01_slice_3.h5 -trainrlessd16_slices/patient069_frame01_slice_4.h5 -trainrlessd16_slices/patient069_frame01_slice_5.h5 -trainrlessd16_slices/patient069_frame01_slice_6.h5 -trainrlessd16_slices/patient070_frame01_slice_0.h5 -trainrlessd16_slices/patient070_frame01_slice_1.h5 -trainrlessd16_slices/patient070_frame01_slice_2.h5 -trainrlessd16_slices/patient070_frame01_slice_3.h5 -trainrlessd16_slices/patient070_frame01_slice_4.h5 -trainrlessd16_slices/patient070_frame01_slice_5.h5 -trainrlessd16_slices/patient071_frame09_slice_0.h5 -trainrlessd16_slices/patient071_frame09_slice_1.h5 -trainrlessd16_slices/patient071_frame09_slice_2.h5 -trainrlessd16_slices/patient071_frame09_slice_3.h5 -trainrlessd16_slices/patient071_frame09_slice_4.h5 -trainrlessd16_slices/patient071_frame09_slice_5.h5 -trainrlessd16_slices/patient071_frame09_slice_6.h5 -trainrlessd16_slices/patient071_frame09_slice_7.h5 -trainrlessd16_slices/patient071_frame09_slice_8.h5 -trainrlessd16_slices/patient071_frame09_slice_9.h5 -trainrlessd16_slices/patient072_frame01_slice_0.h5 -trainrlessd16_slices/patient072_frame01_slice_1.h5 -trainrlessd16_slices/patient072_frame01_slice_2.h5 -trainrlessd16_slices/patient072_frame01_slice_3.h5 -trainrlessd16_slices/patient072_frame01_slice_4.h5 -trainrlessd16_slices/patient072_frame01_slice_5.h5 -trainrlessd16_slices/patient072_frame01_slice_6.h5 -trainrlessd16_slices/patient072_frame01_slice_7.h5 -trainrlessd16_slices/patient073_frame10_slice_0.h5 -trainrlessd16_slices/patient073_frame10_slice_1.h5 -trainrlessd16_slices/patient073_frame10_slice_2.h5 -trainrlessd16_slices/patient073_frame10_slice_3.h5 -trainrlessd16_slices/patient073_frame10_slice_4.h5 -trainrlessd16_slices/patient073_frame10_slice_5.h5 -trainrlessd16_slices/patient073_frame10_slice_6.h5 -trainrlessd16_slices/patient074_frame12_slice_0.h5 -trainrlessd16_slices/patient074_frame12_slice_1.h5 -trainrlessd16_slices/patient074_frame12_slice_2.h5 -trainrlessd16_slices/patient074_frame12_slice_3.h5 -trainrlessd16_slices/patient074_frame12_slice_4.h5 -trainrlessd16_slices/patient074_frame12_slice_5.h5 -trainrlessd16_slices/patient074_frame12_slice_6.h5 -trainrlessd16_slices/patient074_frame12_slice_7.h5 -trainrlessd16_slices/patient075_frame01_slice_0.h5 -trainrlessd16_slices/patient075_frame01_slice_1.h5 -trainrlessd16_slices/patient075_frame01_slice_10.h5 -trainrlessd16_slices/patient075_frame01_slice_11.h5 -trainrlessd16_slices/patient075_frame01_slice_12.h5 -trainrlessd16_slices/patient075_frame01_slice_13.h5 -trainrlessd16_slices/patient075_frame01_slice_2.h5 -trainrlessd16_slices/patient075_frame01_slice_3.h5 -trainrlessd16_slices/patient075_frame01_slice_4.h5 -trainrlessd16_slices/patient075_frame01_slice_5.h5 -trainrlessd16_slices/patient075_frame01_slice_6.h5 -trainrlessd16_slices/patient075_frame01_slice_7.h5 -trainrlessd16_slices/patient075_frame01_slice_8.h5 -trainrlessd16_slices/patient075_frame01_slice_9.h5 -trainrlessd16_slices/patient076_frame12_slice_0.h5 -trainrlessd16_slices/patient076_frame12_slice_1.h5 -trainrlessd16_slices/patient076_frame12_slice_2.h5 -trainrlessd16_slices/patient076_frame12_slice_3.h5 -trainrlessd16_slices/patient076_frame12_slice_4.h5 -trainrlessd16_slices/patient076_frame12_slice_5.h5 -trainrlessd16_slices/patient076_frame12_slice_6.h5 -trainrlessd16_slices/patient076_frame12_slice_7.h5 -trainrlessd16_slices/patient077_frame09_slice_0.h5 -trainrlessd16_slices/patient077_frame09_slice_1.h5 -trainrlessd16_slices/patient077_frame09_slice_2.h5 -trainrlessd16_slices/patient077_frame09_slice_3.h5 -trainrlessd16_slices/patient077_frame09_slice_4.h5 -trainrlessd16_slices/patient077_frame09_slice_5.h5 -trainrlessd16_slices/patient077_frame09_slice_6.h5 -trainrlessd16_slices/patient077_frame09_slice_7.h5 -trainrlessd16_slices/patient078_frame01_slice_0.h5 -trainrlessd16_slices/patient078_frame01_slice_1.h5 -trainrlessd16_slices/patient078_frame01_slice_2.h5 -trainrlessd16_slices/patient078_frame01_slice_3.h5 -trainrlessd16_slices/patient078_frame01_slice_4.h5 -trainrlessd16_slices/patient078_frame01_slice_5.h5 -trainrlessd16_slices/patient078_frame01_slice_6.h5 -trainrlessd16_slices/patient078_frame01_slice_7.h5 -trainrlessd16_slices/patient078_frame09_slice_0.h5 -trainrlessd16_slices/patient078_frame09_slice_1.h5 -trainrlessd16_slices/patient078_frame09_slice_2.h5 -trainrlessd16_slices/patient078_frame09_slice_3.h5 -trainrlessd16_slices/patient078_frame09_slice_4.h5 -trainrlessd16_slices/patient078_frame09_slice_5.h5 -trainrlessd16_slices/patient078_frame09_slice_6.h5 -trainrlessd16_slices/patient078_frame09_slice_7.h5 -trainrlessd16_slices/patient079_frame01_slice_0.h5 -trainrlessd16_slices/patient079_frame01_slice_1.h5 -trainrlessd16_slices/patient079_frame01_slice_2.h5 -trainrlessd16_slices/patient079_frame01_slice_3.h5 -trainrlessd16_slices/patient079_frame01_slice_4.h5 -trainrlessd16_slices/patient079_frame01_slice_5.h5 -trainrlessd16_slices/patient079_frame01_slice_6.h5 -trainrlessd16_slices/patient079_frame01_slice_7.h5 -trainrlessd16_slices/patient079_frame01_slice_8.h5 -trainrlessd16_slices/patient079_frame11_slice_0.h5 -trainrlessd16_slices/patient079_frame11_slice_1.h5 -trainrlessd16_slices/patient079_frame11_slice_2.h5 -trainrlessd16_slices/patient079_frame11_slice_3.h5 -trainrlessd16_slices/patient079_frame11_slice_4.h5 -trainrlessd16_slices/patient079_frame11_slice_5.h5 -trainrlessd16_slices/patient079_frame11_slice_6.h5 -trainrlessd16_slices/patient079_frame11_slice_7.h5 -trainrlessd16_slices/patient079_frame11_slice_8.h5 -trainrlessd16_slices/patient080_frame01_slice_0.h5 -trainrlessd16_slices/patient080_frame01_slice_1.h5 -trainrlessd16_slices/patient080_frame01_slice_2.h5 -trainrlessd16_slices/patient080_frame01_slice_3.h5 -trainrlessd16_slices/patient080_frame01_slice_4.h5 -trainrlessd16_slices/patient080_frame01_slice_5.h5 -trainrlessd16_slices/patient080_frame10_slice_0.h5 -trainrlessd16_slices/patient080_frame10_slice_1.h5 -trainrlessd16_slices/patient080_frame10_slice_2.h5 -trainrlessd16_slices/patient080_frame10_slice_3.h5 -trainrlessd16_slices/patient080_frame10_slice_4.h5 -trainrlessd16_slices/patient080_frame10_slice_5.h5 -trainrlessd16_slices/patient081_frame07_slice_0.h5 -trainrlessd16_slices/patient081_frame07_slice_1.h5 -trainrlessd16_slices/patient081_frame07_slice_10.h5 -trainrlessd16_slices/patient081_frame07_slice_11.h5 -trainrlessd16_slices/patient081_frame07_slice_12.h5 -trainrlessd16_slices/patient081_frame07_slice_13.h5 -trainrlessd16_slices/patient081_frame07_slice_14.h5 -trainrlessd16_slices/patient081_frame07_slice_15.h5 -trainrlessd16_slices/patient081_frame07_slice_16.h5 -trainrlessd16_slices/patient081_frame07_slice_2.h5 -trainrlessd16_slices/patient081_frame07_slice_3.h5 -trainrlessd16_slices/patient081_frame07_slice_4.h5 -trainrlessd16_slices/patient081_frame07_slice_5.h5 -trainrlessd16_slices/patient081_frame07_slice_6.h5 -trainrlessd16_slices/patient081_frame07_slice_7.h5 -trainrlessd16_slices/patient081_frame07_slice_8.h5 -trainrlessd16_slices/patient081_frame07_slice_9.h5 -trainrlessd16_slices/patient082_frame01_slice_0.h5 -trainrlessd16_slices/patient082_frame01_slice_1.h5 -trainrlessd16_slices/patient082_frame01_slice_10.h5 -trainrlessd16_slices/patient082_frame01_slice_11.h5 -trainrlessd16_slices/patient082_frame01_slice_12.h5 -trainrlessd16_slices/patient082_frame01_slice_13.h5 -trainrlessd16_slices/patient082_frame01_slice_14.h5 -trainrlessd16_slices/patient082_frame01_slice_15.h5 -trainrlessd16_slices/patient082_frame01_slice_2.h5 -trainrlessd16_slices/patient082_frame01_slice_3.h5 -trainrlessd16_slices/patient082_frame01_slice_4.h5 -trainrlessd16_slices/patient082_frame01_slice_5.h5 -trainrlessd16_slices/patient082_frame01_slice_6.h5 -trainrlessd16_slices/patient082_frame01_slice_7.h5 -trainrlessd16_slices/patient082_frame01_slice_8.h5 -trainrlessd16_slices/patient082_frame01_slice_9.h5 -trainrlessd16_slices/patient082_frame07_slice_0.h5 -trainrlessd16_slices/patient082_frame07_slice_1.h5 -trainrlessd16_slices/patient082_frame07_slice_10.h5 -trainrlessd16_slices/patient082_frame07_slice_11.h5 -trainrlessd16_slices/patient082_frame07_slice_12.h5 -trainrlessd16_slices/patient082_frame07_slice_13.h5 -trainrlessd16_slices/patient082_frame07_slice_14.h5 -trainrlessd16_slices/patient082_frame07_slice_15.h5 -trainrlessd16_slices/patient082_frame07_slice_2.h5 -trainrlessd16_slices/patient082_frame07_slice_3.h5 -trainrlessd16_slices/patient082_frame07_slice_4.h5 -trainrlessd16_slices/patient082_frame07_slice_5.h5 -trainrlessd16_slices/patient082_frame07_slice_6.h5 -trainrlessd16_slices/patient082_frame07_slice_7.h5 -trainrlessd16_slices/patient082_frame07_slice_8.h5 -trainrlessd16_slices/patient082_frame07_slice_9.h5 -trainrlessd16_slices/patient083_frame01_slice_0.h5 -trainrlessd16_slices/patient083_frame01_slice_1.h5 -trainrlessd16_slices/patient083_frame01_slice_2.h5 -trainrlessd16_slices/patient083_frame01_slice_3.h5 -trainrlessd16_slices/patient083_frame01_slice_4.h5 -trainrlessd16_slices/patient083_frame01_slice_5.h5 -trainrlessd16_slices/patient084_frame01_slice_0.h5 -trainrlessd16_slices/patient084_frame01_slice_1.h5 -trainrlessd16_slices/patient084_frame01_slice_10.h5 -trainrlessd16_slices/patient084_frame01_slice_11.h5 -trainrlessd16_slices/patient084_frame01_slice_2.h5 -trainrlessd16_slices/patient084_frame01_slice_3.h5 -trainrlessd16_slices/patient084_frame01_slice_4.h5 -trainrlessd16_slices/patient084_frame01_slice_5.h5 -trainrlessd16_slices/patient084_frame01_slice_6.h5 -trainrlessd16_slices/patient084_frame01_slice_7.h5 -trainrlessd16_slices/patient084_frame01_slice_8.h5 -trainrlessd16_slices/patient084_frame01_slice_9.h5 -trainrlessd16_slices/patient084_frame10_slice_0.h5 -trainrlessd16_slices/patient084_frame10_slice_1.h5 -trainrlessd16_slices/patient084_frame10_slice_10.h5 -trainrlessd16_slices/patient084_frame10_slice_11.h5 -trainrlessd16_slices/patient084_frame10_slice_2.h5 -trainrlessd16_slices/patient084_frame10_slice_3.h5 -trainrlessd16_slices/patient084_frame10_slice_4.h5 -trainrlessd16_slices/patient084_frame10_slice_5.h5 -trainrlessd16_slices/patient084_frame10_slice_6.h5 -trainrlessd16_slices/patient084_frame10_slice_7.h5 -trainrlessd16_slices/patient084_frame10_slice_8.h5 -trainrlessd16_slices/patient084_frame10_slice_9.h5 -trainrlessd16_slices/patient085_frame01_slice_0.h5 -trainrlessd16_slices/patient085_frame01_slice_1.h5 -trainrlessd16_slices/patient085_frame01_slice_10.h5 -trainrlessd16_slices/patient085_frame01_slice_11.h5 -trainrlessd16_slices/patient085_frame01_slice_12.h5 -trainrlessd16_slices/patient085_frame01_slice_13.h5 -trainrlessd16_slices/patient085_frame01_slice_14.h5 -trainrlessd16_slices/patient085_frame01_slice_2.h5 -trainrlessd16_slices/patient085_frame01_slice_3.h5 -trainrlessd16_slices/patient085_frame01_slice_4.h5 -trainrlessd16_slices/patient085_frame01_slice_5.h5 -trainrlessd16_slices/patient085_frame01_slice_6.h5 -trainrlessd16_slices/patient085_frame01_slice_7.h5 -trainrlessd16_slices/patient085_frame01_slice_8.h5 -trainrlessd16_slices/patient085_frame01_slice_9.h5 -trainrlessd16_slices/patient087_frame01_slice_0.h5 -trainrlessd16_slices/patient087_frame01_slice_1.h5 -trainrlessd16_slices/patient087_frame01_slice_2.h5 -trainrlessd16_slices/patient087_frame01_slice_3.h5 -trainrlessd16_slices/patient087_frame01_slice_4.h5 -trainrlessd16_slices/patient087_frame01_slice_5.h5 -trainrlessd16_slices/patient087_frame01_slice_6.h5 -trainrlessd16_slices/patient087_frame01_slice_7.h5 -trainrlessd16_slices/patient088_frame01_slice_0.h5 -trainrlessd16_slices/patient088_frame01_slice_1.h5 -trainrlessd16_slices/patient088_frame01_slice_10.h5 -trainrlessd16_slices/patient088_frame01_slice_11.h5 -trainrlessd16_slices/patient088_frame01_slice_12.h5 -trainrlessd16_slices/patient088_frame01_slice_13.h5 -trainrlessd16_slices/patient088_frame01_slice_14.h5 -trainrlessd16_slices/patient088_frame01_slice_15.h5 -trainrlessd16_slices/patient088_frame01_slice_2.h5 -trainrlessd16_slices/patient088_frame01_slice_3.h5 -trainrlessd16_slices/patient088_frame01_slice_4.h5 -trainrlessd16_slices/patient088_frame01_slice_5.h5 -trainrlessd16_slices/patient088_frame01_slice_6.h5 -trainrlessd16_slices/patient088_frame01_slice_7.h5 -trainrlessd16_slices/patient088_frame01_slice_8.h5 -trainrlessd16_slices/patient088_frame01_slice_9.h5 -trainrlessd16_slices/patient088_frame12_slice_0.h5 -trainrlessd16_slices/patient088_frame12_slice_1.h5 -trainrlessd16_slices/patient088_frame12_slice_10.h5 -trainrlessd16_slices/patient088_frame12_slice_11.h5 -trainrlessd16_slices/patient088_frame12_slice_12.h5 -trainrlessd16_slices/patient088_frame12_slice_13.h5 -trainrlessd16_slices/patient088_frame12_slice_14.h5 -trainrlessd16_slices/patient088_frame12_slice_15.h5 -trainrlessd16_slices/patient088_frame12_slice_2.h5 -trainrlessd16_slices/patient088_frame12_slice_3.h5 -trainrlessd16_slices/patient088_frame12_slice_4.h5 -trainrlessd16_slices/patient088_frame12_slice_5.h5 -trainrlessd16_slices/patient088_frame12_slice_6.h5 -trainrlessd16_slices/patient088_frame12_slice_7.h5 -trainrlessd16_slices/patient088_frame12_slice_8.h5 -trainrlessd16_slices/patient088_frame12_slice_9.h5 -trainrlessd16_slices/patient090_frame11_slice_0.h5 -trainrlessd16_slices/patient090_frame11_slice_1.h5 -trainrlessd16_slices/patient090_frame11_slice_2.h5 -trainrlessd16_slices/patient090_frame11_slice_3.h5 -trainrlessd16_slices/patient090_frame11_slice_4.h5 -trainrlessd16_slices/patient090_frame11_slice_5.h5 -trainrlessd16_slices/patient090_frame11_slice_6.h5 -trainrlessd16_slices/patient091_frame01_slice_0.h5 -trainrlessd16_slices/patient091_frame01_slice_1.h5 -trainrlessd16_slices/patient091_frame01_slice_2.h5 -trainrlessd16_slices/patient091_frame01_slice_3.h5 -trainrlessd16_slices/patient091_frame01_slice_4.h5 -trainrlessd16_slices/patient091_frame01_slice_5.h5 -trainrlessd16_slices/patient091_frame01_slice_6.h5 -trainrlessd16_slices/patient091_frame01_slice_7.h5 -trainrlessd16_slices/patient091_frame09_slice_0.h5 -trainrlessd16_slices/patient091_frame09_slice_1.h5 -trainrlessd16_slices/patient091_frame09_slice_2.h5 -trainrlessd16_slices/patient091_frame09_slice_3.h5 -trainrlessd16_slices/patient091_frame09_slice_4.h5 -trainrlessd16_slices/patient091_frame09_slice_5.h5 -trainrlessd16_slices/patient091_frame09_slice_6.h5 -trainrlessd16_slices/patient091_frame09_slice_7.h5 -trainrlessd16_slices/patient092_frame01_slice_0.h5 -trainrlessd16_slices/patient092_frame01_slice_1.h5 -trainrlessd16_slices/patient092_frame01_slice_10.h5 -trainrlessd16_slices/patient092_frame01_slice_11.h5 -trainrlessd16_slices/patient092_frame01_slice_12.h5 -trainrlessd16_slices/patient092_frame01_slice_13.h5 -trainrlessd16_slices/patient092_frame01_slice_14.h5 -trainrlessd16_slices/patient092_frame01_slice_2.h5 -trainrlessd16_slices/patient092_frame01_slice_3.h5 -trainrlessd16_slices/patient092_frame01_slice_4.h5 -trainrlessd16_slices/patient092_frame01_slice_5.h5 -trainrlessd16_slices/patient092_frame01_slice_6.h5 -trainrlessd16_slices/patient092_frame01_slice_7.h5 -trainrlessd16_slices/patient092_frame01_slice_8.h5 -trainrlessd16_slices/patient092_frame01_slice_9.h5 -trainrlessd16_slices/patient092_frame06_slice_0.h5 -trainrlessd16_slices/patient092_frame06_slice_1.h5 -trainrlessd16_slices/patient092_frame06_slice_10.h5 -trainrlessd16_slices/patient092_frame06_slice_11.h5 -trainrlessd16_slices/patient092_frame06_slice_12.h5 -trainrlessd16_slices/patient092_frame06_slice_13.h5 -trainrlessd16_slices/patient092_frame06_slice_14.h5 -trainrlessd16_slices/patient092_frame06_slice_2.h5 -trainrlessd16_slices/patient092_frame06_slice_3.h5 -trainrlessd16_slices/patient092_frame06_slice_4.h5 -trainrlessd16_slices/patient092_frame06_slice_5.h5 -trainrlessd16_slices/patient092_frame06_slice_6.h5 -trainrlessd16_slices/patient092_frame06_slice_7.h5 -trainrlessd16_slices/patient092_frame06_slice_8.h5 -trainrlessd16_slices/patient092_frame06_slice_9.h5 -trainrlessd16_slices/patient093_frame14_slice_0.h5 -trainrlessd16_slices/patient093_frame14_slice_1.h5 -trainrlessd16_slices/patient093_frame14_slice_2.h5 -trainrlessd16_slices/patient093_frame14_slice_3.h5 -trainrlessd16_slices/patient093_frame14_slice_4.h5 -trainrlessd16_slices/patient093_frame14_slice_5.h5 -trainrlessd16_slices/patient093_frame14_slice_6.h5 -trainrlessd16_slices/patient093_frame14_slice_7.h5 -trainrlessd16_slices/patient093_frame14_slice_8.h5 -trainrlessd16_slices/patient093_frame14_slice_9.h5 -trainrlessd16_slices/patient095_frame01_slice_0.h5 -trainrlessd16_slices/patient095_frame01_slice_1.h5 -trainrlessd16_slices/patient095_frame01_slice_10.h5 -trainrlessd16_slices/patient095_frame01_slice_11.h5 -trainrlessd16_slices/patient095_frame01_slice_12.h5 -trainrlessd16_slices/patient095_frame01_slice_13.h5 -trainrlessd16_slices/patient095_frame01_slice_2.h5 -trainrlessd16_slices/patient095_frame01_slice_3.h5 -trainrlessd16_slices/patient095_frame01_slice_4.h5 -trainrlessd16_slices/patient095_frame01_slice_5.h5 -trainrlessd16_slices/patient095_frame01_slice_6.h5 -trainrlessd16_slices/patient095_frame01_slice_7.h5 -trainrlessd16_slices/patient095_frame01_slice_8.h5 -trainrlessd16_slices/patient095_frame01_slice_9.h5 -trainrlessd16_slices/patient095_frame12_slice_0.h5 -trainrlessd16_slices/patient095_frame12_slice_1.h5 -trainrlessd16_slices/patient095_frame12_slice_10.h5 -trainrlessd16_slices/patient095_frame12_slice_11.h5 -trainrlessd16_slices/patient095_frame12_slice_12.h5 -trainrlessd16_slices/patient095_frame12_slice_13.h5 -trainrlessd16_slices/patient095_frame12_slice_2.h5 -trainrlessd16_slices/patient095_frame12_slice_3.h5 -trainrlessd16_slices/patient095_frame12_slice_4.h5 -trainrlessd16_slices/patient095_frame12_slice_5.h5 -trainrlessd16_slices/patient095_frame12_slice_6.h5 -trainrlessd16_slices/patient095_frame12_slice_7.h5 -trainrlessd16_slices/patient095_frame12_slice_8.h5 -trainrlessd16_slices/patient095_frame12_slice_9.h5 -trainrlessd16_slices/patient096_frame08_slice_0.h5 -trainrlessd16_slices/patient096_frame08_slice_1.h5 -trainrlessd16_slices/patient096_frame08_slice_10.h5 -trainrlessd16_slices/patient096_frame08_slice_11.h5 -trainrlessd16_slices/patient096_frame08_slice_12.h5 -trainrlessd16_slices/patient096_frame08_slice_13.h5 -trainrlessd16_slices/patient096_frame08_slice_14.h5 -trainrlessd16_slices/patient096_frame08_slice_15.h5 -trainrlessd16_slices/patient096_frame08_slice_16.h5 -trainrlessd16_slices/patient096_frame08_slice_17.h5 -trainrlessd16_slices/patient096_frame08_slice_2.h5 -trainrlessd16_slices/patient096_frame08_slice_3.h5 -trainrlessd16_slices/patient096_frame08_slice_4.h5 -trainrlessd16_slices/patient096_frame08_slice_5.h5 -trainrlessd16_slices/patient096_frame08_slice_6.h5 -trainrlessd16_slices/patient096_frame08_slice_7.h5 -trainrlessd16_slices/patient096_frame08_slice_8.h5 -trainrlessd16_slices/patient096_frame08_slice_9.h5 -trainrlessd16_slices/patient097_frame01_slice_0.h5 -trainrlessd16_slices/patient097_frame01_slice_1.h5 -trainrlessd16_slices/patient097_frame01_slice_2.h5 -trainrlessd16_slices/patient097_frame01_slice_3.h5 -trainrlessd16_slices/patient097_frame01_slice_4.h5 -trainrlessd16_slices/patient097_frame01_slice_5.h5 -trainrlessd16_slices/patient097_frame01_slice_6.h5 -trainrlessd16_slices/patient097_frame01_slice_7.h5 -trainrlessd16_slices/patient097_frame11_slice_0.h5 -trainrlessd16_slices/patient097_frame11_slice_1.h5 -trainrlessd16_slices/patient097_frame11_slice_2.h5 -trainrlessd16_slices/patient097_frame11_slice_3.h5 -trainrlessd16_slices/patient097_frame11_slice_4.h5 -trainrlessd16_slices/patient097_frame11_slice_5.h5 -trainrlessd16_slices/patient097_frame11_slice_6.h5 -trainrlessd16_slices/patient097_frame11_slice_7.h5 -trainrlessd16_slices/patient099_frame01_slice_0.h5 -trainrlessd16_slices/patient099_frame01_slice_1.h5 -trainrlessd16_slices/patient099_frame01_slice_10.h5 -trainrlessd16_slices/patient099_frame01_slice_11.h5 -trainrlessd16_slices/patient099_frame01_slice_12.h5 -trainrlessd16_slices/patient099_frame01_slice_13.h5 -trainrlessd16_slices/patient099_frame01_slice_14.h5 -trainrlessd16_slices/patient099_frame01_slice_15.h5 -trainrlessd16_slices/patient099_frame01_slice_2.h5 -trainrlessd16_slices/patient099_frame01_slice_3.h5 -trainrlessd16_slices/patient099_frame01_slice_4.h5 -trainrlessd16_slices/patient099_frame01_slice_5.h5 -trainrlessd16_slices/patient099_frame01_slice_6.h5 -trainrlessd16_slices/patient099_frame01_slice_7.h5 -trainrlessd16_slices/patient099_frame01_slice_8.h5 -trainrlessd16_slices/patient099_frame01_slice_9.h5 -trainrlessd16_slices/patient099_frame09_slice_0.h5 -trainrlessd16_slices/patient099_frame09_slice_1.h5 -trainrlessd16_slices/patient099_frame09_slice_10.h5 -trainrlessd16_slices/patient099_frame09_slice_11.h5 -trainrlessd16_slices/patient099_frame09_slice_12.h5 -trainrlessd16_slices/patient099_frame09_slice_13.h5 -trainrlessd16_slices/patient099_frame09_slice_14.h5 -trainrlessd16_slices/patient099_frame09_slice_15.h5 -trainrlessd16_slices/patient099_frame09_slice_2.h5 -trainrlessd16_slices/patient099_frame09_slice_3.h5 -trainrlessd16_slices/patient099_frame09_slice_4.h5 -trainrlessd16_slices/patient099_frame09_slice_5.h5 -trainrlessd16_slices/patient099_frame09_slice_6.h5 -trainrlessd16_slices/patient099_frame09_slice_7.h5 -trainrlessd16_slices/patient099_frame09_slice_8.h5 -trainrlessd16_slices/patient099_frame09_slice_9.h5 -trainrlessd16_slices/patient100_frame01_slice_0.h5 -trainrlessd16_slices/patient100_frame01_slice_1.h5 -trainrlessd16_slices/patient100_frame01_slice_2.h5 -trainrlessd16_slices/patient100_frame01_slice_3.h5 -trainrlessd16_slices/patient100_frame01_slice_4.h5 -trainrlessd16_slices/patient100_frame01_slice_5.h5 -trainrlessd16_slices/patient100_frame01_slice_6.h5 -trainrlessd16_slices/patient100_frame01_slice_7.h5 -trainrlessd16_slices/patient100_frame13_slice_0.h5 -trainrlessd16_slices/patient100_frame13_slice_1.h5 -trainrlessd16_slices/patient100_frame13_slice_2.h5 -trainrlessd16_slices/patient100_frame13_slice_3.h5 -trainrlessd16_slices/patient100_frame13_slice_4.h5 -trainrlessd16_slices/patient100_frame13_slice_5.h5 -trainrlessd16_slices/patient100_frame13_slice_6.h5 -trainrlessd16_slices/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/trainrlessd4.txt b/data/ACDC2017/ACDC_for2D/trainrlessd4.txt deleted file mode 100644 index b97de7a..0000000 --- a/data/ACDC2017/ACDC_for2D/trainrlessd4.txt +++ /dev/null @@ -1,1356 +0,0 @@ -trainrlessd4_slices/patient001_frame01_slice_0.h5 -trainrlessd4_slices/patient001_frame01_slice_1.h5 -trainrlessd4_slices/patient001_frame01_slice_2.h5 -trainrlessd4_slices/patient001_frame01_slice_3.h5 -trainrlessd4_slices/patient001_frame01_slice_4.h5 -trainrlessd4_slices/patient001_frame01_slice_5.h5 -trainrlessd4_slices/patient001_frame01_slice_6.h5 -trainrlessd4_slices/patient001_frame01_slice_7.h5 -trainrlessd4_slices/patient001_frame01_slice_8.h5 -trainrlessd4_slices/patient001_frame01_slice_9.h5 -trainrlessd4_slices/patient001_frame12_slice_0.h5 -trainrlessd4_slices/patient001_frame12_slice_1.h5 -trainrlessd4_slices/patient001_frame12_slice_2.h5 -trainrlessd4_slices/patient001_frame12_slice_3.h5 -trainrlessd4_slices/patient001_frame12_slice_4.h5 -trainrlessd4_slices/patient001_frame12_slice_5.h5 -trainrlessd4_slices/patient001_frame12_slice_6.h5 -trainrlessd4_slices/patient001_frame12_slice_7.h5 -trainrlessd4_slices/patient001_frame12_slice_8.h5 -trainrlessd4_slices/patient001_frame12_slice_9.h5 -trainrlessd4_slices/patient002_frame01_slice_0.h5 -trainrlessd4_slices/patient002_frame01_slice_1.h5 -trainrlessd4_slices/patient002_frame01_slice_2.h5 -trainrlessd4_slices/patient002_frame01_slice_3.h5 -trainrlessd4_slices/patient002_frame01_slice_4.h5 -trainrlessd4_slices/patient002_frame01_slice_5.h5 -trainrlessd4_slices/patient002_frame01_slice_6.h5 -trainrlessd4_slices/patient002_frame01_slice_7.h5 -trainrlessd4_slices/patient002_frame01_slice_8.h5 -trainrlessd4_slices/patient002_frame01_slice_9.h5 -trainrlessd4_slices/patient002_frame12_slice_0.h5 -trainrlessd4_slices/patient002_frame12_slice_1.h5 -trainrlessd4_slices/patient002_frame12_slice_2.h5 -trainrlessd4_slices/patient002_frame12_slice_3.h5 -trainrlessd4_slices/patient002_frame12_slice_4.h5 -trainrlessd4_slices/patient002_frame12_slice_5.h5 -trainrlessd4_slices/patient002_frame12_slice_6.h5 -trainrlessd4_slices/patient002_frame12_slice_7.h5 -trainrlessd4_slices/patient002_frame12_slice_8.h5 -trainrlessd4_slices/patient002_frame12_slice_9.h5 -trainrlessd4_slices/patient003_frame01_slice_0.h5 -trainrlessd4_slices/patient003_frame01_slice_1.h5 -trainrlessd4_slices/patient003_frame01_slice_2.h5 -trainrlessd4_slices/patient003_frame01_slice_3.h5 -trainrlessd4_slices/patient003_frame01_slice_4.h5 -trainrlessd4_slices/patient003_frame01_slice_5.h5 -trainrlessd4_slices/patient003_frame01_slice_6.h5 -trainrlessd4_slices/patient003_frame01_slice_7.h5 -trainrlessd4_slices/patient003_frame01_slice_8.h5 -trainrlessd4_slices/patient003_frame01_slice_9.h5 -trainrlessd4_slices/patient003_frame15_slice_0.h5 -trainrlessd4_slices/patient003_frame15_slice_1.h5 -trainrlessd4_slices/patient003_frame15_slice_2.h5 -trainrlessd4_slices/patient003_frame15_slice_3.h5 -trainrlessd4_slices/patient003_frame15_slice_4.h5 -trainrlessd4_slices/patient003_frame15_slice_5.h5 -trainrlessd4_slices/patient003_frame15_slice_6.h5 -trainrlessd4_slices/patient003_frame15_slice_7.h5 -trainrlessd4_slices/patient003_frame15_slice_8.h5 -trainrlessd4_slices/patient003_frame15_slice_9.h5 -trainrlessd4_slices/patient004_frame01_slice_0.h5 -trainrlessd4_slices/patient004_frame01_slice_1.h5 -trainrlessd4_slices/patient004_frame01_slice_2.h5 -trainrlessd4_slices/patient004_frame01_slice_3.h5 -trainrlessd4_slices/patient004_frame01_slice_4.h5 -trainrlessd4_slices/patient004_frame01_slice_5.h5 -trainrlessd4_slices/patient004_frame01_slice_6.h5 -trainrlessd4_slices/patient004_frame01_slice_7.h5 -trainrlessd4_slices/patient004_frame01_slice_8.h5 -trainrlessd4_slices/patient004_frame01_slice_9.h5 -trainrlessd4_slices/patient005_frame01_slice_0.h5 -trainrlessd4_slices/patient005_frame01_slice_1.h5 -trainrlessd4_slices/patient005_frame01_slice_2.h5 -trainrlessd4_slices/patient005_frame01_slice_3.h5 -trainrlessd4_slices/patient005_frame01_slice_4.h5 -trainrlessd4_slices/patient005_frame01_slice_5.h5 -trainrlessd4_slices/patient005_frame01_slice_6.h5 -trainrlessd4_slices/patient005_frame01_slice_7.h5 -trainrlessd4_slices/patient005_frame01_slice_8.h5 -trainrlessd4_slices/patient005_frame01_slice_9.h5 -trainrlessd4_slices/patient005_frame13_slice_0.h5 -trainrlessd4_slices/patient005_frame13_slice_1.h5 -trainrlessd4_slices/patient005_frame13_slice_2.h5 -trainrlessd4_slices/patient005_frame13_slice_3.h5 -trainrlessd4_slices/patient005_frame13_slice_4.h5 -trainrlessd4_slices/patient005_frame13_slice_5.h5 -trainrlessd4_slices/patient005_frame13_slice_6.h5 -trainrlessd4_slices/patient005_frame13_slice_7.h5 -trainrlessd4_slices/patient005_frame13_slice_8.h5 -trainrlessd4_slices/patient005_frame13_slice_9.h5 -trainrlessd4_slices/patient006_frame16_slice_0.h5 -trainrlessd4_slices/patient006_frame16_slice_1.h5 -trainrlessd4_slices/patient006_frame16_slice_10.h5 -trainrlessd4_slices/patient006_frame16_slice_2.h5 -trainrlessd4_slices/patient006_frame16_slice_3.h5 -trainrlessd4_slices/patient006_frame16_slice_4.h5 -trainrlessd4_slices/patient006_frame16_slice_5.h5 -trainrlessd4_slices/patient006_frame16_slice_6.h5 -trainrlessd4_slices/patient006_frame16_slice_7.h5 -trainrlessd4_slices/patient006_frame16_slice_8.h5 -trainrlessd4_slices/patient006_frame16_slice_9.h5 -trainrlessd4_slices/patient007_frame01_slice_0.h5 -trainrlessd4_slices/patient007_frame01_slice_1.h5 -trainrlessd4_slices/patient007_frame01_slice_2.h5 -trainrlessd4_slices/patient007_frame01_slice_3.h5 -trainrlessd4_slices/patient007_frame01_slice_4.h5 -trainrlessd4_slices/patient007_frame01_slice_5.h5 -trainrlessd4_slices/patient007_frame01_slice_6.h5 -trainrlessd4_slices/patient007_frame01_slice_7.h5 -trainrlessd4_slices/patient007_frame01_slice_8.h5 -trainrlessd4_slices/patient007_frame01_slice_9.h5 -trainrlessd4_slices/patient007_frame07_slice_0.h5 -trainrlessd4_slices/patient007_frame07_slice_1.h5 -trainrlessd4_slices/patient007_frame07_slice_2.h5 -trainrlessd4_slices/patient007_frame07_slice_3.h5 -trainrlessd4_slices/patient007_frame07_slice_4.h5 -trainrlessd4_slices/patient007_frame07_slice_5.h5 -trainrlessd4_slices/patient007_frame07_slice_6.h5 -trainrlessd4_slices/patient007_frame07_slice_7.h5 -trainrlessd4_slices/patient007_frame07_slice_8.h5 -trainrlessd4_slices/patient007_frame07_slice_9.h5 -trainrlessd4_slices/patient008_frame13_slice_0.h5 -trainrlessd4_slices/patient008_frame13_slice_1.h5 -trainrlessd4_slices/patient008_frame13_slice_2.h5 -trainrlessd4_slices/patient008_frame13_slice_3.h5 -trainrlessd4_slices/patient008_frame13_slice_4.h5 -trainrlessd4_slices/patient008_frame13_slice_5.h5 -trainrlessd4_slices/patient008_frame13_slice_6.h5 -trainrlessd4_slices/patient008_frame13_slice_7.h5 -trainrlessd4_slices/patient008_frame13_slice_8.h5 -trainrlessd4_slices/patient008_frame13_slice_9.h5 -trainrlessd4_slices/patient009_frame01_slice_0.h5 -trainrlessd4_slices/patient009_frame01_slice_1.h5 -trainrlessd4_slices/patient009_frame01_slice_2.h5 -trainrlessd4_slices/patient009_frame01_slice_3.h5 -trainrlessd4_slices/patient009_frame01_slice_4.h5 -trainrlessd4_slices/patient009_frame01_slice_5.h5 -trainrlessd4_slices/patient009_frame01_slice_6.h5 -trainrlessd4_slices/patient009_frame01_slice_7.h5 -trainrlessd4_slices/patient009_frame01_slice_8.h5 -trainrlessd4_slices/patient009_frame01_slice_9.h5 -trainrlessd4_slices/patient010_frame01_slice_0.h5 -trainrlessd4_slices/patient010_frame01_slice_1.h5 -trainrlessd4_slices/patient010_frame01_slice_2.h5 -trainrlessd4_slices/patient010_frame01_slice_3.h5 -trainrlessd4_slices/patient010_frame01_slice_4.h5 -trainrlessd4_slices/patient010_frame01_slice_5.h5 -trainrlessd4_slices/patient010_frame01_slice_6.h5 -trainrlessd4_slices/patient010_frame01_slice_7.h5 -trainrlessd4_slices/patient010_frame01_slice_8.h5 -trainrlessd4_slices/patient010_frame01_slice_9.h5 -trainrlessd4_slices/patient010_frame13_slice_0.h5 -trainrlessd4_slices/patient010_frame13_slice_1.h5 -trainrlessd4_slices/patient010_frame13_slice_2.h5 -trainrlessd4_slices/patient010_frame13_slice_3.h5 -trainrlessd4_slices/patient010_frame13_slice_4.h5 -trainrlessd4_slices/patient010_frame13_slice_5.h5 -trainrlessd4_slices/patient010_frame13_slice_6.h5 -trainrlessd4_slices/patient010_frame13_slice_7.h5 -trainrlessd4_slices/patient010_frame13_slice_8.h5 -trainrlessd4_slices/patient010_frame13_slice_9.h5 -trainrlessd4_slices/patient011_frame01_slice_0.h5 -trainrlessd4_slices/patient011_frame01_slice_1.h5 -trainrlessd4_slices/patient011_frame01_slice_2.h5 -trainrlessd4_slices/patient011_frame01_slice_3.h5 -trainrlessd4_slices/patient011_frame01_slice_4.h5 -trainrlessd4_slices/patient011_frame01_slice_5.h5 -trainrlessd4_slices/patient011_frame01_slice_6.h5 -trainrlessd4_slices/patient011_frame01_slice_7.h5 -trainrlessd4_slices/patient011_frame01_slice_8.h5 -trainrlessd4_slices/patient011_frame08_slice_0.h5 -trainrlessd4_slices/patient011_frame08_slice_1.h5 -trainrlessd4_slices/patient011_frame08_slice_2.h5 -trainrlessd4_slices/patient011_frame08_slice_3.h5 -trainrlessd4_slices/patient011_frame08_slice_4.h5 -trainrlessd4_slices/patient011_frame08_slice_5.h5 -trainrlessd4_slices/patient011_frame08_slice_6.h5 -trainrlessd4_slices/patient011_frame08_slice_7.h5 -trainrlessd4_slices/patient011_frame08_slice_8.h5 -trainrlessd4_slices/patient012_frame01_slice_0.h5 -trainrlessd4_slices/patient012_frame01_slice_1.h5 -trainrlessd4_slices/patient012_frame01_slice_2.h5 -trainrlessd4_slices/patient012_frame01_slice_3.h5 -trainrlessd4_slices/patient012_frame01_slice_4.h5 -trainrlessd4_slices/patient012_frame01_slice_5.h5 -trainrlessd4_slices/patient012_frame01_slice_6.h5 -trainrlessd4_slices/patient012_frame01_slice_7.h5 -trainrlessd4_slices/patient012_frame01_slice_8.h5 -trainrlessd4_slices/patient012_frame01_slice_9.h5 -trainrlessd4_slices/patient013_frame01_slice_0.h5 -trainrlessd4_slices/patient013_frame01_slice_1.h5 -trainrlessd4_slices/patient013_frame01_slice_2.h5 -trainrlessd4_slices/patient013_frame01_slice_3.h5 -trainrlessd4_slices/patient013_frame01_slice_4.h5 -trainrlessd4_slices/patient013_frame01_slice_5.h5 -trainrlessd4_slices/patient013_frame01_slice_6.h5 -trainrlessd4_slices/patient013_frame01_slice_7.h5 -trainrlessd4_slices/patient013_frame01_slice_8.h5 -trainrlessd4_slices/patient013_frame01_slice_9.h5 -trainrlessd4_slices/patient014_frame13_slice_0.h5 -trainrlessd4_slices/patient014_frame13_slice_1.h5 -trainrlessd4_slices/patient014_frame13_slice_2.h5 -trainrlessd4_slices/patient014_frame13_slice_3.h5 -trainrlessd4_slices/patient014_frame13_slice_4.h5 -trainrlessd4_slices/patient014_frame13_slice_5.h5 -trainrlessd4_slices/patient014_frame13_slice_6.h5 -trainrlessd4_slices/patient014_frame13_slice_7.h5 -trainrlessd4_slices/patient014_frame13_slice_8.h5 -trainrlessd4_slices/patient014_frame13_slice_9.h5 -trainrlessd4_slices/patient015_frame10_slice_0.h5 -trainrlessd4_slices/patient015_frame10_slice_1.h5 -trainrlessd4_slices/patient015_frame10_slice_2.h5 -trainrlessd4_slices/patient015_frame10_slice_3.h5 -trainrlessd4_slices/patient015_frame10_slice_4.h5 -trainrlessd4_slices/patient015_frame10_slice_5.h5 -trainrlessd4_slices/patient015_frame10_slice_6.h5 -trainrlessd4_slices/patient015_frame10_slice_7.h5 -trainrlessd4_slices/patient015_frame10_slice_8.h5 -trainrlessd4_slices/patient016_frame12_slice_0.h5 -trainrlessd4_slices/patient016_frame12_slice_1.h5 -trainrlessd4_slices/patient016_frame12_slice_2.h5 -trainrlessd4_slices/patient016_frame12_slice_3.h5 -trainrlessd4_slices/patient016_frame12_slice_4.h5 -trainrlessd4_slices/patient016_frame12_slice_5.h5 -trainrlessd4_slices/patient016_frame12_slice_6.h5 -trainrlessd4_slices/patient016_frame12_slice_7.h5 -trainrlessd4_slices/patient016_frame12_slice_8.h5 -trainrlessd4_slices/patient016_frame12_slice_9.h5 -trainrlessd4_slices/patient017_frame01_slice_0.h5 -trainrlessd4_slices/patient017_frame01_slice_1.h5 -trainrlessd4_slices/patient017_frame01_slice_2.h5 -trainrlessd4_slices/patient017_frame01_slice_3.h5 -trainrlessd4_slices/patient017_frame01_slice_4.h5 -trainrlessd4_slices/patient017_frame01_slice_5.h5 -trainrlessd4_slices/patient017_frame01_slice_6.h5 -trainrlessd4_slices/patient017_frame01_slice_7.h5 -trainrlessd4_slices/patient017_frame01_slice_8.h5 -trainrlessd4_slices/patient017_frame09_slice_0.h5 -trainrlessd4_slices/patient017_frame09_slice_1.h5 -trainrlessd4_slices/patient017_frame09_slice_2.h5 -trainrlessd4_slices/patient017_frame09_slice_3.h5 -trainrlessd4_slices/patient017_frame09_slice_4.h5 -trainrlessd4_slices/patient017_frame09_slice_5.h5 -trainrlessd4_slices/patient017_frame09_slice_6.h5 -trainrlessd4_slices/patient017_frame09_slice_7.h5 -trainrlessd4_slices/patient017_frame09_slice_8.h5 -trainrlessd4_slices/patient018_frame01_slice_0.h5 -trainrlessd4_slices/patient018_frame01_slice_1.h5 -trainrlessd4_slices/patient018_frame01_slice_2.h5 -trainrlessd4_slices/patient018_frame01_slice_3.h5 -trainrlessd4_slices/patient018_frame01_slice_4.h5 -trainrlessd4_slices/patient018_frame01_slice_5.h5 -trainrlessd4_slices/patient018_frame01_slice_6.h5 -trainrlessd4_slices/patient018_frame01_slice_7.h5 -trainrlessd4_slices/patient018_frame10_slice_0.h5 -trainrlessd4_slices/patient018_frame10_slice_1.h5 -trainrlessd4_slices/patient018_frame10_slice_2.h5 -trainrlessd4_slices/patient018_frame10_slice_3.h5 -trainrlessd4_slices/patient018_frame10_slice_4.h5 -trainrlessd4_slices/patient018_frame10_slice_5.h5 -trainrlessd4_slices/patient018_frame10_slice_6.h5 -trainrlessd4_slices/patient018_frame10_slice_7.h5 -trainrlessd4_slices/patient019_frame11_slice_0.h5 -trainrlessd4_slices/patient019_frame11_slice_1.h5 -trainrlessd4_slices/patient019_frame11_slice_10.h5 -trainrlessd4_slices/patient019_frame11_slice_2.h5 -trainrlessd4_slices/patient019_frame11_slice_3.h5 -trainrlessd4_slices/patient019_frame11_slice_4.h5 -trainrlessd4_slices/patient019_frame11_slice_5.h5 -trainrlessd4_slices/patient019_frame11_slice_6.h5 -trainrlessd4_slices/patient019_frame11_slice_7.h5 -trainrlessd4_slices/patient019_frame11_slice_8.h5 -trainrlessd4_slices/patient019_frame11_slice_9.h5 -trainrlessd4_slices/patient020_frame01_slice_0.h5 -trainrlessd4_slices/patient020_frame01_slice_1.h5 -trainrlessd4_slices/patient020_frame01_slice_2.h5 -trainrlessd4_slices/patient020_frame01_slice_3.h5 -trainrlessd4_slices/patient020_frame01_slice_4.h5 -trainrlessd4_slices/patient020_frame01_slice_5.h5 -trainrlessd4_slices/patient020_frame01_slice_6.h5 -trainrlessd4_slices/patient020_frame01_slice_7.h5 -trainrlessd4_slices/patient021_frame01_slice_0.h5 -trainrlessd4_slices/patient021_frame01_slice_1.h5 -trainrlessd4_slices/patient021_frame01_slice_2.h5 -trainrlessd4_slices/patient021_frame01_slice_3.h5 -trainrlessd4_slices/patient021_frame01_slice_4.h5 -trainrlessd4_slices/patient021_frame01_slice_5.h5 -trainrlessd4_slices/patient021_frame01_slice_6.h5 -trainrlessd4_slices/patient021_frame01_slice_7.h5 -trainrlessd4_slices/patient021_frame01_slice_8.h5 -trainrlessd4_slices/patient021_frame01_slice_9.h5 -trainrlessd4_slices/patient021_frame13_slice_0.h5 -trainrlessd4_slices/patient021_frame13_slice_1.h5 -trainrlessd4_slices/patient021_frame13_slice_2.h5 -trainrlessd4_slices/patient021_frame13_slice_3.h5 -trainrlessd4_slices/patient021_frame13_slice_4.h5 -trainrlessd4_slices/patient021_frame13_slice_5.h5 -trainrlessd4_slices/patient021_frame13_slice_6.h5 -trainrlessd4_slices/patient021_frame13_slice_7.h5 -trainrlessd4_slices/patient021_frame13_slice_8.h5 -trainrlessd4_slices/patient021_frame13_slice_9.h5 -trainrlessd4_slices/patient022_frame01_slice_0.h5 -trainrlessd4_slices/patient022_frame01_slice_1.h5 -trainrlessd4_slices/patient022_frame01_slice_2.h5 -trainrlessd4_slices/patient022_frame01_slice_3.h5 -trainrlessd4_slices/patient022_frame01_slice_4.h5 -trainrlessd4_slices/patient022_frame01_slice_5.h5 -trainrlessd4_slices/patient022_frame01_slice_6.h5 -trainrlessd4_slices/patient022_frame11_slice_0.h5 -trainrlessd4_slices/patient022_frame11_slice_1.h5 -trainrlessd4_slices/patient022_frame11_slice_2.h5 -trainrlessd4_slices/patient022_frame11_slice_3.h5 -trainrlessd4_slices/patient022_frame11_slice_4.h5 -trainrlessd4_slices/patient022_frame11_slice_5.h5 -trainrlessd4_slices/patient022_frame11_slice_6.h5 -trainrlessd4_slices/patient023_frame01_slice_0.h5 -trainrlessd4_slices/patient023_frame01_slice_1.h5 -trainrlessd4_slices/patient023_frame01_slice_2.h5 -trainrlessd4_slices/patient023_frame01_slice_3.h5 -trainrlessd4_slices/patient023_frame01_slice_4.h5 -trainrlessd4_slices/patient023_frame01_slice_5.h5 -trainrlessd4_slices/patient023_frame01_slice_6.h5 -trainrlessd4_slices/patient023_frame01_slice_7.h5 -trainrlessd4_slices/patient023_frame01_slice_8.h5 -trainrlessd4_slices/patient024_frame09_slice_0.h5 -trainrlessd4_slices/patient024_frame09_slice_1.h5 -trainrlessd4_slices/patient024_frame09_slice_2.h5 -trainrlessd4_slices/patient024_frame09_slice_3.h5 -trainrlessd4_slices/patient024_frame09_slice_4.h5 -trainrlessd4_slices/patient024_frame09_slice_5.h5 -trainrlessd4_slices/patient024_frame09_slice_6.h5 -trainrlessd4_slices/patient024_frame09_slice_7.h5 -trainrlessd4_slices/patient025_frame01_slice_0.h5 -trainrlessd4_slices/patient025_frame01_slice_1.h5 -trainrlessd4_slices/patient025_frame01_slice_2.h5 -trainrlessd4_slices/patient025_frame01_slice_3.h5 -trainrlessd4_slices/patient025_frame01_slice_4.h5 -trainrlessd4_slices/patient025_frame01_slice_5.h5 -trainrlessd4_slices/patient025_frame01_slice_6.h5 -trainrlessd4_slices/patient025_frame01_slice_7.h5 -trainrlessd4_slices/patient025_frame01_slice_8.h5 -trainrlessd4_slices/patient026_frame01_slice_0.h5 -trainrlessd4_slices/patient026_frame01_slice_1.h5 -trainrlessd4_slices/patient026_frame01_slice_2.h5 -trainrlessd4_slices/patient026_frame01_slice_3.h5 -trainrlessd4_slices/patient026_frame01_slice_4.h5 -trainrlessd4_slices/patient026_frame01_slice_5.h5 -trainrlessd4_slices/patient026_frame01_slice_6.h5 -trainrlessd4_slices/patient026_frame01_slice_7.h5 -trainrlessd4_slices/patient026_frame01_slice_8.h5 -trainrlessd4_slices/patient026_frame01_slice_9.h5 -trainrlessd4_slices/patient026_frame12_slice_0.h5 -trainrlessd4_slices/patient026_frame12_slice_1.h5 -trainrlessd4_slices/patient026_frame12_slice_2.h5 -trainrlessd4_slices/patient026_frame12_slice_3.h5 -trainrlessd4_slices/patient026_frame12_slice_4.h5 -trainrlessd4_slices/patient026_frame12_slice_5.h5 -trainrlessd4_slices/patient026_frame12_slice_6.h5 -trainrlessd4_slices/patient026_frame12_slice_7.h5 -trainrlessd4_slices/patient026_frame12_slice_8.h5 -trainrlessd4_slices/patient026_frame12_slice_9.h5 -trainrlessd4_slices/patient027_frame01_slice_0.h5 -trainrlessd4_slices/patient027_frame01_slice_1.h5 -trainrlessd4_slices/patient027_frame01_slice_2.h5 -trainrlessd4_slices/patient027_frame01_slice_3.h5 -trainrlessd4_slices/patient027_frame01_slice_4.h5 -trainrlessd4_slices/patient027_frame01_slice_5.h5 -trainrlessd4_slices/patient027_frame01_slice_6.h5 -trainrlessd4_slices/patient027_frame01_slice_7.h5 -trainrlessd4_slices/patient027_frame01_slice_8.h5 -trainrlessd4_slices/patient027_frame01_slice_9.h5 -trainrlessd4_slices/patient027_frame11_slice_0.h5 -trainrlessd4_slices/patient027_frame11_slice_1.h5 -trainrlessd4_slices/patient027_frame11_slice_2.h5 -trainrlessd4_slices/patient027_frame11_slice_3.h5 -trainrlessd4_slices/patient027_frame11_slice_4.h5 -trainrlessd4_slices/patient027_frame11_slice_5.h5 -trainrlessd4_slices/patient027_frame11_slice_6.h5 -trainrlessd4_slices/patient027_frame11_slice_7.h5 -trainrlessd4_slices/patient027_frame11_slice_8.h5 -trainrlessd4_slices/patient027_frame11_slice_9.h5 -trainrlessd4_slices/patient028_frame01_slice_0.h5 -trainrlessd4_slices/patient028_frame01_slice_1.h5 -trainrlessd4_slices/patient028_frame01_slice_2.h5 -trainrlessd4_slices/patient028_frame01_slice_3.h5 -trainrlessd4_slices/patient028_frame01_slice_4.h5 -trainrlessd4_slices/patient028_frame01_slice_5.h5 -trainrlessd4_slices/patient028_frame01_slice_6.h5 -trainrlessd4_slices/patient028_frame01_slice_7.h5 -trainrlessd4_slices/patient028_frame01_slice_8.h5 -trainrlessd4_slices/patient028_frame01_slice_9.h5 -trainrlessd4_slices/patient028_frame09_slice_0.h5 -trainrlessd4_slices/patient028_frame09_slice_1.h5 -trainrlessd4_slices/patient028_frame09_slice_2.h5 -trainrlessd4_slices/patient028_frame09_slice_3.h5 -trainrlessd4_slices/patient028_frame09_slice_4.h5 -trainrlessd4_slices/patient028_frame09_slice_5.h5 -trainrlessd4_slices/patient028_frame09_slice_6.h5 -trainrlessd4_slices/patient028_frame09_slice_7.h5 -trainrlessd4_slices/patient028_frame09_slice_8.h5 -trainrlessd4_slices/patient028_frame09_slice_9.h5 -trainrlessd4_slices/patient029_frame12_slice_0.h5 -trainrlessd4_slices/patient029_frame12_slice_1.h5 -trainrlessd4_slices/patient029_frame12_slice_10.h5 -trainrlessd4_slices/patient029_frame12_slice_2.h5 -trainrlessd4_slices/patient029_frame12_slice_3.h5 -trainrlessd4_slices/patient029_frame12_slice_4.h5 -trainrlessd4_slices/patient029_frame12_slice_5.h5 -trainrlessd4_slices/patient029_frame12_slice_6.h5 -trainrlessd4_slices/patient029_frame12_slice_7.h5 -trainrlessd4_slices/patient029_frame12_slice_8.h5 -trainrlessd4_slices/patient029_frame12_slice_9.h5 -trainrlessd4_slices/patient030_frame12_slice_0.h5 -trainrlessd4_slices/patient030_frame12_slice_1.h5 -trainrlessd4_slices/patient030_frame12_slice_2.h5 -trainrlessd4_slices/patient030_frame12_slice_3.h5 -trainrlessd4_slices/patient030_frame12_slice_4.h5 -trainrlessd4_slices/patient030_frame12_slice_5.h5 -trainrlessd4_slices/patient030_frame12_slice_6.h5 -trainrlessd4_slices/patient030_frame12_slice_7.h5 -trainrlessd4_slices/patient030_frame12_slice_8.h5 -trainrlessd4_slices/patient030_frame12_slice_9.h5 -trainrlessd4_slices/patient031_frame01_slice_0.h5 -trainrlessd4_slices/patient031_frame01_slice_1.h5 -trainrlessd4_slices/patient031_frame01_slice_2.h5 -trainrlessd4_slices/patient031_frame01_slice_3.h5 -trainrlessd4_slices/patient031_frame01_slice_4.h5 -trainrlessd4_slices/patient031_frame01_slice_5.h5 -trainrlessd4_slices/patient031_frame01_slice_6.h5 -trainrlessd4_slices/patient031_frame01_slice_7.h5 -trainrlessd4_slices/patient031_frame01_slice_8.h5 -trainrlessd4_slices/patient031_frame01_slice_9.h5 -trainrlessd4_slices/patient032_frame12_slice_0.h5 -trainrlessd4_slices/patient032_frame12_slice_1.h5 -trainrlessd4_slices/patient032_frame12_slice_2.h5 -trainrlessd4_slices/patient032_frame12_slice_3.h5 -trainrlessd4_slices/patient032_frame12_slice_4.h5 -trainrlessd4_slices/patient032_frame12_slice_5.h5 -trainrlessd4_slices/patient032_frame12_slice_6.h5 -trainrlessd4_slices/patient032_frame12_slice_7.h5 -trainrlessd4_slices/patient032_frame12_slice_8.h5 -trainrlessd4_slices/patient032_frame12_slice_9.h5 -trainrlessd4_slices/patient033_frame01_slice_0.h5 -trainrlessd4_slices/patient033_frame01_slice_1.h5 -trainrlessd4_slices/patient033_frame01_slice_2.h5 -trainrlessd4_slices/patient033_frame01_slice_3.h5 -trainrlessd4_slices/patient033_frame01_slice_4.h5 -trainrlessd4_slices/patient033_frame01_slice_5.h5 -trainrlessd4_slices/patient033_frame01_slice_6.h5 -trainrlessd4_slices/patient033_frame01_slice_7.h5 -trainrlessd4_slices/patient033_frame01_slice_8.h5 -trainrlessd4_slices/patient033_frame01_slice_9.h5 -trainrlessd4_slices/patient033_frame14_slice_0.h5 -trainrlessd4_slices/patient033_frame14_slice_1.h5 -trainrlessd4_slices/patient033_frame14_slice_2.h5 -trainrlessd4_slices/patient033_frame14_slice_3.h5 -trainrlessd4_slices/patient033_frame14_slice_4.h5 -trainrlessd4_slices/patient033_frame14_slice_5.h5 -trainrlessd4_slices/patient033_frame14_slice_6.h5 -trainrlessd4_slices/patient033_frame14_slice_7.h5 -trainrlessd4_slices/patient033_frame14_slice_8.h5 -trainrlessd4_slices/patient033_frame14_slice_9.h5 -trainrlessd4_slices/patient034_frame01_slice_0.h5 -trainrlessd4_slices/patient034_frame01_slice_1.h5 -trainrlessd4_slices/patient034_frame01_slice_2.h5 -trainrlessd4_slices/patient034_frame01_slice_3.h5 -trainrlessd4_slices/patient034_frame01_slice_4.h5 -trainrlessd4_slices/patient034_frame01_slice_5.h5 -trainrlessd4_slices/patient034_frame01_slice_6.h5 -trainrlessd4_slices/patient034_frame01_slice_7.h5 -trainrlessd4_slices/patient034_frame01_slice_8.h5 -trainrlessd4_slices/patient034_frame01_slice_9.h5 -trainrlessd4_slices/patient035_frame01_slice_0.h5 -trainrlessd4_slices/patient035_frame01_slice_1.h5 -trainrlessd4_slices/patient035_frame01_slice_10.h5 -trainrlessd4_slices/patient035_frame01_slice_11.h5 -trainrlessd4_slices/patient035_frame01_slice_12.h5 -trainrlessd4_slices/patient035_frame01_slice_2.h5 -trainrlessd4_slices/patient035_frame01_slice_3.h5 -trainrlessd4_slices/patient035_frame01_slice_4.h5 -trainrlessd4_slices/patient035_frame01_slice_5.h5 -trainrlessd4_slices/patient035_frame01_slice_6.h5 -trainrlessd4_slices/patient035_frame01_slice_7.h5 -trainrlessd4_slices/patient035_frame01_slice_8.h5 -trainrlessd4_slices/patient035_frame01_slice_9.h5 -trainrlessd4_slices/patient035_frame11_slice_0.h5 -trainrlessd4_slices/patient035_frame11_slice_1.h5 -trainrlessd4_slices/patient035_frame11_slice_10.h5 -trainrlessd4_slices/patient035_frame11_slice_11.h5 -trainrlessd4_slices/patient035_frame11_slice_12.h5 -trainrlessd4_slices/patient035_frame11_slice_2.h5 -trainrlessd4_slices/patient035_frame11_slice_3.h5 -trainrlessd4_slices/patient035_frame11_slice_4.h5 -trainrlessd4_slices/patient035_frame11_slice_5.h5 -trainrlessd4_slices/patient035_frame11_slice_6.h5 -trainrlessd4_slices/patient035_frame11_slice_7.h5 -trainrlessd4_slices/patient035_frame11_slice_8.h5 -trainrlessd4_slices/patient035_frame11_slice_9.h5 -trainrlessd4_slices/patient036_frame12_slice_0.h5 -trainrlessd4_slices/patient036_frame12_slice_1.h5 -trainrlessd4_slices/patient036_frame12_slice_2.h5 -trainrlessd4_slices/patient036_frame12_slice_3.h5 -trainrlessd4_slices/patient036_frame12_slice_4.h5 -trainrlessd4_slices/patient036_frame12_slice_5.h5 -trainrlessd4_slices/patient036_frame12_slice_6.h5 -trainrlessd4_slices/patient036_frame12_slice_7.h5 -trainrlessd4_slices/patient037_frame01_slice_0.h5 -trainrlessd4_slices/patient037_frame01_slice_1.h5 -trainrlessd4_slices/patient037_frame01_slice_2.h5 -trainrlessd4_slices/patient037_frame01_slice_3.h5 -trainrlessd4_slices/patient037_frame01_slice_4.h5 -trainrlessd4_slices/patient037_frame01_slice_5.h5 -trainrlessd4_slices/patient037_frame01_slice_6.h5 -trainrlessd4_slices/patient037_frame12_slice_0.h5 -trainrlessd4_slices/patient037_frame12_slice_1.h5 -trainrlessd4_slices/patient037_frame12_slice_2.h5 -trainrlessd4_slices/patient037_frame12_slice_3.h5 -trainrlessd4_slices/patient037_frame12_slice_4.h5 -trainrlessd4_slices/patient037_frame12_slice_5.h5 -trainrlessd4_slices/patient037_frame12_slice_6.h5 -trainrlessd4_slices/patient038_frame01_slice_0.h5 -trainrlessd4_slices/patient038_frame01_slice_1.h5 -trainrlessd4_slices/patient038_frame01_slice_2.h5 -trainrlessd4_slices/patient038_frame01_slice_3.h5 -trainrlessd4_slices/patient038_frame01_slice_4.h5 -trainrlessd4_slices/patient038_frame01_slice_5.h5 -trainrlessd4_slices/patient038_frame01_slice_6.h5 -trainrlessd4_slices/patient038_frame01_slice_7.h5 -trainrlessd4_slices/patient039_frame01_slice_0.h5 -trainrlessd4_slices/patient039_frame01_slice_1.h5 -trainrlessd4_slices/patient039_frame01_slice_2.h5 -trainrlessd4_slices/patient039_frame01_slice_3.h5 -trainrlessd4_slices/patient039_frame01_slice_4.h5 -trainrlessd4_slices/patient039_frame01_slice_5.h5 -trainrlessd4_slices/patient039_frame01_slice_6.h5 -trainrlessd4_slices/patient039_frame01_slice_7.h5 -trainrlessd4_slices/patient039_frame01_slice_8.h5 -trainrlessd4_slices/patient039_frame10_slice_0.h5 -trainrlessd4_slices/patient039_frame10_slice_1.h5 -trainrlessd4_slices/patient039_frame10_slice_2.h5 -trainrlessd4_slices/patient039_frame10_slice_3.h5 -trainrlessd4_slices/patient039_frame10_slice_4.h5 -trainrlessd4_slices/patient039_frame10_slice_5.h5 -trainrlessd4_slices/patient039_frame10_slice_6.h5 -trainrlessd4_slices/patient039_frame10_slice_7.h5 -trainrlessd4_slices/patient039_frame10_slice_8.h5 -trainrlessd4_slices/patient040_frame01_slice_0.h5 -trainrlessd4_slices/patient040_frame01_slice_1.h5 -trainrlessd4_slices/patient040_frame01_slice_2.h5 -trainrlessd4_slices/patient040_frame01_slice_3.h5 -trainrlessd4_slices/patient040_frame01_slice_4.h5 -trainrlessd4_slices/patient040_frame01_slice_5.h5 -trainrlessd4_slices/patient040_frame01_slice_6.h5 -trainrlessd4_slices/patient040_frame01_slice_7.h5 -trainrlessd4_slices/patient040_frame01_slice_8.h5 -trainrlessd4_slices/patient040_frame01_slice_9.h5 -trainrlessd4_slices/patient041_frame01_slice_0.h5 -trainrlessd4_slices/patient041_frame01_slice_1.h5 -trainrlessd4_slices/patient041_frame01_slice_2.h5 -trainrlessd4_slices/patient041_frame01_slice_3.h5 -trainrlessd4_slices/patient041_frame01_slice_4.h5 -trainrlessd4_slices/patient041_frame01_slice_5.h5 -trainrlessd4_slices/patient041_frame11_slice_0.h5 -trainrlessd4_slices/patient041_frame11_slice_1.h5 -trainrlessd4_slices/patient041_frame11_slice_2.h5 -trainrlessd4_slices/patient041_frame11_slice_3.h5 -trainrlessd4_slices/patient041_frame11_slice_4.h5 -trainrlessd4_slices/patient041_frame11_slice_5.h5 -trainrlessd4_slices/patient042_frame01_slice_0.h5 -trainrlessd4_slices/patient042_frame01_slice_1.h5 -trainrlessd4_slices/patient042_frame01_slice_2.h5 -trainrlessd4_slices/patient042_frame01_slice_3.h5 -trainrlessd4_slices/patient042_frame01_slice_4.h5 -trainrlessd4_slices/patient042_frame01_slice_5.h5 -trainrlessd4_slices/patient042_frame01_slice_6.h5 -trainrlessd4_slices/patient042_frame01_slice_7.h5 -trainrlessd4_slices/patient042_frame01_slice_8.h5 -trainrlessd4_slices/patient042_frame16_slice_0.h5 -trainrlessd4_slices/patient042_frame16_slice_1.h5 -trainrlessd4_slices/patient042_frame16_slice_2.h5 -trainrlessd4_slices/patient042_frame16_slice_3.h5 -trainrlessd4_slices/patient042_frame16_slice_4.h5 -trainrlessd4_slices/patient042_frame16_slice_5.h5 -trainrlessd4_slices/patient042_frame16_slice_6.h5 -trainrlessd4_slices/patient042_frame16_slice_7.h5 -trainrlessd4_slices/patient042_frame16_slice_8.h5 -trainrlessd4_slices/patient043_frame01_slice_0.h5 -trainrlessd4_slices/patient043_frame01_slice_1.h5 -trainrlessd4_slices/patient043_frame01_slice_10.h5 -trainrlessd4_slices/patient043_frame01_slice_11.h5 -trainrlessd4_slices/patient043_frame01_slice_2.h5 -trainrlessd4_slices/patient043_frame01_slice_3.h5 -trainrlessd4_slices/patient043_frame01_slice_4.h5 -trainrlessd4_slices/patient043_frame01_slice_5.h5 -trainrlessd4_slices/patient043_frame01_slice_6.h5 -trainrlessd4_slices/patient043_frame01_slice_7.h5 -trainrlessd4_slices/patient043_frame01_slice_8.h5 -trainrlessd4_slices/patient043_frame01_slice_9.h5 -trainrlessd4_slices/patient043_frame07_slice_0.h5 -trainrlessd4_slices/patient043_frame07_slice_1.h5 -trainrlessd4_slices/patient043_frame07_slice_10.h5 -trainrlessd4_slices/patient043_frame07_slice_11.h5 -trainrlessd4_slices/patient043_frame07_slice_2.h5 -trainrlessd4_slices/patient043_frame07_slice_3.h5 -trainrlessd4_slices/patient043_frame07_slice_4.h5 -trainrlessd4_slices/patient043_frame07_slice_5.h5 -trainrlessd4_slices/patient043_frame07_slice_6.h5 -trainrlessd4_slices/patient043_frame07_slice_7.h5 -trainrlessd4_slices/patient043_frame07_slice_8.h5 -trainrlessd4_slices/patient043_frame07_slice_9.h5 -trainrlessd4_slices/patient044_frame01_slice_0.h5 -trainrlessd4_slices/patient044_frame01_slice_1.h5 -trainrlessd4_slices/patient044_frame01_slice_2.h5 -trainrlessd4_slices/patient044_frame01_slice_3.h5 -trainrlessd4_slices/patient044_frame01_slice_4.h5 -trainrlessd4_slices/patient044_frame01_slice_5.h5 -trainrlessd4_slices/patient044_frame01_slice_6.h5 -trainrlessd4_slices/patient044_frame01_slice_7.h5 -trainrlessd4_slices/patient044_frame01_slice_8.h5 -trainrlessd4_slices/patient044_frame11_slice_0.h5 -trainrlessd4_slices/patient044_frame11_slice_1.h5 -trainrlessd4_slices/patient044_frame11_slice_2.h5 -trainrlessd4_slices/patient044_frame11_slice_3.h5 -trainrlessd4_slices/patient044_frame11_slice_4.h5 -trainrlessd4_slices/patient044_frame11_slice_5.h5 -trainrlessd4_slices/patient044_frame11_slice_6.h5 -trainrlessd4_slices/patient044_frame11_slice_7.h5 -trainrlessd4_slices/patient044_frame11_slice_8.h5 -trainrlessd4_slices/patient045_frame01_slice_0.h5 -trainrlessd4_slices/patient045_frame01_slice_1.h5 -trainrlessd4_slices/patient045_frame01_slice_2.h5 -trainrlessd4_slices/patient045_frame01_slice_3.h5 -trainrlessd4_slices/patient045_frame01_slice_4.h5 -trainrlessd4_slices/patient045_frame01_slice_5.h5 -trainrlessd4_slices/patient045_frame01_slice_6.h5 -trainrlessd4_slices/patient045_frame01_slice_7.h5 -trainrlessd4_slices/patient046_frame01_slice_0.h5 -trainrlessd4_slices/patient046_frame01_slice_1.h5 -trainrlessd4_slices/patient046_frame01_slice_2.h5 -trainrlessd4_slices/patient046_frame01_slice_3.h5 -trainrlessd4_slices/patient046_frame01_slice_4.h5 -trainrlessd4_slices/patient046_frame01_slice_5.h5 -trainrlessd4_slices/patient046_frame01_slice_6.h5 -trainrlessd4_slices/patient046_frame01_slice_7.h5 -trainrlessd4_slices/patient046_frame01_slice_8.h5 -trainrlessd4_slices/patient046_frame10_slice_0.h5 -trainrlessd4_slices/patient046_frame10_slice_1.h5 -trainrlessd4_slices/patient046_frame10_slice_2.h5 -trainrlessd4_slices/patient046_frame10_slice_3.h5 -trainrlessd4_slices/patient046_frame10_slice_4.h5 -trainrlessd4_slices/patient046_frame10_slice_5.h5 -trainrlessd4_slices/patient046_frame10_slice_6.h5 -trainrlessd4_slices/patient046_frame10_slice_7.h5 -trainrlessd4_slices/patient046_frame10_slice_8.h5 -trainrlessd4_slices/patient047_frame01_slice_0.h5 -trainrlessd4_slices/patient047_frame01_slice_1.h5 -trainrlessd4_slices/patient047_frame01_slice_2.h5 -trainrlessd4_slices/patient047_frame01_slice_3.h5 -trainrlessd4_slices/patient047_frame01_slice_4.h5 -trainrlessd4_slices/patient047_frame01_slice_5.h5 -trainrlessd4_slices/patient047_frame01_slice_6.h5 -trainrlessd4_slices/patient047_frame01_slice_7.h5 -trainrlessd4_slices/patient047_frame01_slice_8.h5 -trainrlessd4_slices/patient048_frame01_slice_0.h5 -trainrlessd4_slices/patient048_frame01_slice_1.h5 -trainrlessd4_slices/patient048_frame01_slice_2.h5 -trainrlessd4_slices/patient048_frame01_slice_3.h5 -trainrlessd4_slices/patient048_frame01_slice_4.h5 -trainrlessd4_slices/patient048_frame01_slice_5.h5 -trainrlessd4_slices/patient048_frame01_slice_6.h5 -trainrlessd4_slices/patient048_frame01_slice_7.h5 -trainrlessd4_slices/patient049_frame01_slice_0.h5 -trainrlessd4_slices/patient049_frame01_slice_1.h5 -trainrlessd4_slices/patient049_frame01_slice_2.h5 -trainrlessd4_slices/patient049_frame01_slice_3.h5 -trainrlessd4_slices/patient049_frame01_slice_4.h5 -trainrlessd4_slices/patient049_frame01_slice_5.h5 -trainrlessd4_slices/patient049_frame01_slice_6.h5 -trainrlessd4_slices/patient049_frame11_slice_0.h5 -trainrlessd4_slices/patient049_frame11_slice_1.h5 -trainrlessd4_slices/patient049_frame11_slice_2.h5 -trainrlessd4_slices/patient049_frame11_slice_3.h5 -trainrlessd4_slices/patient049_frame11_slice_4.h5 -trainrlessd4_slices/patient049_frame11_slice_5.h5 -trainrlessd4_slices/patient049_frame11_slice_6.h5 -trainrlessd4_slices/patient050_frame01_slice_0.h5 -trainrlessd4_slices/patient050_frame01_slice_1.h5 -trainrlessd4_slices/patient050_frame01_slice_2.h5 -trainrlessd4_slices/patient050_frame01_slice_3.h5 -trainrlessd4_slices/patient050_frame01_slice_4.h5 -trainrlessd4_slices/patient050_frame01_slice_5.h5 -trainrlessd4_slices/patient050_frame01_slice_6.h5 -trainrlessd4_slices/patient050_frame01_slice_7.h5 -trainrlessd4_slices/patient050_frame01_slice_8.h5 -trainrlessd4_slices/patient050_frame01_slice_9.h5 -trainrlessd4_slices/patient050_frame12_slice_0.h5 -trainrlessd4_slices/patient050_frame12_slice_1.h5 -trainrlessd4_slices/patient050_frame12_slice_2.h5 -trainrlessd4_slices/patient050_frame12_slice_3.h5 -trainrlessd4_slices/patient050_frame12_slice_4.h5 -trainrlessd4_slices/patient050_frame12_slice_5.h5 -trainrlessd4_slices/patient050_frame12_slice_6.h5 -trainrlessd4_slices/patient050_frame12_slice_7.h5 -trainrlessd4_slices/patient050_frame12_slice_8.h5 -trainrlessd4_slices/patient050_frame12_slice_9.h5 -trainrlessd4_slices/patient051_frame01_slice_0.h5 -trainrlessd4_slices/patient051_frame01_slice_1.h5 -trainrlessd4_slices/patient051_frame01_slice_2.h5 -trainrlessd4_slices/patient051_frame01_slice_3.h5 -trainrlessd4_slices/patient051_frame01_slice_4.h5 -trainrlessd4_slices/patient051_frame01_slice_5.h5 -trainrlessd4_slices/patient051_frame01_slice_6.h5 -trainrlessd4_slices/patient051_frame01_slice_7.h5 -trainrlessd4_slices/patient051_frame01_slice_8.h5 -trainrlessd4_slices/patient051_frame01_slice_9.h5 -trainrlessd4_slices/patient051_frame11_slice_0.h5 -trainrlessd4_slices/patient051_frame11_slice_1.h5 -trainrlessd4_slices/patient051_frame11_slice_2.h5 -trainrlessd4_slices/patient051_frame11_slice_3.h5 -trainrlessd4_slices/patient051_frame11_slice_4.h5 -trainrlessd4_slices/patient051_frame11_slice_5.h5 -trainrlessd4_slices/patient051_frame11_slice_6.h5 -trainrlessd4_slices/patient051_frame11_slice_7.h5 -trainrlessd4_slices/patient051_frame11_slice_8.h5 -trainrlessd4_slices/patient051_frame11_slice_9.h5 -trainrlessd4_slices/patient052_frame01_slice_0.h5 -trainrlessd4_slices/patient052_frame01_slice_1.h5 -trainrlessd4_slices/patient052_frame01_slice_2.h5 -trainrlessd4_slices/patient052_frame01_slice_3.h5 -trainrlessd4_slices/patient052_frame01_slice_4.h5 -trainrlessd4_slices/patient052_frame01_slice_5.h5 -trainrlessd4_slices/patient052_frame01_slice_6.h5 -trainrlessd4_slices/patient052_frame01_slice_7.h5 -trainrlessd4_slices/patient052_frame09_slice_0.h5 -trainrlessd4_slices/patient052_frame09_slice_1.h5 -trainrlessd4_slices/patient052_frame09_slice_2.h5 -trainrlessd4_slices/patient052_frame09_slice_3.h5 -trainrlessd4_slices/patient052_frame09_slice_4.h5 -trainrlessd4_slices/patient052_frame09_slice_5.h5 -trainrlessd4_slices/patient052_frame09_slice_6.h5 -trainrlessd4_slices/patient052_frame09_slice_7.h5 -trainrlessd4_slices/patient053_frame12_slice_0.h5 -trainrlessd4_slices/patient053_frame12_slice_1.h5 -trainrlessd4_slices/patient053_frame12_slice_2.h5 -trainrlessd4_slices/patient053_frame12_slice_3.h5 -trainrlessd4_slices/patient053_frame12_slice_4.h5 -trainrlessd4_slices/patient053_frame12_slice_5.h5 -trainrlessd4_slices/patient053_frame12_slice_6.h5 -trainrlessd4_slices/patient054_frame01_slice_0.h5 -trainrlessd4_slices/patient054_frame01_slice_1.h5 -trainrlessd4_slices/patient054_frame01_slice_2.h5 -trainrlessd4_slices/patient054_frame01_slice_3.h5 -trainrlessd4_slices/patient054_frame01_slice_4.h5 -trainrlessd4_slices/patient054_frame01_slice_5.h5 -trainrlessd4_slices/patient054_frame01_slice_6.h5 -trainrlessd4_slices/patient054_frame01_slice_7.h5 -trainrlessd4_slices/patient054_frame12_slice_0.h5 -trainrlessd4_slices/patient054_frame12_slice_1.h5 -trainrlessd4_slices/patient054_frame12_slice_2.h5 -trainrlessd4_slices/patient054_frame12_slice_3.h5 -trainrlessd4_slices/patient054_frame12_slice_4.h5 -trainrlessd4_slices/patient054_frame12_slice_5.h5 -trainrlessd4_slices/patient054_frame12_slice_6.h5 -trainrlessd4_slices/patient054_frame12_slice_7.h5 -trainrlessd4_slices/patient055_frame10_slice_0.h5 -trainrlessd4_slices/patient055_frame10_slice_1.h5 -trainrlessd4_slices/patient055_frame10_slice_2.h5 -trainrlessd4_slices/patient055_frame10_slice_3.h5 -trainrlessd4_slices/patient055_frame10_slice_4.h5 -trainrlessd4_slices/patient055_frame10_slice_5.h5 -trainrlessd4_slices/patient055_frame10_slice_6.h5 -trainrlessd4_slices/patient055_frame10_slice_7.h5 -trainrlessd4_slices/patient055_frame10_slice_8.h5 -trainrlessd4_slices/patient056_frame01_slice_0.h5 -trainrlessd4_slices/patient056_frame01_slice_1.h5 -trainrlessd4_slices/patient056_frame01_slice_2.h5 -trainrlessd4_slices/patient056_frame01_slice_3.h5 -trainrlessd4_slices/patient056_frame01_slice_4.h5 -trainrlessd4_slices/patient056_frame01_slice_5.h5 -trainrlessd4_slices/patient056_frame01_slice_6.h5 -trainrlessd4_slices/patient056_frame01_slice_7.h5 -trainrlessd4_slices/patient056_frame01_slice_8.h5 -trainrlessd4_slices/patient056_frame12_slice_0.h5 -trainrlessd4_slices/patient056_frame12_slice_1.h5 -trainrlessd4_slices/patient056_frame12_slice_2.h5 -trainrlessd4_slices/patient056_frame12_slice_3.h5 -trainrlessd4_slices/patient056_frame12_slice_4.h5 -trainrlessd4_slices/patient056_frame12_slice_5.h5 -trainrlessd4_slices/patient056_frame12_slice_6.h5 -trainrlessd4_slices/patient056_frame12_slice_7.h5 -trainrlessd4_slices/patient056_frame12_slice_8.h5 -trainrlessd4_slices/patient057_frame01_slice_0.h5 -trainrlessd4_slices/patient057_frame01_slice_1.h5 -trainrlessd4_slices/patient057_frame01_slice_2.h5 -trainrlessd4_slices/patient057_frame01_slice_3.h5 -trainrlessd4_slices/patient057_frame01_slice_4.h5 -trainrlessd4_slices/patient057_frame01_slice_5.h5 -trainrlessd4_slices/patient057_frame01_slice_6.h5 -trainrlessd4_slices/patient057_frame01_slice_7.h5 -trainrlessd4_slices/patient058_frame14_slice_0.h5 -trainrlessd4_slices/patient058_frame14_slice_1.h5 -trainrlessd4_slices/patient058_frame14_slice_2.h5 -trainrlessd4_slices/patient058_frame14_slice_3.h5 -trainrlessd4_slices/patient058_frame14_slice_4.h5 -trainrlessd4_slices/patient058_frame14_slice_5.h5 -trainrlessd4_slices/patient058_frame14_slice_6.h5 -trainrlessd4_slices/patient058_frame14_slice_7.h5 -trainrlessd4_slices/patient058_frame14_slice_8.h5 -trainrlessd4_slices/patient059_frame01_slice_0.h5 -trainrlessd4_slices/patient059_frame01_slice_1.h5 -trainrlessd4_slices/patient059_frame01_slice_2.h5 -trainrlessd4_slices/patient059_frame01_slice_3.h5 -trainrlessd4_slices/patient059_frame01_slice_4.h5 -trainrlessd4_slices/patient059_frame01_slice_5.h5 -trainrlessd4_slices/patient059_frame01_slice_6.h5 -trainrlessd4_slices/patient059_frame01_slice_7.h5 -trainrlessd4_slices/patient059_frame01_slice_8.h5 -trainrlessd4_slices/patient059_frame09_slice_0.h5 -trainrlessd4_slices/patient059_frame09_slice_1.h5 -trainrlessd4_slices/patient059_frame09_slice_2.h5 -trainrlessd4_slices/patient059_frame09_slice_3.h5 -trainrlessd4_slices/patient059_frame09_slice_4.h5 -trainrlessd4_slices/patient059_frame09_slice_5.h5 -trainrlessd4_slices/patient059_frame09_slice_6.h5 -trainrlessd4_slices/patient059_frame09_slice_7.h5 -trainrlessd4_slices/patient059_frame09_slice_8.h5 -trainrlessd4_slices/patient060_frame14_slice_0.h5 -trainrlessd4_slices/patient060_frame14_slice_1.h5 -trainrlessd4_slices/patient060_frame14_slice_2.h5 -trainrlessd4_slices/patient060_frame14_slice_3.h5 -trainrlessd4_slices/patient060_frame14_slice_4.h5 -trainrlessd4_slices/patient060_frame14_slice_5.h5 -trainrlessd4_slices/patient060_frame14_slice_6.h5 -trainrlessd4_slices/patient060_frame14_slice_7.h5 -trainrlessd4_slices/patient060_frame14_slice_8.h5 -trainrlessd4_slices/patient061_frame01_slice_0.h5 -trainrlessd4_slices/patient061_frame01_slice_1.h5 -trainrlessd4_slices/patient061_frame01_slice_2.h5 -trainrlessd4_slices/patient061_frame01_slice_3.h5 -trainrlessd4_slices/patient061_frame01_slice_4.h5 -trainrlessd4_slices/patient061_frame01_slice_5.h5 -trainrlessd4_slices/patient061_frame01_slice_6.h5 -trainrlessd4_slices/patient061_frame01_slice_7.h5 -trainrlessd4_slices/patient061_frame01_slice_8.h5 -trainrlessd4_slices/patient061_frame10_slice_0.h5 -trainrlessd4_slices/patient061_frame10_slice_1.h5 -trainrlessd4_slices/patient061_frame10_slice_2.h5 -trainrlessd4_slices/patient061_frame10_slice_3.h5 -trainrlessd4_slices/patient061_frame10_slice_4.h5 -trainrlessd4_slices/patient061_frame10_slice_5.h5 -trainrlessd4_slices/patient061_frame10_slice_6.h5 -trainrlessd4_slices/patient061_frame10_slice_7.h5 -trainrlessd4_slices/patient061_frame10_slice_8.h5 -trainrlessd4_slices/patient062_frame01_slice_0.h5 -trainrlessd4_slices/patient062_frame01_slice_1.h5 -trainrlessd4_slices/patient062_frame01_slice_2.h5 -trainrlessd4_slices/patient062_frame01_slice_3.h5 -trainrlessd4_slices/patient062_frame01_slice_4.h5 -trainrlessd4_slices/patient062_frame01_slice_5.h5 -trainrlessd4_slices/patient062_frame01_slice_6.h5 -trainrlessd4_slices/patient062_frame01_slice_7.h5 -trainrlessd4_slices/patient062_frame01_slice_8.h5 -trainrlessd4_slices/patient062_frame01_slice_9.h5 -trainrlessd4_slices/patient062_frame09_slice_0.h5 -trainrlessd4_slices/patient062_frame09_slice_1.h5 -trainrlessd4_slices/patient062_frame09_slice_2.h5 -trainrlessd4_slices/patient062_frame09_slice_3.h5 -trainrlessd4_slices/patient062_frame09_slice_4.h5 -trainrlessd4_slices/patient062_frame09_slice_5.h5 -trainrlessd4_slices/patient062_frame09_slice_6.h5 -trainrlessd4_slices/patient062_frame09_slice_7.h5 -trainrlessd4_slices/patient062_frame09_slice_8.h5 -trainrlessd4_slices/patient062_frame09_slice_9.h5 -trainrlessd4_slices/patient063_frame16_slice_0.h5 -trainrlessd4_slices/patient063_frame16_slice_1.h5 -trainrlessd4_slices/patient063_frame16_slice_2.h5 -trainrlessd4_slices/patient063_frame16_slice_3.h5 -trainrlessd4_slices/patient063_frame16_slice_4.h5 -trainrlessd4_slices/patient063_frame16_slice_5.h5 -trainrlessd4_slices/patient063_frame16_slice_6.h5 -trainrlessd4_slices/patient063_frame16_slice_7.h5 -trainrlessd4_slices/patient064_frame01_slice_0.h5 -trainrlessd4_slices/patient064_frame01_slice_1.h5 -trainrlessd4_slices/patient064_frame01_slice_2.h5 -trainrlessd4_slices/patient064_frame01_slice_3.h5 -trainrlessd4_slices/patient064_frame01_slice_4.h5 -trainrlessd4_slices/patient064_frame01_slice_5.h5 -trainrlessd4_slices/patient064_frame01_slice_6.h5 -trainrlessd4_slices/patient064_frame01_slice_7.h5 -trainrlessd4_slices/patient064_frame01_slice_8.h5 -trainrlessd4_slices/patient064_frame01_slice_9.h5 -trainrlessd4_slices/patient066_frame01_slice_0.h5 -trainrlessd4_slices/patient066_frame01_slice_1.h5 -trainrlessd4_slices/patient066_frame01_slice_2.h5 -trainrlessd4_slices/patient066_frame01_slice_3.h5 -trainrlessd4_slices/patient066_frame01_slice_4.h5 -trainrlessd4_slices/patient066_frame01_slice_5.h5 -trainrlessd4_slices/patient066_frame01_slice_6.h5 -trainrlessd4_slices/patient066_frame01_slice_7.h5 -trainrlessd4_slices/patient066_frame01_slice_8.h5 -trainrlessd4_slices/patient067_frame01_slice_0.h5 -trainrlessd4_slices/patient067_frame01_slice_1.h5 -trainrlessd4_slices/patient067_frame01_slice_2.h5 -trainrlessd4_slices/patient067_frame01_slice_3.h5 -trainrlessd4_slices/patient067_frame01_slice_4.h5 -trainrlessd4_slices/patient067_frame01_slice_5.h5 -trainrlessd4_slices/patient067_frame01_slice_6.h5 -trainrlessd4_slices/patient067_frame01_slice_7.h5 -trainrlessd4_slices/patient067_frame01_slice_8.h5 -trainrlessd4_slices/patient067_frame01_slice_9.h5 -trainrlessd4_slices/patient067_frame10_slice_0.h5 -trainrlessd4_slices/patient067_frame10_slice_1.h5 -trainrlessd4_slices/patient067_frame10_slice_2.h5 -trainrlessd4_slices/patient067_frame10_slice_3.h5 -trainrlessd4_slices/patient067_frame10_slice_4.h5 -trainrlessd4_slices/patient067_frame10_slice_5.h5 -trainrlessd4_slices/patient067_frame10_slice_6.h5 -trainrlessd4_slices/patient067_frame10_slice_7.h5 -trainrlessd4_slices/patient067_frame10_slice_8.h5 -trainrlessd4_slices/patient067_frame10_slice_9.h5 -trainrlessd4_slices/patient068_frame01_slice_0.h5 -trainrlessd4_slices/patient068_frame01_slice_1.h5 -trainrlessd4_slices/patient068_frame01_slice_2.h5 -trainrlessd4_slices/patient068_frame01_slice_3.h5 -trainrlessd4_slices/patient068_frame01_slice_4.h5 -trainrlessd4_slices/patient068_frame01_slice_5.h5 -trainrlessd4_slices/patient068_frame01_slice_6.h5 -trainrlessd4_slices/patient069_frame01_slice_0.h5 -trainrlessd4_slices/patient069_frame01_slice_1.h5 -trainrlessd4_slices/patient069_frame01_slice_2.h5 -trainrlessd4_slices/patient069_frame01_slice_3.h5 -trainrlessd4_slices/patient069_frame01_slice_4.h5 -trainrlessd4_slices/patient069_frame01_slice_5.h5 -trainrlessd4_slices/patient069_frame01_slice_6.h5 -trainrlessd4_slices/patient070_frame01_slice_0.h5 -trainrlessd4_slices/patient070_frame01_slice_1.h5 -trainrlessd4_slices/patient070_frame01_slice_2.h5 -trainrlessd4_slices/patient070_frame01_slice_3.h5 -trainrlessd4_slices/patient070_frame01_slice_4.h5 -trainrlessd4_slices/patient070_frame01_slice_5.h5 -trainrlessd4_slices/patient071_frame09_slice_0.h5 -trainrlessd4_slices/patient071_frame09_slice_1.h5 -trainrlessd4_slices/patient071_frame09_slice_2.h5 -trainrlessd4_slices/patient071_frame09_slice_3.h5 -trainrlessd4_slices/patient071_frame09_slice_4.h5 -trainrlessd4_slices/patient071_frame09_slice_5.h5 -trainrlessd4_slices/patient071_frame09_slice_6.h5 -trainrlessd4_slices/patient071_frame09_slice_7.h5 -trainrlessd4_slices/patient071_frame09_slice_8.h5 -trainrlessd4_slices/patient071_frame09_slice_9.h5 -trainrlessd4_slices/patient072_frame01_slice_0.h5 -trainrlessd4_slices/patient072_frame01_slice_1.h5 -trainrlessd4_slices/patient072_frame01_slice_2.h5 -trainrlessd4_slices/patient072_frame01_slice_3.h5 -trainrlessd4_slices/patient072_frame01_slice_4.h5 -trainrlessd4_slices/patient072_frame01_slice_5.h5 -trainrlessd4_slices/patient072_frame01_slice_6.h5 -trainrlessd4_slices/patient072_frame01_slice_7.h5 -trainrlessd4_slices/patient073_frame10_slice_0.h5 -trainrlessd4_slices/patient073_frame10_slice_1.h5 -trainrlessd4_slices/patient073_frame10_slice_2.h5 -trainrlessd4_slices/patient073_frame10_slice_3.h5 -trainrlessd4_slices/patient073_frame10_slice_4.h5 -trainrlessd4_slices/patient073_frame10_slice_5.h5 -trainrlessd4_slices/patient073_frame10_slice_6.h5 -trainrlessd4_slices/patient074_frame12_slice_0.h5 -trainrlessd4_slices/patient074_frame12_slice_1.h5 -trainrlessd4_slices/patient074_frame12_slice_2.h5 -trainrlessd4_slices/patient074_frame12_slice_3.h5 -trainrlessd4_slices/patient074_frame12_slice_4.h5 -trainrlessd4_slices/patient074_frame12_slice_5.h5 -trainrlessd4_slices/patient074_frame12_slice_6.h5 -trainrlessd4_slices/patient074_frame12_slice_7.h5 -trainrlessd4_slices/patient075_frame01_slice_0.h5 -trainrlessd4_slices/patient075_frame01_slice_1.h5 -trainrlessd4_slices/patient075_frame01_slice_10.h5 -trainrlessd4_slices/patient075_frame01_slice_11.h5 -trainrlessd4_slices/patient075_frame01_slice_12.h5 -trainrlessd4_slices/patient075_frame01_slice_13.h5 -trainrlessd4_slices/patient075_frame01_slice_2.h5 -trainrlessd4_slices/patient075_frame01_slice_3.h5 -trainrlessd4_slices/patient075_frame01_slice_4.h5 -trainrlessd4_slices/patient075_frame01_slice_5.h5 -trainrlessd4_slices/patient075_frame01_slice_6.h5 -trainrlessd4_slices/patient075_frame01_slice_7.h5 -trainrlessd4_slices/patient075_frame01_slice_8.h5 -trainrlessd4_slices/patient075_frame01_slice_9.h5 -trainrlessd4_slices/patient076_frame12_slice_0.h5 -trainrlessd4_slices/patient076_frame12_slice_1.h5 -trainrlessd4_slices/patient076_frame12_slice_2.h5 -trainrlessd4_slices/patient076_frame12_slice_3.h5 -trainrlessd4_slices/patient076_frame12_slice_4.h5 -trainrlessd4_slices/patient076_frame12_slice_5.h5 -trainrlessd4_slices/patient076_frame12_slice_6.h5 -trainrlessd4_slices/patient076_frame12_slice_7.h5 -trainrlessd4_slices/patient077_frame09_slice_0.h5 -trainrlessd4_slices/patient077_frame09_slice_1.h5 -trainrlessd4_slices/patient077_frame09_slice_2.h5 -trainrlessd4_slices/patient077_frame09_slice_3.h5 -trainrlessd4_slices/patient077_frame09_slice_4.h5 -trainrlessd4_slices/patient077_frame09_slice_5.h5 -trainrlessd4_slices/patient077_frame09_slice_6.h5 -trainrlessd4_slices/patient077_frame09_slice_7.h5 -trainrlessd4_slices/patient078_frame01_slice_0.h5 -trainrlessd4_slices/patient078_frame01_slice_1.h5 -trainrlessd4_slices/patient078_frame01_slice_2.h5 -trainrlessd4_slices/patient078_frame01_slice_3.h5 -trainrlessd4_slices/patient078_frame01_slice_4.h5 -trainrlessd4_slices/patient078_frame01_slice_5.h5 -trainrlessd4_slices/patient078_frame01_slice_6.h5 -trainrlessd4_slices/patient078_frame01_slice_7.h5 -trainrlessd4_slices/patient078_frame09_slice_0.h5 -trainrlessd4_slices/patient078_frame09_slice_1.h5 -trainrlessd4_slices/patient078_frame09_slice_2.h5 -trainrlessd4_slices/patient078_frame09_slice_3.h5 -trainrlessd4_slices/patient078_frame09_slice_4.h5 -trainrlessd4_slices/patient078_frame09_slice_5.h5 -trainrlessd4_slices/patient078_frame09_slice_6.h5 -trainrlessd4_slices/patient078_frame09_slice_7.h5 -trainrlessd4_slices/patient079_frame01_slice_0.h5 -trainrlessd4_slices/patient079_frame01_slice_1.h5 -trainrlessd4_slices/patient079_frame01_slice_2.h5 -trainrlessd4_slices/patient079_frame01_slice_3.h5 -trainrlessd4_slices/patient079_frame01_slice_4.h5 -trainrlessd4_slices/patient079_frame01_slice_5.h5 -trainrlessd4_slices/patient079_frame01_slice_6.h5 -trainrlessd4_slices/patient079_frame01_slice_7.h5 -trainrlessd4_slices/patient079_frame01_slice_8.h5 -trainrlessd4_slices/patient079_frame11_slice_0.h5 -trainrlessd4_slices/patient079_frame11_slice_1.h5 -trainrlessd4_slices/patient079_frame11_slice_2.h5 -trainrlessd4_slices/patient079_frame11_slice_3.h5 -trainrlessd4_slices/patient079_frame11_slice_4.h5 -trainrlessd4_slices/patient079_frame11_slice_5.h5 -trainrlessd4_slices/patient079_frame11_slice_6.h5 -trainrlessd4_slices/patient079_frame11_slice_7.h5 -trainrlessd4_slices/patient079_frame11_slice_8.h5 -trainrlessd4_slices/patient080_frame01_slice_0.h5 -trainrlessd4_slices/patient080_frame01_slice_1.h5 -trainrlessd4_slices/patient080_frame01_slice_2.h5 -trainrlessd4_slices/patient080_frame01_slice_3.h5 -trainrlessd4_slices/patient080_frame01_slice_4.h5 -trainrlessd4_slices/patient080_frame01_slice_5.h5 -trainrlessd4_slices/patient080_frame10_slice_0.h5 -trainrlessd4_slices/patient080_frame10_slice_1.h5 -trainrlessd4_slices/patient080_frame10_slice_2.h5 -trainrlessd4_slices/patient080_frame10_slice_3.h5 -trainrlessd4_slices/patient080_frame10_slice_4.h5 -trainrlessd4_slices/patient080_frame10_slice_5.h5 -trainrlessd4_slices/patient081_frame07_slice_0.h5 -trainrlessd4_slices/patient081_frame07_slice_1.h5 -trainrlessd4_slices/patient081_frame07_slice_10.h5 -trainrlessd4_slices/patient081_frame07_slice_11.h5 -trainrlessd4_slices/patient081_frame07_slice_12.h5 -trainrlessd4_slices/patient081_frame07_slice_13.h5 -trainrlessd4_slices/patient081_frame07_slice_14.h5 -trainrlessd4_slices/patient081_frame07_slice_15.h5 -trainrlessd4_slices/patient081_frame07_slice_16.h5 -trainrlessd4_slices/patient081_frame07_slice_2.h5 -trainrlessd4_slices/patient081_frame07_slice_3.h5 -trainrlessd4_slices/patient081_frame07_slice_4.h5 -trainrlessd4_slices/patient081_frame07_slice_5.h5 -trainrlessd4_slices/patient081_frame07_slice_6.h5 -trainrlessd4_slices/patient081_frame07_slice_7.h5 -trainrlessd4_slices/patient081_frame07_slice_8.h5 -trainrlessd4_slices/patient081_frame07_slice_9.h5 -trainrlessd4_slices/patient082_frame01_slice_0.h5 -trainrlessd4_slices/patient082_frame01_slice_1.h5 -trainrlessd4_slices/patient082_frame01_slice_10.h5 -trainrlessd4_slices/patient082_frame01_slice_11.h5 -trainrlessd4_slices/patient082_frame01_slice_12.h5 -trainrlessd4_slices/patient082_frame01_slice_13.h5 -trainrlessd4_slices/patient082_frame01_slice_14.h5 -trainrlessd4_slices/patient082_frame01_slice_15.h5 -trainrlessd4_slices/patient082_frame01_slice_2.h5 -trainrlessd4_slices/patient082_frame01_slice_3.h5 -trainrlessd4_slices/patient082_frame01_slice_4.h5 -trainrlessd4_slices/patient082_frame01_slice_5.h5 -trainrlessd4_slices/patient082_frame01_slice_6.h5 -trainrlessd4_slices/patient082_frame01_slice_7.h5 -trainrlessd4_slices/patient082_frame01_slice_8.h5 -trainrlessd4_slices/patient082_frame01_slice_9.h5 -trainrlessd4_slices/patient082_frame07_slice_0.h5 -trainrlessd4_slices/patient082_frame07_slice_1.h5 -trainrlessd4_slices/patient082_frame07_slice_10.h5 -trainrlessd4_slices/patient082_frame07_slice_11.h5 -trainrlessd4_slices/patient082_frame07_slice_12.h5 -trainrlessd4_slices/patient082_frame07_slice_13.h5 -trainrlessd4_slices/patient082_frame07_slice_14.h5 -trainrlessd4_slices/patient082_frame07_slice_15.h5 -trainrlessd4_slices/patient082_frame07_slice_2.h5 -trainrlessd4_slices/patient082_frame07_slice_3.h5 -trainrlessd4_slices/patient082_frame07_slice_4.h5 -trainrlessd4_slices/patient082_frame07_slice_5.h5 -trainrlessd4_slices/patient082_frame07_slice_6.h5 -trainrlessd4_slices/patient082_frame07_slice_7.h5 -trainrlessd4_slices/patient082_frame07_slice_8.h5 -trainrlessd4_slices/patient082_frame07_slice_9.h5 -trainrlessd4_slices/patient083_frame01_slice_0.h5 -trainrlessd4_slices/patient083_frame01_slice_1.h5 -trainrlessd4_slices/patient083_frame01_slice_2.h5 -trainrlessd4_slices/patient083_frame01_slice_3.h5 -trainrlessd4_slices/patient083_frame01_slice_4.h5 -trainrlessd4_slices/patient083_frame01_slice_5.h5 -trainrlessd4_slices/patient084_frame01_slice_0.h5 -trainrlessd4_slices/patient084_frame01_slice_1.h5 -trainrlessd4_slices/patient084_frame01_slice_10.h5 -trainrlessd4_slices/patient084_frame01_slice_11.h5 -trainrlessd4_slices/patient084_frame01_slice_2.h5 -trainrlessd4_slices/patient084_frame01_slice_3.h5 -trainrlessd4_slices/patient084_frame01_slice_4.h5 -trainrlessd4_slices/patient084_frame01_slice_5.h5 -trainrlessd4_slices/patient084_frame01_slice_6.h5 -trainrlessd4_slices/patient084_frame01_slice_7.h5 -trainrlessd4_slices/patient084_frame01_slice_8.h5 -trainrlessd4_slices/patient084_frame01_slice_9.h5 -trainrlessd4_slices/patient084_frame10_slice_0.h5 -trainrlessd4_slices/patient084_frame10_slice_1.h5 -trainrlessd4_slices/patient084_frame10_slice_10.h5 -trainrlessd4_slices/patient084_frame10_slice_11.h5 -trainrlessd4_slices/patient084_frame10_slice_2.h5 -trainrlessd4_slices/patient084_frame10_slice_3.h5 -trainrlessd4_slices/patient084_frame10_slice_4.h5 -trainrlessd4_slices/patient084_frame10_slice_5.h5 -trainrlessd4_slices/patient084_frame10_slice_6.h5 -trainrlessd4_slices/patient084_frame10_slice_7.h5 -trainrlessd4_slices/patient084_frame10_slice_8.h5 -trainrlessd4_slices/patient084_frame10_slice_9.h5 -trainrlessd4_slices/patient085_frame01_slice_0.h5 -trainrlessd4_slices/patient085_frame01_slice_1.h5 -trainrlessd4_slices/patient085_frame01_slice_10.h5 -trainrlessd4_slices/patient085_frame01_slice_11.h5 -trainrlessd4_slices/patient085_frame01_slice_12.h5 -trainrlessd4_slices/patient085_frame01_slice_13.h5 -trainrlessd4_slices/patient085_frame01_slice_14.h5 -trainrlessd4_slices/patient085_frame01_slice_2.h5 -trainrlessd4_slices/patient085_frame01_slice_3.h5 -trainrlessd4_slices/patient085_frame01_slice_4.h5 -trainrlessd4_slices/patient085_frame01_slice_5.h5 -trainrlessd4_slices/patient085_frame01_slice_6.h5 -trainrlessd4_slices/patient085_frame01_slice_7.h5 -trainrlessd4_slices/patient085_frame01_slice_8.h5 -trainrlessd4_slices/patient085_frame01_slice_9.h5 -trainrlessd4_slices/patient087_frame01_slice_0.h5 -trainrlessd4_slices/patient087_frame01_slice_1.h5 -trainrlessd4_slices/patient087_frame01_slice_2.h5 -trainrlessd4_slices/patient087_frame01_slice_3.h5 -trainrlessd4_slices/patient087_frame01_slice_4.h5 -trainrlessd4_slices/patient087_frame01_slice_5.h5 -trainrlessd4_slices/patient087_frame01_slice_6.h5 -trainrlessd4_slices/patient087_frame01_slice_7.h5 -trainrlessd4_slices/patient088_frame01_slice_0.h5 -trainrlessd4_slices/patient088_frame01_slice_1.h5 -trainrlessd4_slices/patient088_frame01_slice_10.h5 -trainrlessd4_slices/patient088_frame01_slice_11.h5 -trainrlessd4_slices/patient088_frame01_slice_12.h5 -trainrlessd4_slices/patient088_frame01_slice_13.h5 -trainrlessd4_slices/patient088_frame01_slice_14.h5 -trainrlessd4_slices/patient088_frame01_slice_15.h5 -trainrlessd4_slices/patient088_frame01_slice_2.h5 -trainrlessd4_slices/patient088_frame01_slice_3.h5 -trainrlessd4_slices/patient088_frame01_slice_4.h5 -trainrlessd4_slices/patient088_frame01_slice_5.h5 -trainrlessd4_slices/patient088_frame01_slice_6.h5 -trainrlessd4_slices/patient088_frame01_slice_7.h5 -trainrlessd4_slices/patient088_frame01_slice_8.h5 -trainrlessd4_slices/patient088_frame01_slice_9.h5 -trainrlessd4_slices/patient088_frame12_slice_0.h5 -trainrlessd4_slices/patient088_frame12_slice_1.h5 -trainrlessd4_slices/patient088_frame12_slice_10.h5 -trainrlessd4_slices/patient088_frame12_slice_11.h5 -trainrlessd4_slices/patient088_frame12_slice_12.h5 -trainrlessd4_slices/patient088_frame12_slice_13.h5 -trainrlessd4_slices/patient088_frame12_slice_14.h5 -trainrlessd4_slices/patient088_frame12_slice_15.h5 -trainrlessd4_slices/patient088_frame12_slice_2.h5 -trainrlessd4_slices/patient088_frame12_slice_3.h5 -trainrlessd4_slices/patient088_frame12_slice_4.h5 -trainrlessd4_slices/patient088_frame12_slice_5.h5 -trainrlessd4_slices/patient088_frame12_slice_6.h5 -trainrlessd4_slices/patient088_frame12_slice_7.h5 -trainrlessd4_slices/patient088_frame12_slice_8.h5 -trainrlessd4_slices/patient088_frame12_slice_9.h5 -trainrlessd4_slices/patient090_frame11_slice_0.h5 -trainrlessd4_slices/patient090_frame11_slice_1.h5 -trainrlessd4_slices/patient090_frame11_slice_2.h5 -trainrlessd4_slices/patient090_frame11_slice_3.h5 -trainrlessd4_slices/patient090_frame11_slice_4.h5 -trainrlessd4_slices/patient090_frame11_slice_5.h5 -trainrlessd4_slices/patient090_frame11_slice_6.h5 -trainrlessd4_slices/patient091_frame01_slice_0.h5 -trainrlessd4_slices/patient091_frame01_slice_1.h5 -trainrlessd4_slices/patient091_frame01_slice_2.h5 -trainrlessd4_slices/patient091_frame01_slice_3.h5 -trainrlessd4_slices/patient091_frame01_slice_4.h5 -trainrlessd4_slices/patient091_frame01_slice_5.h5 -trainrlessd4_slices/patient091_frame01_slice_6.h5 -trainrlessd4_slices/patient091_frame01_slice_7.h5 -trainrlessd4_slices/patient091_frame09_slice_0.h5 -trainrlessd4_slices/patient091_frame09_slice_1.h5 -trainrlessd4_slices/patient091_frame09_slice_2.h5 -trainrlessd4_slices/patient091_frame09_slice_3.h5 -trainrlessd4_slices/patient091_frame09_slice_4.h5 -trainrlessd4_slices/patient091_frame09_slice_5.h5 -trainrlessd4_slices/patient091_frame09_slice_6.h5 -trainrlessd4_slices/patient091_frame09_slice_7.h5 -trainrlessd4_slices/patient092_frame01_slice_0.h5 -trainrlessd4_slices/patient092_frame01_slice_1.h5 -trainrlessd4_slices/patient092_frame01_slice_10.h5 -trainrlessd4_slices/patient092_frame01_slice_11.h5 -trainrlessd4_slices/patient092_frame01_slice_12.h5 -trainrlessd4_slices/patient092_frame01_slice_13.h5 -trainrlessd4_slices/patient092_frame01_slice_14.h5 -trainrlessd4_slices/patient092_frame01_slice_2.h5 -trainrlessd4_slices/patient092_frame01_slice_3.h5 -trainrlessd4_slices/patient092_frame01_slice_4.h5 -trainrlessd4_slices/patient092_frame01_slice_5.h5 -trainrlessd4_slices/patient092_frame01_slice_6.h5 -trainrlessd4_slices/patient092_frame01_slice_7.h5 -trainrlessd4_slices/patient092_frame01_slice_8.h5 -trainrlessd4_slices/patient092_frame01_slice_9.h5 -trainrlessd4_slices/patient092_frame06_slice_0.h5 -trainrlessd4_slices/patient092_frame06_slice_1.h5 -trainrlessd4_slices/patient092_frame06_slice_10.h5 -trainrlessd4_slices/patient092_frame06_slice_11.h5 -trainrlessd4_slices/patient092_frame06_slice_12.h5 -trainrlessd4_slices/patient092_frame06_slice_13.h5 -trainrlessd4_slices/patient092_frame06_slice_14.h5 -trainrlessd4_slices/patient092_frame06_slice_2.h5 -trainrlessd4_slices/patient092_frame06_slice_3.h5 -trainrlessd4_slices/patient092_frame06_slice_4.h5 -trainrlessd4_slices/patient092_frame06_slice_5.h5 -trainrlessd4_slices/patient092_frame06_slice_6.h5 -trainrlessd4_slices/patient092_frame06_slice_7.h5 -trainrlessd4_slices/patient092_frame06_slice_8.h5 -trainrlessd4_slices/patient092_frame06_slice_9.h5 -trainrlessd4_slices/patient093_frame14_slice_0.h5 -trainrlessd4_slices/patient093_frame14_slice_1.h5 -trainrlessd4_slices/patient093_frame14_slice_2.h5 -trainrlessd4_slices/patient093_frame14_slice_3.h5 -trainrlessd4_slices/patient093_frame14_slice_4.h5 -trainrlessd4_slices/patient093_frame14_slice_5.h5 -trainrlessd4_slices/patient093_frame14_slice_6.h5 -trainrlessd4_slices/patient093_frame14_slice_7.h5 -trainrlessd4_slices/patient093_frame14_slice_8.h5 -trainrlessd4_slices/patient093_frame14_slice_9.h5 -trainrlessd4_slices/patient095_frame01_slice_0.h5 -trainrlessd4_slices/patient095_frame01_slice_1.h5 -trainrlessd4_slices/patient095_frame01_slice_10.h5 -trainrlessd4_slices/patient095_frame01_slice_11.h5 -trainrlessd4_slices/patient095_frame01_slice_12.h5 -trainrlessd4_slices/patient095_frame01_slice_13.h5 -trainrlessd4_slices/patient095_frame01_slice_2.h5 -trainrlessd4_slices/patient095_frame01_slice_3.h5 -trainrlessd4_slices/patient095_frame01_slice_4.h5 -trainrlessd4_slices/patient095_frame01_slice_5.h5 -trainrlessd4_slices/patient095_frame01_slice_6.h5 -trainrlessd4_slices/patient095_frame01_slice_7.h5 -trainrlessd4_slices/patient095_frame01_slice_8.h5 -trainrlessd4_slices/patient095_frame01_slice_9.h5 -trainrlessd4_slices/patient095_frame12_slice_0.h5 -trainrlessd4_slices/patient095_frame12_slice_1.h5 -trainrlessd4_slices/patient095_frame12_slice_10.h5 -trainrlessd4_slices/patient095_frame12_slice_11.h5 -trainrlessd4_slices/patient095_frame12_slice_12.h5 -trainrlessd4_slices/patient095_frame12_slice_13.h5 -trainrlessd4_slices/patient095_frame12_slice_2.h5 -trainrlessd4_slices/patient095_frame12_slice_3.h5 -trainrlessd4_slices/patient095_frame12_slice_4.h5 -trainrlessd4_slices/patient095_frame12_slice_5.h5 -trainrlessd4_slices/patient095_frame12_slice_6.h5 -trainrlessd4_slices/patient095_frame12_slice_7.h5 -trainrlessd4_slices/patient095_frame12_slice_8.h5 -trainrlessd4_slices/patient095_frame12_slice_9.h5 -trainrlessd4_slices/patient096_frame08_slice_0.h5 -trainrlessd4_slices/patient096_frame08_slice_1.h5 -trainrlessd4_slices/patient096_frame08_slice_10.h5 -trainrlessd4_slices/patient096_frame08_slice_11.h5 -trainrlessd4_slices/patient096_frame08_slice_12.h5 -trainrlessd4_slices/patient096_frame08_slice_13.h5 -trainrlessd4_slices/patient096_frame08_slice_14.h5 -trainrlessd4_slices/patient096_frame08_slice_15.h5 -trainrlessd4_slices/patient096_frame08_slice_16.h5 -trainrlessd4_slices/patient096_frame08_slice_17.h5 -trainrlessd4_slices/patient096_frame08_slice_2.h5 -trainrlessd4_slices/patient096_frame08_slice_3.h5 -trainrlessd4_slices/patient096_frame08_slice_4.h5 -trainrlessd4_slices/patient096_frame08_slice_5.h5 -trainrlessd4_slices/patient096_frame08_slice_6.h5 -trainrlessd4_slices/patient096_frame08_slice_7.h5 -trainrlessd4_slices/patient096_frame08_slice_8.h5 -trainrlessd4_slices/patient096_frame08_slice_9.h5 -trainrlessd4_slices/patient097_frame01_slice_0.h5 -trainrlessd4_slices/patient097_frame01_slice_1.h5 -trainrlessd4_slices/patient097_frame01_slice_2.h5 -trainrlessd4_slices/patient097_frame01_slice_3.h5 -trainrlessd4_slices/patient097_frame01_slice_4.h5 -trainrlessd4_slices/patient097_frame01_slice_5.h5 -trainrlessd4_slices/patient097_frame01_slice_6.h5 -trainrlessd4_slices/patient097_frame01_slice_7.h5 -trainrlessd4_slices/patient097_frame11_slice_0.h5 -trainrlessd4_slices/patient097_frame11_slice_1.h5 -trainrlessd4_slices/patient097_frame11_slice_2.h5 -trainrlessd4_slices/patient097_frame11_slice_3.h5 -trainrlessd4_slices/patient097_frame11_slice_4.h5 -trainrlessd4_slices/patient097_frame11_slice_5.h5 -trainrlessd4_slices/patient097_frame11_slice_6.h5 -trainrlessd4_slices/patient097_frame11_slice_7.h5 -trainrlessd4_slices/patient099_frame01_slice_0.h5 -trainrlessd4_slices/patient099_frame01_slice_1.h5 -trainrlessd4_slices/patient099_frame01_slice_10.h5 -trainrlessd4_slices/patient099_frame01_slice_11.h5 -trainrlessd4_slices/patient099_frame01_slice_12.h5 -trainrlessd4_slices/patient099_frame01_slice_13.h5 -trainrlessd4_slices/patient099_frame01_slice_14.h5 -trainrlessd4_slices/patient099_frame01_slice_15.h5 -trainrlessd4_slices/patient099_frame01_slice_2.h5 -trainrlessd4_slices/patient099_frame01_slice_3.h5 -trainrlessd4_slices/patient099_frame01_slice_4.h5 -trainrlessd4_slices/patient099_frame01_slice_5.h5 -trainrlessd4_slices/patient099_frame01_slice_6.h5 -trainrlessd4_slices/patient099_frame01_slice_7.h5 -trainrlessd4_slices/patient099_frame01_slice_8.h5 -trainrlessd4_slices/patient099_frame01_slice_9.h5 -trainrlessd4_slices/patient099_frame09_slice_0.h5 -trainrlessd4_slices/patient099_frame09_slice_1.h5 -trainrlessd4_slices/patient099_frame09_slice_10.h5 -trainrlessd4_slices/patient099_frame09_slice_11.h5 -trainrlessd4_slices/patient099_frame09_slice_12.h5 -trainrlessd4_slices/patient099_frame09_slice_13.h5 -trainrlessd4_slices/patient099_frame09_slice_14.h5 -trainrlessd4_slices/patient099_frame09_slice_15.h5 -trainrlessd4_slices/patient099_frame09_slice_2.h5 -trainrlessd4_slices/patient099_frame09_slice_3.h5 -trainrlessd4_slices/patient099_frame09_slice_4.h5 -trainrlessd4_slices/patient099_frame09_slice_5.h5 -trainrlessd4_slices/patient099_frame09_slice_6.h5 -trainrlessd4_slices/patient099_frame09_slice_7.h5 -trainrlessd4_slices/patient099_frame09_slice_8.h5 -trainrlessd4_slices/patient099_frame09_slice_9.h5 -trainrlessd4_slices/patient100_frame01_slice_0.h5 -trainrlessd4_slices/patient100_frame01_slice_1.h5 -trainrlessd4_slices/patient100_frame01_slice_2.h5 -trainrlessd4_slices/patient100_frame01_slice_3.h5 -trainrlessd4_slices/patient100_frame01_slice_4.h5 -trainrlessd4_slices/patient100_frame01_slice_5.h5 -trainrlessd4_slices/patient100_frame01_slice_6.h5 -trainrlessd4_slices/patient100_frame01_slice_7.h5 -trainrlessd4_slices/patient100_frame13_slice_0.h5 -trainrlessd4_slices/patient100_frame13_slice_1.h5 -trainrlessd4_slices/patient100_frame13_slice_2.h5 -trainrlessd4_slices/patient100_frame13_slice_3.h5 -trainrlessd4_slices/patient100_frame13_slice_4.h5 -trainrlessd4_slices/patient100_frame13_slice_5.h5 -trainrlessd4_slices/patient100_frame13_slice_6.h5 -trainrlessd4_slices/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/trainrlessd8.txt b/data/ACDC2017/ACDC_for2D/trainrlessd8.txt deleted file mode 100644 index 2d2fd6f..0000000 --- a/data/ACDC2017/ACDC_for2D/trainrlessd8.txt +++ /dev/null @@ -1,1356 +0,0 @@ -trainrlessd8_slices/patient001_frame01_slice_0.h5 -trainrlessd8_slices/patient001_frame01_slice_1.h5 -trainrlessd8_slices/patient001_frame01_slice_2.h5 -trainrlessd8_slices/patient001_frame01_slice_3.h5 -trainrlessd8_slices/patient001_frame01_slice_4.h5 -trainrlessd8_slices/patient001_frame01_slice_5.h5 -trainrlessd8_slices/patient001_frame01_slice_6.h5 -trainrlessd8_slices/patient001_frame01_slice_7.h5 -trainrlessd8_slices/patient001_frame01_slice_8.h5 -trainrlessd8_slices/patient001_frame01_slice_9.h5 -trainrlessd8_slices/patient001_frame12_slice_0.h5 -trainrlessd8_slices/patient001_frame12_slice_1.h5 -trainrlessd8_slices/patient001_frame12_slice_2.h5 -trainrlessd8_slices/patient001_frame12_slice_3.h5 -trainrlessd8_slices/patient001_frame12_slice_4.h5 -trainrlessd8_slices/patient001_frame12_slice_5.h5 -trainrlessd8_slices/patient001_frame12_slice_6.h5 -trainrlessd8_slices/patient001_frame12_slice_7.h5 -trainrlessd8_slices/patient001_frame12_slice_8.h5 -trainrlessd8_slices/patient001_frame12_slice_9.h5 -trainrlessd8_slices/patient002_frame01_slice_0.h5 -trainrlessd8_slices/patient002_frame01_slice_1.h5 -trainrlessd8_slices/patient002_frame01_slice_2.h5 -trainrlessd8_slices/patient002_frame01_slice_3.h5 -trainrlessd8_slices/patient002_frame01_slice_4.h5 -trainrlessd8_slices/patient002_frame01_slice_5.h5 -trainrlessd8_slices/patient002_frame01_slice_6.h5 -trainrlessd8_slices/patient002_frame01_slice_7.h5 -trainrlessd8_slices/patient002_frame01_slice_8.h5 -trainrlessd8_slices/patient002_frame01_slice_9.h5 -trainrlessd8_slices/patient002_frame12_slice_0.h5 -trainrlessd8_slices/patient002_frame12_slice_1.h5 -trainrlessd8_slices/patient002_frame12_slice_2.h5 -trainrlessd8_slices/patient002_frame12_slice_3.h5 -trainrlessd8_slices/patient002_frame12_slice_4.h5 -trainrlessd8_slices/patient002_frame12_slice_5.h5 -trainrlessd8_slices/patient002_frame12_slice_6.h5 -trainrlessd8_slices/patient002_frame12_slice_7.h5 -trainrlessd8_slices/patient002_frame12_slice_8.h5 -trainrlessd8_slices/patient002_frame12_slice_9.h5 -trainrlessd8_slices/patient003_frame01_slice_0.h5 -trainrlessd8_slices/patient003_frame01_slice_1.h5 -trainrlessd8_slices/patient003_frame01_slice_2.h5 -trainrlessd8_slices/patient003_frame01_slice_3.h5 -trainrlessd8_slices/patient003_frame01_slice_4.h5 -trainrlessd8_slices/patient003_frame01_slice_5.h5 -trainrlessd8_slices/patient003_frame01_slice_6.h5 -trainrlessd8_slices/patient003_frame01_slice_7.h5 -trainrlessd8_slices/patient003_frame01_slice_8.h5 -trainrlessd8_slices/patient003_frame01_slice_9.h5 -trainrlessd8_slices/patient003_frame15_slice_0.h5 -trainrlessd8_slices/patient003_frame15_slice_1.h5 -trainrlessd8_slices/patient003_frame15_slice_2.h5 -trainrlessd8_slices/patient003_frame15_slice_3.h5 -trainrlessd8_slices/patient003_frame15_slice_4.h5 -trainrlessd8_slices/patient003_frame15_slice_5.h5 -trainrlessd8_slices/patient003_frame15_slice_6.h5 -trainrlessd8_slices/patient003_frame15_slice_7.h5 -trainrlessd8_slices/patient003_frame15_slice_8.h5 -trainrlessd8_slices/patient003_frame15_slice_9.h5 -trainrlessd8_slices/patient004_frame01_slice_0.h5 -trainrlessd8_slices/patient004_frame01_slice_1.h5 -trainrlessd8_slices/patient004_frame01_slice_2.h5 -trainrlessd8_slices/patient004_frame01_slice_3.h5 -trainrlessd8_slices/patient004_frame01_slice_4.h5 -trainrlessd8_slices/patient004_frame01_slice_5.h5 -trainrlessd8_slices/patient004_frame01_slice_6.h5 -trainrlessd8_slices/patient004_frame01_slice_7.h5 -trainrlessd8_slices/patient004_frame01_slice_8.h5 -trainrlessd8_slices/patient004_frame01_slice_9.h5 -trainrlessd8_slices/patient005_frame01_slice_0.h5 -trainrlessd8_slices/patient005_frame01_slice_1.h5 -trainrlessd8_slices/patient005_frame01_slice_2.h5 -trainrlessd8_slices/patient005_frame01_slice_3.h5 -trainrlessd8_slices/patient005_frame01_slice_4.h5 -trainrlessd8_slices/patient005_frame01_slice_5.h5 -trainrlessd8_slices/patient005_frame01_slice_6.h5 -trainrlessd8_slices/patient005_frame01_slice_7.h5 -trainrlessd8_slices/patient005_frame01_slice_8.h5 -trainrlessd8_slices/patient005_frame01_slice_9.h5 -trainrlessd8_slices/patient005_frame13_slice_0.h5 -trainrlessd8_slices/patient005_frame13_slice_1.h5 -trainrlessd8_slices/patient005_frame13_slice_2.h5 -trainrlessd8_slices/patient005_frame13_slice_3.h5 -trainrlessd8_slices/patient005_frame13_slice_4.h5 -trainrlessd8_slices/patient005_frame13_slice_5.h5 -trainrlessd8_slices/patient005_frame13_slice_6.h5 -trainrlessd8_slices/patient005_frame13_slice_7.h5 -trainrlessd8_slices/patient005_frame13_slice_8.h5 -trainrlessd8_slices/patient005_frame13_slice_9.h5 -trainrlessd8_slices/patient006_frame16_slice_0.h5 -trainrlessd8_slices/patient006_frame16_slice_1.h5 -trainrlessd8_slices/patient006_frame16_slice_10.h5 -trainrlessd8_slices/patient006_frame16_slice_2.h5 -trainrlessd8_slices/patient006_frame16_slice_3.h5 -trainrlessd8_slices/patient006_frame16_slice_4.h5 -trainrlessd8_slices/patient006_frame16_slice_5.h5 -trainrlessd8_slices/patient006_frame16_slice_6.h5 -trainrlessd8_slices/patient006_frame16_slice_7.h5 -trainrlessd8_slices/patient006_frame16_slice_8.h5 -trainrlessd8_slices/patient006_frame16_slice_9.h5 -trainrlessd8_slices/patient007_frame01_slice_0.h5 -trainrlessd8_slices/patient007_frame01_slice_1.h5 -trainrlessd8_slices/patient007_frame01_slice_2.h5 -trainrlessd8_slices/patient007_frame01_slice_3.h5 -trainrlessd8_slices/patient007_frame01_slice_4.h5 -trainrlessd8_slices/patient007_frame01_slice_5.h5 -trainrlessd8_slices/patient007_frame01_slice_6.h5 -trainrlessd8_slices/patient007_frame01_slice_7.h5 -trainrlessd8_slices/patient007_frame01_slice_8.h5 -trainrlessd8_slices/patient007_frame01_slice_9.h5 -trainrlessd8_slices/patient007_frame07_slice_0.h5 -trainrlessd8_slices/patient007_frame07_slice_1.h5 -trainrlessd8_slices/patient007_frame07_slice_2.h5 -trainrlessd8_slices/patient007_frame07_slice_3.h5 -trainrlessd8_slices/patient007_frame07_slice_4.h5 -trainrlessd8_slices/patient007_frame07_slice_5.h5 -trainrlessd8_slices/patient007_frame07_slice_6.h5 -trainrlessd8_slices/patient007_frame07_slice_7.h5 -trainrlessd8_slices/patient007_frame07_slice_8.h5 -trainrlessd8_slices/patient007_frame07_slice_9.h5 -trainrlessd8_slices/patient008_frame13_slice_0.h5 -trainrlessd8_slices/patient008_frame13_slice_1.h5 -trainrlessd8_slices/patient008_frame13_slice_2.h5 -trainrlessd8_slices/patient008_frame13_slice_3.h5 -trainrlessd8_slices/patient008_frame13_slice_4.h5 -trainrlessd8_slices/patient008_frame13_slice_5.h5 -trainrlessd8_slices/patient008_frame13_slice_6.h5 -trainrlessd8_slices/patient008_frame13_slice_7.h5 -trainrlessd8_slices/patient008_frame13_slice_8.h5 -trainrlessd8_slices/patient008_frame13_slice_9.h5 -trainrlessd8_slices/patient009_frame01_slice_0.h5 -trainrlessd8_slices/patient009_frame01_slice_1.h5 -trainrlessd8_slices/patient009_frame01_slice_2.h5 -trainrlessd8_slices/patient009_frame01_slice_3.h5 -trainrlessd8_slices/patient009_frame01_slice_4.h5 -trainrlessd8_slices/patient009_frame01_slice_5.h5 -trainrlessd8_slices/patient009_frame01_slice_6.h5 -trainrlessd8_slices/patient009_frame01_slice_7.h5 -trainrlessd8_slices/patient009_frame01_slice_8.h5 -trainrlessd8_slices/patient009_frame01_slice_9.h5 -trainrlessd8_slices/patient010_frame01_slice_0.h5 -trainrlessd8_slices/patient010_frame01_slice_1.h5 -trainrlessd8_slices/patient010_frame01_slice_2.h5 -trainrlessd8_slices/patient010_frame01_slice_3.h5 -trainrlessd8_slices/patient010_frame01_slice_4.h5 -trainrlessd8_slices/patient010_frame01_slice_5.h5 -trainrlessd8_slices/patient010_frame01_slice_6.h5 -trainrlessd8_slices/patient010_frame01_slice_7.h5 -trainrlessd8_slices/patient010_frame01_slice_8.h5 -trainrlessd8_slices/patient010_frame01_slice_9.h5 -trainrlessd8_slices/patient010_frame13_slice_0.h5 -trainrlessd8_slices/patient010_frame13_slice_1.h5 -trainrlessd8_slices/patient010_frame13_slice_2.h5 -trainrlessd8_slices/patient010_frame13_slice_3.h5 -trainrlessd8_slices/patient010_frame13_slice_4.h5 -trainrlessd8_slices/patient010_frame13_slice_5.h5 -trainrlessd8_slices/patient010_frame13_slice_6.h5 -trainrlessd8_slices/patient010_frame13_slice_7.h5 -trainrlessd8_slices/patient010_frame13_slice_8.h5 -trainrlessd8_slices/patient010_frame13_slice_9.h5 -trainrlessd8_slices/patient011_frame01_slice_0.h5 -trainrlessd8_slices/patient011_frame01_slice_1.h5 -trainrlessd8_slices/patient011_frame01_slice_2.h5 -trainrlessd8_slices/patient011_frame01_slice_3.h5 -trainrlessd8_slices/patient011_frame01_slice_4.h5 -trainrlessd8_slices/patient011_frame01_slice_5.h5 -trainrlessd8_slices/patient011_frame01_slice_6.h5 -trainrlessd8_slices/patient011_frame01_slice_7.h5 -trainrlessd8_slices/patient011_frame01_slice_8.h5 -trainrlessd8_slices/patient011_frame08_slice_0.h5 -trainrlessd8_slices/patient011_frame08_slice_1.h5 -trainrlessd8_slices/patient011_frame08_slice_2.h5 -trainrlessd8_slices/patient011_frame08_slice_3.h5 -trainrlessd8_slices/patient011_frame08_slice_4.h5 -trainrlessd8_slices/patient011_frame08_slice_5.h5 -trainrlessd8_slices/patient011_frame08_slice_6.h5 -trainrlessd8_slices/patient011_frame08_slice_7.h5 -trainrlessd8_slices/patient011_frame08_slice_8.h5 -trainrlessd8_slices/patient012_frame01_slice_0.h5 -trainrlessd8_slices/patient012_frame01_slice_1.h5 -trainrlessd8_slices/patient012_frame01_slice_2.h5 -trainrlessd8_slices/patient012_frame01_slice_3.h5 -trainrlessd8_slices/patient012_frame01_slice_4.h5 -trainrlessd8_slices/patient012_frame01_slice_5.h5 -trainrlessd8_slices/patient012_frame01_slice_6.h5 -trainrlessd8_slices/patient012_frame01_slice_7.h5 -trainrlessd8_slices/patient012_frame01_slice_8.h5 -trainrlessd8_slices/patient012_frame01_slice_9.h5 -trainrlessd8_slices/patient013_frame01_slice_0.h5 -trainrlessd8_slices/patient013_frame01_slice_1.h5 -trainrlessd8_slices/patient013_frame01_slice_2.h5 -trainrlessd8_slices/patient013_frame01_slice_3.h5 -trainrlessd8_slices/patient013_frame01_slice_4.h5 -trainrlessd8_slices/patient013_frame01_slice_5.h5 -trainrlessd8_slices/patient013_frame01_slice_6.h5 -trainrlessd8_slices/patient013_frame01_slice_7.h5 -trainrlessd8_slices/patient013_frame01_slice_8.h5 -trainrlessd8_slices/patient013_frame01_slice_9.h5 -trainrlessd8_slices/patient014_frame13_slice_0.h5 -trainrlessd8_slices/patient014_frame13_slice_1.h5 -trainrlessd8_slices/patient014_frame13_slice_2.h5 -trainrlessd8_slices/patient014_frame13_slice_3.h5 -trainrlessd8_slices/patient014_frame13_slice_4.h5 -trainrlessd8_slices/patient014_frame13_slice_5.h5 -trainrlessd8_slices/patient014_frame13_slice_6.h5 -trainrlessd8_slices/patient014_frame13_slice_7.h5 -trainrlessd8_slices/patient014_frame13_slice_8.h5 -trainrlessd8_slices/patient014_frame13_slice_9.h5 -trainrlessd8_slices/patient015_frame10_slice_0.h5 -trainrlessd8_slices/patient015_frame10_slice_1.h5 -trainrlessd8_slices/patient015_frame10_slice_2.h5 -trainrlessd8_slices/patient015_frame10_slice_3.h5 -trainrlessd8_slices/patient015_frame10_slice_4.h5 -trainrlessd8_slices/patient015_frame10_slice_5.h5 -trainrlessd8_slices/patient015_frame10_slice_6.h5 -trainrlessd8_slices/patient015_frame10_slice_7.h5 -trainrlessd8_slices/patient015_frame10_slice_8.h5 -trainrlessd8_slices/patient016_frame12_slice_0.h5 -trainrlessd8_slices/patient016_frame12_slice_1.h5 -trainrlessd8_slices/patient016_frame12_slice_2.h5 -trainrlessd8_slices/patient016_frame12_slice_3.h5 -trainrlessd8_slices/patient016_frame12_slice_4.h5 -trainrlessd8_slices/patient016_frame12_slice_5.h5 -trainrlessd8_slices/patient016_frame12_slice_6.h5 -trainrlessd8_slices/patient016_frame12_slice_7.h5 -trainrlessd8_slices/patient016_frame12_slice_8.h5 -trainrlessd8_slices/patient016_frame12_slice_9.h5 -trainrlessd8_slices/patient017_frame01_slice_0.h5 -trainrlessd8_slices/patient017_frame01_slice_1.h5 -trainrlessd8_slices/patient017_frame01_slice_2.h5 -trainrlessd8_slices/patient017_frame01_slice_3.h5 -trainrlessd8_slices/patient017_frame01_slice_4.h5 -trainrlessd8_slices/patient017_frame01_slice_5.h5 -trainrlessd8_slices/patient017_frame01_slice_6.h5 -trainrlessd8_slices/patient017_frame01_slice_7.h5 -trainrlessd8_slices/patient017_frame01_slice_8.h5 -trainrlessd8_slices/patient017_frame09_slice_0.h5 -trainrlessd8_slices/patient017_frame09_slice_1.h5 -trainrlessd8_slices/patient017_frame09_slice_2.h5 -trainrlessd8_slices/patient017_frame09_slice_3.h5 -trainrlessd8_slices/patient017_frame09_slice_4.h5 -trainrlessd8_slices/patient017_frame09_slice_5.h5 -trainrlessd8_slices/patient017_frame09_slice_6.h5 -trainrlessd8_slices/patient017_frame09_slice_7.h5 -trainrlessd8_slices/patient017_frame09_slice_8.h5 -trainrlessd8_slices/patient018_frame01_slice_0.h5 -trainrlessd8_slices/patient018_frame01_slice_1.h5 -trainrlessd8_slices/patient018_frame01_slice_2.h5 -trainrlessd8_slices/patient018_frame01_slice_3.h5 -trainrlessd8_slices/patient018_frame01_slice_4.h5 -trainrlessd8_slices/patient018_frame01_slice_5.h5 -trainrlessd8_slices/patient018_frame01_slice_6.h5 -trainrlessd8_slices/patient018_frame01_slice_7.h5 -trainrlessd8_slices/patient018_frame10_slice_0.h5 -trainrlessd8_slices/patient018_frame10_slice_1.h5 -trainrlessd8_slices/patient018_frame10_slice_2.h5 -trainrlessd8_slices/patient018_frame10_slice_3.h5 -trainrlessd8_slices/patient018_frame10_slice_4.h5 -trainrlessd8_slices/patient018_frame10_slice_5.h5 -trainrlessd8_slices/patient018_frame10_slice_6.h5 -trainrlessd8_slices/patient018_frame10_slice_7.h5 -trainrlessd8_slices/patient019_frame11_slice_0.h5 -trainrlessd8_slices/patient019_frame11_slice_1.h5 -trainrlessd8_slices/patient019_frame11_slice_10.h5 -trainrlessd8_slices/patient019_frame11_slice_2.h5 -trainrlessd8_slices/patient019_frame11_slice_3.h5 -trainrlessd8_slices/patient019_frame11_slice_4.h5 -trainrlessd8_slices/patient019_frame11_slice_5.h5 -trainrlessd8_slices/patient019_frame11_slice_6.h5 -trainrlessd8_slices/patient019_frame11_slice_7.h5 -trainrlessd8_slices/patient019_frame11_slice_8.h5 -trainrlessd8_slices/patient019_frame11_slice_9.h5 -trainrlessd8_slices/patient020_frame01_slice_0.h5 -trainrlessd8_slices/patient020_frame01_slice_1.h5 -trainrlessd8_slices/patient020_frame01_slice_2.h5 -trainrlessd8_slices/patient020_frame01_slice_3.h5 -trainrlessd8_slices/patient020_frame01_slice_4.h5 -trainrlessd8_slices/patient020_frame01_slice_5.h5 -trainrlessd8_slices/patient020_frame01_slice_6.h5 -trainrlessd8_slices/patient020_frame01_slice_7.h5 -trainrlessd8_slices/patient021_frame01_slice_0.h5 -trainrlessd8_slices/patient021_frame01_slice_1.h5 -trainrlessd8_slices/patient021_frame01_slice_2.h5 -trainrlessd8_slices/patient021_frame01_slice_3.h5 -trainrlessd8_slices/patient021_frame01_slice_4.h5 -trainrlessd8_slices/patient021_frame01_slice_5.h5 -trainrlessd8_slices/patient021_frame01_slice_6.h5 -trainrlessd8_slices/patient021_frame01_slice_7.h5 -trainrlessd8_slices/patient021_frame01_slice_8.h5 -trainrlessd8_slices/patient021_frame01_slice_9.h5 -trainrlessd8_slices/patient021_frame13_slice_0.h5 -trainrlessd8_slices/patient021_frame13_slice_1.h5 -trainrlessd8_slices/patient021_frame13_slice_2.h5 -trainrlessd8_slices/patient021_frame13_slice_3.h5 -trainrlessd8_slices/patient021_frame13_slice_4.h5 -trainrlessd8_slices/patient021_frame13_slice_5.h5 -trainrlessd8_slices/patient021_frame13_slice_6.h5 -trainrlessd8_slices/patient021_frame13_slice_7.h5 -trainrlessd8_slices/patient021_frame13_slice_8.h5 -trainrlessd8_slices/patient021_frame13_slice_9.h5 -trainrlessd8_slices/patient022_frame01_slice_0.h5 -trainrlessd8_slices/patient022_frame01_slice_1.h5 -trainrlessd8_slices/patient022_frame01_slice_2.h5 -trainrlessd8_slices/patient022_frame01_slice_3.h5 -trainrlessd8_slices/patient022_frame01_slice_4.h5 -trainrlessd8_slices/patient022_frame01_slice_5.h5 -trainrlessd8_slices/patient022_frame01_slice_6.h5 -trainrlessd8_slices/patient022_frame11_slice_0.h5 -trainrlessd8_slices/patient022_frame11_slice_1.h5 -trainrlessd8_slices/patient022_frame11_slice_2.h5 -trainrlessd8_slices/patient022_frame11_slice_3.h5 -trainrlessd8_slices/patient022_frame11_slice_4.h5 -trainrlessd8_slices/patient022_frame11_slice_5.h5 -trainrlessd8_slices/patient022_frame11_slice_6.h5 -trainrlessd8_slices/patient023_frame01_slice_0.h5 -trainrlessd8_slices/patient023_frame01_slice_1.h5 -trainrlessd8_slices/patient023_frame01_slice_2.h5 -trainrlessd8_slices/patient023_frame01_slice_3.h5 -trainrlessd8_slices/patient023_frame01_slice_4.h5 -trainrlessd8_slices/patient023_frame01_slice_5.h5 -trainrlessd8_slices/patient023_frame01_slice_6.h5 -trainrlessd8_slices/patient023_frame01_slice_7.h5 -trainrlessd8_slices/patient023_frame01_slice_8.h5 -trainrlessd8_slices/patient024_frame09_slice_0.h5 -trainrlessd8_slices/patient024_frame09_slice_1.h5 -trainrlessd8_slices/patient024_frame09_slice_2.h5 -trainrlessd8_slices/patient024_frame09_slice_3.h5 -trainrlessd8_slices/patient024_frame09_slice_4.h5 -trainrlessd8_slices/patient024_frame09_slice_5.h5 -trainrlessd8_slices/patient024_frame09_slice_6.h5 -trainrlessd8_slices/patient024_frame09_slice_7.h5 -trainrlessd8_slices/patient025_frame01_slice_0.h5 -trainrlessd8_slices/patient025_frame01_slice_1.h5 -trainrlessd8_slices/patient025_frame01_slice_2.h5 -trainrlessd8_slices/patient025_frame01_slice_3.h5 -trainrlessd8_slices/patient025_frame01_slice_4.h5 -trainrlessd8_slices/patient025_frame01_slice_5.h5 -trainrlessd8_slices/patient025_frame01_slice_6.h5 -trainrlessd8_slices/patient025_frame01_slice_7.h5 -trainrlessd8_slices/patient025_frame01_slice_8.h5 -trainrlessd8_slices/patient026_frame01_slice_0.h5 -trainrlessd8_slices/patient026_frame01_slice_1.h5 -trainrlessd8_slices/patient026_frame01_slice_2.h5 -trainrlessd8_slices/patient026_frame01_slice_3.h5 -trainrlessd8_slices/patient026_frame01_slice_4.h5 -trainrlessd8_slices/patient026_frame01_slice_5.h5 -trainrlessd8_slices/patient026_frame01_slice_6.h5 -trainrlessd8_slices/patient026_frame01_slice_7.h5 -trainrlessd8_slices/patient026_frame01_slice_8.h5 -trainrlessd8_slices/patient026_frame01_slice_9.h5 -trainrlessd8_slices/patient026_frame12_slice_0.h5 -trainrlessd8_slices/patient026_frame12_slice_1.h5 -trainrlessd8_slices/patient026_frame12_slice_2.h5 -trainrlessd8_slices/patient026_frame12_slice_3.h5 -trainrlessd8_slices/patient026_frame12_slice_4.h5 -trainrlessd8_slices/patient026_frame12_slice_5.h5 -trainrlessd8_slices/patient026_frame12_slice_6.h5 -trainrlessd8_slices/patient026_frame12_slice_7.h5 -trainrlessd8_slices/patient026_frame12_slice_8.h5 -trainrlessd8_slices/patient026_frame12_slice_9.h5 -trainrlessd8_slices/patient027_frame01_slice_0.h5 -trainrlessd8_slices/patient027_frame01_slice_1.h5 -trainrlessd8_slices/patient027_frame01_slice_2.h5 -trainrlessd8_slices/patient027_frame01_slice_3.h5 -trainrlessd8_slices/patient027_frame01_slice_4.h5 -trainrlessd8_slices/patient027_frame01_slice_5.h5 -trainrlessd8_slices/patient027_frame01_slice_6.h5 -trainrlessd8_slices/patient027_frame01_slice_7.h5 -trainrlessd8_slices/patient027_frame01_slice_8.h5 -trainrlessd8_slices/patient027_frame01_slice_9.h5 -trainrlessd8_slices/patient027_frame11_slice_0.h5 -trainrlessd8_slices/patient027_frame11_slice_1.h5 -trainrlessd8_slices/patient027_frame11_slice_2.h5 -trainrlessd8_slices/patient027_frame11_slice_3.h5 -trainrlessd8_slices/patient027_frame11_slice_4.h5 -trainrlessd8_slices/patient027_frame11_slice_5.h5 -trainrlessd8_slices/patient027_frame11_slice_6.h5 -trainrlessd8_slices/patient027_frame11_slice_7.h5 -trainrlessd8_slices/patient027_frame11_slice_8.h5 -trainrlessd8_slices/patient027_frame11_slice_9.h5 -trainrlessd8_slices/patient028_frame01_slice_0.h5 -trainrlessd8_slices/patient028_frame01_slice_1.h5 -trainrlessd8_slices/patient028_frame01_slice_2.h5 -trainrlessd8_slices/patient028_frame01_slice_3.h5 -trainrlessd8_slices/patient028_frame01_slice_4.h5 -trainrlessd8_slices/patient028_frame01_slice_5.h5 -trainrlessd8_slices/patient028_frame01_slice_6.h5 -trainrlessd8_slices/patient028_frame01_slice_7.h5 -trainrlessd8_slices/patient028_frame01_slice_8.h5 -trainrlessd8_slices/patient028_frame01_slice_9.h5 -trainrlessd8_slices/patient028_frame09_slice_0.h5 -trainrlessd8_slices/patient028_frame09_slice_1.h5 -trainrlessd8_slices/patient028_frame09_slice_2.h5 -trainrlessd8_slices/patient028_frame09_slice_3.h5 -trainrlessd8_slices/patient028_frame09_slice_4.h5 -trainrlessd8_slices/patient028_frame09_slice_5.h5 -trainrlessd8_slices/patient028_frame09_slice_6.h5 -trainrlessd8_slices/patient028_frame09_slice_7.h5 -trainrlessd8_slices/patient028_frame09_slice_8.h5 -trainrlessd8_slices/patient028_frame09_slice_9.h5 -trainrlessd8_slices/patient029_frame12_slice_0.h5 -trainrlessd8_slices/patient029_frame12_slice_1.h5 -trainrlessd8_slices/patient029_frame12_slice_10.h5 -trainrlessd8_slices/patient029_frame12_slice_2.h5 -trainrlessd8_slices/patient029_frame12_slice_3.h5 -trainrlessd8_slices/patient029_frame12_slice_4.h5 -trainrlessd8_slices/patient029_frame12_slice_5.h5 -trainrlessd8_slices/patient029_frame12_slice_6.h5 -trainrlessd8_slices/patient029_frame12_slice_7.h5 -trainrlessd8_slices/patient029_frame12_slice_8.h5 -trainrlessd8_slices/patient029_frame12_slice_9.h5 -trainrlessd8_slices/patient030_frame12_slice_0.h5 -trainrlessd8_slices/patient030_frame12_slice_1.h5 -trainrlessd8_slices/patient030_frame12_slice_2.h5 -trainrlessd8_slices/patient030_frame12_slice_3.h5 -trainrlessd8_slices/patient030_frame12_slice_4.h5 -trainrlessd8_slices/patient030_frame12_slice_5.h5 -trainrlessd8_slices/patient030_frame12_slice_6.h5 -trainrlessd8_slices/patient030_frame12_slice_7.h5 -trainrlessd8_slices/patient030_frame12_slice_8.h5 -trainrlessd8_slices/patient030_frame12_slice_9.h5 -trainrlessd8_slices/patient031_frame01_slice_0.h5 -trainrlessd8_slices/patient031_frame01_slice_1.h5 -trainrlessd8_slices/patient031_frame01_slice_2.h5 -trainrlessd8_slices/patient031_frame01_slice_3.h5 -trainrlessd8_slices/patient031_frame01_slice_4.h5 -trainrlessd8_slices/patient031_frame01_slice_5.h5 -trainrlessd8_slices/patient031_frame01_slice_6.h5 -trainrlessd8_slices/patient031_frame01_slice_7.h5 -trainrlessd8_slices/patient031_frame01_slice_8.h5 -trainrlessd8_slices/patient031_frame01_slice_9.h5 -trainrlessd8_slices/patient032_frame12_slice_0.h5 -trainrlessd8_slices/patient032_frame12_slice_1.h5 -trainrlessd8_slices/patient032_frame12_slice_2.h5 -trainrlessd8_slices/patient032_frame12_slice_3.h5 -trainrlessd8_slices/patient032_frame12_slice_4.h5 -trainrlessd8_slices/patient032_frame12_slice_5.h5 -trainrlessd8_slices/patient032_frame12_slice_6.h5 -trainrlessd8_slices/patient032_frame12_slice_7.h5 -trainrlessd8_slices/patient032_frame12_slice_8.h5 -trainrlessd8_slices/patient032_frame12_slice_9.h5 -trainrlessd8_slices/patient033_frame01_slice_0.h5 -trainrlessd8_slices/patient033_frame01_slice_1.h5 -trainrlessd8_slices/patient033_frame01_slice_2.h5 -trainrlessd8_slices/patient033_frame01_slice_3.h5 -trainrlessd8_slices/patient033_frame01_slice_4.h5 -trainrlessd8_slices/patient033_frame01_slice_5.h5 -trainrlessd8_slices/patient033_frame01_slice_6.h5 -trainrlessd8_slices/patient033_frame01_slice_7.h5 -trainrlessd8_slices/patient033_frame01_slice_8.h5 -trainrlessd8_slices/patient033_frame01_slice_9.h5 -trainrlessd8_slices/patient033_frame14_slice_0.h5 -trainrlessd8_slices/patient033_frame14_slice_1.h5 -trainrlessd8_slices/patient033_frame14_slice_2.h5 -trainrlessd8_slices/patient033_frame14_slice_3.h5 -trainrlessd8_slices/patient033_frame14_slice_4.h5 -trainrlessd8_slices/patient033_frame14_slice_5.h5 -trainrlessd8_slices/patient033_frame14_slice_6.h5 -trainrlessd8_slices/patient033_frame14_slice_7.h5 -trainrlessd8_slices/patient033_frame14_slice_8.h5 -trainrlessd8_slices/patient033_frame14_slice_9.h5 -trainrlessd8_slices/patient034_frame01_slice_0.h5 -trainrlessd8_slices/patient034_frame01_slice_1.h5 -trainrlessd8_slices/patient034_frame01_slice_2.h5 -trainrlessd8_slices/patient034_frame01_slice_3.h5 -trainrlessd8_slices/patient034_frame01_slice_4.h5 -trainrlessd8_slices/patient034_frame01_slice_5.h5 -trainrlessd8_slices/patient034_frame01_slice_6.h5 -trainrlessd8_slices/patient034_frame01_slice_7.h5 -trainrlessd8_slices/patient034_frame01_slice_8.h5 -trainrlessd8_slices/patient034_frame01_slice_9.h5 -trainrlessd8_slices/patient035_frame01_slice_0.h5 -trainrlessd8_slices/patient035_frame01_slice_1.h5 -trainrlessd8_slices/patient035_frame01_slice_10.h5 -trainrlessd8_slices/patient035_frame01_slice_11.h5 -trainrlessd8_slices/patient035_frame01_slice_12.h5 -trainrlessd8_slices/patient035_frame01_slice_2.h5 -trainrlessd8_slices/patient035_frame01_slice_3.h5 -trainrlessd8_slices/patient035_frame01_slice_4.h5 -trainrlessd8_slices/patient035_frame01_slice_5.h5 -trainrlessd8_slices/patient035_frame01_slice_6.h5 -trainrlessd8_slices/patient035_frame01_slice_7.h5 -trainrlessd8_slices/patient035_frame01_slice_8.h5 -trainrlessd8_slices/patient035_frame01_slice_9.h5 -trainrlessd8_slices/patient035_frame11_slice_0.h5 -trainrlessd8_slices/patient035_frame11_slice_1.h5 -trainrlessd8_slices/patient035_frame11_slice_10.h5 -trainrlessd8_slices/patient035_frame11_slice_11.h5 -trainrlessd8_slices/patient035_frame11_slice_12.h5 -trainrlessd8_slices/patient035_frame11_slice_2.h5 -trainrlessd8_slices/patient035_frame11_slice_3.h5 -trainrlessd8_slices/patient035_frame11_slice_4.h5 -trainrlessd8_slices/patient035_frame11_slice_5.h5 -trainrlessd8_slices/patient035_frame11_slice_6.h5 -trainrlessd8_slices/patient035_frame11_slice_7.h5 -trainrlessd8_slices/patient035_frame11_slice_8.h5 -trainrlessd8_slices/patient035_frame11_slice_9.h5 -trainrlessd8_slices/patient036_frame12_slice_0.h5 -trainrlessd8_slices/patient036_frame12_slice_1.h5 -trainrlessd8_slices/patient036_frame12_slice_2.h5 -trainrlessd8_slices/patient036_frame12_slice_3.h5 -trainrlessd8_slices/patient036_frame12_slice_4.h5 -trainrlessd8_slices/patient036_frame12_slice_5.h5 -trainrlessd8_slices/patient036_frame12_slice_6.h5 -trainrlessd8_slices/patient036_frame12_slice_7.h5 -trainrlessd8_slices/patient037_frame01_slice_0.h5 -trainrlessd8_slices/patient037_frame01_slice_1.h5 -trainrlessd8_slices/patient037_frame01_slice_2.h5 -trainrlessd8_slices/patient037_frame01_slice_3.h5 -trainrlessd8_slices/patient037_frame01_slice_4.h5 -trainrlessd8_slices/patient037_frame01_slice_5.h5 -trainrlessd8_slices/patient037_frame01_slice_6.h5 -trainrlessd8_slices/patient037_frame12_slice_0.h5 -trainrlessd8_slices/patient037_frame12_slice_1.h5 -trainrlessd8_slices/patient037_frame12_slice_2.h5 -trainrlessd8_slices/patient037_frame12_slice_3.h5 -trainrlessd8_slices/patient037_frame12_slice_4.h5 -trainrlessd8_slices/patient037_frame12_slice_5.h5 -trainrlessd8_slices/patient037_frame12_slice_6.h5 -trainrlessd8_slices/patient038_frame01_slice_0.h5 -trainrlessd8_slices/patient038_frame01_slice_1.h5 -trainrlessd8_slices/patient038_frame01_slice_2.h5 -trainrlessd8_slices/patient038_frame01_slice_3.h5 -trainrlessd8_slices/patient038_frame01_slice_4.h5 -trainrlessd8_slices/patient038_frame01_slice_5.h5 -trainrlessd8_slices/patient038_frame01_slice_6.h5 -trainrlessd8_slices/patient038_frame01_slice_7.h5 -trainrlessd8_slices/patient039_frame01_slice_0.h5 -trainrlessd8_slices/patient039_frame01_slice_1.h5 -trainrlessd8_slices/patient039_frame01_slice_2.h5 -trainrlessd8_slices/patient039_frame01_slice_3.h5 -trainrlessd8_slices/patient039_frame01_slice_4.h5 -trainrlessd8_slices/patient039_frame01_slice_5.h5 -trainrlessd8_slices/patient039_frame01_slice_6.h5 -trainrlessd8_slices/patient039_frame01_slice_7.h5 -trainrlessd8_slices/patient039_frame01_slice_8.h5 -trainrlessd8_slices/patient039_frame10_slice_0.h5 -trainrlessd8_slices/patient039_frame10_slice_1.h5 -trainrlessd8_slices/patient039_frame10_slice_2.h5 -trainrlessd8_slices/patient039_frame10_slice_3.h5 -trainrlessd8_slices/patient039_frame10_slice_4.h5 -trainrlessd8_slices/patient039_frame10_slice_5.h5 -trainrlessd8_slices/patient039_frame10_slice_6.h5 -trainrlessd8_slices/patient039_frame10_slice_7.h5 -trainrlessd8_slices/patient039_frame10_slice_8.h5 -trainrlessd8_slices/patient040_frame01_slice_0.h5 -trainrlessd8_slices/patient040_frame01_slice_1.h5 -trainrlessd8_slices/patient040_frame01_slice_2.h5 -trainrlessd8_slices/patient040_frame01_slice_3.h5 -trainrlessd8_slices/patient040_frame01_slice_4.h5 -trainrlessd8_slices/patient040_frame01_slice_5.h5 -trainrlessd8_slices/patient040_frame01_slice_6.h5 -trainrlessd8_slices/patient040_frame01_slice_7.h5 -trainrlessd8_slices/patient040_frame01_slice_8.h5 -trainrlessd8_slices/patient040_frame01_slice_9.h5 -trainrlessd8_slices/patient041_frame01_slice_0.h5 -trainrlessd8_slices/patient041_frame01_slice_1.h5 -trainrlessd8_slices/patient041_frame01_slice_2.h5 -trainrlessd8_slices/patient041_frame01_slice_3.h5 -trainrlessd8_slices/patient041_frame01_slice_4.h5 -trainrlessd8_slices/patient041_frame01_slice_5.h5 -trainrlessd8_slices/patient041_frame11_slice_0.h5 -trainrlessd8_slices/patient041_frame11_slice_1.h5 -trainrlessd8_slices/patient041_frame11_slice_2.h5 -trainrlessd8_slices/patient041_frame11_slice_3.h5 -trainrlessd8_slices/patient041_frame11_slice_4.h5 -trainrlessd8_slices/patient041_frame11_slice_5.h5 -trainrlessd8_slices/patient042_frame01_slice_0.h5 -trainrlessd8_slices/patient042_frame01_slice_1.h5 -trainrlessd8_slices/patient042_frame01_slice_2.h5 -trainrlessd8_slices/patient042_frame01_slice_3.h5 -trainrlessd8_slices/patient042_frame01_slice_4.h5 -trainrlessd8_slices/patient042_frame01_slice_5.h5 -trainrlessd8_slices/patient042_frame01_slice_6.h5 -trainrlessd8_slices/patient042_frame01_slice_7.h5 -trainrlessd8_slices/patient042_frame01_slice_8.h5 -trainrlessd8_slices/patient042_frame16_slice_0.h5 -trainrlessd8_slices/patient042_frame16_slice_1.h5 -trainrlessd8_slices/patient042_frame16_slice_2.h5 -trainrlessd8_slices/patient042_frame16_slice_3.h5 -trainrlessd8_slices/patient042_frame16_slice_4.h5 -trainrlessd8_slices/patient042_frame16_slice_5.h5 -trainrlessd8_slices/patient042_frame16_slice_6.h5 -trainrlessd8_slices/patient042_frame16_slice_7.h5 -trainrlessd8_slices/patient042_frame16_slice_8.h5 -trainrlessd8_slices/patient043_frame01_slice_0.h5 -trainrlessd8_slices/patient043_frame01_slice_1.h5 -trainrlessd8_slices/patient043_frame01_slice_10.h5 -trainrlessd8_slices/patient043_frame01_slice_11.h5 -trainrlessd8_slices/patient043_frame01_slice_2.h5 -trainrlessd8_slices/patient043_frame01_slice_3.h5 -trainrlessd8_slices/patient043_frame01_slice_4.h5 -trainrlessd8_slices/patient043_frame01_slice_5.h5 -trainrlessd8_slices/patient043_frame01_slice_6.h5 -trainrlessd8_slices/patient043_frame01_slice_7.h5 -trainrlessd8_slices/patient043_frame01_slice_8.h5 -trainrlessd8_slices/patient043_frame01_slice_9.h5 -trainrlessd8_slices/patient043_frame07_slice_0.h5 -trainrlessd8_slices/patient043_frame07_slice_1.h5 -trainrlessd8_slices/patient043_frame07_slice_10.h5 -trainrlessd8_slices/patient043_frame07_slice_11.h5 -trainrlessd8_slices/patient043_frame07_slice_2.h5 -trainrlessd8_slices/patient043_frame07_slice_3.h5 -trainrlessd8_slices/patient043_frame07_slice_4.h5 -trainrlessd8_slices/patient043_frame07_slice_5.h5 -trainrlessd8_slices/patient043_frame07_slice_6.h5 -trainrlessd8_slices/patient043_frame07_slice_7.h5 -trainrlessd8_slices/patient043_frame07_slice_8.h5 -trainrlessd8_slices/patient043_frame07_slice_9.h5 -trainrlessd8_slices/patient044_frame01_slice_0.h5 -trainrlessd8_slices/patient044_frame01_slice_1.h5 -trainrlessd8_slices/patient044_frame01_slice_2.h5 -trainrlessd8_slices/patient044_frame01_slice_3.h5 -trainrlessd8_slices/patient044_frame01_slice_4.h5 -trainrlessd8_slices/patient044_frame01_slice_5.h5 -trainrlessd8_slices/patient044_frame01_slice_6.h5 -trainrlessd8_slices/patient044_frame01_slice_7.h5 -trainrlessd8_slices/patient044_frame01_slice_8.h5 -trainrlessd8_slices/patient044_frame11_slice_0.h5 -trainrlessd8_slices/patient044_frame11_slice_1.h5 -trainrlessd8_slices/patient044_frame11_slice_2.h5 -trainrlessd8_slices/patient044_frame11_slice_3.h5 -trainrlessd8_slices/patient044_frame11_slice_4.h5 -trainrlessd8_slices/patient044_frame11_slice_5.h5 -trainrlessd8_slices/patient044_frame11_slice_6.h5 -trainrlessd8_slices/patient044_frame11_slice_7.h5 -trainrlessd8_slices/patient044_frame11_slice_8.h5 -trainrlessd8_slices/patient045_frame01_slice_0.h5 -trainrlessd8_slices/patient045_frame01_slice_1.h5 -trainrlessd8_slices/patient045_frame01_slice_2.h5 -trainrlessd8_slices/patient045_frame01_slice_3.h5 -trainrlessd8_slices/patient045_frame01_slice_4.h5 -trainrlessd8_slices/patient045_frame01_slice_5.h5 -trainrlessd8_slices/patient045_frame01_slice_6.h5 -trainrlessd8_slices/patient045_frame01_slice_7.h5 -trainrlessd8_slices/patient046_frame01_slice_0.h5 -trainrlessd8_slices/patient046_frame01_slice_1.h5 -trainrlessd8_slices/patient046_frame01_slice_2.h5 -trainrlessd8_slices/patient046_frame01_slice_3.h5 -trainrlessd8_slices/patient046_frame01_slice_4.h5 -trainrlessd8_slices/patient046_frame01_slice_5.h5 -trainrlessd8_slices/patient046_frame01_slice_6.h5 -trainrlessd8_slices/patient046_frame01_slice_7.h5 -trainrlessd8_slices/patient046_frame01_slice_8.h5 -trainrlessd8_slices/patient046_frame10_slice_0.h5 -trainrlessd8_slices/patient046_frame10_slice_1.h5 -trainrlessd8_slices/patient046_frame10_slice_2.h5 -trainrlessd8_slices/patient046_frame10_slice_3.h5 -trainrlessd8_slices/patient046_frame10_slice_4.h5 -trainrlessd8_slices/patient046_frame10_slice_5.h5 -trainrlessd8_slices/patient046_frame10_slice_6.h5 -trainrlessd8_slices/patient046_frame10_slice_7.h5 -trainrlessd8_slices/patient046_frame10_slice_8.h5 -trainrlessd8_slices/patient047_frame01_slice_0.h5 -trainrlessd8_slices/patient047_frame01_slice_1.h5 -trainrlessd8_slices/patient047_frame01_slice_2.h5 -trainrlessd8_slices/patient047_frame01_slice_3.h5 -trainrlessd8_slices/patient047_frame01_slice_4.h5 -trainrlessd8_slices/patient047_frame01_slice_5.h5 -trainrlessd8_slices/patient047_frame01_slice_6.h5 -trainrlessd8_slices/patient047_frame01_slice_7.h5 -trainrlessd8_slices/patient047_frame01_slice_8.h5 -trainrlessd8_slices/patient048_frame01_slice_0.h5 -trainrlessd8_slices/patient048_frame01_slice_1.h5 -trainrlessd8_slices/patient048_frame01_slice_2.h5 -trainrlessd8_slices/patient048_frame01_slice_3.h5 -trainrlessd8_slices/patient048_frame01_slice_4.h5 -trainrlessd8_slices/patient048_frame01_slice_5.h5 -trainrlessd8_slices/patient048_frame01_slice_6.h5 -trainrlessd8_slices/patient048_frame01_slice_7.h5 -trainrlessd8_slices/patient049_frame01_slice_0.h5 -trainrlessd8_slices/patient049_frame01_slice_1.h5 -trainrlessd8_slices/patient049_frame01_slice_2.h5 -trainrlessd8_slices/patient049_frame01_slice_3.h5 -trainrlessd8_slices/patient049_frame01_slice_4.h5 -trainrlessd8_slices/patient049_frame01_slice_5.h5 -trainrlessd8_slices/patient049_frame01_slice_6.h5 -trainrlessd8_slices/patient049_frame11_slice_0.h5 -trainrlessd8_slices/patient049_frame11_slice_1.h5 -trainrlessd8_slices/patient049_frame11_slice_2.h5 -trainrlessd8_slices/patient049_frame11_slice_3.h5 -trainrlessd8_slices/patient049_frame11_slice_4.h5 -trainrlessd8_slices/patient049_frame11_slice_5.h5 -trainrlessd8_slices/patient049_frame11_slice_6.h5 -trainrlessd8_slices/patient050_frame01_slice_0.h5 -trainrlessd8_slices/patient050_frame01_slice_1.h5 -trainrlessd8_slices/patient050_frame01_slice_2.h5 -trainrlessd8_slices/patient050_frame01_slice_3.h5 -trainrlessd8_slices/patient050_frame01_slice_4.h5 -trainrlessd8_slices/patient050_frame01_slice_5.h5 -trainrlessd8_slices/patient050_frame01_slice_6.h5 -trainrlessd8_slices/patient050_frame01_slice_7.h5 -trainrlessd8_slices/patient050_frame01_slice_8.h5 -trainrlessd8_slices/patient050_frame01_slice_9.h5 -trainrlessd8_slices/patient050_frame12_slice_0.h5 -trainrlessd8_slices/patient050_frame12_slice_1.h5 -trainrlessd8_slices/patient050_frame12_slice_2.h5 -trainrlessd8_slices/patient050_frame12_slice_3.h5 -trainrlessd8_slices/patient050_frame12_slice_4.h5 -trainrlessd8_slices/patient050_frame12_slice_5.h5 -trainrlessd8_slices/patient050_frame12_slice_6.h5 -trainrlessd8_slices/patient050_frame12_slice_7.h5 -trainrlessd8_slices/patient050_frame12_slice_8.h5 -trainrlessd8_slices/patient050_frame12_slice_9.h5 -trainrlessd8_slices/patient051_frame01_slice_0.h5 -trainrlessd8_slices/patient051_frame01_slice_1.h5 -trainrlessd8_slices/patient051_frame01_slice_2.h5 -trainrlessd8_slices/patient051_frame01_slice_3.h5 -trainrlessd8_slices/patient051_frame01_slice_4.h5 -trainrlessd8_slices/patient051_frame01_slice_5.h5 -trainrlessd8_slices/patient051_frame01_slice_6.h5 -trainrlessd8_slices/patient051_frame01_slice_7.h5 -trainrlessd8_slices/patient051_frame01_slice_8.h5 -trainrlessd8_slices/patient051_frame01_slice_9.h5 -trainrlessd8_slices/patient051_frame11_slice_0.h5 -trainrlessd8_slices/patient051_frame11_slice_1.h5 -trainrlessd8_slices/patient051_frame11_slice_2.h5 -trainrlessd8_slices/patient051_frame11_slice_3.h5 -trainrlessd8_slices/patient051_frame11_slice_4.h5 -trainrlessd8_slices/patient051_frame11_slice_5.h5 -trainrlessd8_slices/patient051_frame11_slice_6.h5 -trainrlessd8_slices/patient051_frame11_slice_7.h5 -trainrlessd8_slices/patient051_frame11_slice_8.h5 -trainrlessd8_slices/patient051_frame11_slice_9.h5 -trainrlessd8_slices/patient052_frame01_slice_0.h5 -trainrlessd8_slices/patient052_frame01_slice_1.h5 -trainrlessd8_slices/patient052_frame01_slice_2.h5 -trainrlessd8_slices/patient052_frame01_slice_3.h5 -trainrlessd8_slices/patient052_frame01_slice_4.h5 -trainrlessd8_slices/patient052_frame01_slice_5.h5 -trainrlessd8_slices/patient052_frame01_slice_6.h5 -trainrlessd8_slices/patient052_frame01_slice_7.h5 -trainrlessd8_slices/patient052_frame09_slice_0.h5 -trainrlessd8_slices/patient052_frame09_slice_1.h5 -trainrlessd8_slices/patient052_frame09_slice_2.h5 -trainrlessd8_slices/patient052_frame09_slice_3.h5 -trainrlessd8_slices/patient052_frame09_slice_4.h5 -trainrlessd8_slices/patient052_frame09_slice_5.h5 -trainrlessd8_slices/patient052_frame09_slice_6.h5 -trainrlessd8_slices/patient052_frame09_slice_7.h5 -trainrlessd8_slices/patient053_frame12_slice_0.h5 -trainrlessd8_slices/patient053_frame12_slice_1.h5 -trainrlessd8_slices/patient053_frame12_slice_2.h5 -trainrlessd8_slices/patient053_frame12_slice_3.h5 -trainrlessd8_slices/patient053_frame12_slice_4.h5 -trainrlessd8_slices/patient053_frame12_slice_5.h5 -trainrlessd8_slices/patient053_frame12_slice_6.h5 -trainrlessd8_slices/patient054_frame01_slice_0.h5 -trainrlessd8_slices/patient054_frame01_slice_1.h5 -trainrlessd8_slices/patient054_frame01_slice_2.h5 -trainrlessd8_slices/patient054_frame01_slice_3.h5 -trainrlessd8_slices/patient054_frame01_slice_4.h5 -trainrlessd8_slices/patient054_frame01_slice_5.h5 -trainrlessd8_slices/patient054_frame01_slice_6.h5 -trainrlessd8_slices/patient054_frame01_slice_7.h5 -trainrlessd8_slices/patient054_frame12_slice_0.h5 -trainrlessd8_slices/patient054_frame12_slice_1.h5 -trainrlessd8_slices/patient054_frame12_slice_2.h5 -trainrlessd8_slices/patient054_frame12_slice_3.h5 -trainrlessd8_slices/patient054_frame12_slice_4.h5 -trainrlessd8_slices/patient054_frame12_slice_5.h5 -trainrlessd8_slices/patient054_frame12_slice_6.h5 -trainrlessd8_slices/patient054_frame12_slice_7.h5 -trainrlessd8_slices/patient055_frame10_slice_0.h5 -trainrlessd8_slices/patient055_frame10_slice_1.h5 -trainrlessd8_slices/patient055_frame10_slice_2.h5 -trainrlessd8_slices/patient055_frame10_slice_3.h5 -trainrlessd8_slices/patient055_frame10_slice_4.h5 -trainrlessd8_slices/patient055_frame10_slice_5.h5 -trainrlessd8_slices/patient055_frame10_slice_6.h5 -trainrlessd8_slices/patient055_frame10_slice_7.h5 -trainrlessd8_slices/patient055_frame10_slice_8.h5 -trainrlessd8_slices/patient056_frame01_slice_0.h5 -trainrlessd8_slices/patient056_frame01_slice_1.h5 -trainrlessd8_slices/patient056_frame01_slice_2.h5 -trainrlessd8_slices/patient056_frame01_slice_3.h5 -trainrlessd8_slices/patient056_frame01_slice_4.h5 -trainrlessd8_slices/patient056_frame01_slice_5.h5 -trainrlessd8_slices/patient056_frame01_slice_6.h5 -trainrlessd8_slices/patient056_frame01_slice_7.h5 -trainrlessd8_slices/patient056_frame01_slice_8.h5 -trainrlessd8_slices/patient056_frame12_slice_0.h5 -trainrlessd8_slices/patient056_frame12_slice_1.h5 -trainrlessd8_slices/patient056_frame12_slice_2.h5 -trainrlessd8_slices/patient056_frame12_slice_3.h5 -trainrlessd8_slices/patient056_frame12_slice_4.h5 -trainrlessd8_slices/patient056_frame12_slice_5.h5 -trainrlessd8_slices/patient056_frame12_slice_6.h5 -trainrlessd8_slices/patient056_frame12_slice_7.h5 -trainrlessd8_slices/patient056_frame12_slice_8.h5 -trainrlessd8_slices/patient057_frame01_slice_0.h5 -trainrlessd8_slices/patient057_frame01_slice_1.h5 -trainrlessd8_slices/patient057_frame01_slice_2.h5 -trainrlessd8_slices/patient057_frame01_slice_3.h5 -trainrlessd8_slices/patient057_frame01_slice_4.h5 -trainrlessd8_slices/patient057_frame01_slice_5.h5 -trainrlessd8_slices/patient057_frame01_slice_6.h5 -trainrlessd8_slices/patient057_frame01_slice_7.h5 -trainrlessd8_slices/patient058_frame14_slice_0.h5 -trainrlessd8_slices/patient058_frame14_slice_1.h5 -trainrlessd8_slices/patient058_frame14_slice_2.h5 -trainrlessd8_slices/patient058_frame14_slice_3.h5 -trainrlessd8_slices/patient058_frame14_slice_4.h5 -trainrlessd8_slices/patient058_frame14_slice_5.h5 -trainrlessd8_slices/patient058_frame14_slice_6.h5 -trainrlessd8_slices/patient058_frame14_slice_7.h5 -trainrlessd8_slices/patient058_frame14_slice_8.h5 -trainrlessd8_slices/patient059_frame01_slice_0.h5 -trainrlessd8_slices/patient059_frame01_slice_1.h5 -trainrlessd8_slices/patient059_frame01_slice_2.h5 -trainrlessd8_slices/patient059_frame01_slice_3.h5 -trainrlessd8_slices/patient059_frame01_slice_4.h5 -trainrlessd8_slices/patient059_frame01_slice_5.h5 -trainrlessd8_slices/patient059_frame01_slice_6.h5 -trainrlessd8_slices/patient059_frame01_slice_7.h5 -trainrlessd8_slices/patient059_frame01_slice_8.h5 -trainrlessd8_slices/patient059_frame09_slice_0.h5 -trainrlessd8_slices/patient059_frame09_slice_1.h5 -trainrlessd8_slices/patient059_frame09_slice_2.h5 -trainrlessd8_slices/patient059_frame09_slice_3.h5 -trainrlessd8_slices/patient059_frame09_slice_4.h5 -trainrlessd8_slices/patient059_frame09_slice_5.h5 -trainrlessd8_slices/patient059_frame09_slice_6.h5 -trainrlessd8_slices/patient059_frame09_slice_7.h5 -trainrlessd8_slices/patient059_frame09_slice_8.h5 -trainrlessd8_slices/patient060_frame14_slice_0.h5 -trainrlessd8_slices/patient060_frame14_slice_1.h5 -trainrlessd8_slices/patient060_frame14_slice_2.h5 -trainrlessd8_slices/patient060_frame14_slice_3.h5 -trainrlessd8_slices/patient060_frame14_slice_4.h5 -trainrlessd8_slices/patient060_frame14_slice_5.h5 -trainrlessd8_slices/patient060_frame14_slice_6.h5 -trainrlessd8_slices/patient060_frame14_slice_7.h5 -trainrlessd8_slices/patient060_frame14_slice_8.h5 -trainrlessd8_slices/patient061_frame01_slice_0.h5 -trainrlessd8_slices/patient061_frame01_slice_1.h5 -trainrlessd8_slices/patient061_frame01_slice_2.h5 -trainrlessd8_slices/patient061_frame01_slice_3.h5 -trainrlessd8_slices/patient061_frame01_slice_4.h5 -trainrlessd8_slices/patient061_frame01_slice_5.h5 -trainrlessd8_slices/patient061_frame01_slice_6.h5 -trainrlessd8_slices/patient061_frame01_slice_7.h5 -trainrlessd8_slices/patient061_frame01_slice_8.h5 -trainrlessd8_slices/patient061_frame10_slice_0.h5 -trainrlessd8_slices/patient061_frame10_slice_1.h5 -trainrlessd8_slices/patient061_frame10_slice_2.h5 -trainrlessd8_slices/patient061_frame10_slice_3.h5 -trainrlessd8_slices/patient061_frame10_slice_4.h5 -trainrlessd8_slices/patient061_frame10_slice_5.h5 -trainrlessd8_slices/patient061_frame10_slice_6.h5 -trainrlessd8_slices/patient061_frame10_slice_7.h5 -trainrlessd8_slices/patient061_frame10_slice_8.h5 -trainrlessd8_slices/patient062_frame01_slice_0.h5 -trainrlessd8_slices/patient062_frame01_slice_1.h5 -trainrlessd8_slices/patient062_frame01_slice_2.h5 -trainrlessd8_slices/patient062_frame01_slice_3.h5 -trainrlessd8_slices/patient062_frame01_slice_4.h5 -trainrlessd8_slices/patient062_frame01_slice_5.h5 -trainrlessd8_slices/patient062_frame01_slice_6.h5 -trainrlessd8_slices/patient062_frame01_slice_7.h5 -trainrlessd8_slices/patient062_frame01_slice_8.h5 -trainrlessd8_slices/patient062_frame01_slice_9.h5 -trainrlessd8_slices/patient062_frame09_slice_0.h5 -trainrlessd8_slices/patient062_frame09_slice_1.h5 -trainrlessd8_slices/patient062_frame09_slice_2.h5 -trainrlessd8_slices/patient062_frame09_slice_3.h5 -trainrlessd8_slices/patient062_frame09_slice_4.h5 -trainrlessd8_slices/patient062_frame09_slice_5.h5 -trainrlessd8_slices/patient062_frame09_slice_6.h5 -trainrlessd8_slices/patient062_frame09_slice_7.h5 -trainrlessd8_slices/patient062_frame09_slice_8.h5 -trainrlessd8_slices/patient062_frame09_slice_9.h5 -trainrlessd8_slices/patient063_frame16_slice_0.h5 -trainrlessd8_slices/patient063_frame16_slice_1.h5 -trainrlessd8_slices/patient063_frame16_slice_2.h5 -trainrlessd8_slices/patient063_frame16_slice_3.h5 -trainrlessd8_slices/patient063_frame16_slice_4.h5 -trainrlessd8_slices/patient063_frame16_slice_5.h5 -trainrlessd8_slices/patient063_frame16_slice_6.h5 -trainrlessd8_slices/patient063_frame16_slice_7.h5 -trainrlessd8_slices/patient064_frame01_slice_0.h5 -trainrlessd8_slices/patient064_frame01_slice_1.h5 -trainrlessd8_slices/patient064_frame01_slice_2.h5 -trainrlessd8_slices/patient064_frame01_slice_3.h5 -trainrlessd8_slices/patient064_frame01_slice_4.h5 -trainrlessd8_slices/patient064_frame01_slice_5.h5 -trainrlessd8_slices/patient064_frame01_slice_6.h5 -trainrlessd8_slices/patient064_frame01_slice_7.h5 -trainrlessd8_slices/patient064_frame01_slice_8.h5 -trainrlessd8_slices/patient064_frame01_slice_9.h5 -trainrlessd8_slices/patient066_frame01_slice_0.h5 -trainrlessd8_slices/patient066_frame01_slice_1.h5 -trainrlessd8_slices/patient066_frame01_slice_2.h5 -trainrlessd8_slices/patient066_frame01_slice_3.h5 -trainrlessd8_slices/patient066_frame01_slice_4.h5 -trainrlessd8_slices/patient066_frame01_slice_5.h5 -trainrlessd8_slices/patient066_frame01_slice_6.h5 -trainrlessd8_slices/patient066_frame01_slice_7.h5 -trainrlessd8_slices/patient066_frame01_slice_8.h5 -trainrlessd8_slices/patient067_frame01_slice_0.h5 -trainrlessd8_slices/patient067_frame01_slice_1.h5 -trainrlessd8_slices/patient067_frame01_slice_2.h5 -trainrlessd8_slices/patient067_frame01_slice_3.h5 -trainrlessd8_slices/patient067_frame01_slice_4.h5 -trainrlessd8_slices/patient067_frame01_slice_5.h5 -trainrlessd8_slices/patient067_frame01_slice_6.h5 -trainrlessd8_slices/patient067_frame01_slice_7.h5 -trainrlessd8_slices/patient067_frame01_slice_8.h5 -trainrlessd8_slices/patient067_frame01_slice_9.h5 -trainrlessd8_slices/patient067_frame10_slice_0.h5 -trainrlessd8_slices/patient067_frame10_slice_1.h5 -trainrlessd8_slices/patient067_frame10_slice_2.h5 -trainrlessd8_slices/patient067_frame10_slice_3.h5 -trainrlessd8_slices/patient067_frame10_slice_4.h5 -trainrlessd8_slices/patient067_frame10_slice_5.h5 -trainrlessd8_slices/patient067_frame10_slice_6.h5 -trainrlessd8_slices/patient067_frame10_slice_7.h5 -trainrlessd8_slices/patient067_frame10_slice_8.h5 -trainrlessd8_slices/patient067_frame10_slice_9.h5 -trainrlessd8_slices/patient068_frame01_slice_0.h5 -trainrlessd8_slices/patient068_frame01_slice_1.h5 -trainrlessd8_slices/patient068_frame01_slice_2.h5 -trainrlessd8_slices/patient068_frame01_slice_3.h5 -trainrlessd8_slices/patient068_frame01_slice_4.h5 -trainrlessd8_slices/patient068_frame01_slice_5.h5 -trainrlessd8_slices/patient068_frame01_slice_6.h5 -trainrlessd8_slices/patient069_frame01_slice_0.h5 -trainrlessd8_slices/patient069_frame01_slice_1.h5 -trainrlessd8_slices/patient069_frame01_slice_2.h5 -trainrlessd8_slices/patient069_frame01_slice_3.h5 -trainrlessd8_slices/patient069_frame01_slice_4.h5 -trainrlessd8_slices/patient069_frame01_slice_5.h5 -trainrlessd8_slices/patient069_frame01_slice_6.h5 -trainrlessd8_slices/patient070_frame01_slice_0.h5 -trainrlessd8_slices/patient070_frame01_slice_1.h5 -trainrlessd8_slices/patient070_frame01_slice_2.h5 -trainrlessd8_slices/patient070_frame01_slice_3.h5 -trainrlessd8_slices/patient070_frame01_slice_4.h5 -trainrlessd8_slices/patient070_frame01_slice_5.h5 -trainrlessd8_slices/patient071_frame09_slice_0.h5 -trainrlessd8_slices/patient071_frame09_slice_1.h5 -trainrlessd8_slices/patient071_frame09_slice_2.h5 -trainrlessd8_slices/patient071_frame09_slice_3.h5 -trainrlessd8_slices/patient071_frame09_slice_4.h5 -trainrlessd8_slices/patient071_frame09_slice_5.h5 -trainrlessd8_slices/patient071_frame09_slice_6.h5 -trainrlessd8_slices/patient071_frame09_slice_7.h5 -trainrlessd8_slices/patient071_frame09_slice_8.h5 -trainrlessd8_slices/patient071_frame09_slice_9.h5 -trainrlessd8_slices/patient072_frame01_slice_0.h5 -trainrlessd8_slices/patient072_frame01_slice_1.h5 -trainrlessd8_slices/patient072_frame01_slice_2.h5 -trainrlessd8_slices/patient072_frame01_slice_3.h5 -trainrlessd8_slices/patient072_frame01_slice_4.h5 -trainrlessd8_slices/patient072_frame01_slice_5.h5 -trainrlessd8_slices/patient072_frame01_slice_6.h5 -trainrlessd8_slices/patient072_frame01_slice_7.h5 -trainrlessd8_slices/patient073_frame10_slice_0.h5 -trainrlessd8_slices/patient073_frame10_slice_1.h5 -trainrlessd8_slices/patient073_frame10_slice_2.h5 -trainrlessd8_slices/patient073_frame10_slice_3.h5 -trainrlessd8_slices/patient073_frame10_slice_4.h5 -trainrlessd8_slices/patient073_frame10_slice_5.h5 -trainrlessd8_slices/patient073_frame10_slice_6.h5 -trainrlessd8_slices/patient074_frame12_slice_0.h5 -trainrlessd8_slices/patient074_frame12_slice_1.h5 -trainrlessd8_slices/patient074_frame12_slice_2.h5 -trainrlessd8_slices/patient074_frame12_slice_3.h5 -trainrlessd8_slices/patient074_frame12_slice_4.h5 -trainrlessd8_slices/patient074_frame12_slice_5.h5 -trainrlessd8_slices/patient074_frame12_slice_6.h5 -trainrlessd8_slices/patient074_frame12_slice_7.h5 -trainrlessd8_slices/patient075_frame01_slice_0.h5 -trainrlessd8_slices/patient075_frame01_slice_1.h5 -trainrlessd8_slices/patient075_frame01_slice_10.h5 -trainrlessd8_slices/patient075_frame01_slice_11.h5 -trainrlessd8_slices/patient075_frame01_slice_12.h5 -trainrlessd8_slices/patient075_frame01_slice_13.h5 -trainrlessd8_slices/patient075_frame01_slice_2.h5 -trainrlessd8_slices/patient075_frame01_slice_3.h5 -trainrlessd8_slices/patient075_frame01_slice_4.h5 -trainrlessd8_slices/patient075_frame01_slice_5.h5 -trainrlessd8_slices/patient075_frame01_slice_6.h5 -trainrlessd8_slices/patient075_frame01_slice_7.h5 -trainrlessd8_slices/patient075_frame01_slice_8.h5 -trainrlessd8_slices/patient075_frame01_slice_9.h5 -trainrlessd8_slices/patient076_frame12_slice_0.h5 -trainrlessd8_slices/patient076_frame12_slice_1.h5 -trainrlessd8_slices/patient076_frame12_slice_2.h5 -trainrlessd8_slices/patient076_frame12_slice_3.h5 -trainrlessd8_slices/patient076_frame12_slice_4.h5 -trainrlessd8_slices/patient076_frame12_slice_5.h5 -trainrlessd8_slices/patient076_frame12_slice_6.h5 -trainrlessd8_slices/patient076_frame12_slice_7.h5 -trainrlessd8_slices/patient077_frame09_slice_0.h5 -trainrlessd8_slices/patient077_frame09_slice_1.h5 -trainrlessd8_slices/patient077_frame09_slice_2.h5 -trainrlessd8_slices/patient077_frame09_slice_3.h5 -trainrlessd8_slices/patient077_frame09_slice_4.h5 -trainrlessd8_slices/patient077_frame09_slice_5.h5 -trainrlessd8_slices/patient077_frame09_slice_6.h5 -trainrlessd8_slices/patient077_frame09_slice_7.h5 -trainrlessd8_slices/patient078_frame01_slice_0.h5 -trainrlessd8_slices/patient078_frame01_slice_1.h5 -trainrlessd8_slices/patient078_frame01_slice_2.h5 -trainrlessd8_slices/patient078_frame01_slice_3.h5 -trainrlessd8_slices/patient078_frame01_slice_4.h5 -trainrlessd8_slices/patient078_frame01_slice_5.h5 -trainrlessd8_slices/patient078_frame01_slice_6.h5 -trainrlessd8_slices/patient078_frame01_slice_7.h5 -trainrlessd8_slices/patient078_frame09_slice_0.h5 -trainrlessd8_slices/patient078_frame09_slice_1.h5 -trainrlessd8_slices/patient078_frame09_slice_2.h5 -trainrlessd8_slices/patient078_frame09_slice_3.h5 -trainrlessd8_slices/patient078_frame09_slice_4.h5 -trainrlessd8_slices/patient078_frame09_slice_5.h5 -trainrlessd8_slices/patient078_frame09_slice_6.h5 -trainrlessd8_slices/patient078_frame09_slice_7.h5 -trainrlessd8_slices/patient079_frame01_slice_0.h5 -trainrlessd8_slices/patient079_frame01_slice_1.h5 -trainrlessd8_slices/patient079_frame01_slice_2.h5 -trainrlessd8_slices/patient079_frame01_slice_3.h5 -trainrlessd8_slices/patient079_frame01_slice_4.h5 -trainrlessd8_slices/patient079_frame01_slice_5.h5 -trainrlessd8_slices/patient079_frame01_slice_6.h5 -trainrlessd8_slices/patient079_frame01_slice_7.h5 -trainrlessd8_slices/patient079_frame01_slice_8.h5 -trainrlessd8_slices/patient079_frame11_slice_0.h5 -trainrlessd8_slices/patient079_frame11_slice_1.h5 -trainrlessd8_slices/patient079_frame11_slice_2.h5 -trainrlessd8_slices/patient079_frame11_slice_3.h5 -trainrlessd8_slices/patient079_frame11_slice_4.h5 -trainrlessd8_slices/patient079_frame11_slice_5.h5 -trainrlessd8_slices/patient079_frame11_slice_6.h5 -trainrlessd8_slices/patient079_frame11_slice_7.h5 -trainrlessd8_slices/patient079_frame11_slice_8.h5 -trainrlessd8_slices/patient080_frame01_slice_0.h5 -trainrlessd8_slices/patient080_frame01_slice_1.h5 -trainrlessd8_slices/patient080_frame01_slice_2.h5 -trainrlessd8_slices/patient080_frame01_slice_3.h5 -trainrlessd8_slices/patient080_frame01_slice_4.h5 -trainrlessd8_slices/patient080_frame01_slice_5.h5 -trainrlessd8_slices/patient080_frame10_slice_0.h5 -trainrlessd8_slices/patient080_frame10_slice_1.h5 -trainrlessd8_slices/patient080_frame10_slice_2.h5 -trainrlessd8_slices/patient080_frame10_slice_3.h5 -trainrlessd8_slices/patient080_frame10_slice_4.h5 -trainrlessd8_slices/patient080_frame10_slice_5.h5 -trainrlessd8_slices/patient081_frame07_slice_0.h5 -trainrlessd8_slices/patient081_frame07_slice_1.h5 -trainrlessd8_slices/patient081_frame07_slice_10.h5 -trainrlessd8_slices/patient081_frame07_slice_11.h5 -trainrlessd8_slices/patient081_frame07_slice_12.h5 -trainrlessd8_slices/patient081_frame07_slice_13.h5 -trainrlessd8_slices/patient081_frame07_slice_14.h5 -trainrlessd8_slices/patient081_frame07_slice_15.h5 -trainrlessd8_slices/patient081_frame07_slice_16.h5 -trainrlessd8_slices/patient081_frame07_slice_2.h5 -trainrlessd8_slices/patient081_frame07_slice_3.h5 -trainrlessd8_slices/patient081_frame07_slice_4.h5 -trainrlessd8_slices/patient081_frame07_slice_5.h5 -trainrlessd8_slices/patient081_frame07_slice_6.h5 -trainrlessd8_slices/patient081_frame07_slice_7.h5 -trainrlessd8_slices/patient081_frame07_slice_8.h5 -trainrlessd8_slices/patient081_frame07_slice_9.h5 -trainrlessd8_slices/patient082_frame01_slice_0.h5 -trainrlessd8_slices/patient082_frame01_slice_1.h5 -trainrlessd8_slices/patient082_frame01_slice_10.h5 -trainrlessd8_slices/patient082_frame01_slice_11.h5 -trainrlessd8_slices/patient082_frame01_slice_12.h5 -trainrlessd8_slices/patient082_frame01_slice_13.h5 -trainrlessd8_slices/patient082_frame01_slice_14.h5 -trainrlessd8_slices/patient082_frame01_slice_15.h5 -trainrlessd8_slices/patient082_frame01_slice_2.h5 -trainrlessd8_slices/patient082_frame01_slice_3.h5 -trainrlessd8_slices/patient082_frame01_slice_4.h5 -trainrlessd8_slices/patient082_frame01_slice_5.h5 -trainrlessd8_slices/patient082_frame01_slice_6.h5 -trainrlessd8_slices/patient082_frame01_slice_7.h5 -trainrlessd8_slices/patient082_frame01_slice_8.h5 -trainrlessd8_slices/patient082_frame01_slice_9.h5 -trainrlessd8_slices/patient082_frame07_slice_0.h5 -trainrlessd8_slices/patient082_frame07_slice_1.h5 -trainrlessd8_slices/patient082_frame07_slice_10.h5 -trainrlessd8_slices/patient082_frame07_slice_11.h5 -trainrlessd8_slices/patient082_frame07_slice_12.h5 -trainrlessd8_slices/patient082_frame07_slice_13.h5 -trainrlessd8_slices/patient082_frame07_slice_14.h5 -trainrlessd8_slices/patient082_frame07_slice_15.h5 -trainrlessd8_slices/patient082_frame07_slice_2.h5 -trainrlessd8_slices/patient082_frame07_slice_3.h5 -trainrlessd8_slices/patient082_frame07_slice_4.h5 -trainrlessd8_slices/patient082_frame07_slice_5.h5 -trainrlessd8_slices/patient082_frame07_slice_6.h5 -trainrlessd8_slices/patient082_frame07_slice_7.h5 -trainrlessd8_slices/patient082_frame07_slice_8.h5 -trainrlessd8_slices/patient082_frame07_slice_9.h5 -trainrlessd8_slices/patient083_frame01_slice_0.h5 -trainrlessd8_slices/patient083_frame01_slice_1.h5 -trainrlessd8_slices/patient083_frame01_slice_2.h5 -trainrlessd8_slices/patient083_frame01_slice_3.h5 -trainrlessd8_slices/patient083_frame01_slice_4.h5 -trainrlessd8_slices/patient083_frame01_slice_5.h5 -trainrlessd8_slices/patient084_frame01_slice_0.h5 -trainrlessd8_slices/patient084_frame01_slice_1.h5 -trainrlessd8_slices/patient084_frame01_slice_10.h5 -trainrlessd8_slices/patient084_frame01_slice_11.h5 -trainrlessd8_slices/patient084_frame01_slice_2.h5 -trainrlessd8_slices/patient084_frame01_slice_3.h5 -trainrlessd8_slices/patient084_frame01_slice_4.h5 -trainrlessd8_slices/patient084_frame01_slice_5.h5 -trainrlessd8_slices/patient084_frame01_slice_6.h5 -trainrlessd8_slices/patient084_frame01_slice_7.h5 -trainrlessd8_slices/patient084_frame01_slice_8.h5 -trainrlessd8_slices/patient084_frame01_slice_9.h5 -trainrlessd8_slices/patient084_frame10_slice_0.h5 -trainrlessd8_slices/patient084_frame10_slice_1.h5 -trainrlessd8_slices/patient084_frame10_slice_10.h5 -trainrlessd8_slices/patient084_frame10_slice_11.h5 -trainrlessd8_slices/patient084_frame10_slice_2.h5 -trainrlessd8_slices/patient084_frame10_slice_3.h5 -trainrlessd8_slices/patient084_frame10_slice_4.h5 -trainrlessd8_slices/patient084_frame10_slice_5.h5 -trainrlessd8_slices/patient084_frame10_slice_6.h5 -trainrlessd8_slices/patient084_frame10_slice_7.h5 -trainrlessd8_slices/patient084_frame10_slice_8.h5 -trainrlessd8_slices/patient084_frame10_slice_9.h5 -trainrlessd8_slices/patient085_frame01_slice_0.h5 -trainrlessd8_slices/patient085_frame01_slice_1.h5 -trainrlessd8_slices/patient085_frame01_slice_10.h5 -trainrlessd8_slices/patient085_frame01_slice_11.h5 -trainrlessd8_slices/patient085_frame01_slice_12.h5 -trainrlessd8_slices/patient085_frame01_slice_13.h5 -trainrlessd8_slices/patient085_frame01_slice_14.h5 -trainrlessd8_slices/patient085_frame01_slice_2.h5 -trainrlessd8_slices/patient085_frame01_slice_3.h5 -trainrlessd8_slices/patient085_frame01_slice_4.h5 -trainrlessd8_slices/patient085_frame01_slice_5.h5 -trainrlessd8_slices/patient085_frame01_slice_6.h5 -trainrlessd8_slices/patient085_frame01_slice_7.h5 -trainrlessd8_slices/patient085_frame01_slice_8.h5 -trainrlessd8_slices/patient085_frame01_slice_9.h5 -trainrlessd8_slices/patient087_frame01_slice_0.h5 -trainrlessd8_slices/patient087_frame01_slice_1.h5 -trainrlessd8_slices/patient087_frame01_slice_2.h5 -trainrlessd8_slices/patient087_frame01_slice_3.h5 -trainrlessd8_slices/patient087_frame01_slice_4.h5 -trainrlessd8_slices/patient087_frame01_slice_5.h5 -trainrlessd8_slices/patient087_frame01_slice_6.h5 -trainrlessd8_slices/patient087_frame01_slice_7.h5 -trainrlessd8_slices/patient088_frame01_slice_0.h5 -trainrlessd8_slices/patient088_frame01_slice_1.h5 -trainrlessd8_slices/patient088_frame01_slice_10.h5 -trainrlessd8_slices/patient088_frame01_slice_11.h5 -trainrlessd8_slices/patient088_frame01_slice_12.h5 -trainrlessd8_slices/patient088_frame01_slice_13.h5 -trainrlessd8_slices/patient088_frame01_slice_14.h5 -trainrlessd8_slices/patient088_frame01_slice_15.h5 -trainrlessd8_slices/patient088_frame01_slice_2.h5 -trainrlessd8_slices/patient088_frame01_slice_3.h5 -trainrlessd8_slices/patient088_frame01_slice_4.h5 -trainrlessd8_slices/patient088_frame01_slice_5.h5 -trainrlessd8_slices/patient088_frame01_slice_6.h5 -trainrlessd8_slices/patient088_frame01_slice_7.h5 -trainrlessd8_slices/patient088_frame01_slice_8.h5 -trainrlessd8_slices/patient088_frame01_slice_9.h5 -trainrlessd8_slices/patient088_frame12_slice_0.h5 -trainrlessd8_slices/patient088_frame12_slice_1.h5 -trainrlessd8_slices/patient088_frame12_slice_10.h5 -trainrlessd8_slices/patient088_frame12_slice_11.h5 -trainrlessd8_slices/patient088_frame12_slice_12.h5 -trainrlessd8_slices/patient088_frame12_slice_13.h5 -trainrlessd8_slices/patient088_frame12_slice_14.h5 -trainrlessd8_slices/patient088_frame12_slice_15.h5 -trainrlessd8_slices/patient088_frame12_slice_2.h5 -trainrlessd8_slices/patient088_frame12_slice_3.h5 -trainrlessd8_slices/patient088_frame12_slice_4.h5 -trainrlessd8_slices/patient088_frame12_slice_5.h5 -trainrlessd8_slices/patient088_frame12_slice_6.h5 -trainrlessd8_slices/patient088_frame12_slice_7.h5 -trainrlessd8_slices/patient088_frame12_slice_8.h5 -trainrlessd8_slices/patient088_frame12_slice_9.h5 -trainrlessd8_slices/patient090_frame11_slice_0.h5 -trainrlessd8_slices/patient090_frame11_slice_1.h5 -trainrlessd8_slices/patient090_frame11_slice_2.h5 -trainrlessd8_slices/patient090_frame11_slice_3.h5 -trainrlessd8_slices/patient090_frame11_slice_4.h5 -trainrlessd8_slices/patient090_frame11_slice_5.h5 -trainrlessd8_slices/patient090_frame11_slice_6.h5 -trainrlessd8_slices/patient091_frame01_slice_0.h5 -trainrlessd8_slices/patient091_frame01_slice_1.h5 -trainrlessd8_slices/patient091_frame01_slice_2.h5 -trainrlessd8_slices/patient091_frame01_slice_3.h5 -trainrlessd8_slices/patient091_frame01_slice_4.h5 -trainrlessd8_slices/patient091_frame01_slice_5.h5 -trainrlessd8_slices/patient091_frame01_slice_6.h5 -trainrlessd8_slices/patient091_frame01_slice_7.h5 -trainrlessd8_slices/patient091_frame09_slice_0.h5 -trainrlessd8_slices/patient091_frame09_slice_1.h5 -trainrlessd8_slices/patient091_frame09_slice_2.h5 -trainrlessd8_slices/patient091_frame09_slice_3.h5 -trainrlessd8_slices/patient091_frame09_slice_4.h5 -trainrlessd8_slices/patient091_frame09_slice_5.h5 -trainrlessd8_slices/patient091_frame09_slice_6.h5 -trainrlessd8_slices/patient091_frame09_slice_7.h5 -trainrlessd8_slices/patient092_frame01_slice_0.h5 -trainrlessd8_slices/patient092_frame01_slice_1.h5 -trainrlessd8_slices/patient092_frame01_slice_10.h5 -trainrlessd8_slices/patient092_frame01_slice_11.h5 -trainrlessd8_slices/patient092_frame01_slice_12.h5 -trainrlessd8_slices/patient092_frame01_slice_13.h5 -trainrlessd8_slices/patient092_frame01_slice_14.h5 -trainrlessd8_slices/patient092_frame01_slice_2.h5 -trainrlessd8_slices/patient092_frame01_slice_3.h5 -trainrlessd8_slices/patient092_frame01_slice_4.h5 -trainrlessd8_slices/patient092_frame01_slice_5.h5 -trainrlessd8_slices/patient092_frame01_slice_6.h5 -trainrlessd8_slices/patient092_frame01_slice_7.h5 -trainrlessd8_slices/patient092_frame01_slice_8.h5 -trainrlessd8_slices/patient092_frame01_slice_9.h5 -trainrlessd8_slices/patient092_frame06_slice_0.h5 -trainrlessd8_slices/patient092_frame06_slice_1.h5 -trainrlessd8_slices/patient092_frame06_slice_10.h5 -trainrlessd8_slices/patient092_frame06_slice_11.h5 -trainrlessd8_slices/patient092_frame06_slice_12.h5 -trainrlessd8_slices/patient092_frame06_slice_13.h5 -trainrlessd8_slices/patient092_frame06_slice_14.h5 -trainrlessd8_slices/patient092_frame06_slice_2.h5 -trainrlessd8_slices/patient092_frame06_slice_3.h5 -trainrlessd8_slices/patient092_frame06_slice_4.h5 -trainrlessd8_slices/patient092_frame06_slice_5.h5 -trainrlessd8_slices/patient092_frame06_slice_6.h5 -trainrlessd8_slices/patient092_frame06_slice_7.h5 -trainrlessd8_slices/patient092_frame06_slice_8.h5 -trainrlessd8_slices/patient092_frame06_slice_9.h5 -trainrlessd8_slices/patient093_frame14_slice_0.h5 -trainrlessd8_slices/patient093_frame14_slice_1.h5 -trainrlessd8_slices/patient093_frame14_slice_2.h5 -trainrlessd8_slices/patient093_frame14_slice_3.h5 -trainrlessd8_slices/patient093_frame14_slice_4.h5 -trainrlessd8_slices/patient093_frame14_slice_5.h5 -trainrlessd8_slices/patient093_frame14_slice_6.h5 -trainrlessd8_slices/patient093_frame14_slice_7.h5 -trainrlessd8_slices/patient093_frame14_slice_8.h5 -trainrlessd8_slices/patient093_frame14_slice_9.h5 -trainrlessd8_slices/patient095_frame01_slice_0.h5 -trainrlessd8_slices/patient095_frame01_slice_1.h5 -trainrlessd8_slices/patient095_frame01_slice_10.h5 -trainrlessd8_slices/patient095_frame01_slice_11.h5 -trainrlessd8_slices/patient095_frame01_slice_12.h5 -trainrlessd8_slices/patient095_frame01_slice_13.h5 -trainrlessd8_slices/patient095_frame01_slice_2.h5 -trainrlessd8_slices/patient095_frame01_slice_3.h5 -trainrlessd8_slices/patient095_frame01_slice_4.h5 -trainrlessd8_slices/patient095_frame01_slice_5.h5 -trainrlessd8_slices/patient095_frame01_slice_6.h5 -trainrlessd8_slices/patient095_frame01_slice_7.h5 -trainrlessd8_slices/patient095_frame01_slice_8.h5 -trainrlessd8_slices/patient095_frame01_slice_9.h5 -trainrlessd8_slices/patient095_frame12_slice_0.h5 -trainrlessd8_slices/patient095_frame12_slice_1.h5 -trainrlessd8_slices/patient095_frame12_slice_10.h5 -trainrlessd8_slices/patient095_frame12_slice_11.h5 -trainrlessd8_slices/patient095_frame12_slice_12.h5 -trainrlessd8_slices/patient095_frame12_slice_13.h5 -trainrlessd8_slices/patient095_frame12_slice_2.h5 -trainrlessd8_slices/patient095_frame12_slice_3.h5 -trainrlessd8_slices/patient095_frame12_slice_4.h5 -trainrlessd8_slices/patient095_frame12_slice_5.h5 -trainrlessd8_slices/patient095_frame12_slice_6.h5 -trainrlessd8_slices/patient095_frame12_slice_7.h5 -trainrlessd8_slices/patient095_frame12_slice_8.h5 -trainrlessd8_slices/patient095_frame12_slice_9.h5 -trainrlessd8_slices/patient096_frame08_slice_0.h5 -trainrlessd8_slices/patient096_frame08_slice_1.h5 -trainrlessd8_slices/patient096_frame08_slice_10.h5 -trainrlessd8_slices/patient096_frame08_slice_11.h5 -trainrlessd8_slices/patient096_frame08_slice_12.h5 -trainrlessd8_slices/patient096_frame08_slice_13.h5 -trainrlessd8_slices/patient096_frame08_slice_14.h5 -trainrlessd8_slices/patient096_frame08_slice_15.h5 -trainrlessd8_slices/patient096_frame08_slice_16.h5 -trainrlessd8_slices/patient096_frame08_slice_17.h5 -trainrlessd8_slices/patient096_frame08_slice_2.h5 -trainrlessd8_slices/patient096_frame08_slice_3.h5 -trainrlessd8_slices/patient096_frame08_slice_4.h5 -trainrlessd8_slices/patient096_frame08_slice_5.h5 -trainrlessd8_slices/patient096_frame08_slice_6.h5 -trainrlessd8_slices/patient096_frame08_slice_7.h5 -trainrlessd8_slices/patient096_frame08_slice_8.h5 -trainrlessd8_slices/patient096_frame08_slice_9.h5 -trainrlessd8_slices/patient097_frame01_slice_0.h5 -trainrlessd8_slices/patient097_frame01_slice_1.h5 -trainrlessd8_slices/patient097_frame01_slice_2.h5 -trainrlessd8_slices/patient097_frame01_slice_3.h5 -trainrlessd8_slices/patient097_frame01_slice_4.h5 -trainrlessd8_slices/patient097_frame01_slice_5.h5 -trainrlessd8_slices/patient097_frame01_slice_6.h5 -trainrlessd8_slices/patient097_frame01_slice_7.h5 -trainrlessd8_slices/patient097_frame11_slice_0.h5 -trainrlessd8_slices/patient097_frame11_slice_1.h5 -trainrlessd8_slices/patient097_frame11_slice_2.h5 -trainrlessd8_slices/patient097_frame11_slice_3.h5 -trainrlessd8_slices/patient097_frame11_slice_4.h5 -trainrlessd8_slices/patient097_frame11_slice_5.h5 -trainrlessd8_slices/patient097_frame11_slice_6.h5 -trainrlessd8_slices/patient097_frame11_slice_7.h5 -trainrlessd8_slices/patient099_frame01_slice_0.h5 -trainrlessd8_slices/patient099_frame01_slice_1.h5 -trainrlessd8_slices/patient099_frame01_slice_10.h5 -trainrlessd8_slices/patient099_frame01_slice_11.h5 -trainrlessd8_slices/patient099_frame01_slice_12.h5 -trainrlessd8_slices/patient099_frame01_slice_13.h5 -trainrlessd8_slices/patient099_frame01_slice_14.h5 -trainrlessd8_slices/patient099_frame01_slice_15.h5 -trainrlessd8_slices/patient099_frame01_slice_2.h5 -trainrlessd8_slices/patient099_frame01_slice_3.h5 -trainrlessd8_slices/patient099_frame01_slice_4.h5 -trainrlessd8_slices/patient099_frame01_slice_5.h5 -trainrlessd8_slices/patient099_frame01_slice_6.h5 -trainrlessd8_slices/patient099_frame01_slice_7.h5 -trainrlessd8_slices/patient099_frame01_slice_8.h5 -trainrlessd8_slices/patient099_frame01_slice_9.h5 -trainrlessd8_slices/patient099_frame09_slice_0.h5 -trainrlessd8_slices/patient099_frame09_slice_1.h5 -trainrlessd8_slices/patient099_frame09_slice_10.h5 -trainrlessd8_slices/patient099_frame09_slice_11.h5 -trainrlessd8_slices/patient099_frame09_slice_12.h5 -trainrlessd8_slices/patient099_frame09_slice_13.h5 -trainrlessd8_slices/patient099_frame09_slice_14.h5 -trainrlessd8_slices/patient099_frame09_slice_15.h5 -trainrlessd8_slices/patient099_frame09_slice_2.h5 -trainrlessd8_slices/patient099_frame09_slice_3.h5 -trainrlessd8_slices/patient099_frame09_slice_4.h5 -trainrlessd8_slices/patient099_frame09_slice_5.h5 -trainrlessd8_slices/patient099_frame09_slice_6.h5 -trainrlessd8_slices/patient099_frame09_slice_7.h5 -trainrlessd8_slices/patient099_frame09_slice_8.h5 -trainrlessd8_slices/patient099_frame09_slice_9.h5 -trainrlessd8_slices/patient100_frame01_slice_0.h5 -trainrlessd8_slices/patient100_frame01_slice_1.h5 -trainrlessd8_slices/patient100_frame01_slice_2.h5 -trainrlessd8_slices/patient100_frame01_slice_3.h5 -trainrlessd8_slices/patient100_frame01_slice_4.h5 -trainrlessd8_slices/patient100_frame01_slice_5.h5 -trainrlessd8_slices/patient100_frame01_slice_6.h5 -trainrlessd8_slices/patient100_frame01_slice_7.h5 -trainrlessd8_slices/patient100_frame13_slice_0.h5 -trainrlessd8_slices/patient100_frame13_slice_1.h5 -trainrlessd8_slices/patient100_frame13_slice_2.h5 -trainrlessd8_slices/patient100_frame13_slice_3.h5 -trainrlessd8_slices/patient100_frame13_slice_4.h5 -trainrlessd8_slices/patient100_frame13_slice_5.h5 -trainrlessd8_slices/patient100_frame13_slice_6.h5 -trainrlessd8_slices/patient100_frame13_slice_7.h5 diff --git a/data/ACDC2017/ACDC_for2D/trainvol.csv b/data/ACDC2017/ACDC_for2D/trainvol.csv deleted file mode 100644 index 84c8d9d..0000000 --- a/data/ACDC2017/ACDC_for2D/trainvol.csv +++ /dev/null @@ -1,141 +0,0 @@ -image -train_volumes/patient001_frame01.h5 -train_volumes/patient001_frame12.h5 -train_volumes/patient002_frame01.h5 -train_volumes/patient002_frame12.h5 -train_volumes/patient003_frame01.h5 -train_volumes/patient003_frame15.h5 -train_volumes/patient004_frame01.h5 -train_volumes/patient005_frame01.h5 -train_volumes/patient005_frame13.h5 -train_volumes/patient006_frame16.h5 -train_volumes/patient007_frame01.h5 -train_volumes/patient007_frame07.h5 -train_volumes/patient008_frame13.h5 -train_volumes/patient009_frame01.h5 -train_volumes/patient010_frame01.h5 -train_volumes/patient010_frame13.h5 -train_volumes/patient011_frame01.h5 -train_volumes/patient011_frame08.h5 -train_volumes/patient012_frame01.h5 -train_volumes/patient013_frame01.h5 -train_volumes/patient014_frame13.h5 -train_volumes/patient015_frame10.h5 -train_volumes/patient016_frame12.h5 -train_volumes/patient017_frame01.h5 -train_volumes/patient017_frame09.h5 -train_volumes/patient018_frame01.h5 -train_volumes/patient018_frame10.h5 -train_volumes/patient019_frame11.h5 -train_volumes/patient020_frame01.h5 -train_volumes/patient021_frame01.h5 -train_volumes/patient021_frame13.h5 -train_volumes/patient022_frame01.h5 -train_volumes/patient022_frame11.h5 -train_volumes/patient023_frame01.h5 -train_volumes/patient024_frame09.h5 -train_volumes/patient025_frame01.h5 -train_volumes/patient026_frame01.h5 -train_volumes/patient026_frame12.h5 -train_volumes/patient027_frame01.h5 -train_volumes/patient027_frame11.h5 -train_volumes/patient028_frame01.h5 -train_volumes/patient028_frame09.h5 -train_volumes/patient029_frame12.h5 -train_volumes/patient030_frame12.h5 -train_volumes/patient031_frame01.h5 -train_volumes/patient032_frame12.h5 -train_volumes/patient033_frame01.h5 -train_volumes/patient033_frame14.h5 -train_volumes/patient034_frame01.h5 -train_volumes/patient035_frame01.h5 -train_volumes/patient035_frame11.h5 -train_volumes/patient036_frame12.h5 -train_volumes/patient037_frame01.h5 -train_volumes/patient037_frame12.h5 -train_volumes/patient038_frame01.h5 -train_volumes/patient039_frame01.h5 -train_volumes/patient039_frame10.h5 -train_volumes/patient040_frame01.h5 -train_volumes/patient041_frame01.h5 -train_volumes/patient041_frame11.h5 -train_volumes/patient042_frame01.h5 -train_volumes/patient042_frame16.h5 -train_volumes/patient043_frame01.h5 -train_volumes/patient043_frame07.h5 -train_volumes/patient044_frame01.h5 -train_volumes/patient044_frame11.h5 -train_volumes/patient045_frame01.h5 -train_volumes/patient046_frame01.h5 -train_volumes/patient046_frame10.h5 -train_volumes/patient047_frame01.h5 -train_volumes/patient048_frame01.h5 -train_volumes/patient049_frame01.h5 -train_volumes/patient049_frame11.h5 -train_volumes/patient050_frame01.h5 -train_volumes/patient050_frame12.h5 -train_volumes/patient051_frame01.h5 -train_volumes/patient051_frame11.h5 -train_volumes/patient052_frame01.h5 -train_volumes/patient052_frame09.h5 -train_volumes/patient053_frame12.h5 -train_volumes/patient054_frame01.h5 -train_volumes/patient054_frame12.h5 -train_volumes/patient055_frame10.h5 -train_volumes/patient056_frame01.h5 -train_volumes/patient056_frame12.h5 -train_volumes/patient057_frame01.h5 -train_volumes/patient058_frame14.h5 -train_volumes/patient059_frame01.h5 -train_volumes/patient059_frame09.h5 -train_volumes/patient060_frame14.h5 -train_volumes/patient061_frame01.h5 -train_volumes/patient061_frame10.h5 -train_volumes/patient062_frame01.h5 -train_volumes/patient062_frame09.h5 -train_volumes/patient063_frame16.h5 -train_volumes/patient064_frame01.h5 -train_volumes/patient066_frame01.h5 -train_volumes/patient067_frame01.h5 -train_volumes/patient067_frame10.h5 -train_volumes/patient068_frame01.h5 -train_volumes/patient069_frame01.h5 -train_volumes/patient070_frame01.h5 -train_volumes/patient071_frame09.h5 -train_volumes/patient072_frame01.h5 -train_volumes/patient073_frame10.h5 -train_volumes/patient074_frame12.h5 -train_volumes/patient075_frame01.h5 -train_volumes/patient076_frame12.h5 -train_volumes/patient077_frame09.h5 -train_volumes/patient078_frame01.h5 -train_volumes/patient078_frame09.h5 -train_volumes/patient079_frame01.h5 -train_volumes/patient079_frame11.h5 -train_volumes/patient080_frame01.h5 -train_volumes/patient080_frame10.h5 -train_volumes/patient081_frame07.h5 -train_volumes/patient082_frame01.h5 -train_volumes/patient082_frame07.h5 -train_volumes/patient083_frame01.h5 -train_volumes/patient084_frame01.h5 -train_volumes/patient084_frame10.h5 -train_volumes/patient085_frame01.h5 -train_volumes/patient087_frame01.h5 -train_volumes/patient088_frame01.h5 -train_volumes/patient088_frame12.h5 -train_volumes/patient090_frame11.h5 -train_volumes/patient091_frame01.h5 -train_volumes/patient091_frame09.h5 -train_volumes/patient092_frame01.h5 -train_volumes/patient092_frame06.h5 -train_volumes/patient093_frame14.h5 -train_volumes/patient095_frame01.h5 -train_volumes/patient095_frame12.h5 -train_volumes/patient096_frame08.h5 -train_volumes/patient097_frame01.h5 -train_volumes/patient097_frame11.h5 -train_volumes/patient099_frame01.h5 -train_volumes/patient099_frame09.h5 -train_volumes/patient100_frame01.h5 -train_volumes/patient100_frame13.h5 diff --git a/data/ACDC2017/ACDC_for2D/trainvol.txt b/data/ACDC2017/ACDC_for2D/trainvol.txt deleted file mode 100644 index 25675b9..0000000 --- a/data/ACDC2017/ACDC_for2D/trainvol.txt +++ /dev/null @@ -1,140 +0,0 @@ -train_volumes/patient001_frame01.h5 -train_volumes/patient001_frame12.h5 -train_volumes/patient002_frame01.h5 -train_volumes/patient002_frame12.h5 -train_volumes/patient003_frame01.h5 -train_volumes/patient003_frame15.h5 -train_volumes/patient004_frame01.h5 -train_volumes/patient005_frame01.h5 -train_volumes/patient005_frame13.h5 -train_volumes/patient006_frame16.h5 -train_volumes/patient007_frame01.h5 -train_volumes/patient007_frame07.h5 -train_volumes/patient008_frame13.h5 -train_volumes/patient009_frame01.h5 -train_volumes/patient010_frame01.h5 -train_volumes/patient010_frame13.h5 -train_volumes/patient011_frame01.h5 -train_volumes/patient011_frame08.h5 -train_volumes/patient012_frame01.h5 -train_volumes/patient013_frame01.h5 -train_volumes/patient014_frame13.h5 -train_volumes/patient015_frame10.h5 -train_volumes/patient016_frame12.h5 -train_volumes/patient017_frame01.h5 -train_volumes/patient017_frame09.h5 -train_volumes/patient018_frame01.h5 -train_volumes/patient018_frame10.h5 -train_volumes/patient019_frame11.h5 -train_volumes/patient020_frame01.h5 -train_volumes/patient021_frame01.h5 -train_volumes/patient021_frame13.h5 -train_volumes/patient022_frame01.h5 -train_volumes/patient022_frame11.h5 -train_volumes/patient023_frame01.h5 -train_volumes/patient024_frame09.h5 -train_volumes/patient025_frame01.h5 -train_volumes/patient026_frame01.h5 -train_volumes/patient026_frame12.h5 -train_volumes/patient027_frame01.h5 -train_volumes/patient027_frame11.h5 -train_volumes/patient028_frame01.h5 -train_volumes/patient028_frame09.h5 -train_volumes/patient029_frame12.h5 -train_volumes/patient030_frame12.h5 -train_volumes/patient031_frame01.h5 -train_volumes/patient032_frame12.h5 -train_volumes/patient033_frame01.h5 -train_volumes/patient033_frame14.h5 -train_volumes/patient034_frame01.h5 -train_volumes/patient035_frame01.h5 -train_volumes/patient035_frame11.h5 -train_volumes/patient036_frame12.h5 -train_volumes/patient037_frame01.h5 -train_volumes/patient037_frame12.h5 -train_volumes/patient038_frame01.h5 -train_volumes/patient039_frame01.h5 -train_volumes/patient039_frame10.h5 -train_volumes/patient040_frame01.h5 -train_volumes/patient041_frame01.h5 -train_volumes/patient041_frame11.h5 -train_volumes/patient042_frame01.h5 -train_volumes/patient042_frame16.h5 -train_volumes/patient043_frame01.h5 -train_volumes/patient043_frame07.h5 -train_volumes/patient044_frame01.h5 -train_volumes/patient044_frame11.h5 -train_volumes/patient045_frame01.h5 -train_volumes/patient046_frame01.h5 -train_volumes/patient046_frame10.h5 -train_volumes/patient047_frame01.h5 -train_volumes/patient048_frame01.h5 -train_volumes/patient049_frame01.h5 -train_volumes/patient049_frame11.h5 -train_volumes/patient050_frame01.h5 -train_volumes/patient050_frame12.h5 -train_volumes/patient051_frame01.h5 -train_volumes/patient051_frame11.h5 -train_volumes/patient052_frame01.h5 -train_volumes/patient052_frame09.h5 -train_volumes/patient053_frame12.h5 -train_volumes/patient054_frame01.h5 -train_volumes/patient054_frame12.h5 -train_volumes/patient055_frame10.h5 -train_volumes/patient056_frame01.h5 -train_volumes/patient056_frame12.h5 -train_volumes/patient057_frame01.h5 -train_volumes/patient058_frame14.h5 -train_volumes/patient059_frame01.h5 -train_volumes/patient059_frame09.h5 -train_volumes/patient060_frame14.h5 -train_volumes/patient061_frame01.h5 -train_volumes/patient061_frame10.h5 -train_volumes/patient062_frame01.h5 -train_volumes/patient062_frame09.h5 -train_volumes/patient063_frame16.h5 -train_volumes/patient064_frame01.h5 -train_volumes/patient066_frame01.h5 -train_volumes/patient067_frame01.h5 -train_volumes/patient067_frame10.h5 -train_volumes/patient068_frame01.h5 -train_volumes/patient069_frame01.h5 -train_volumes/patient070_frame01.h5 -train_volumes/patient071_frame09.h5 -train_volumes/patient072_frame01.h5 -train_volumes/patient073_frame10.h5 -train_volumes/patient074_frame12.h5 -train_volumes/patient075_frame01.h5 -train_volumes/patient076_frame12.h5 -train_volumes/patient077_frame09.h5 -train_volumes/patient078_frame01.h5 -train_volumes/patient078_frame09.h5 -train_volumes/patient079_frame01.h5 -train_volumes/patient079_frame11.h5 -train_volumes/patient080_frame01.h5 -train_volumes/patient080_frame10.h5 -train_volumes/patient081_frame07.h5 -train_volumes/patient082_frame01.h5 -train_volumes/patient082_frame07.h5 -train_volumes/patient083_frame01.h5 -train_volumes/patient084_frame01.h5 -train_volumes/patient084_frame10.h5 -train_volumes/patient085_frame01.h5 -train_volumes/patient087_frame01.h5 -train_volumes/patient088_frame01.h5 -train_volumes/patient088_frame12.h5 -train_volumes/patient090_frame11.h5 -train_volumes/patient091_frame01.h5 -train_volumes/patient091_frame09.h5 -train_volumes/patient092_frame01.h5 -train_volumes/patient092_frame06.h5 -train_volumes/patient093_frame14.h5 -train_volumes/patient095_frame01.h5 -train_volumes/patient095_frame12.h5 -train_volumes/patient096_frame08.h5 -train_volumes/patient097_frame01.h5 -train_volumes/patient097_frame11.h5 -train_volumes/patient099_frame01.h5 -train_volumes/patient099_frame09.h5 -train_volumes/patient100_frame01.h5 -train_volumes/patient100_frame13.h5 diff --git a/data/ACDC2017/ACDC_for2D/valid.csv b/data/ACDC2017/ACDC_for2D/valid.csv deleted file mode 100644 index 8c0cf1b..0000000 --- a/data/ACDC2017/ACDC_for2D/valid.csv +++ /dev/null @@ -1,31 +0,0 @@ -image -val_volumes/patient006_frame01.h5 -val_volumes/patient008_frame01.h5 -val_volumes/patient009_frame13.h5 -val_volumes/patient016_frame01.h5 -val_volumes/patient019_frame01.h5 -val_volumes/patient023_frame09.h5 -val_volumes/patient024_frame01.h5 -val_volumes/patient029_frame01.h5 -val_volumes/patient031_frame10.h5 -val_volumes/patient032_frame01.h5 -val_volumes/patient047_frame09.h5 -val_volumes/patient048_frame08.h5 -val_volumes/patient055_frame01.h5 -val_volumes/patient057_frame09.h5 -val_volumes/patient060_frame01.h5 -val_volumes/patient063_frame01.h5 -val_volumes/patient065_frame01.h5 -val_volumes/patient065_frame14.h5 -val_volumes/patient068_frame12.h5 -val_volumes/patient069_frame12.h5 -val_volumes/patient070_frame10.h5 -val_volumes/patient071_frame01.h5 -val_volumes/patient073_frame01.h5 -val_volumes/patient077_frame01.h5 -val_volumes/patient083_frame08.h5 -val_volumes/patient086_frame08.h5 -val_volumes/patient087_frame10.h5 -val_volumes/patient090_frame04.h5 -val_volumes/patient094_frame07.h5 -val_volumes/patient098_frame09.h5 diff --git a/data/ACDC2017/ACDC_for2D/valid.txt b/data/ACDC2017/ACDC_for2D/valid.txt deleted file mode 100644 index dbf8331..0000000 --- a/data/ACDC2017/ACDC_for2D/valid.txt +++ /dev/null @@ -1,30 +0,0 @@ -val_volumes/patient006_frame01.h5 -val_volumes/patient008_frame01.h5 -val_volumes/patient009_frame13.h5 -val_volumes/patient016_frame01.h5 -val_volumes/patient019_frame01.h5 -val_volumes/patient023_frame09.h5 -val_volumes/patient024_frame01.h5 -val_volumes/patient029_frame01.h5 -val_volumes/patient031_frame10.h5 -val_volumes/patient032_frame01.h5 -val_volumes/patient047_frame09.h5 -val_volumes/patient048_frame08.h5 -val_volumes/patient055_frame01.h5 -val_volumes/patient057_frame09.h5 -val_volumes/patient060_frame01.h5 -val_volumes/patient063_frame01.h5 -val_volumes/patient065_frame01.h5 -val_volumes/patient065_frame14.h5 -val_volumes/patient068_frame12.h5 -val_volumes/patient069_frame12.h5 -val_volumes/patient070_frame10.h5 -val_volumes/patient071_frame01.h5 -val_volumes/patient073_frame01.h5 -val_volumes/patient077_frame01.h5 -val_volumes/patient083_frame08.h5 -val_volumes/patient086_frame08.h5 -val_volumes/patient087_frame10.h5 -val_volumes/patient090_frame04.h5 -val_volumes/patient094_frame07.h5 -val_volumes/patient098_frame09.h5 diff --git a/image_process.py b/image_process.py deleted file mode 100644 index 33344bc..0000000 --- a/image_process.py +++ /dev/null @@ -1,118 +0,0 @@ -import SimpleITK as sitk -import numpy as np -from scipy import ndimage -from PIL import Image -import os -import sys -import argparse -import shutil -import h5py - -ACDC_DIR = "/home/disk16t/data/heart/ACDC_DMSPS" - -def copy_test_images(data_root): - for subdir in ["images_N", "labels"]: - source_dir = ACDC_DIR + "/TestSet/" + subdir - target_dir = data_root + "/../ACDC/TestSet/" + subdir - shutil.copytree(source_dir, target_dir, dirs_exist_ok=True) - -def write_3dh5_files(data_root, stage = 'train'): - # data_root = "./data/ACDC2017/ACDC_for2D" - volume_dir = ACDC_DIR + "/" + stage + "/images_N" - volume_names = os.listdir(volume_dir) - for volume_name in volume_names: - img_obj = sitk.ReadImage(volume_dir + "/" + volume_name) - img = sitk.GetArrayFromImage(img_obj) - print(volume_name, img.shape) - - # write 3D volumes - out_3dh5_name = volume_name.replace(".nii.gz", ".h5") - out_3dh5_dir = data_root + "/{0:}_volumes/".format(stage) - if(not os.path.exists(out_3dh5_dir)): - os.mkdir(out_3dh5_dir) - h5file = h5py.File(out_3dh5_dir + "/" + out_3dh5_name, 'w') - h5file.create_dataset('image', data = img, compression="gzip") - label_folders = ["labels"] - key_names = ["label"] - postfixes = ["gt"] - for i in range(len(label_folders)): - lab_name_i = volume_name.replace(".nii.gz", "_{0:}.nii.gz".format(postfixes[i])) - lab_dir_i = ACDC_DIR + "/" + stage + "/" + label_folders[i] - lab_obj_i = sitk.ReadImage(lab_dir_i + "/" + lab_name_i) - lab_i = sitk.GetArrayFromImage(lab_obj_i) - h5file.create_dataset(key_names[i], data = lab_i, compression="gzip") - h5file.close() - -def write_2dh5_files_for_training(data_root): - volume_dir = ACDC_DIR + "/train/images_N" - h5_dir = data_root + "/train_slices" - if(not os.path.exists(h5_dir)): - os.mkdir(h5_dir) - volume_names = os.listdir(volume_dir) - for volume_name in volume_names: - key_folders = ["images_N","labels", "scribbles", "scribbles_rless2"] + \ - ["scribbles_rlessd4", "scribbles_rlessd8", "scribbles_rlessd16"] - key_names = ["image","label", "scribble", "scribble_rless2"] + \ - ["scribble_rlessd4", "scribble_rlessd8", "scribble_rlessd16"] - postfixes = [".nii.gz", "_gt.nii.gz"] + ["_scribble.nii.gz"] * 5 - images = [] - for i in range(len(key_folders)): - img_name_i = volume_name.replace(".nii.gz", postfixes[i]) - img_dir_i = ACDC_DIR + "/train/" + key_folders[i] - img_obj_i = sitk.ReadImage(img_dir_i + "/" + img_name_i) - img_i = sitk.GetArrayFromImage(img_obj_i) - images.append(img_i) - slice_num = images[0].shape[0] - for idx in range(slice_num): - patient_name = volume_name.split(".")[0] - h5_name = patient_name + "_slice_{0:}.h5".format(idx) - h5file = h5py.File(h5_dir + "/" + h5_name, 'w') - for i in range(len(key_folders)): - key = key_names[i] - data = images[i][idx] - h5file.create_dataset(key, data = data, compression="gzip") - h5file.close() - -def write_2dh5_files_for_training2(data_root, pred_data_path): - volume_dir = ACDC_DIR + "/train/images_N" - stage2_path = data_root + "/train_slices_stage2" - if(not os.path.exists(stage2_path)): - os.mkdir(stage2_path) - volume_names = os.listdir(volume_dir) - for volume_name in volume_names: - patient_name = volume_name[:18] - img_obj = sitk.ReadImage(volume_dir + "/" + volume_name) - img = sitk.GetArrayFromImage(img_obj) - seed_name = volume_name.replace(".nii.gz", "_seeds_expand.nii.gz") - seed_obj = sitk.ReadImage(pred_data_path + "/" + seed_name) - seed = sitk.GetArrayFromImage(seed_obj) - # scrb_name = volume_name.replace(".nii.gz", "_scribble.nii.gz") - # scrb_obj = sitk.ReadImage(volume_dir + "/../scribbles/" + scrb_name) - # scrb = sitk.GetArrayFromImage(scrb_obj) - - D, H, W = img.shape - for idx in range(D): - h5_name = patient_name + "_slice_{0:}.h5".format(idx) - h5file = h5py.File(stage2_path + "/" + h5_name, 'w') - h5file.create_dataset('image', data = img[idx], compression="gzip") - h5file.create_dataset('expanded_seeds', data = seed[idx], compression="gzip") - h5file.close() - - - -if __name__ == "__main__": - data_root = "data/ACDC2017/ACDC_for2D" - if(len(sys.argv) < 2): - print('Number of arguments should be at least 2. e.g.') - print(' python image_process.py 0') - exit() - if(sys.argv[1] == '0'): - print(sys.argv[1]) - write_3dh5_files(data_root, "train") - write_3dh5_files(data_root, "val") - write_2dh5_files_for_training(data_root) - copy_test_images(data_root) - else: - pred_data_path = "result/acdc_dmsps_train" - write_2dh5_files_for_training2(data_root, pred_data_path) - diff --git a/imgs/framework.png b/imgs/framework.png deleted file mode 100644 index 5808307..0000000 Binary files a/imgs/framework.png and /dev/null differ diff --git a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/log/events.out.tfevents.1691236391.x-Super-Server b/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/log/events.out.tfevents.1691236391.x-Super-Server deleted file mode 100644 index 891e342..0000000 Binary files a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/log/events.out.tfevents.1691236391.x-Super-Server and /dev/null differ diff --git a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/train_log.txt b/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/train_log.txt deleted file mode 100644 index cca3d49..0000000 --- a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/train_log.txt +++ /dev/null @@ -1,760 +0,0 @@ -[19:53:07.933] Namespace(base_lr=0.01, batch_size=24, data_name='ACDC', data_type='HeartM', deterministic=1, exp='A3_weakly_PLS_2d', fold='v2_soft_ce_l8_0805', max_iterations=30000, model='unet_cct', num_classes=4, patch_size=[256, 256], root_path='/mnt/data/HM/Datasets/ACDC2017/ACDC_for2D', seed=2022, sup_type='scribble', trainData='train.txt', validData='valid.txt') -[19:53:11.052] 57 iterations per epoch -[19:53:11.053] max epoch: 527 -[19:54:41.655] iteration 200 : loss : 6.427439, loss_ce: 0.239125, loss_pse_sup_soft: 0.773539, alpha: 0.093016 -[19:54:44.445] avg_metric:[[0.54227575] - [0.63170759] - [0.6869965 ]] -[19:54:44.445] iteration 200 : dice_score : 0.620327 -[19:56:13.245] iteration 400 : loss : 6.168567, loss_ce: 0.125565, loss_pse_sup_soft: 0.755375, alpha: 0.438119 -[19:56:15.601] avg_metric:[[0.71092674] - [0.75862056] - [0.87074275]] -[19:56:15.601] iteration 400 : dice_score : 0.780097 -[19:57:26.945] iteration 600 : loss : 6.117565, loss_ce: 0.103681, loss_pse_sup_soft: 0.751735, alpha: 0.547861 -[19:57:29.816] avg_metric:[[0.60198255] - [0.74495714] - [0.82022222]] -[19:57:29.817] iteration 600 : dice_score : 0.722387 -[19:59:02.782] iteration 800 : loss : 6.069458, loss_ce: 0.065016, loss_pse_sup_soft: 0.750555, alpha: 0.023007 -[19:59:05.779] avg_metric:[[0.79149593] - [0.79635148] - [0.87667717]] -[19:59:05.780] iteration 800 : dice_score : 0.821508 -[20:00:30.792] iteration 1000 : loss : 6.064914, loss_ce: 0.063818, loss_pse_sup_soft: 0.750137, alpha: 0.060510 -[20:00:33.102] avg_metric:[[0.74636742] - [0.71820697] - [0.82162328]] -[20:00:33.103] iteration 1000 : dice_score : 0.762066 -[20:01:49.383] iteration 1200 : loss : 6.125109, loss_ce: 0.113080, loss_pse_sup_soft: 0.751504, alpha: 0.511315 -[20:01:52.216] avg_metric:[[0.81391363] - [0.79592116] - [0.88683651]] -[20:01:52.216] iteration 1200 : dice_score : 0.832224 -[20:03:23.976] iteration 1400 : loss : 6.116121, loss_ce: 0.108244, loss_pse_sup_soft: 0.750985, alpha: 0.691276 -[20:03:26.551] avg_metric:[[0.80098123] - [0.77221667] - [0.87374035]] -[20:03:26.552] iteration 1400 : dice_score : 0.815646 -[20:04:48.653] iteration 1600 : loss : 6.040705, loss_ce: 0.040634, loss_pse_sup_soft: 0.750009, alpha: 0.057457 -[20:04:51.177] avg_metric:[[0.81461837] - [0.79985176] - [0.88301862]] -[20:04:51.177] iteration 1600 : dice_score : 0.832496 -[20:06:09.608] iteration 1800 : loss : 6.029346, loss_ce: 0.034780, loss_pse_sup_soft: 0.749321, alpha: 0.985193 -[20:06:12.432] avg_metric:[[0.82468438] - [0.81945189] - [0.89681312]] -[20:06:12.433] iteration 1800 : dice_score : 0.846983 -[20:07:44.851] iteration 2000 : loss : 6.031072, loss_ce: 0.044842, loss_pse_sup_soft: 0.748279, alpha: 0.782608 -[20:07:47.392] avg_metric:[[0.83908348] - [0.79827309] - [0.89093498]] -[20:07:47.393] iteration 2000 : dice_score : 0.842764 -[20:09:04.954] iteration 2200 : loss : 6.005624, loss_ce: 0.022075, loss_pse_sup_soft: 0.747944, alpha: 0.328230 -[20:09:07.526] avg_metric:[[0.82238318] - [0.82356186] - [0.89910055]] -[20:09:07.526] iteration 2200 : dice_score : 0.848349 -[20:10:29.374] iteration 2400 : loss : 6.017882, loss_ce: 0.027848, loss_pse_sup_soft: 0.748754, alpha: 0.703715 -[20:10:32.198] avg_metric:[[0.81676278] - [0.8126343 ] - [0.88739696]] -[20:10:32.199] iteration 2400 : dice_score : 0.838931 -[20:12:03.360] iteration 2600 : loss : 6.026493, loss_ce: 0.031160, loss_pse_sup_soft: 0.749417, alpha: 0.381020 -[20:12:06.104] avg_metric:[[0.82660208] - [0.79655566] - [0.89300154]] -[20:12:06.106] iteration 2600 : dice_score : 0.838720 -[20:13:20.717] iteration 2800 : loss : 6.024775, loss_ce: 0.039347, loss_pse_sup_soft: 0.748178, alpha: 0.049184 -[20:13:23.108] avg_metric:[[0.82988187] - [0.81764888] - [0.89825344]] -[20:13:23.109] iteration 2800 : dice_score : 0.848595 -[20:14:47.403] iteration 3000 : loss : 6.013090, loss_ce: 0.029380, loss_pse_sup_soft: 0.747964, alpha: 0.051762 -[20:14:49.969] avg_metric:[[0.82206111] - [0.79835105] - [0.89004651]] -[20:14:49.971] iteration 3000 : dice_score : 0.836820 -[20:16:22.182] iteration 3200 : loss : 5.999783, loss_ce: 0.017345, loss_pse_sup_soft: 0.747805, alpha: 0.085885 -[20:16:24.917] avg_metric:[[0.81830707] - [0.80331264] - [0.88816911]] -[20:16:24.917] iteration 3200 : dice_score : 0.836596 -[20:17:36.107] iteration 3400 : loss : 6.071870, loss_ce: 0.086227, loss_pse_sup_soft: 0.748205, alpha: 0.889961 -[20:17:38.536] avg_metric:[[0.84141648] - [0.81867121] - [0.89008544]] -[20:17:38.536] iteration 3400 : dice_score : 0.850058 -[20:19:06.020] iteration 3600 : loss : 5.999686, loss_ce: 0.013973, loss_pse_sup_soft: 0.748214, alpha: 0.750462 -[20:19:08.830] avg_metric:[[0.84312181] - [0.83578066] - [0.91373647]] -[20:19:08.831] iteration 3600 : dice_score : 0.864213 -[20:20:38.514] iteration 3800 : loss : 6.014184, loss_ce: 0.031970, loss_pse_sup_soft: 0.747777, alpha: 0.788061 -[20:20:40.858] avg_metric:[[0.83358453] - [0.81191442] - [0.89255947]] -[20:20:40.859] iteration 3800 : dice_score : 0.846019 -[20:21:53.988] iteration 4000 : loss : 6.001860, loss_ce: 0.027172, loss_pse_sup_soft: 0.746836, alpha: 0.403655 -[20:21:56.148] avg_metric:[[0.83261007] - [0.80986398] - [0.88105164]] -[20:21:56.148] iteration 4000 : dice_score : 0.841175 -[20:23:25.483] iteration 4200 : loss : 5.993118, loss_ce: 0.014960, loss_pse_sup_soft: 0.747270, alpha: 0.152091 -[20:23:28.159] avg_metric:[[0.85229869] - [0.83887882] - [0.91542819]] -[20:23:28.159] iteration 4200 : dice_score : 0.868869 -[20:24:56.222] iteration 4400 : loss : 5.985749, loss_ce: 0.014561, loss_pse_sup_soft: 0.746398, alpha: 0.722330 -[20:24:58.954] avg_metric:[[0.85771227] - [0.84016518] - [0.9195142 ]] -[20:24:58.955] iteration 4400 : dice_score : 0.872464 -[20:26:11.503] iteration 4600 : loss : 6.000108, loss_ce: 0.022344, loss_pse_sup_soft: 0.747220, alpha: 0.026087 -[20:26:14.135] avg_metric:[[0.84873153] - [0.84168408] - [0.90511805]] -[20:26:14.136] iteration 4600 : dice_score : 0.865178 -[20:27:46.926] iteration 4800 : loss : 5.989534, loss_ce: 0.011388, loss_pse_sup_soft: 0.747268, alpha: 0.929736 -[20:27:49.668] avg_metric:[[0.83368825] - [0.82179909] - [0.89527907]] -[20:27:49.669] iteration 4800 : dice_score : 0.850255 -[20:29:12.888] iteration 5000 : loss : 5.988081, loss_ce: 0.012248, loss_pse_sup_soft: 0.746979, alpha: 0.212928 -[20:29:15.072] avg_metric:[[0.84956395] - [0.8281856 ] - [0.88864534]] -[20:29:15.074] iteration 5000 : dice_score : 0.855465 -[20:29:15.123] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_soft_ce_l8_0805/iter_5000.pth -[20:30:32.304] iteration 5200 : loss : 5.996626, loss_ce: 0.021635, loss_pse_sup_soft: 0.746874, alpha: 0.399972 -[20:30:34.827] avg_metric:[[0.85120335] - [0.84027263] - [0.8945237 ]] -[20:30:34.828] iteration 5200 : dice_score : 0.862000 -[20:32:06.397] iteration 5400 : loss : 5.997557, loss_ce: 0.015023, loss_pse_sup_soft: 0.747817, alpha: 0.965603 -[20:32:08.953] avg_metric:[[0.84880066] - [0.82938646] - [0.89061642]] -[20:32:08.953] iteration 5400 : dice_score : 0.856268 -[20:33:29.382] iteration 5600 : loss : 5.999147, loss_ce: 0.021414, loss_pse_sup_soft: 0.747217, alpha: 0.551517 -[20:33:31.586] avg_metric:[[0.86189243] - [0.8371436 ] - [0.90789939]] -[20:33:31.588] iteration 5600 : dice_score : 0.868978 -[20:34:51.215] iteration 5800 : loss : 5.981710, loss_ce: 0.009419, loss_pse_sup_soft: 0.746536, alpha: 0.565185 -[20:34:53.924] avg_metric:[[0.8471317 ] - [0.82330352] - [0.89276381]] -[20:34:53.925] iteration 5800 : dice_score : 0.854400 -[20:36:25.895] iteration 6000 : loss : 5.982307, loss_ce: 0.010394, loss_pse_sup_soft: 0.746489, alpha: 0.372450 -[20:36:28.608] avg_metric:[[0.82686191] - [0.83017685] - [0.90806608]] -[20:36:28.610] iteration 6000 : dice_score : 0.855035 -[20:37:44.415] iteration 6200 : loss : 6.002254, loss_ce: 0.032092, loss_pse_sup_soft: 0.746270, alpha: 0.157151 -[20:37:46.973] avg_metric:[[0.85144792] - [0.82211647] - [0.90602935]] -[20:37:46.974] iteration 6200 : dice_score : 0.859865 -[20:39:09.652] iteration 6400 : loss : 5.989679, loss_ce: 0.015837, loss_pse_sup_soft: 0.746730, alpha: 0.410799 -[20:39:12.233] avg_metric:[[0.86076994] - [0.82954485] - [0.91713471]] -[20:39:12.234] iteration 6400 : dice_score : 0.869150 -[20:40:43.771] iteration 6600 : loss : 5.973016, loss_ce: 0.004012, loss_pse_sup_soft: 0.746126, alpha: 0.912722 -[20:40:46.460] avg_metric:[[0.86376928] - [0.84025285] - [0.9041854 ]] -[20:40:46.462] iteration 6600 : dice_score : 0.869403 -[20:41:59.825] iteration 6800 : loss : 5.984056, loss_ce: 0.014071, loss_pse_sup_soft: 0.746248, alpha: 0.732540 -[20:42:02.268] avg_metric:[[0.85029282] - [0.84364251] - [0.89402279]] -[20:42:02.269] iteration 6800 : dice_score : 0.862653 -[20:43:27.757] iteration 7000 : loss : 5.988935, loss_ce: 0.014284, loss_pse_sup_soft: 0.746831, alpha: 0.547269 -[20:43:30.819] avg_metric:[[0.85894245] - [0.84350664] - [0.90498631]] -[20:43:30.820] iteration 7000 : dice_score : 0.869145 -[20:45:02.169] iteration 7200 : loss : 5.978070, loss_ce: 0.009816, loss_pse_sup_soft: 0.746032, alpha: 0.477678 -[20:45:04.442] avg_metric:[[0.85466151] - [0.83507318] - [0.90997738]] -[20:45:04.442] iteration 7200 : dice_score : 0.866571 -[20:46:17.166] iteration 7400 : loss : 5.983348, loss_ce: 0.010827, loss_pse_sup_soft: 0.746565, alpha: 0.026709 -[20:46:19.708] avg_metric:[[0.86365084] - [0.83859179] - [0.91697449]] -[20:46:19.709] iteration 7400 : dice_score : 0.873072 -[20:47:48.227] iteration 7600 : loss : 5.982670, loss_ce: 0.013728, loss_pse_sup_soft: 0.746118, alpha: 0.237706 -[20:47:51.148] avg_metric:[[0.86725653] - [0.83503019] - [0.90971487]] -[20:47:51.149] iteration 7600 : dice_score : 0.870667 -[20:49:19.734] iteration 7800 : loss : 5.983641, loss_ce: 0.013756, loss_pse_sup_soft: 0.746236, alpha: 0.874727 -[20:49:22.409] avg_metric:[[0.86147798] - [0.8432249 ] - [0.9221208 ]] -[20:49:22.410] iteration 7800 : dice_score : 0.875608 -[20:50:33.912] iteration 8000 : loss : 5.980670, loss_ce: 0.011200, loss_pse_sup_soft: 0.746184, alpha: 0.082410 -[20:50:36.825] avg_metric:[[0.86183242] - [0.83939051] - [0.91092817]] -[20:50:36.826] iteration 8000 : dice_score : 0.870717 -[20:52:08.679] iteration 8200 : loss : 5.996132, loss_ce: 0.023912, loss_pse_sup_soft: 0.746528, alpha: 0.676088 -[20:52:11.504] avg_metric:[[0.86497105] - [0.84649594] - [0.92221845]] -[20:52:11.505] iteration 8200 : dice_score : 0.877895 -[20:53:37.158] iteration 8400 : loss : 5.990515, loss_ce: 0.020529, loss_pse_sup_soft: 0.746248, alpha: 0.806474 -[20:53:39.679] avg_metric:[[0.85905559] - [0.84115592] - [0.91224198]] -[20:53:39.680] iteration 8400 : dice_score : 0.870818 -[20:54:54.945] iteration 8600 : loss : 5.975759, loss_ce: 0.009762, loss_pse_sup_soft: 0.745750, alpha: 0.353954 -[20:54:57.707] avg_metric:[[0.86250162] - [0.83526827] - [0.9118083 ]] -[20:54:57.708] iteration 8600 : dice_score : 0.869859 -[20:56:30.305] iteration 8800 : loss : 5.974112, loss_ce: 0.004484, loss_pse_sup_soft: 0.746204, alpha: 0.020247 -[20:56:32.996] avg_metric:[[0.86067731] - [0.83823166] - [0.91546683]] -[20:56:32.997] iteration 8800 : dice_score : 0.871459 -[20:57:53.908] iteration 9000 : loss : 5.978140, loss_ce: 0.007507, loss_pse_sup_soft: 0.746329, alpha: 0.044747 -[20:57:56.464] avg_metric:[[0.86863935] - [0.8349469 ] - [0.91898576]] -[20:57:56.465] iteration 9000 : dice_score : 0.874191 -[20:59:15.264] iteration 9200 : loss : 5.991429, loss_ce: 0.015732, loss_pse_sup_soft: 0.746962, alpha: 0.582162 -[20:59:17.919] avg_metric:[[0.86974268] - [0.84657435] - [0.90542357]] -[20:59:17.921] iteration 9200 : dice_score : 0.873914 -[21:00:50.018] iteration 9400 : loss : 5.976101, loss_ce: 0.009883, loss_pse_sup_soft: 0.745777, alpha: 0.685391 -[21:00:52.730] avg_metric:[[0.87280452] - [0.84475389] - [0.92060899]] -[21:00:52.731] iteration 9400 : dice_score : 0.879389 -[21:02:10.172] iteration 9600 : loss : 5.987581, loss_ce: 0.019843, loss_pse_sup_soft: 0.745967, alpha: 0.800580 -[21:02:12.476] avg_metric:[[0.86680701] - [0.83853249] - [0.91834747]] -[21:02:12.478] iteration 9600 : dice_score : 0.874562 -[21:03:34.567] iteration 9800 : loss : 5.980419, loss_ce: 0.013187, loss_pse_sup_soft: 0.745904, alpha: 0.987378 -[21:03:37.139] avg_metric:[[0.86541098] - [0.85205724] - [0.8977736 ]] -[21:03:37.139] iteration 9800 : dice_score : 0.871747 -[21:05:09.946] iteration 10000 : loss : 5.977162, loss_ce: 0.010202, loss_pse_sup_soft: 0.745870, alpha: 0.234998 -[21:05:12.638] avg_metric:[[0.86957558] - [0.84097418] - [0.9080202 ]] -[21:05:12.639] iteration 10000 : dice_score : 0.872857 -[21:05:12.684] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_soft_ce_l8_0805/iter_10000.pth -[21:06:27.309] iteration 10200 : loss : 5.984520, loss_ce: 0.017647, loss_pse_sup_soft: 0.745859, alpha: 0.841821 -[21:06:29.987] avg_metric:[[0.86385535] - [0.83387393] - [0.90655854]] -[21:06:29.987] iteration 10200 : dice_score : 0.868096 -[21:07:55.852] iteration 10400 : loss : 5.982946, loss_ce: 0.017356, loss_pse_sup_soft: 0.745699, alpha: 0.336909 -[21:07:58.658] avg_metric:[[0.8625626 ] - [0.84537647] - [0.90689559]] -[21:07:58.659] iteration 10400 : dice_score : 0.871612 -[21:09:30.544] iteration 10600 : loss : 5.974940, loss_ce: 0.008383, loss_pse_sup_soft: 0.745820, alpha: 0.898399 -[21:09:32.854] avg_metric:[[0.86785686] - [0.84343887] - [0.91991297]] -[21:09:32.855] iteration 10600 : dice_score : 0.877070 -[21:10:44.873] iteration 10800 : loss : 5.970513, loss_ce: 0.005881, loss_pse_sup_soft: 0.745579, alpha: 0.223824 -[21:10:47.334] avg_metric:[[0.86168591] - [0.850021 ] - [0.91187165]] -[21:10:47.335] iteration 10800 : dice_score : 0.874526 -[21:12:16.585] iteration 11000 : loss : 5.978604, loss_ce: 0.014337, loss_pse_sup_soft: 0.745533, alpha: 0.935009 -[21:12:18.947] avg_metric:[[0.86575707] - [0.8493368 ] - [0.91806105]] -[21:12:18.947] iteration 11000 : dice_score : 0.877718 -[21:13:48.880] iteration 11200 : loss : 5.975898, loss_ce: 0.012764, loss_pse_sup_soft: 0.745392, alpha: 0.762962 -[21:13:51.378] avg_metric:[[0.87407198] - [0.85036717] - [0.92032053]] -[21:13:51.379] iteration 11200 : dice_score : 0.881587 -[21:15:02.386] iteration 11400 : loss : 5.966578, loss_ce: 0.003856, loss_pse_sup_soft: 0.745340, alpha: 0.818018 -[21:15:04.841] avg_metric:[[0.86887452] - [0.8493474 ] - [0.91842415]] -[21:15:04.842] iteration 11400 : dice_score : 0.878882 -[21:16:36.182] iteration 11600 : loss : 5.986506, loss_ce: 0.016439, loss_pse_sup_soft: 0.746258, alpha: 0.056232 -[21:16:39.124] avg_metric:[[0.86818973] - [0.84873262] - [0.9236651 ]] -[21:16:39.126] iteration 11600 : dice_score : 0.880196 -[21:18:05.422] iteration 11800 : loss : 5.968777, loss_ce: 0.005466, loss_pse_sup_soft: 0.745414, alpha: 0.364555 -[21:18:07.861] avg_metric:[[0.86626366] - [0.8463004 ] - [0.92649172]] -[21:18:07.862] iteration 11800 : dice_score : 0.879685 -[21:19:20.043] iteration 12000 : loss : 5.970903, loss_ce: 0.004015, loss_pse_sup_soft: 0.745861, alpha: 0.000577 -[21:19:22.810] avg_metric:[[0.86071945] - [0.83691064] - [0.91201524]] -[21:19:22.811] iteration 12000 : dice_score : 0.869882 -[21:20:55.471] iteration 12200 : loss : 5.970310, loss_ce: 0.004345, loss_pse_sup_soft: 0.745746, alpha: 0.069479 -[21:20:58.081] avg_metric:[[0.86705859] - [0.84291532] - [0.90072857]] -[21:20:58.082] iteration 12200 : dice_score : 0.870234 -[21:22:20.068] iteration 12400 : loss : 5.971586, loss_ce: 0.005403, loss_pse_sup_soft: 0.745773, alpha: 0.662625 -[21:22:22.657] avg_metric:[[0.86953439] - [0.83952683] - [0.91300963]] -[21:22:22.658] iteration 12400 : dice_score : 0.874024 -[21:23:40.974] iteration 12600 : loss : 5.967258, loss_ce: 0.003030, loss_pse_sup_soft: 0.745529, alpha: 0.933536 -[21:23:43.692] avg_metric:[[0.87614625] - [0.84717682] - [0.91747666]] -[21:23:43.693] iteration 12600 : dice_score : 0.880267 -[21:25:14.396] iteration 12800 : loss : 5.972811, loss_ce: 0.006608, loss_pse_sup_soft: 0.745775, alpha: 0.374596 -[21:25:16.987] avg_metric:[[0.87180747] - [0.83294253] - [0.90479448]] -[21:25:16.989] iteration 12800 : dice_score : 0.869848 -[21:26:35.137] iteration 13000 : loss : 5.973714, loss_ce: 0.008485, loss_pse_sup_soft: 0.745654, alpha: 0.334795 -[21:26:37.525] avg_metric:[[0.86637874] - [0.84275949] - [0.92042001]] -[21:26:37.525] iteration 13000 : dice_score : 0.876519 -[21:27:58.250] iteration 13200 : loss : 5.966079, loss_ce: 0.003311, loss_pse_sup_soft: 0.745346, alpha: 0.677066 -[21:28:01.026] avg_metric:[[0.87318864] - [0.84188893] - [0.9135268 ]] -[21:28:01.027] iteration 13200 : dice_score : 0.876201 -[21:29:32.037] iteration 13400 : loss : 5.977319, loss_ce: 0.011601, loss_pse_sup_soft: 0.745715, alpha: 0.719439 -[21:29:35.054] avg_metric:[[0.87586669] - [0.85370386] - [0.92223628]] -[21:29:35.054] iteration 13400 : dice_score : 0.883936 -[21:30:48.978] iteration 13600 : loss : 5.977070, loss_ce: 0.011469, loss_pse_sup_soft: 0.745700, alpha: 0.342312 -[21:30:51.330] avg_metric:[[0.86854622] - [0.84391866] - [0.9106614 ]] -[21:30:51.331] iteration 13600 : dice_score : 0.874375 -[21:32:16.402] iteration 13800 : loss : 5.975690, loss_ce: 0.006613, loss_pse_sup_soft: 0.746135, alpha: 0.089510 -[21:32:19.146] avg_metric:[[0.86504283] - [0.84254552] - [0.90734092]] -[21:32:19.147] iteration 13800 : dice_score : 0.871643 -[21:33:49.791] iteration 14000 : loss : 5.976664, loss_ce: 0.008779, loss_pse_sup_soft: 0.745986, alpha: 0.282470 -[21:33:52.071] avg_metric:[[0.86423614] - [0.83808191] - [0.9004573 ]] -[21:33:52.072] iteration 14000 : dice_score : 0.867592 -[21:35:03.141] iteration 14200 : loss : 5.967903, loss_ce: 0.003833, loss_pse_sup_soft: 0.745509, alpha: 0.513668 -[21:35:05.746] avg_metric:[[0.87007869] - [0.84746239] - [0.91517727]] -[21:35:05.747] iteration 14200 : dice_score : 0.877573 -[21:36:32.832] iteration 14400 : loss : 5.971081, loss_ce: 0.007109, loss_pse_sup_soft: 0.745496, alpha: 0.348119 -[21:36:35.270] avg_metric:[[0.86704127] - [0.8399297 ] - [0.91539471]] -[21:36:35.270] iteration 14400 : dice_score : 0.874122 -[21:38:03.637] iteration 14600 : loss : 5.967681, loss_ce: 0.004392, loss_pse_sup_soft: 0.745411, alpha: 0.732853 -[21:38:06.210] avg_metric:[[0.87725395] - [0.85173494] - [0.92813821]] -[21:38:06.210] iteration 14600 : dice_score : 0.885709 -[21:39:16.764] iteration 14800 : loss : 5.971276, loss_ce: 0.006985, loss_pse_sup_soft: 0.745536, alpha: 0.589592 -[21:39:19.366] avg_metric:[[0.86768978] - [0.84196994] - [0.91083074]] -[21:39:19.367] iteration 14800 : dice_score : 0.873497 -[21:40:48.437] iteration 15000 : loss : 5.971807, loss_ce: 0.007938, loss_pse_sup_soft: 0.745484, alpha: 0.438765 -[21:40:51.198] avg_metric:[[0.87360771] - [0.84333755] - [0.91587378]] -[21:40:51.200] iteration 15000 : dice_score : 0.877606 -[21:40:51.245] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_soft_ce_l8_0805/iter_15000.pth -[21:42:16.670] iteration 15200 : loss : 5.966677, loss_ce: 0.003331, loss_pse_sup_soft: 0.745418, alpha: 0.582978 -[21:42:19.004] avg_metric:[[0.87333093] - [0.84052494] - [0.9114718 ]] -[21:42:19.005] iteration 15200 : dice_score : 0.875109 -[21:43:31.514] iteration 15400 : loss : 5.966218, loss_ce: 0.002270, loss_pse_sup_soft: 0.745494, alpha: 0.126045 -[21:43:34.156] avg_metric:[[0.87467527] - [0.85147206] - [0.91830809]] -[21:43:34.157] iteration 15400 : dice_score : 0.881485 -[21:45:04.630] iteration 15600 : loss : 5.972775, loss_ce: 0.007359, loss_pse_sup_soft: 0.745677, alpha: 0.647897 -[21:45:07.274] avg_metric:[[0.87252874] - [0.84592664] - [0.92086305]] -[21:45:07.275] iteration 15600 : dice_score : 0.879773 -[21:46:28.946] iteration 15800 : loss : 5.967352, loss_ce: 0.002175, loss_pse_sup_soft: 0.745647, alpha: 0.396698 -[21:46:31.487] avg_metric:[[0.87554728] - [0.84869302] - [0.91690913]] -[21:46:31.488] iteration 15800 : dice_score : 0.880383 -[21:47:46.905] iteration 16000 : loss : 5.967099, loss_ce: 0.003879, loss_pse_sup_soft: 0.745403, alpha: 0.601766 -[21:47:49.649] avg_metric:[[0.87408119] - [0.85631262] - [0.92732322]] -[21:47:49.649] iteration 16000 : dice_score : 0.885906 -[21:49:20.798] iteration 16200 : loss : 5.973147, loss_ce: 0.007978, loss_pse_sup_soft: 0.745646, alpha: 0.767826 -[21:49:23.602] avg_metric:[[0.87333393] - [0.84799878] - [0.92578489]] -[21:49:23.603] iteration 16200 : dice_score : 0.882373 -[21:50:41.136] iteration 16400 : loss : 6.004604, loss_ce: 0.040821, loss_pse_sup_soft: 0.745473, alpha: 0.290716 -[21:50:44.179] avg_metric:[[0.87279272] - [0.84443037] - [0.9229016 ]] -[21:50:44.180] iteration 16400 : dice_score : 0.880042 -[21:52:04.438] iteration 16600 : loss : 5.965456, loss_ce: 0.002240, loss_pse_sup_soft: 0.745402, alpha: 0.420156 -[21:52:07.125] avg_metric:[[0.87421357] - [0.84466063] - [0.91806296]] -[21:52:07.127] iteration 16600 : dice_score : 0.878979 -[21:53:37.715] iteration 16800 : loss : 5.978939, loss_ce: 0.013429, loss_pse_sup_soft: 0.745689, alpha: 0.308593 -[21:53:40.311] avg_metric:[[0.87411436] - [0.85201008] - [0.92408523]] -[21:53:40.312] iteration 16800 : dice_score : 0.883403 -[21:54:54.893] iteration 17000 : loss : 5.968325, loss_ce: 0.002504, loss_pse_sup_soft: 0.745728, alpha: 0.631983 -[21:54:57.529] avg_metric:[[0.88294541] - [0.84054724] - [0.90685171]] -[21:54:57.530] iteration 17000 : dice_score : 0.876781 -[21:56:20.912] iteration 17200 : loss : 5.967004, loss_ce: 0.002597, loss_pse_sup_soft: 0.745551, alpha: 0.336475 -[21:56:23.588] avg_metric:[[0.86985529] - [0.85194678] - [0.91704805]] -[21:56:23.590] iteration 17200 : dice_score : 0.879617 -[21:57:54.814] iteration 17400 : loss : 5.971920, loss_ce: 0.009811, loss_pse_sup_soft: 0.745264, alpha: 0.803886 -[21:57:57.089] avg_metric:[[0.8757914 ] - [0.84642036] - [0.91870346]] -[21:57:57.091] iteration 17400 : dice_score : 0.880305 -[21:59:07.374] iteration 17600 : loss : 5.964679, loss_ce: 0.003333, loss_pse_sup_soft: 0.745168, alpha: 0.384893 -[21:59:09.775] avg_metric:[[0.87385383] - [0.84133176] - [0.90666051]] -[21:59:09.776] iteration 17600 : dice_score : 0.873949 -[22:00:36.719] iteration 17800 : loss : 5.971680, loss_ce: 0.006264, loss_pse_sup_soft: 0.745677, alpha: 0.097897 -[22:00:39.368] avg_metric:[[0.87463948] - [0.84558032] - [0.91804705]] -[22:00:39.369] iteration 17800 : dice_score : 0.879422 -[22:02:06.383] iteration 18000 : loss : 5.971320, loss_ce: 0.005420, loss_pse_sup_soft: 0.745737, alpha: 0.877891 -[22:02:08.906] avg_metric:[[0.87382023] - [0.84992596] - [0.91322527]] -[22:02:08.906] iteration 18000 : dice_score : 0.878990 -[22:03:20.373] iteration 18200 : loss : 5.972499, loss_ce: 0.007831, loss_pse_sup_soft: 0.745584, alpha: 0.363489 -[22:03:22.874] avg_metric:[[0.874725 ] - [0.84425324] - [0.91557331]] -[22:03:22.875] iteration 18200 : dice_score : 0.878184 -[22:04:50.999] iteration 18400 : loss : 5.964115, loss_ce: 0.001160, loss_pse_sup_soft: 0.745369, alpha: 0.825629 -[22:04:53.805] avg_metric:[[0.86963585] - [0.84519314] - [0.90974908]] -[22:04:53.807] iteration 18400 : dice_score : 0.874859 -[22:06:19.443] iteration 18600 : loss : 5.972089, loss_ce: 0.008052, loss_pse_sup_soft: 0.745505, alpha: 0.510830 -[22:06:21.803] avg_metric:[[0.87515304] - [0.85404126] - [0.92269948]] -[22:06:21.804] iteration 18600 : dice_score : 0.883965 -[22:07:32.995] iteration 18800 : loss : 5.968177, loss_ce: 0.007072, loss_pse_sup_soft: 0.745138, alpha: 0.989350 -[22:07:35.890] avg_metric:[[0.86678038] - [0.84842385] - [0.91305463]] -[22:07:35.890] iteration 18800 : dice_score : 0.876086 -[22:09:06.763] iteration 19000 : loss : 5.967896, loss_ce: 0.003195, loss_pse_sup_soft: 0.745588, alpha: 0.842633 -[22:09:09.469] avg_metric:[[0.87416658] - [0.84784148] - [0.91319288]] -[22:09:09.470] iteration 19000 : dice_score : 0.878400 -[22:10:30.754] iteration 19200 : loss : 5.967897, loss_ce: 0.004321, loss_pse_sup_soft: 0.745447, alpha: 0.278862 -[22:10:33.207] avg_metric:[[0.87504131] - [0.84535135] - [0.90910243]] -[22:10:33.208] iteration 19200 : dice_score : 0.876498 -[22:11:49.549] iteration 19400 : loss : 5.963555, loss_ce: 0.001726, loss_pse_sup_soft: 0.745229, alpha: 0.933314 -[22:11:52.287] avg_metric:[[0.86780785] - [0.85196529] - [0.91358568]] -[22:11:52.288] iteration 19400 : dice_score : 0.877786 -[22:13:22.459] iteration 19600 : loss : 5.980431, loss_ce: 0.014236, loss_pse_sup_soft: 0.745774, alpha: 0.554988 -[22:13:25.265] avg_metric:[[0.87960299] - [0.84675547] - [0.91371849]] -[22:13:25.265] iteration 19600 : dice_score : 0.880026 -[22:14:43.666] iteration 19800 : loss : 5.969723, loss_ce: 0.007004, loss_pse_sup_soft: 0.745340, alpha: 0.633755 -[22:14:45.953] avg_metric:[[0.87431353] - [0.84904425] - [0.91749766]] -[22:14:45.955] iteration 19800 : dice_score : 0.880285 -[22:16:05.506] iteration 20000 : loss : 5.968650, loss_ce: 0.004748, loss_pse_sup_soft: 0.745488, alpha: 0.342870 -[22:16:08.212] avg_metric:[[0.87649054] - [0.85371922] - [0.92188156]] -[22:16:08.213] iteration 20000 : dice_score : 0.884030 -[22:16:08.255] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_soft_ce_l8_0805/iter_20000.pth -[22:17:38.784] iteration 20200 : loss : 5.965518, loss_ce: 0.002971, loss_pse_sup_soft: 0.745318, alpha: 0.605724 -[22:17:41.473] avg_metric:[[0.87344456] - [0.84907579] - [0.91608707]] -[22:17:41.474] iteration 20200 : dice_score : 0.879536 -[22:18:55.504] iteration 20400 : loss : 5.964634, loss_ce: 0.001306, loss_pse_sup_soft: 0.745416, alpha: 0.022194 -[22:18:58.086] avg_metric:[[0.87115544] - [0.85008012] - [0.92253269]] -[22:18:58.088] iteration 20400 : dice_score : 0.881256 -[22:20:21.328] iteration 20600 : loss : 5.967785, loss_ce: 0.004680, loss_pse_sup_soft: 0.745388, alpha: 0.422622 -[22:20:24.120] avg_metric:[[0.87693195] - [0.85240885] - [0.92439721]] -[22:20:24.122] iteration 20600 : dice_score : 0.884579 -[22:21:54.316] iteration 20800 : loss : 5.968815, loss_ce: 0.006246, loss_pse_sup_soft: 0.745321, alpha: 0.142986 -[22:21:56.930] avg_metric:[[0.87608823] - [0.8528782 ] - [0.91838248]] -[22:21:56.931] iteration 20800 : dice_score : 0.882450 -[22:23:08.068] iteration 21000 : loss : 5.965192, loss_ce: 0.003921, loss_pse_sup_soft: 0.745159, alpha: 0.461334 -[22:23:10.289] avg_metric:[[0.87954539] - [0.8514104 ] - [0.92081231]] -[22:23:10.290] iteration 21000 : dice_score : 0.883923 -[22:24:36.624] iteration 21200 : loss : 5.965425, loss_ce: 0.002877, loss_pse_sup_soft: 0.745319, alpha: 0.539398 -[22:24:39.339] avg_metric:[[0.87490354] - [0.85287362] - [0.92256032]] -[22:24:39.341] iteration 21200 : dice_score : 0.883446 -[22:26:07.650] iteration 21400 : loss : 5.968057, loss_ce: 0.003992, loss_pse_sup_soft: 0.745508, alpha: 0.329030 -[22:26:10.214] avg_metric:[[0.87899039] - [0.85046451] - [0.92705368]] -[22:26:10.215] iteration 21400 : dice_score : 0.885503 -[22:27:20.972] iteration 21600 : loss : 5.971498, loss_ce: 0.008681, loss_pse_sup_soft: 0.745352, alpha: 0.693089 -[22:27:23.569] avg_metric:[[0.87940428] - [0.84754758] - [0.92412296]] -[22:27:23.569] iteration 21600 : dice_score : 0.883692 -[22:28:52.480] iteration 21800 : loss : 5.967663, loss_ce: 0.005703, loss_pse_sup_soft: 0.745245, alpha: 0.499555 -[22:28:55.225] avg_metric:[[0.87840639] - [0.84873664] - [0.92153616]] -[22:28:55.226] iteration 21800 : dice_score : 0.882893 -[22:30:20.563] iteration 22000 : loss : 5.963749, loss_ce: 0.004208, loss_pse_sup_soft: 0.744943, alpha: 0.644564 -[22:30:23.037] avg_metric:[[0.87795094] - [0.84683929] - [0.92239969]] -[22:30:23.038] iteration 22000 : dice_score : 0.882397 -[22:31:35.508] iteration 22200 : loss : 5.966345, loss_ce: 0.004464, loss_pse_sup_soft: 0.745235, alpha: 0.757313 -[22:31:38.238] avg_metric:[[0.87757289] - [0.85377299] - [0.92353371]] -[22:31:38.239] iteration 22200 : dice_score : 0.884960 -[22:33:09.226] iteration 22400 : loss : 5.966612, loss_ce: 0.004873, loss_pse_sup_soft: 0.745217, alpha: 0.897646 -[22:33:11.992] avg_metric:[[0.87685476] - [0.85638661] - [0.92402327]] -[22:33:11.993] iteration 22400 : dice_score : 0.885755 -[22:34:33.577] iteration 22600 : loss : 5.972985, loss_ce: 0.010391, loss_pse_sup_soft: 0.745324, alpha: 0.006473 -[22:34:36.337] avg_metric:[[0.87376387] - [0.85023759] - [0.92223624]] -[22:34:36.338] iteration 22600 : dice_score : 0.882079 -[22:35:52.261] iteration 22800 : loss : 5.962369, loss_ce: 0.001031, loss_pse_sup_soft: 0.745167, alpha: 0.771763 -[22:35:54.919] avg_metric:[[0.87535608] - [0.85312411] - [0.91753916]] -[22:35:54.920] iteration 22800 : dice_score : 0.882006 -[22:37:25.691] iteration 23000 : loss : 5.965615, loss_ce: 0.004050, loss_pse_sup_soft: 0.745196, alpha: 0.578769 -[22:37:28.285] avg_metric:[[0.8760909 ] - [0.85116192] - [0.92368699]] -[22:37:28.286] iteration 23000 : dice_score : 0.883647 -[22:38:46.325] iteration 23200 : loss : 5.963677, loss_ce: 0.002330, loss_pse_sup_soft: 0.745168, alpha: 0.738124 -[22:38:48.395] avg_metric:[[0.87373819] - [0.84954624] - [0.91662692]] -[22:38:48.395] iteration 23200 : dice_score : 0.879970 -[22:40:07.557] iteration 23400 : loss : 5.976304, loss_ce: 0.013405, loss_pse_sup_soft: 0.745362, alpha: 0.972117 -[22:40:10.285] avg_metric:[[0.87752519] - [0.85237897] - [0.92327051]] -[22:40:10.286] iteration 23400 : dice_score : 0.884392 -[22:41:40.797] iteration 23600 : loss : 5.969290, loss_ce: 0.006564, loss_pse_sup_soft: 0.745341, alpha: 0.486746 -[22:41:43.399] avg_metric:[[0.87609336] - [0.85232811] - [0.92166936]] -[22:41:43.401] iteration 23600 : dice_score : 0.883364 -[22:42:56.856] iteration 23800 : loss : 5.966740, loss_ce: 0.003095, loss_pse_sup_soft: 0.745456, alpha: 0.099166 -[22:42:59.174] avg_metric:[[0.87454249] - [0.85178463] - [0.91865275]] -[22:42:59.175] iteration 23800 : dice_score : 0.881660 -[22:44:22.202] iteration 24000 : loss : 5.966425, loss_ce: 0.003516, loss_pse_sup_soft: 0.745364, alpha: 0.084777 -[22:44:24.933] avg_metric:[[0.87620212] - [0.85069096] - [0.91817821]] -[22:44:24.934] iteration 24000 : dice_score : 0.881690 -[22:45:54.927] iteration 24200 : loss : 5.963477, loss_ce: 0.002099, loss_pse_sup_soft: 0.745172, alpha: 0.351433 -[22:45:57.577] avg_metric:[[0.87436886] - [0.84959021] - [0.92132048]] -[22:45:57.578] iteration 24200 : dice_score : 0.881760 -[22:47:08.032] iteration 24400 : loss : 5.963677, loss_ce: 0.003410, loss_pse_sup_soft: 0.745033, alpha: 0.908610 -[22:47:10.513] avg_metric:[[0.87169812] - [0.8482116 ] - [0.91953513]] -[22:47:10.514] iteration 24400 : dice_score : 0.879815 -[22:48:35.880] iteration 24600 : loss : 5.964213, loss_ce: 0.001587, loss_pse_sup_soft: 0.745328, alpha: 0.183770 -[22:48:38.669] avg_metric:[[0.87443888] - [0.85452237] - [0.9199463 ]] -[22:48:38.670] iteration 24600 : dice_score : 0.882969 -[22:50:07.562] iteration 24800 : loss : 5.963874, loss_ce: 0.002541, loss_pse_sup_soft: 0.745167, alpha: 0.902544 -[22:50:09.951] avg_metric:[[0.87532443] - [0.84902178] - [0.92137151]] -[22:50:09.953] iteration 24800 : dice_score : 0.881906 -[22:51:19.442] iteration 25000 : loss : 5.962822, loss_ce: 0.001954, loss_pse_sup_soft: 0.745109, alpha: 0.066243 -[22:51:21.859] avg_metric:[[0.8723751 ] - [0.84926863] - [0.91868721]] -[22:51:21.860] iteration 25000 : dice_score : 0.880110 -[22:51:21.905] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_soft_ce_l8_0805/iter_25000.pth -[22:52:50.383] iteration 25200 : loss : 5.965597, loss_ce: 0.006236, loss_pse_sup_soft: 0.744920, alpha: 0.858375 -[22:52:52.858] avg_metric:[[0.87557818] - [0.85206493] - [0.91729913]] -[22:52:52.859] iteration 25200 : dice_score : 0.881647 -[22:54:19.660] iteration 25400 : loss : 5.973622, loss_ce: 0.006493, loss_pse_sup_soft: 0.745891, alpha: 0.144878 -[22:54:22.034] avg_metric:[[0.87695998] - [0.85497119] - [0.92288841]] -[22:54:22.034] iteration 25400 : dice_score : 0.884940 -[22:55:32.189] iteration 25600 : loss : 5.968319, loss_ce: 0.006740, loss_pse_sup_soft: 0.745197, alpha: 0.158830 -[22:55:34.525] avg_metric:[[0.87431733] - [0.84902184] - [0.91920898]] -[22:55:34.527] iteration 25600 : dice_score : 0.880849 -[22:57:05.378] iteration 25800 : loss : 5.963784, loss_ce: 0.002996, loss_pse_sup_soft: 0.745098, alpha: 0.916378 -[22:57:08.222] avg_metric:[[0.87916849] - [0.85542979] - [0.92625548]] -[22:57:08.223] iteration 25800 : dice_score : 0.886951 -[22:58:32.556] iteration 26000 : loss : 5.962714, loss_ce: 0.001590, loss_pse_sup_soft: 0.745141, alpha: 0.934527 -[22:58:34.974] avg_metric:[[0.8759535 ] - [0.85405947] - [0.92707663]] -[22:58:34.974] iteration 26000 : dice_score : 0.885697 -[22:59:45.900] iteration 26200 : loss : 5.966578, loss_ce: 0.005300, loss_pse_sup_soft: 0.745160, alpha: 0.355472 -[22:59:48.672] avg_metric:[[0.87794398] - [0.85455039] - [0.92257857]] -[22:59:48.673] iteration 26200 : dice_score : 0.885024 -[23:01:19.543] iteration 26400 : loss : 5.965425, loss_ce: 0.002478, loss_pse_sup_soft: 0.745368, alpha: 0.111174 -[23:01:22.365] avg_metric:[[0.88100202] - [0.85743523] - [0.92401896]] -[23:01:22.366] iteration 26400 : dice_score : 0.887485 -[23:02:42.624] iteration 26600 : loss : 5.964130, loss_ce: 0.004072, loss_pse_sup_soft: 0.745007, alpha: 0.778200 -[23:02:45.430] avg_metric:[[0.87900572] - [0.85687198] - [0.92466374]] -[23:02:45.431] iteration 26600 : dice_score : 0.886847 -[23:04:01.337] iteration 26800 : loss : 5.963907, loss_ce: 0.002808, loss_pse_sup_soft: 0.745137, alpha: 0.819975 -[23:04:03.944] avg_metric:[[0.87736627] - [0.85354947] - [0.91923004]] -[23:04:03.945] iteration 26800 : dice_score : 0.883382 -[23:05:34.427] iteration 27000 : loss : 5.964171, loss_ce: 0.003861, loss_pse_sup_soft: 0.745039, alpha: 0.165710 -[23:05:37.120] avg_metric:[[0.8792525 ] - [0.8533952 ] - [0.92222688]] -[23:05:37.121] iteration 27000 : dice_score : 0.884958 -[23:06:54.454] iteration 27200 : loss : 5.962627, loss_ce: 0.000416, loss_pse_sup_soft: 0.745276, alpha: 0.173979 -[23:06:56.886] avg_metric:[[0.87805195] - [0.85355122] - [0.92097176]] -[23:06:56.888] iteration 27200 : dice_score : 0.884192 -[23:08:14.858] iteration 27400 : loss : 5.968379, loss_ce: 0.008088, loss_pse_sup_soft: 0.745036, alpha: 0.708037 -[23:08:17.416] avg_metric:[[0.87751702] - [0.85476057] - [0.92281354]] -[23:08:17.417] iteration 27400 : dice_score : 0.885030 -[23:09:48.248] iteration 27600 : loss : 5.962736, loss_ce: 0.002035, loss_pse_sup_soft: 0.745088, alpha: 0.839224 -[23:09:50.986] avg_metric:[[0.87944705] - [0.85456457] - [0.9268741 ]] -[23:09:50.987] iteration 27600 : dice_score : 0.886962 -[23:11:04.816] iteration 27800 : loss : 5.963359, loss_ce: 0.002596, loss_pse_sup_soft: 0.745095, alpha: 0.477905 -[23:11:07.019] avg_metric:[[0.8778731 ] - [0.85435982] - [0.92482727]] -[23:11:07.020] iteration 27800 : dice_score : 0.885687 -[23:12:28.756] iteration 28000 : loss : 5.963294, loss_ce: 0.002292, loss_pse_sup_soft: 0.745125, alpha: 0.928330 -[23:12:31.429] avg_metric:[[0.87718991] - [0.85423352] - [0.92382445]] -[23:12:31.431] iteration 28000 : dice_score : 0.885083 -[23:14:01.681] iteration 28200 : loss : 5.964975, loss_ce: 0.003284, loss_pse_sup_soft: 0.745211, alpha: 0.381996 -[23:14:04.315] avg_metric:[[0.87813155] - [0.85506273] - [0.92295327]] -[23:14:04.315] iteration 28200 : dice_score : 0.885383 -[23:15:15.509] iteration 28400 : loss : 5.964536, loss_ce: 0.004343, loss_pse_sup_soft: 0.745024, alpha: 0.721679 -[23:15:17.912] avg_metric:[[0.87895943] - [0.85641751] - [0.92540829]] -[23:15:17.914] iteration 28400 : dice_score : 0.886928 -[23:16:42.796] iteration 28600 : loss : 5.962246, loss_ce: 0.003173, loss_pse_sup_soft: 0.744884, alpha: 0.560758 -[23:16:45.435] avg_metric:[[0.87721807] - [0.85462685] - [0.92084562]] -[23:16:45.436] iteration 28600 : dice_score : 0.884230 -[23:18:14.361] iteration 28800 : loss : 5.972118, loss_ce: 0.007543, loss_pse_sup_soft: 0.745572, alpha: 0.269928 -[23:18:16.964] avg_metric:[[0.87833492] - [0.85429971] - [0.92143681]] -[23:18:16.965] iteration 28800 : dice_score : 0.884690 -[23:19:26.595] iteration 29000 : loss : 5.963699, loss_ce: 0.003704, loss_pse_sup_soft: 0.744999, alpha: 0.488476 -[23:19:28.775] avg_metric:[[0.87886215] - [0.85355132] - [0.92351885]] -[23:19:28.776] iteration 29000 : dice_score : 0.885311 -[23:20:55.871] iteration 29200 : loss : 5.962341, loss_ce: 0.002519, loss_pse_sup_soft: 0.744978, alpha: 0.477899 -[23:20:58.622] avg_metric:[[0.87835741] - [0.85368966] - [0.92241838]] -[23:20:58.623] iteration 29200 : dice_score : 0.884822 -[23:22:25.287] iteration 29400 : loss : 5.964690, loss_ce: 0.004272, loss_pse_sup_soft: 0.745052, alpha: 0.585183 -[23:22:27.663] avg_metric:[[0.87814779] - [0.85382001] - [0.922014 ]] -[23:22:27.664] iteration 29400 : dice_score : 0.884661 -[23:23:38.349] iteration 29600 : loss : 5.961778, loss_ce: 0.001966, loss_pse_sup_soft: 0.744976, alpha: 0.452677 -[23:23:40.795] avg_metric:[[0.87682991] - [0.85586805] - [0.92152136]] -[23:23:40.795] iteration 29600 : dice_score : 0.884740 -[23:25:10.932] iteration 29800 : loss : 5.962020, loss_ce: 0.001442, loss_pse_sup_soft: 0.745072, alpha: 0.138123 -[23:25:13.584] avg_metric:[[0.87688831] - [0.8546819 ] - [0.92262777]] -[23:25:13.585] iteration 29800 : dice_score : 0.884733 -[23:26:37.840] iteration 30000 : loss : 5.963469, loss_ce: 0.001813, loss_pse_sup_soft: 0.745207, alpha: 0.605944 -[23:26:40.159] avg_metric:[[0.87697743] - [0.85492712] - [0.92295308]] -[23:26:40.160] iteration 30000 : dice_score : 0.884953 -[23:26:40.207] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_soft_ce_l8_0805/iter_30000.pth -[23:26:40.299] time cost: 12812.366875171661 s, i.e, 3.5589907986587948 h diff --git a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/unet_cct_best_model.pth b/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/unet_cct_best_model.pth deleted file mode 100644 index db717ff..0000000 Binary files a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage1/unet_cct_best_model.pth and /dev/null differ diff --git a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/log/events.out.tfevents.1695125841.x-Super-Server b/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/log/events.out.tfevents.1695125841.x-Super-Server deleted file mode 100644 index d6e3d82..0000000 Binary files a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/log/events.out.tfevents.1695125841.x-Super-Server and /dev/null differ diff --git a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/train_log.txt b/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/train_log.txt deleted file mode 100644 index 025e119..0000000 --- a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/train_log.txt +++ /dev/null @@ -1,760 +0,0 @@ -[20:17:19.256] Namespace(base_lr=0.01, batch_size=24, data_name='ACDC', data_type='HeartM', deterministic=1, exp='A3_weakly_PLS_2d', fold='v2_softcel8_ReUnmC_T01_0919', max_iterations=30000, model='unet_cct', num_classes=4, patch_size=[256, 256], root_path='/mnt/data/HM/Datasets/ACDC2017/ACDC_for2D', seed=2022, sup_type='pseudoLab', trainData='traincel8_0805_ReUnmC_T01.txt', validData='valid.txt') -[20:17:21.903] 57 iterations per epoch -[20:17:21.903] max epoch: 527 -[20:18:06.018] iteration 200 : loss : 5.980419, loss_ce: 0.010719, loss_pse_sup_soft: 0.746212, alpha: 0.093016 -[20:18:08.007] avg_metric:[[0.87648669] - [0.86441801] - [0.91557202]] -[20:18:08.007] iteration 200 : dice_score : 0.885492 -[20:18:52.350] iteration 400 : loss : 5.975521, loss_ce: 0.009182, loss_pse_sup_soft: 0.745792, alpha: 0.438119 -[20:18:54.253] avg_metric:[[0.8790981] - [0.8622422] - [0.9188567]] -[20:18:54.253] iteration 400 : dice_score : 0.886732 -[20:19:39.463] iteration 600 : loss : 5.973123, loss_ce: 0.007948, loss_pse_sup_soft: 0.745647, alpha: 0.547861 -[20:19:41.372] avg_metric:[[0.88264731] - [0.86838387] - [0.92509959]] -[20:19:41.373] iteration 600 : dice_score : 0.892044 -[20:20:27.841] iteration 800 : loss : 5.974387, loss_ce: 0.009179, loss_pse_sup_soft: 0.745651, alpha: 0.023007 -[20:20:29.768] avg_metric:[[0.87576711] - [0.86459041] - [0.917671 ]] -[20:20:29.769] iteration 800 : dice_score : 0.886010 -[20:21:15.902] iteration 1000 : loss : 5.974164, loss_ce: 0.008717, loss_pse_sup_soft: 0.745681, alpha: 0.060510 -[20:21:17.578] avg_metric:[[0.88161784] - [0.86495535] - [0.92237368]] -[20:21:17.578] iteration 1000 : dice_score : 0.889649 -[20:22:04.662] iteration 1200 : loss : 5.974434, loss_ce: 0.009525, loss_pse_sup_soft: 0.745614, alpha: 0.511315 -[20:22:06.656] avg_metric:[[0.88116373] - [0.86310259] - [0.91984403]] -[20:22:06.657] iteration 1200 : dice_score : 0.888037 -[20:22:53.159] iteration 1400 : loss : 5.977764, loss_ce: 0.009827, loss_pse_sup_soft: 0.745992, alpha: 0.691276 -[20:22:54.970] avg_metric:[[0.87493082] - [0.86300739] - [0.91695604]] -[20:22:54.971] iteration 1400 : dice_score : 0.884965 -[20:23:42.113] iteration 1600 : loss : 5.975539, loss_ce: 0.009603, loss_pse_sup_soft: 0.745742, alpha: 0.057457 -[20:23:44.042] avg_metric:[[0.88256801] - [0.86106848] - [0.92027461]] -[20:23:44.043] iteration 1600 : dice_score : 0.887970 -[20:24:30.546] iteration 1800 : loss : 5.976646, loss_ce: 0.009253, loss_pse_sup_soft: 0.745924, alpha: 0.985193 -[20:24:32.334] avg_metric:[[0.88140669] - [0.86415383] - [0.92441151]] -[20:24:32.335] iteration 1800 : dice_score : 0.889991 -[20:25:19.475] iteration 2000 : loss : 5.972576, loss_ce: 0.008662, loss_pse_sup_soft: 0.745489, alpha: 0.782608 -[20:25:21.324] avg_metric:[[0.87958944] - [0.8645342 ] - [0.92080845]] -[20:25:21.325] iteration 2000 : dice_score : 0.888311 -[20:26:07.661] iteration 2200 : loss : 5.978781, loss_ce: 0.010780, loss_pse_sup_soft: 0.746000, alpha: 0.328230 -[20:26:09.629] avg_metric:[[0.87795635] - [0.86392782] - [0.92198619]] -[20:26:09.630] iteration 2200 : dice_score : 0.887957 -[20:26:57.040] iteration 2400 : loss : 5.973535, loss_ce: 0.008143, loss_pse_sup_soft: 0.745674, alpha: 0.703715 -[20:26:58.945] avg_metric:[[0.87972124] - [0.86355346] - [0.92058474]] -[20:26:58.946] iteration 2400 : dice_score : 0.887953 -[20:27:45.271] iteration 2600 : loss : 5.973924, loss_ce: 0.008615, loss_pse_sup_soft: 0.745664, alpha: 0.381020 -[20:27:47.151] avg_metric:[[0.88146744] - [0.86340721] - [0.92342846]] -[20:27:47.151] iteration 2600 : dice_score : 0.889434 -[20:28:34.213] iteration 2800 : loss : 5.972441, loss_ce: 0.008206, loss_pse_sup_soft: 0.745529, alpha: 0.049184 -[20:28:36.170] avg_metric:[[0.88249671] - [0.86431812] - [0.92770861]] -[20:28:36.171] iteration 2800 : dice_score : 0.891508 -[20:29:22.657] iteration 3000 : loss : 5.970676, loss_ce: 0.007759, loss_pse_sup_soft: 0.745365, alpha: 0.051762 -[20:29:24.582] avg_metric:[[0.88172917] - [0.8654791 ] - [0.92633398]] -[20:29:24.583] iteration 3000 : dice_score : 0.891181 -[20:30:11.650] iteration 3200 : loss : 5.977510, loss_ce: 0.009787, loss_pse_sup_soft: 0.745965, alpha: 0.085885 -[20:30:13.860] avg_metric:[[0.88399776] - [0.86773758] - [0.92831363]] -[20:30:13.861] iteration 3200 : dice_score : 0.893350 -[20:31:00.147] iteration 3400 : loss : 5.973048, loss_ce: 0.009618, loss_pse_sup_soft: 0.745429, alpha: 0.889961 -[20:31:01.944] avg_metric:[[0.88130195] - [0.86475923] - [0.92611142]] -[20:31:01.946] iteration 3400 : dice_score : 0.890724 -[20:31:48.823] iteration 3600 : loss : 5.973029, loss_ce: 0.007403, loss_pse_sup_soft: 0.745703, alpha: 0.750462 -[20:31:50.584] avg_metric:[[0.88229106] - [0.86556787] - [0.92601532]] -[20:31:50.585] iteration 3600 : dice_score : 0.891291 -[20:32:36.929] iteration 3800 : loss : 5.977376, loss_ce: 0.010569, loss_pse_sup_soft: 0.745851, alpha: 0.788061 -[20:32:38.624] avg_metric:[[0.88195165] - [0.86689012] - [0.9289291 ]] -[20:32:38.625] iteration 3800 : dice_score : 0.892590 -[20:33:25.559] iteration 4000 : loss : 5.975507, loss_ce: 0.008650, loss_pse_sup_soft: 0.745857, alpha: 0.403655 -[20:33:27.291] avg_metric:[[0.88070069] - [0.86500088] - [0.92648523]] -[20:33:27.293] iteration 4000 : dice_score : 0.890729 -[20:34:13.617] iteration 4200 : loss : 5.976439, loss_ce: 0.009084, loss_pse_sup_soft: 0.745919, alpha: 0.152091 -[20:34:15.487] avg_metric:[[0.88271776] - [0.86758121] - [0.93004255]] -[20:34:15.488] iteration 4200 : dice_score : 0.893447 -[20:35:02.358] iteration 4400 : loss : 5.973740, loss_ce: 0.007970, loss_pse_sup_soft: 0.745721, alpha: 0.722330 -[20:35:04.185] avg_metric:[[0.8847908 ] - [0.86724955] - [0.92888944]] -[20:35:04.185] iteration 4400 : dice_score : 0.893643 -[20:35:50.580] iteration 4600 : loss : 5.974013, loss_ce: 0.009121, loss_pse_sup_soft: 0.745612, alpha: 0.026087 -[20:35:52.316] avg_metric:[[0.8839157 ] - [0.86517786] - [0.92796234]] -[20:35:52.317] iteration 4600 : dice_score : 0.892352 -[20:36:39.129] iteration 4800 : loss : 5.982628, loss_ce: 0.010582, loss_pse_sup_soft: 0.746506, alpha: 0.929736 -[20:36:40.855] avg_metric:[[0.88231275] - [0.86543873] - [0.92994088]] -[20:36:40.856] iteration 4800 : dice_score : 0.892564 -[20:37:27.151] iteration 5000 : loss : 5.974837, loss_ce: 0.008344, loss_pse_sup_soft: 0.745812, alpha: 0.212928 -[20:37:28.878] avg_metric:[[0.88212305] - [0.86748275] - [0.92849869]] -[20:37:28.879] iteration 5000 : dice_score : 0.892701 -[20:37:28.927] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_softcel8_ReUnmC_T01_0919/iter_5000.pth -[20:38:15.624] iteration 5200 : loss : 5.976008, loss_ce: 0.008462, loss_pse_sup_soft: 0.745943, alpha: 0.399972 -[20:38:17.457] avg_metric:[[0.88155832] - [0.8677833 ] - [0.92658678]] -[20:38:17.458] iteration 5200 : dice_score : 0.891976 -[20:39:03.724] iteration 5400 : loss : 5.974431, loss_ce: 0.009059, loss_pse_sup_soft: 0.745671, alpha: 0.965603 -[20:39:05.913] avg_metric:[[0.88352966] - [0.86878693] - [0.93050166]] -[20:39:05.913] iteration 5400 : dice_score : 0.894273 -[20:39:52.633] iteration 5600 : loss : 5.975401, loss_ce: 0.008971, loss_pse_sup_soft: 0.745804, alpha: 0.551517 -[20:39:54.407] avg_metric:[[0.88107648] - [0.86758739] - [0.92795226]] -[20:39:54.409] iteration 5600 : dice_score : 0.892205 -[20:40:40.747] iteration 5800 : loss : 5.974850, loss_ce: 0.008329, loss_pse_sup_soft: 0.745815, alpha: 0.565185 -[20:40:42.751] avg_metric:[[0.87856663] - [0.8672463 ] - [0.92495468]] -[20:40:42.752] iteration 5800 : dice_score : 0.890256 -[20:41:29.603] iteration 6000 : loss : 5.973795, loss_ce: 0.009506, loss_pse_sup_soft: 0.745536, alpha: 0.372450 -[20:41:31.386] avg_metric:[[0.88005137] - [0.8669711 ] - [0.92625654]] -[20:41:31.387] iteration 6000 : dice_score : 0.891093 -[20:42:17.776] iteration 6200 : loss : 5.972259, loss_ce: 0.008855, loss_pse_sup_soft: 0.745426, alpha: 0.157151 -[20:42:19.870] avg_metric:[[0.87679815] - [0.86447473] - [0.92167732]] -[20:42:19.871] iteration 6200 : dice_score : 0.887650 -[20:43:06.508] iteration 6400 : loss : 5.978344, loss_ce: 0.009578, loss_pse_sup_soft: 0.746096, alpha: 0.410799 -[20:43:08.457] avg_metric:[[0.88044735] - [0.86670866] - [0.92501892]] -[20:43:08.458] iteration 6400 : dice_score : 0.890725 -[20:43:54.555] iteration 6600 : loss : 5.974486, loss_ce: 0.008346, loss_pse_sup_soft: 0.745767, alpha: 0.912722 -[20:43:56.515] avg_metric:[[0.88078718] - [0.86815721] - [0.92901894]] -[20:43:56.516] iteration 6600 : dice_score : 0.892654 -[20:44:42.987] iteration 6800 : loss : 5.975307, loss_ce: 0.008932, loss_pse_sup_soft: 0.745797, alpha: 0.732540 -[20:44:45.022] avg_metric:[[0.87858835] - [0.86660343] - [0.92451621]] -[20:44:45.023] iteration 6800 : dice_score : 0.889903 -[20:45:30.839] iteration 7000 : loss : 5.979308, loss_ce: 0.010417, loss_pse_sup_soft: 0.746111, alpha: 0.547269 -[20:45:32.878] avg_metric:[[0.88162865] - [0.86811028] - [0.92585982]] -[20:45:32.879] iteration 7000 : dice_score : 0.891866 -[20:46:19.521] iteration 7200 : loss : 5.973737, loss_ce: 0.008199, loss_pse_sup_soft: 0.745692, alpha: 0.477678 -[20:46:21.575] avg_metric:[[0.88091223] - [0.86554848] - [0.92586594]] -[20:46:21.576] iteration 7200 : dice_score : 0.890776 -[20:47:07.734] iteration 7400 : loss : 5.973521, loss_ce: 0.008808, loss_pse_sup_soft: 0.745589, alpha: 0.026709 -[20:47:09.666] avg_metric:[[0.88127394] - [0.86626407] - [0.9276795 ]] -[20:47:09.666] iteration 7400 : dice_score : 0.891739 -[20:47:56.260] iteration 7600 : loss : 5.976016, loss_ce: 0.008697, loss_pse_sup_soft: 0.745915, alpha: 0.237706 -[20:47:58.101] avg_metric:[[0.88118941] - [0.86831918] - [0.92848493]] -[20:47:58.102] iteration 7600 : dice_score : 0.892665 -[20:48:44.286] iteration 7800 : loss : 5.975284, loss_ce: 0.009441, loss_pse_sup_soft: 0.745730, alpha: 0.874727 -[20:48:46.286] avg_metric:[[0.8819771 ] - [0.8661154 ] - [0.92605702]] -[20:48:46.288] iteration 7800 : dice_score : 0.891383 -[20:49:33.119] iteration 8000 : loss : 5.972620, loss_ce: 0.008280, loss_pse_sup_soft: 0.745542, alpha: 0.082410 -[20:49:35.140] avg_metric:[[0.88153416] - [0.86851878] - [0.92924493]] -[20:49:35.141] iteration 8000 : dice_score : 0.893099 -[20:50:21.100] iteration 8200 : loss : 5.971004, loss_ce: 0.007506, loss_pse_sup_soft: 0.745437, alpha: 0.676088 -[20:50:23.178] avg_metric:[[0.88231006] - [0.86725528] - [0.92579981]] -[20:50:23.179] iteration 8200 : dice_score : 0.891788 -[20:51:09.845] iteration 8400 : loss : 5.975394, loss_ce: 0.008636, loss_pse_sup_soft: 0.745845, alpha: 0.806474 -[20:51:12.119] avg_metric:[[0.88088812] - [0.86692066] - [0.92459329]] -[20:51:12.120] iteration 8400 : dice_score : 0.890801 -[20:51:58.376] iteration 8600 : loss : 5.969532, loss_ce: 0.007800, loss_pse_sup_soft: 0.745216, alpha: 0.353954 -[20:52:00.185] avg_metric:[[0.88146526] - [0.86694093] - [0.92864443]] -[20:52:00.186] iteration 8600 : dice_score : 0.892350 -[20:52:46.884] iteration 8800 : loss : 5.976654, loss_ce: 0.009375, loss_pse_sup_soft: 0.745910, alpha: 0.020247 -[20:52:48.862] avg_metric:[[0.88250554] - [0.86849115] - [0.92812522]] -[20:52:48.863] iteration 8800 : dice_score : 0.893041 -[20:53:35.250] iteration 9000 : loss : 5.975565, loss_ce: 0.009305, loss_pse_sup_soft: 0.745782, alpha: 0.044747 -[20:53:37.087] avg_metric:[[0.88199957] - [0.86566749] - [0.92704433]] -[20:53:37.087] iteration 9000 : dice_score : 0.891570 -[20:54:23.932] iteration 9200 : loss : 5.975513, loss_ce: 0.008397, loss_pse_sup_soft: 0.745890, alpha: 0.582162 -[20:54:25.811] avg_metric:[[0.88128779] - [0.86826833] - [0.92698324]] -[20:54:25.813] iteration 9200 : dice_score : 0.892180 -[20:55:12.126] iteration 9400 : loss : 5.975313, loss_ce: 0.009687, loss_pse_sup_soft: 0.745703, alpha: 0.685391 -[20:55:13.906] avg_metric:[[0.88196475] - [0.86821572] - [0.92886311]] -[20:55:13.907] iteration 9400 : dice_score : 0.893015 -[20:56:00.807] iteration 9600 : loss : 5.976209, loss_ce: 0.009629, loss_pse_sup_soft: 0.745823, alpha: 0.800580 -[20:56:02.913] avg_metric:[[0.88285043] - [0.86838701] - [0.92951331]] -[20:56:02.915] iteration 9600 : dice_score : 0.893584 -[20:56:49.095] iteration 9800 : loss : 5.973011, loss_ce: 0.008350, loss_pse_sup_soft: 0.745583, alpha: 0.987378 -[20:56:51.235] avg_metric:[[0.88199484] - [0.86951039] - [0.928113 ]] -[20:56:51.236] iteration 9800 : dice_score : 0.893206 -[20:57:38.043] iteration 10000 : loss : 5.973408, loss_ce: 0.008726, loss_pse_sup_soft: 0.745585, alpha: 0.234998 -[20:57:40.295] avg_metric:[[0.88269477] - [0.8672382 ] - [0.92790097]] -[20:57:40.296] iteration 10000 : dice_score : 0.892611 -[20:57:40.339] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_softcel8_ReUnmC_T01_0919/iter_10000.pth -[20:58:26.695] iteration 10200 : loss : 5.974185, loss_ce: 0.009388, loss_pse_sup_soft: 0.745600, alpha: 0.841821 -[20:58:28.848] avg_metric:[[0.88323265] - [0.8659683 ] - [0.92785414]] -[20:58:28.849] iteration 10200 : dice_score : 0.892352 -[20:59:15.817] iteration 10400 : loss : 5.972246, loss_ce: 0.008734, loss_pse_sup_soft: 0.745439, alpha: 0.336909 -[20:59:17.877] avg_metric:[[0.88180212] - [0.86636918] - [0.92763634]] -[20:59:17.878] iteration 10400 : dice_score : 0.891936 -[21:00:04.445] iteration 10600 : loss : 5.972514, loss_ce: 0.008161, loss_pse_sup_soft: 0.745544, alpha: 0.898399 -[21:00:06.593] avg_metric:[[0.88181765] - [0.86565778] - [0.92766299]] -[21:00:06.594] iteration 10600 : dice_score : 0.891713 -[21:00:53.853] iteration 10800 : loss : 5.970516, loss_ce: 0.007374, loss_pse_sup_soft: 0.745393, alpha: 0.223824 -[21:00:55.993] avg_metric:[[0.88350595] - [0.86846232] - [0.92734111]] -[21:00:55.994] iteration 10800 : dice_score : 0.893103 -[21:01:42.617] iteration 11000 : loss : 5.972404, loss_ce: 0.008548, loss_pse_sup_soft: 0.745482, alpha: 0.935009 -[21:01:44.451] avg_metric:[[0.88130408] - [0.86812738] - [0.92779183]] -[21:01:44.452] iteration 11000 : dice_score : 0.892408 -[21:02:31.720] iteration 11200 : loss : 5.971123, loss_ce: 0.007858, loss_pse_sup_soft: 0.745408, alpha: 0.762962 -[21:02:33.720] avg_metric:[[0.88143286] - [0.86733955] - [0.9276642 ]] -[21:02:33.720] iteration 11200 : dice_score : 0.892146 -[21:03:20.090] iteration 11400 : loss : 5.972239, loss_ce: 0.007219, loss_pse_sup_soft: 0.745628, alpha: 0.818018 -[21:03:21.931] avg_metric:[[0.88075426] - [0.86871075] - [0.92597643]] -[21:03:21.932] iteration 11400 : dice_score : 0.891814 -[21:04:09.046] iteration 11600 : loss : 5.976927, loss_ce: 0.008947, loss_pse_sup_soft: 0.745997, alpha: 0.056232 -[21:04:10.883] avg_metric:[[0.88193433] - [0.86853321] - [0.92509611]] -[21:04:10.883] iteration 11600 : dice_score : 0.891855 -[21:04:57.887] iteration 11800 : loss : 5.970126, loss_ce: 0.007523, loss_pse_sup_soft: 0.745325, alpha: 0.364555 -[21:04:59.972] avg_metric:[[0.88328512] - [0.86619298] - [0.92755684]] -[21:04:59.972] iteration 11800 : dice_score : 0.892345 -[21:05:46.555] iteration 12000 : loss : 5.971245, loss_ce: 0.007812, loss_pse_sup_soft: 0.745429, alpha: 0.000577 -[21:05:48.750] avg_metric:[[0.88503989] - [0.86664799] - [0.92962562]] -[21:05:48.750] iteration 12000 : dice_score : 0.893771 -[21:06:35.918] iteration 12200 : loss : 5.977669, loss_ce: 0.009952, loss_pse_sup_soft: 0.745965, alpha: 0.069479 -[21:06:38.038] avg_metric:[[0.88262288] - [0.86735939] - [0.92456239]] -[21:06:38.039] iteration 12200 : dice_score : 0.891515 -[21:07:24.566] iteration 12400 : loss : 5.972939, loss_ce: 0.008048, loss_pse_sup_soft: 0.745611, alpha: 0.662625 -[21:07:26.982] avg_metric:[[0.88313144] - [0.86642038] - [0.92716303]] -[21:07:26.983] iteration 12400 : dice_score : 0.892238 -[21:08:14.288] iteration 12600 : loss : 5.973434, loss_ce: 0.008563, loss_pse_sup_soft: 0.745609, alpha: 0.933536 -[21:08:16.376] avg_metric:[[0.88275049] - [0.868744 ] - [0.92826885]] -[21:08:16.377] iteration 12600 : dice_score : 0.893254 -[21:09:03.081] iteration 12800 : loss : 5.974279, loss_ce: 0.007953, loss_pse_sup_soft: 0.745791, alpha: 0.374596 -[21:09:05.207] avg_metric:[[0.88425627] - [0.8687673 ] - [0.92939501]] -[21:09:05.207] iteration 12800 : dice_score : 0.894140 -[21:09:52.402] iteration 13000 : loss : 5.973150, loss_ce: 0.008696, loss_pse_sup_soft: 0.745557, alpha: 0.334795 -[21:09:54.682] avg_metric:[[0.88084678] - [0.8680328 ] - [0.92896991]] -[21:09:54.682] iteration 13000 : dice_score : 0.892616 -[21:10:41.475] iteration 13200 : loss : 5.970605, loss_ce: 0.007363, loss_pse_sup_soft: 0.745405, alpha: 0.677066 -[21:10:43.396] avg_metric:[[0.88349728] - [0.86629566] - [0.92758573]] -[21:10:43.397] iteration 13200 : dice_score : 0.892460 -[21:11:30.799] iteration 13400 : loss : 5.974057, loss_ce: 0.008539, loss_pse_sup_soft: 0.745690, alpha: 0.719439 -[21:11:32.788] avg_metric:[[0.88249961] - [0.86887066] - [0.92968122]] -[21:11:32.790] iteration 13400 : dice_score : 0.893684 -[21:12:19.415] iteration 13600 : loss : 5.974960, loss_ce: 0.009281, loss_pse_sup_soft: 0.745710, alpha: 0.342312 -[21:12:21.451] avg_metric:[[0.88227407] - [0.8680071 ] - [0.92873024]] -[21:12:21.453] iteration 13600 : dice_score : 0.893004 -[21:13:08.887] iteration 13800 : loss : 5.973451, loss_ce: 0.008480, loss_pse_sup_soft: 0.745621, alpha: 0.089510 -[21:13:10.831] avg_metric:[[0.88171803] - [0.86615764] - [0.92724314]] -[21:13:10.832] iteration 13800 : dice_score : 0.891706 -[21:13:57.765] iteration 14000 : loss : 5.972824, loss_ce: 0.007800, loss_pse_sup_soft: 0.745628, alpha: 0.282470 -[21:13:59.809] avg_metric:[[0.88058405] - [0.86880139] - [0.92850615]] -[21:13:59.810] iteration 14000 : dice_score : 0.892631 -[21:14:47.256] iteration 14200 : loss : 5.971217, loss_ce: 0.007326, loss_pse_sup_soft: 0.745486, alpha: 0.513668 -[21:14:49.306] avg_metric:[[0.88047588] - [0.86779058] - [0.92611687]] -[21:14:49.307] iteration 14200 : dice_score : 0.891461 -[21:15:35.941] iteration 14400 : loss : 5.971910, loss_ce: 0.008077, loss_pse_sup_soft: 0.745479, alpha: 0.348119 -[21:15:37.742] avg_metric:[[0.88273757] - [0.86803925] - [0.92793896]] -[21:15:37.744] iteration 14400 : dice_score : 0.892905 -[21:16:25.057] iteration 14600 : loss : 5.973749, loss_ce: 0.008632, loss_pse_sup_soft: 0.745640, alpha: 0.732853 -[21:16:27.186] avg_metric:[[0.88112211] - [0.86876576] - [0.92757849]] -[21:16:27.187] iteration 14600 : dice_score : 0.892489 -[21:17:14.085] iteration 14800 : loss : 5.974804, loss_ce: 0.008972, loss_pse_sup_soft: 0.745729, alpha: 0.589592 -[21:17:16.156] avg_metric:[[0.88088795] - [0.86760444] - [0.92805263]] -[21:17:16.156] iteration 14800 : dice_score : 0.892182 -[21:18:03.512] iteration 15000 : loss : 5.971297, loss_ce: 0.007142, loss_pse_sup_soft: 0.745519, alpha: 0.438765 -[21:18:05.605] avg_metric:[[0.88331383] - [0.86753371] - [0.92870259]] -[21:18:05.606] iteration 15000 : dice_score : 0.893183 -[21:18:05.648] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_softcel8_ReUnmC_T01_0919/iter_15000.pth -[21:18:52.494] iteration 15200 : loss : 5.971592, loss_ce: 0.007460, loss_pse_sup_soft: 0.745517, alpha: 0.582978 -[21:18:54.716] avg_metric:[[0.88389035] - [0.86914492] - [0.92896994]] -[21:18:54.717] iteration 15200 : dice_score : 0.894002 -[21:19:42.130] iteration 15400 : loss : 5.973725, loss_ce: 0.008900, loss_pse_sup_soft: 0.745603, alpha: 0.126045 -[21:19:44.369] avg_metric:[[0.88392101] - [0.86802462] - [0.9283001 ]] -[21:19:44.370] iteration 15400 : dice_score : 0.893415 -[21:20:31.015] iteration 15600 : loss : 5.974988, loss_ce: 0.008436, loss_pse_sup_soft: 0.745819, alpha: 0.647897 -[21:20:33.194] avg_metric:[[0.88234842] - [0.86834242] - [0.92840097]] -[21:20:33.194] iteration 15600 : dice_score : 0.893031 -[21:21:20.939] iteration 15800 : loss : 5.977225, loss_ce: 0.009589, loss_pse_sup_soft: 0.745955, alpha: 0.396698 -[21:21:22.881] avg_metric:[[0.88140898] - [0.86878384] - [0.92746773]] -[21:21:22.882] iteration 15800 : dice_score : 0.892554 -[21:22:09.834] iteration 16000 : loss : 5.973506, loss_ce: 0.008701, loss_pse_sup_soft: 0.745601, alpha: 0.601766 -[21:22:12.052] avg_metric:[[0.88311279] - [0.86960993] - [0.93044825]] -[21:22:12.053] iteration 16000 : dice_score : 0.894390 -[21:22:59.899] iteration 16200 : loss : 5.975991, loss_ce: 0.008715, loss_pse_sup_soft: 0.745909, alpha: 0.767826 -[21:23:02.046] avg_metric:[[0.88278178] - [0.86854377] - [0.92975554]] -[21:23:02.047] iteration 16200 : dice_score : 0.893694 -[21:23:49.251] iteration 16400 : loss : 5.972873, loss_ce: 0.008336, loss_pse_sup_soft: 0.745567, alpha: 0.290716 -[21:23:51.234] avg_metric:[[0.88137315] - [0.86868367] - [0.92812559]] -[21:23:51.234] iteration 16400 : dice_score : 0.892727 -[21:24:39.023] iteration 16600 : loss : 5.973007, loss_ce: 0.008360, loss_pse_sup_soft: 0.745581, alpha: 0.420156 -[21:24:41.359] avg_metric:[[0.88276672] - [0.87095491] - [0.93101937]] -[21:24:41.360] iteration 16600 : dice_score : 0.894914 -[21:25:28.470] iteration 16800 : loss : 5.976577, loss_ce: 0.008878, loss_pse_sup_soft: 0.745962, alpha: 0.308593 -[21:25:30.624] avg_metric:[[0.87961445] - [0.86930811] - [0.92956152]] -[21:25:30.625] iteration 16800 : dice_score : 0.892828 -[21:26:18.484] iteration 17000 : loss : 5.971000, loss_ce: 0.007396, loss_pse_sup_soft: 0.745450, alpha: 0.631983 -[21:26:20.577] avg_metric:[[0.882211 ] - [0.86857855] - [0.92796261]] -[21:26:20.578] iteration 17000 : dice_score : 0.892917 -[21:27:07.734] iteration 17200 : loss : 5.974470, loss_ce: 0.008435, loss_pse_sup_soft: 0.745754, alpha: 0.336475 -[21:27:09.707] avg_metric:[[0.88201332] - [0.86898768] - [0.93003149]] -[21:27:09.708] iteration 17200 : dice_score : 0.893677 -[21:27:57.876] iteration 17400 : loss : 5.971260, loss_ce: 0.007896, loss_pse_sup_soft: 0.745420, alpha: 0.803886 -[21:28:00.000] avg_metric:[[0.88419533] - [0.87023291] - [0.93346047]] -[21:28:00.001] iteration 17400 : dice_score : 0.895963 -[21:28:47.131] iteration 17600 : loss : 5.969317, loss_ce: 0.007260, loss_pse_sup_soft: 0.745257, alpha: 0.384893 -[21:28:49.086] avg_metric:[[0.88310888] - [0.86736864] - [0.92755473]] -[21:28:49.088] iteration 17600 : dice_score : 0.892677 -[21:29:36.916] iteration 17800 : loss : 5.976277, loss_ce: 0.008798, loss_pse_sup_soft: 0.745935, alpha: 0.097897 -[21:29:39.025] avg_metric:[[0.88269455] - [0.86949798] - [0.93016328]] -[21:29:39.026] iteration 17800 : dice_score : 0.894119 -[21:30:26.168] iteration 18000 : loss : 5.977642, loss_ce: 0.009485, loss_pse_sup_soft: 0.746020, alpha: 0.877891 -[21:30:28.444] avg_metric:[[0.88400779] - [0.87034884] - [0.93025732]] -[21:30:28.445] iteration 18000 : dice_score : 0.894871 -[21:31:16.157] iteration 18200 : loss : 5.973194, loss_ce: 0.008450, loss_pse_sup_soft: 0.745593, alpha: 0.363489 -[21:31:18.282] avg_metric:[[0.88241599] - [0.86759985] - [0.92934599]] -[21:31:18.283] iteration 18200 : dice_score : 0.893121 -[21:32:05.508] iteration 18400 : loss : 5.974234, loss_ce: 0.008230, loss_pse_sup_soft: 0.745751, alpha: 0.825629 -[21:32:07.385] avg_metric:[[0.88337914] - [0.86884552] - [0.92837729]] -[21:32:07.387] iteration 18400 : dice_score : 0.893534 -[21:32:55.319] iteration 18600 : loss : 5.976980, loss_ce: 0.009614, loss_pse_sup_soft: 0.745921, alpha: 0.510830 -[21:32:57.405] avg_metric:[[0.88252572] - [0.8710099 ] - [0.92935659]] -[21:32:57.406] iteration 18600 : dice_score : 0.894297 -[21:33:44.735] iteration 18800 : loss : 5.969488, loss_ce: 0.007788, loss_pse_sup_soft: 0.745213, alpha: 0.989350 -[21:33:46.948] avg_metric:[[0.88222613] - [0.86673816] - [0.92700268]] -[21:33:46.950] iteration 18800 : dice_score : 0.891989 -[21:34:34.721] iteration 19000 : loss : 5.971971, loss_ce: 0.007492, loss_pse_sup_soft: 0.745560, alpha: 0.842633 -[21:34:36.861] avg_metric:[[0.88247413] - [0.86899656] - [0.92979819]] -[21:34:36.863] iteration 19000 : dice_score : 0.893756 -[21:35:23.971] iteration 19200 : loss : 5.972138, loss_ce: 0.008215, loss_pse_sup_soft: 0.745490, alpha: 0.278862 -[21:35:25.916] avg_metric:[[0.88244373] - [0.86857043] - [0.93102464]] -[21:35:25.918] iteration 19200 : dice_score : 0.894013 -[21:36:13.838] iteration 19400 : loss : 5.974434, loss_ce: 0.008998, loss_pse_sup_soft: 0.745680, alpha: 0.933314 -[21:36:15.703] avg_metric:[[0.88075468] - [0.87007741] - [0.92808066]] -[21:36:15.704] iteration 19400 : dice_score : 0.892971 -[21:37:03.189] iteration 19600 : loss : 5.976727, loss_ce: 0.009611, loss_pse_sup_soft: 0.745889, alpha: 0.554988 -[21:37:05.316] avg_metric:[[0.88275124] - [0.86869475] - [0.9282738 ]] -[21:37:05.317] iteration 19600 : dice_score : 0.893240 -[21:37:53.411] iteration 19800 : loss : 5.974136, loss_ce: 0.008517, loss_pse_sup_soft: 0.745702, alpha: 0.633755 -[21:37:55.470] avg_metric:[[0.88344047] - [0.86792981] - [0.93034472]] -[21:37:55.470] iteration 19800 : dice_score : 0.893905 -[21:38:42.615] iteration 20000 : loss : 5.973078, loss_ce: 0.007538, loss_pse_sup_soft: 0.745692, alpha: 0.342870 -[21:38:44.717] avg_metric:[[0.88295626] - [0.86973787] - [0.92821667]] -[21:38:44.718] iteration 20000 : dice_score : 0.893637 -[21:38:44.764] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_softcel8_ReUnmC_T01_0919/iter_20000.pth -[21:39:32.693] iteration 20200 : loss : 5.975029, loss_ce: 0.009175, loss_pse_sup_soft: 0.745732, alpha: 0.605724 -[21:39:34.597] avg_metric:[[0.88269092] - [0.86968085] - [0.92982734]] -[21:39:34.597] iteration 20200 : dice_score : 0.894066 -[21:40:22.102] iteration 20400 : loss : 5.972341, loss_ce: 0.008262, loss_pse_sup_soft: 0.745510, alpha: 0.022194 -[21:40:24.350] avg_metric:[[0.88267581] - [0.86905558] - [0.92991842]] -[21:40:24.351] iteration 20400 : dice_score : 0.893883 -[21:41:12.371] iteration 20600 : loss : 5.971821, loss_ce: 0.007350, loss_pse_sup_soft: 0.745559, alpha: 0.422622 -[21:41:14.557] avg_metric:[[0.88190505] - [0.86935034] - [0.92779532]] -[21:41:14.558] iteration 20600 : dice_score : 0.893017 -[21:42:01.875] iteration 20800 : loss : 5.973343, loss_ce: 0.007897, loss_pse_sup_soft: 0.745681, alpha: 0.142986 -[21:42:04.150] avg_metric:[[0.88220343] - [0.86905859] - [0.92946759]] -[21:42:04.151] iteration 20800 : dice_score : 0.893577 -[21:42:51.869] iteration 21000 : loss : 5.970727, loss_ce: 0.006765, loss_pse_sup_soft: 0.745495, alpha: 0.461334 -[21:42:53.997] avg_metric:[[0.88234762] - [0.87027924] - [0.92994538]] -[21:42:53.998] iteration 21000 : dice_score : 0.894191 -[21:43:41.211] iteration 21200 : loss : 5.971716, loss_ce: 0.008145, loss_pse_sup_soft: 0.745446, alpha: 0.539398 -[21:43:43.345] avg_metric:[[0.88263844] - [0.87006453] - [0.92940423]] -[21:43:43.346] iteration 21200 : dice_score : 0.894036 -[21:44:31.343] iteration 21400 : loss : 5.974250, loss_ce: 0.007679, loss_pse_sup_soft: 0.745821, alpha: 0.329030 -[21:44:33.448] avg_metric:[[0.88145642] - [0.86985516] - [0.93042943]] -[21:44:33.449] iteration 21400 : dice_score : 0.893914 -[21:45:20.791] iteration 21600 : loss : 5.971435, loss_ce: 0.007764, loss_pse_sup_soft: 0.745459, alpha: 0.693089 -[21:45:23.068] avg_metric:[[0.88259474] - [0.86938826] - [0.92947936]] -[21:45:23.069] iteration 21600 : dice_score : 0.893821 -[21:46:10.990] iteration 21800 : loss : 5.972110, loss_ce: 0.007825, loss_pse_sup_soft: 0.745536, alpha: 0.499555 -[21:46:12.944] avg_metric:[[0.88157191] - [0.86895289] - [0.92944936]] -[21:46:12.945] iteration 21800 : dice_score : 0.893325 -[21:46:59.920] iteration 22000 : loss : 5.969105, loss_ce: 0.007151, loss_pse_sup_soft: 0.745244, alpha: 0.644564 -[21:47:01.972] avg_metric:[[0.88133289] - [0.86928048] - [0.92890748]] -[21:47:01.973] iteration 22000 : dice_score : 0.893174 -[21:47:49.861] iteration 22200 : loss : 5.972764, loss_ce: 0.008098, loss_pse_sup_soft: 0.745583, alpha: 0.757313 -[21:47:51.812] avg_metric:[[0.88337717] - [0.86978926] - [0.92970608]] -[21:47:51.813] iteration 22200 : dice_score : 0.894291 -[21:48:38.915] iteration 22400 : loss : 5.974967, loss_ce: 0.009446, loss_pse_sup_soft: 0.745690, alpha: 0.897646 -[21:48:41.002] avg_metric:[[0.88318803] - [0.86970243] - [0.93056118]] -[21:48:41.003] iteration 22400 : dice_score : 0.894484 -[21:49:28.814] iteration 22600 : loss : 5.970973, loss_ce: 0.007416, loss_pse_sup_soft: 0.745445, alpha: 0.006473 -[21:49:30.884] avg_metric:[[0.88233691] - [0.87014713] - [0.92987683]] -[21:49:30.886] iteration 22600 : dice_score : 0.894120 -[21:50:18.191] iteration 22800 : loss : 5.972545, loss_ce: 0.008608, loss_pse_sup_soft: 0.745492, alpha: 0.771763 -[21:50:20.324] avg_metric:[[0.88326926] - [0.86918749] - [0.93018456]] -[21:50:20.324] iteration 22800 : dice_score : 0.894214 -[21:51:08.228] iteration 23000 : loss : 5.972520, loss_ce: 0.007948, loss_pse_sup_soft: 0.745571, alpha: 0.578769 -[21:51:10.320] avg_metric:[[0.88201218] - [0.86858083] - [0.93022777]] -[21:51:10.322] iteration 23000 : dice_score : 0.893607 -[21:51:58.565] iteration 23200 : loss : 5.971138, loss_ce: 0.007251, loss_pse_sup_soft: 0.745486, alpha: 0.738124 -[21:52:00.705] avg_metric:[[0.88311374] - [0.86912418] - [0.93020424]] -[21:52:00.706] iteration 23200 : dice_score : 0.894147 -[21:52:47.917] iteration 23400 : loss : 5.973992, loss_ce: 0.008921, loss_pse_sup_soft: 0.745634, alpha: 0.972117 -[21:52:49.978] avg_metric:[[0.8824476 ] - [0.86946534] - [0.92883725]] -[21:52:49.979] iteration 23400 : dice_score : 0.893583 -[21:53:37.964] iteration 23600 : loss : 5.973829, loss_ce: 0.009272, loss_pse_sup_soft: 0.745570, alpha: 0.486746 -[21:53:40.133] avg_metric:[[0.88129104] - [0.86989943] - [0.92965772]] -[21:53:40.134] iteration 23600 : dice_score : 0.893616 -[21:54:27.213] iteration 23800 : loss : 5.973519, loss_ce: 0.007905, loss_pse_sup_soft: 0.745702, alpha: 0.099166 -[21:54:29.293] avg_metric:[[0.88188561] - [0.86997776] - [0.93078784]] -[21:54:29.293] iteration 23800 : dice_score : 0.894217 -[21:55:17.682] iteration 24000 : loss : 5.973821, loss_ce: 0.008081, loss_pse_sup_soft: 0.745718, alpha: 0.084777 -[21:55:19.927] avg_metric:[[0.88211333] - [0.87013725] - [0.93023816]] -[21:55:19.928] iteration 24000 : dice_score : 0.894163 -[21:56:07.184] iteration 24200 : loss : 5.970249, loss_ce: 0.007618, loss_pse_sup_soft: 0.745329, alpha: 0.351433 -[21:56:09.191] avg_metric:[[0.88280362] - [0.86862428] - [0.93030103]] -[21:56:09.192] iteration 24200 : dice_score : 0.893910 -[21:56:57.261] iteration 24400 : loss : 5.972057, loss_ce: 0.008693, loss_pse_sup_soft: 0.745421, alpha: 0.908610 -[21:56:59.386] avg_metric:[[0.8803236 ] - [0.86857218] - [0.92850905]] -[21:56:59.386] iteration 24400 : dice_score : 0.892468 -[21:57:46.727] iteration 24600 : loss : 5.974432, loss_ce: 0.008593, loss_pse_sup_soft: 0.745730, alpha: 0.183770 -[21:57:49.178] avg_metric:[[0.88282053] - [0.87006649] - [0.9312719 ]] -[21:57:49.179] iteration 24600 : dice_score : 0.894720 -[21:58:37.311] iteration 24800 : loss : 5.975046, loss_ce: 0.009095, loss_pse_sup_soft: 0.745744, alpha: 0.902544 -[21:58:39.431] avg_metric:[[0.88113546] - [0.86999825] - [0.93035585]] -[21:58:39.432] iteration 24800 : dice_score : 0.893830 -[21:59:27.261] iteration 25000 : loss : 5.969604, loss_ce: 0.007153, loss_pse_sup_soft: 0.745306, alpha: 0.066243 -[21:59:29.442] avg_metric:[[0.88220788] - [0.86894493] - [0.93016802]] -[21:59:29.443] iteration 25000 : dice_score : 0.893774 -[21:59:29.490] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_softcel8_ReUnmC_T01_0919/iter_25000.pth -[22:00:17.739] iteration 25200 : loss : 5.970847, loss_ce: 0.007137, loss_pse_sup_soft: 0.745464, alpha: 0.858375 -[22:00:20.055] avg_metric:[[0.88147934] - [0.86954637] - [0.92824638]] -[22:00:20.056] iteration 25200 : dice_score : 0.893091 -[22:01:07.434] iteration 25400 : loss : 5.977373, loss_ce: 0.009744, loss_pse_sup_soft: 0.745954, alpha: 0.144878 -[22:01:09.397] avg_metric:[[0.88213835] - [0.86962921] - [0.929668 ]] -[22:01:09.398] iteration 25400 : dice_score : 0.893812 -[22:01:57.517] iteration 25600 : loss : 5.973141, loss_ce: 0.008915, loss_pse_sup_soft: 0.745528, alpha: 0.158830 -[22:01:59.874] avg_metric:[[0.88289047] - [0.86826352] - [0.93023004]] -[22:01:59.876] iteration 25600 : dice_score : 0.893795 -[22:02:48.076] iteration 25800 : loss : 5.973017, loss_ce: 0.007791, loss_pse_sup_soft: 0.745653, alpha: 0.916378 -[22:02:50.495] avg_metric:[[0.88316567] - [0.86972964] - [0.93024213]] -[22:02:50.499] iteration 25800 : dice_score : 0.894379 -[22:03:38.525] iteration 26000 : loss : 5.974954, loss_ce: 0.009295, loss_pse_sup_soft: 0.745707, alpha: 0.934527 -[22:03:40.723] avg_metric:[[0.88265547] - [0.8695285 ] - [0.93000074]] -[22:03:40.725] iteration 26000 : dice_score : 0.894062 -[22:04:27.901] iteration 26200 : loss : 5.971660, loss_ce: 0.007935, loss_pse_sup_soft: 0.745466, alpha: 0.355472 -[22:04:30.318] avg_metric:[[0.88265687] - [0.86945279] - [0.93022088]] -[22:04:30.320] iteration 26200 : dice_score : 0.894110 -[22:05:17.976] iteration 26400 : loss : 5.974725, loss_ce: 0.008532, loss_pse_sup_soft: 0.745774, alpha: 0.111174 -[22:05:20.180] avg_metric:[[0.88173634] - [0.86994856] - [0.92858781]] -[22:05:20.181] iteration 26400 : dice_score : 0.893424 -[22:06:07.290] iteration 26600 : loss : 5.972170, loss_ce: 0.007637, loss_pse_sup_soft: 0.745567, alpha: 0.778200 -[22:06:09.369] avg_metric:[[0.88201519] - [0.8701585 ] - [0.93088172]] -[22:06:09.371] iteration 26600 : dice_score : 0.894352 -[22:06:57.448] iteration 26800 : loss : 5.974666, loss_ce: 0.008680, loss_pse_sup_soft: 0.745748, alpha: 0.819975 -[22:06:59.637] avg_metric:[[0.88292361] - [0.87031638] - [0.93159955]] -[22:06:59.638] iteration 26800 : dice_score : 0.894947 -[22:07:47.008] iteration 27000 : loss : 5.970686, loss_ce: 0.007203, loss_pse_sup_soft: 0.745435, alpha: 0.165710 -[22:07:49.084] avg_metric:[[0.88303638] - [0.86899878] - [0.93078058]] -[22:07:49.086] iteration 27000 : dice_score : 0.894272 -[22:08:36.995] iteration 27200 : loss : 5.975157, loss_ce: 0.008281, loss_pse_sup_soft: 0.745860, alpha: 0.173979 -[22:08:39.015] avg_metric:[[0.8817466 ] - [0.87026194] - [0.93109832]] -[22:08:39.017] iteration 27200 : dice_score : 0.894369 -[22:09:26.461] iteration 27400 : loss : 5.970967, loss_ce: 0.008099, loss_pse_sup_soft: 0.745359, alpha: 0.708037 -[22:09:28.687] avg_metric:[[0.88274949] - [0.86990064] - [0.9303478 ]] -[22:09:28.689] iteration 27400 : dice_score : 0.894333 -[22:10:17.209] iteration 27600 : loss : 5.972577, loss_ce: 0.007987, loss_pse_sup_soft: 0.745574, alpha: 0.839224 -[22:10:19.348] avg_metric:[[0.88145404] - [0.86955079] - [0.93027917]] -[22:10:19.349] iteration 27600 : dice_score : 0.893761 -[22:11:06.575] iteration 27800 : loss : 5.973475, loss_ce: 0.008860, loss_pse_sup_soft: 0.745577, alpha: 0.477905 -[22:11:08.790] avg_metric:[[0.88238475] - [0.86950615] - [0.92957513]] -[22:11:08.791] iteration 27800 : dice_score : 0.893822 -[22:11:56.871] iteration 28000 : loss : 5.974567, loss_ce: 0.008164, loss_pse_sup_soft: 0.745800, alpha: 0.928330 -[22:11:58.805] avg_metric:[[0.8823987 ] - [0.87047348] - [0.92992349]] -[22:11:58.806] iteration 28000 : dice_score : 0.894265 -[22:12:46.161] iteration 28200 : loss : 5.972686, loss_ce: 0.008163, loss_pse_sup_soft: 0.745565, alpha: 0.381996 -[22:12:48.252] avg_metric:[[0.88178054] - [0.8696337 ] - [0.92903798]] -[22:12:48.253] iteration 28200 : dice_score : 0.893484 -[22:13:36.381] iteration 28400 : loss : 5.969258, loss_ce: 0.007185, loss_pse_sup_soft: 0.745259, alpha: 0.721679 -[22:13:38.519] avg_metric:[[0.88277671] - [0.86909 ] - [0.92981532]] -[22:13:38.520] iteration 28400 : dice_score : 0.893894 -[22:14:25.990] iteration 28600 : loss : 5.968431, loss_ce: 0.007136, loss_pse_sup_soft: 0.745162, alpha: 0.560758 -[22:14:28.142] avg_metric:[[0.88203134] - [0.86937083] - [0.92836706]] -[22:14:28.143] iteration 28600 : dice_score : 0.893256 -[22:15:16.046] iteration 28800 : loss : 5.974935, loss_ce: 0.008563, loss_pse_sup_soft: 0.745797, alpha: 0.269928 -[22:15:18.250] avg_metric:[[0.8819423 ] - [0.86973213] - [0.9281872 ]] -[22:15:18.251] iteration 28800 : dice_score : 0.893287 -[22:16:05.466] iteration 29000 : loss : 5.971748, loss_ce: 0.008074, loss_pse_sup_soft: 0.745459, alpha: 0.488476 -[22:16:07.666] avg_metric:[[0.88284519] - [0.87002415] - [0.92991064]] -[22:16:07.667] iteration 29000 : dice_score : 0.894260 -[22:16:55.620] iteration 29200 : loss : 5.971180, loss_ce: 0.007657, loss_pse_sup_soft: 0.745440, alpha: 0.477899 -[22:16:57.719] avg_metric:[[0.88226239] - [0.86916706] - [0.92946759]] -[22:16:57.721] iteration 29200 : dice_score : 0.893632 -[22:17:45.007] iteration 29400 : loss : 5.970459, loss_ce: 0.007216, loss_pse_sup_soft: 0.745405, alpha: 0.585183 -[22:17:46.915] avg_metric:[[0.88296304] - [0.86948744] - [0.92943984]] -[22:17:46.915] iteration 29400 : dice_score : 0.893963 -[22:18:34.667] iteration 29600 : loss : 5.969799, loss_ce: 0.006606, loss_pse_sup_soft: 0.745399, alpha: 0.452677 -[22:18:36.650] avg_metric:[[0.88134141] - [0.87025697] - [0.92917683]] -[22:18:36.651] iteration 29600 : dice_score : 0.893592 -[22:19:23.951] iteration 29800 : loss : 5.971266, loss_ce: 0.007906, loss_pse_sup_soft: 0.745420, alpha: 0.138123 -[22:19:26.313] avg_metric:[[0.88198942] - [0.8697592 ] - [0.92994896]] -[22:19:26.314] iteration 29800 : dice_score : 0.893899 -[22:20:14.360] iteration 30000 : loss : 5.974875, loss_ce: 0.008719, loss_pse_sup_soft: 0.745770, alpha: 0.605944 -[22:20:16.576] avg_metric:[[0.88174386] - [0.8702732 ] - [0.93027124]] -[22:20:16.577] iteration 30000 : dice_score : 0.894096 -[22:20:16.623] save model to ../../model/HeartM_ACDC/A3_weakly_PLS_2d_unet_cct_v2_softcel8_ReUnmC_T01_0919/iter_30000.pth -[22:20:16.716] time cost: 7377.461703777313 s, i.e, 2.0492949177159203 h diff --git a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/unet_cct_best_model.pth b/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/unet_cct_best_model.pth deleted file mode 100644 index e50a4cd..0000000 Binary files a/model/Heart_ACDC_Example/A_weakly_SPS_2d_unet_cct_stage2/unet_cct_best_model.pth and /dev/null differ diff --git a/readme.md b/readme.md deleted file mode 100644 index 93bd18b..0000000 --- a/readme.md +++ /dev/null @@ -1,191 +0,0 @@ -# DMSPS -Official code for: DMSPS: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation. [MedIA 2024](https://www.sciencedirect.com/science/article/pii/S1361841524001993?dgcid=author). -And the previous version is published on the [MICCAI 2022](https://link.springer.com/chapter/10.1007/978-3-031-16431-6_50). - -### Overall Framework -The overall framework of DMSPS： -![overall](https://github.com/HiLab-git/DMSPS/blob/master/imgs/framework.png) - -### Citation -If you use this project in your research, please cite the following works: -``` -@article{han2024dmsps, - title={DMSPS: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation}, - author={Han, Meng and Luo, Xiangde and Xie, Xiangjiang and Liao, Wenjun and Zhang, Shichuan and Song, Tao and Wang, Guotai and Zhang, Shaoting}, - journal={Medical Image Analysis}, - pages={103274}, - year={2024}, - publisher={Elsevier} -} - -@inproceedings{luo2022scribble, - title={Scribble-supervised medical image segmentation via dual-branch network and dynamically mixed pseudo labels supervision}, - author={Luo, Xiangde and Hu, Minhao and Liao, Wenjun and Zhai, Shuwei and Song, Tao and Wang, Guotai and Zhang, Shaoting}, - booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention}, - pages={528--538}, - year={2022}, - organization={Springer} -} -``` - -# Dataset -* For ACDC dataset, the images, scribbles and data split can be downloaded from [ACDC BaiduPan][baidu_acdc] (The extraction code is: remr), or [Google Drive][google_acdc]. -* The WORD dataset can be downloaded from [WORD](https://github.com/HiLab-git/WORD?tab=readme-ov-file). -* The BraTS2020 dataset can be downloaded from [BraTS2020](https://www.med.upenn.edu/cbica/brats2020/data.html). Note that this work aimed to segment two foreground classes: the tumor core and the peritumoral -edema. Scribbles could be genearted by this simulation code: [scribble-generate](https://github.com/HiLab-git/DMSPS/blob/master/code/dataloader/scribble_generater.py) - -[baidu_acdc]: https://pan.baidu.com/s/1yWD0zkfy17AlexhKP4dQMQ -[baidu_acdc_old_code_et38]: https://pan.baidu.com/s/1Wqcw_qFNezplzdewQMHXsg -[google_acdc]: https://drive.google.com/file/d/1QffBpxfUgZmMQOiGa24IMhygS_Q8NtrI/view?usp=sharing -# Usage with PyMIC -To facilitate the use of code and make it easier to compare with other methods, we have re-implemented DMSPS in PyMIC, a Pytorch-based framework for annotation-efficient segmentation. The core modules of DMSPS in PyMIC can be found [here][pymic_dmsps]. It is suggested to use PyMIC for this experiment. In the following, we take the ACDC dataset as an example for scribble-supervised segmentation. - -[pymic_dmsps]: https://github.com/HiLab-git/PyMIC/blob/master/pymic/net_run/weak_sup/wsl_dmsps.py - -### Step 0: Preparation -1. Install PyMIC. -``` -pip install pymic==0.5.4 -``` -2. Dataset convert. -To speed up the training process, we convert the data into h5 files. -``` -python image_process.py 0 -``` -To run this code, you need to set `ACDC_DIR` to the path of the ACDC dataset after download. - -### Step 1: Training the first stage model -1. The configurations including dataset, network, optimizer and hyper-parameters are contained in the configure file -`config/acdc_dmsps.cfg`. Train the first-stage model by running: -``` -python run.py train config/acdc_dmsps.cfg -``` -2. Obtain predictions for testing images: -``` -python run.py test config/acdc_dmsps.cfg -``` -3. Obtain quantitative evaluation results: -``` -pymic_eval_seg --metric dice --cls_num 4 \ - --gt_dir data/ACDC2017/ACDC/TestSet/labels --seg_dir ./result/acdc_dmsps \ - --name_pair ./config/image_test_gt_seg.csv -``` -The average Dice on the test set would be around 88.94%. - -4. Then obtain the expanded seeds based on confident predictions from the first stage model. -``` -python run.py test config/acdc_dmsps.cfg --test_csv data/ACDC2017/ACDC_for2D/trainvol.csv \ - --dmsps_test_mode 1 --output_dir result/acdc_dmsps_train -``` -5. Create the training set for the second-stage model: -``` -python image_process.py 1 -``` -### Step 2: Training the second stage model -1. Just like the first stage, train the model use: -``` -python run.py train config/acdc_dmsps_stage2.cfg -``` -Note that to speedup the training process, we finetune the first-stage model here. You may also try to train from scratch. - -2. Test with the second-stage model: -``` -python run.py test config/acdc_dmsps_stage2.cfg -``` -3. Obtain quantitative evaluation results: -``` -pymic_eval_seg --metric dice --cls_num 4 \ - --gt_dir data/ACDC2017/ACDC/TestSet/labels --seg_dir ./result/acdc_dmsps_stage2 \ - --name_pair ./config/image_test_gt_seg.csv -``` -The average Dice on the test set would be around 89.51%. -### Step 3: Training with sparser annotations -The original scribbles for the ACDC dataset was quite dense, and to investigate the performance under sparser annotations, we have reduced the scribble length to 1/2, 1/4, 1/8 and 1/16, respectively. For example, to train and test the model with scribbles at length of 1/4, run: -``` -python run.py train config/acdc_dmsps_r4.cfg -python run.py test config/acdc_dmsps_r4.cfg -pymic_eval_seg --metric dice --cls_num 4 \ - --gt_dir data/ACDC2017/ACDC/TestSet/labels --seg_dir ./result/acdc_dmsps_r4 \ - --name_pair ./config/image_test_gt_seg.csv -``` -The average Dice on the test set would be around 86.78%. - -### Step 4: Compare with other weakly supervised segmentation methods -PyMIC also provides implementation of several other weakly supervised methods (learning from scribbles). Please see [PyMIC_examples/seg_weak_sup/ACDC][PyMIC_example_link] for examples. - -[PyMIC_example_link]:https://github.com/HiLab-git/PyMIC_examples/tree/main/seg_weak_sup/ACDC - -# Usage (a backup of the old version) -### Step0: -1. Clone this project. -``` -git clone https://github.com/HiLab-git/DMSPS -cd DMSPS -``` -2. Data pre-processing. -``` -cd code/dataloaders -python preprocess_ACDC.py -``` - -### Quick test using pre-trained checkpoints: -1. the first stage -``` -cd code/test -python test_2d_forall_fast_txtver.py --data_name Heart_ACDC_Example \ ---exp A_weakly_SPS_2d --fold stage1 --model unet_cct --tt_num 1 -``` -2. the second stage -``` -python test_2d_forall_fast_txtver.py --data_name Heart_ACDC_Example \ ---exp A_weakly_SPS_2d --fold stage2 --model unet_cct --tt_num 1 -``` - -### Train and test for the first stage -1. Train the model -``` -cd code/train -python A_train_weaklySup_SPS_2d_soft.py -``` -2. Test the model -``` -cd code/test -python test_2d_forall_fast_txtver.py -``` - -### Train and test for the second stage -1. test on trainSet and get the uncertainty-filterd pseudo-label -``` -cd code/test -python test_2d_forall_fast_txtver_forTrainSetUncertaintyOnly_Mean.py \ - --data_root_path $yourPath/ACDC2017/ACDC_for2D \ - --model unet_cct --exp A_weakly_SPS_2d --fold stage1 --threshold 0.1 --tt_num 3 -``` -2. deal with the produced confident expanded annotation into h5 file and get the txt -``` -cd code/dataloader -python retrain_postProcess_ACDC_uncertainty.py \ - --data_root_path $yourPath/ACDC2017/ACDC \ - --func 0 --txtName trainReT01 -python retrain_postProcess_ACDC_uncertainty.py \ - --data_root_path $yourPath/ACDC2017/ACDC \ - --func 1 --txtName trainReT01 -``` -3. train for stage2 -``` -cd code/train -python A_train_weaklySup_SPS_2d_soft_retrainUncertainty.py \ - --data_root_path $yourPath/ACDC2017/ACDC_for2D \ - --model unet_cct --exp A_weakly_SPS_2d --fold stage2 \ - --sup_type pseudoLab --trainData trainReT01.txt -``` -4. test for stage2 -``` -cd code/test -python test_2d_forall_fast_txtver.py \ - --data_root_path $yourPath/ACDC2017/ACDC_for2D \ - --model unet_cct --exp A_weakly_SPS_2d --fold stage2 -``` - -### Acknowledgement -The code of scribble-supervised learning framework is borrowed from [WSL4MIS](https://github.com/HiLab-git/WSL4MIS) \ No newline at end of file diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index ea2eebf..0000000 --- a/requirements.txt +++ /dev/null @@ -1,15 +0,0 @@ -h5py -matplotlib>=3.1.2 -numpy>=1.23.5 -pandas>=1.5.2 -scikit-image>=0.19.3 -scikit-learn>=1.2.0 -scipy>=1.10.0 -SimpleITK>=2.0.2 -tensorboard -tensorboardX -torch>=1.13.1 -torchvision>=0.14.1 -causal-conv1d>=1.5.0 -mamba-ssm>=2.2.4 -pymic>=0.5.4 diff --git a/run.py b/run.py deleted file mode 100644 index 0f3f86d..0000000 --- a/run.py +++ /dev/null @@ -1,133 +0,0 @@ -# -*- coding: utf-8 -*- -'''` -Code for the following paper: - https://www.sciencedirect.com/science/article/abs/pii/S1361841524001993?dgcid - @article{han2024dmsps, - title={DMSPS: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation}, - author={Han, Meng and Luo, Xiangde and Xie, Xiangjiang and Liao, Wenjun and Zhang, Shichuan and Song, Tao and Wang, Guotai and Zhang, Shaoting}, - journal={Medical Image Analysis}, - pages={103274}, - year={2024}, - publisher={Elsevier} -} - -''' - -from __future__ import print_function, division -import argparse -import logging -import os -import random -import sys -import torch -import torch.nn as nn -import numpy as np -from scipy import ndimage -from pymic.util.parse_config import * -from pymic.transform.trans_dict import TransformDict -from pymic.net.net_dict_seg import SegNetDict -from pymic.net.net2d.unet2d import Encoder, Decoder -from pymic.net_run.weak_sup import WSLDMSPS - - -def Dropout(x, p=0.5): - x = torch.nn.functional.dropout2d(x, p) - return x - -class DBNet(nn.Module): - def __init__(self, params): - super(DBNet, self).__init__() - self.encoder = Encoder(params) - self.main_decoder = Decoder(params) - self.aux_decoder1 = Decoder(params) - - def forward(self, x): - x_shape = list(x.shape) - if(len(x_shape) == 5): - [N, C, D, H, W] = x_shape - new_shape = [N*D, C, H, W] - x = torch.transpose(x, 1, 2) - x = torch.reshape(x, new_shape) - feature = self.encoder(x) - main_out = self.main_decoder(feature) - aux_feature = [Dropout(i) for i in feature] - aux_out1 = self.aux_decoder1(aux_feature) - - if(len(x_shape) == 5): - new_shape = [N, D] + list(main_out.shape)[1:] - main_out = torch.reshape(main_out, new_shape) - main_out = torch.transpose(main_out, 1, 2) - aux_out1 = torch.reshape(aux_out1, new_shape) - aux_out1 = torch.transpose(aux_out1, 1, 2) - - return main_out, aux_out1 - -class CustomTransform(object): - def __init__(self, param): - self.output_size = param["CustomTransform_output_size".lower()] - - def __call__(self, sample): - image, label = sample["image"], sample["label"] - if random.random() > 0.5: - k = np.random.randint(0, 4) - image = np.rot90(image, k, (-2, -1)) - label = np.rot90(label, k, (-2, -1)) - axis = np.random.randint(-2, -1) - image = np.flip(image, axis=axis).copy() - label = np.flip(label, axis=axis).copy() - elif random.random() > 0.5: - angle = np.random.randint(-20, 20) - image = ndimage.rotate(image, angle, axes=(-2, -1), order=0, reshape=False) - label = ndimage.rotate(label, angle, axes=(-2, -1), order=0, reshape=False, mode="constant", cval=4) - - img_shape = image.shape - zoom_f = [1.0, self.output_size[0]/img_shape[-2], self.output_size[1]/img_shape[-1]] - image = ndimage.zoom(image, zoom_f, order=0) - label = ndimage.zoom(label, zoom_f, order=0) - sample = {"image": image, "label": label, "gt":label} - return sample - -def main(): - if(len(sys.argv) < 2): - print('Number of arguments should be at least 3. e.g.') - print(' python run.py train config.cfg') - exit() - parser = argparse.ArgumentParser() - parser.add_argument("stage", type = str, help="stage of train or test") - parser.add_argument("cfg", type = str, help="configuration file") - parser.add_argument("--test_csv", type = str, required=False, help="the csv file for testing images", - default='./data/ACDC2017/ACDC_for2D/test.csv') - parser.add_argument("--dmsps_test_mode", type = str, required=False, default='0', - help="mode for testing. 0: obtain segmentation label map from the main decoder;" + - "1: obtain the uncertainty map and expanded seeds based on the two decoders.") - parser.add_argument("--output_dir", type = str, required=False, help="the path of output dir", - default=None) - args = parser.parse_args() - if(not os.path.isfile(args.cfg)): - raise ValueError("The config file does not exist: " + args.cfg) - config = parse_config(args) - config = synchronize_config(config) - - log_dir = config['training']['ckpt_dir'] - if(not os.path.exists(log_dir)): - os.makedirs(log_dir) - if sys.version.startswith("3.9"): - logging.basicConfig(filename=log_dir+"/log_{0:}.txt".format(args.stage), level=logging.INFO, - format='%(message)s', force=True) # for python 3.9 - else: - logging.basicConfig(filename=log_dir+"/log_{0:}.txt".format(args.stage), level=logging.INFO, - format='%(message)s') # for python 3.6 - logging.getLogger().addHandler(logging.StreamHandler(sys.stdout)) - logging_config(config) - - agent = WSLDMSPS(config, args.stage) - trans_dict = {"CustomTransform":CustomTransform} - trans_dict.update(TransformDict) - net_dict = {"DBNet": DBNet} - net_dict.update(SegNetDict) - agent.set_transform_dict(trans_dict) - agent.set_net_dict(net_dict) - agent.run() - -if __name__ == "__main__": - main()