From fc7fbd354831d95c08dfed4357b6d4d7a95c9dea Mon Sep 17 00:00:00 2001 From: Guotai Wang Date: Fri, 12 Jan 2018 21:11:42 +0000 Subject: [PATCH] prepared for docker --- config/test_all_class.txt | 33 +- config/test_names.txt | 50 ++ config/test_names_example.txt | 20 - config/train_en_ax.txt | 14 +- config/train_en_cr.txt | 18 +- config/train_en_sg.txt | 18 +- config/train_names.txt | 224 +++++++ config/train_names_all.txt | 559 +++++++++--------- config/train_names_all_lggx3.txt | 438 +------------- config/train_tc_ax.txt | 10 +- config/train_tc_cr.txt | 18 +- config/train_tc_sg.txt | 18 +- config/train_wt_ax.txt | 8 +- config/train_wt_cr.txt | 18 +- config/train_wt_sg.txt | 14 +- convert_brats_image.py | 38 ++ evaluation.py | 12 +- model/checkpoint | 6 + .../msnet_en32_20000.ckpt.data-00000-of-00001 | Bin 0 -> 2493804 bytes model/msnet_en32_20000.ckpt.index | Bin 0 -> 18475 bytes model/msnet_en32_20000.ckpt.meta | Bin 0 -> 3174230 bytes ...msnet_en32cr_5000.ckpt.data-00000-of-00001 | Bin 0 -> 2493804 bytes model/msnet_en32cr_5000.ckpt.index | Bin 0 -> 18603 bytes model/msnet_en32cr_5000.ckpt.meta | Bin 0 -> 3250667 bytes ...msnet_en32sg_5000.ckpt.data-00000-of-00001 | Bin 0 -> 2493804 bytes model/msnet_en32sg_5000.ckpt.index | Bin 0 -> 18603 bytes model/msnet_en32sg_5000.ckpt.meta | Bin 0 -> 3250667 bytes .../msnet_tc32_20000.ckpt.data-00000-of-00001 | Bin 0 -> 2587176 bytes model/msnet_tc32_20000.ckpt.index | Bin 0 -> 21134 bytes model/msnet_tc32_20000.ckpt.meta | Bin 0 -> 3661816 bytes ...msnet_tc32cr_5000.ckpt.data-00000-of-00001 | Bin 0 -> 2587176 bytes model/msnet_tc32cr_5000.ckpt.index | Bin 0 -> 21280 bytes model/msnet_tc32cr_5000.ckpt.meta | Bin 0 -> 3749120 bytes ...msnet_tc32sg_5000.ckpt.data-00000-of-00001 | Bin 0 -> 2587176 bytes model/msnet_tc32sg_5000.ckpt.index | Bin 0 -> 21280 bytes model/msnet_tc32sg_5000.ckpt.meta | Bin 0 -> 3749120 bytes .../msnet_wt32_10000.ckpt.data-00000-of-00001 | Bin 0 -> 2587176 bytes model/msnet_wt32_10000.ckpt.index | Bin 0 -> 21134 bytes model/msnet_wt32_10000.ckpt.meta | Bin 0 -> 3662587 bytes ...msnet_wt32cr_5000.ckpt.data-00000-of-00001 | Bin 0 -> 2587176 bytes model/msnet_wt32cr_5000.ckpt.index | Bin 0 -> 21280 bytes model/msnet_wt32cr_5000.ckpt.meta | Bin 0 -> 3749891 bytes ...msnet_wt32sg_5000.ckpt.data-00000-of-00001 | Bin 0 -> 2587176 bytes model/msnet_wt32sg_5000.ckpt.index | Bin 0 -> 21280 bytes model/msnet_wt32sg_5000.ckpt.meta | Bin 0 -> 3749891 bytes pre_process.py | 65 +- rename_variables.py | 33 ++ test.py | 9 +- test_data.txt | 90 +++ util/data_loader.py | 91 +-- util/data_process.py | 13 + 51 files changed, 921 insertions(+), 896 deletions(-) create mode 100644 config/test_names.txt delete mode 100755 config/test_names_example.txt create mode 100644 config/train_names.txt create mode 100644 convert_brats_image.py create mode 100644 model/checkpoint create mode 100644 model/msnet_en32_20000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_en32_20000.ckpt.index create mode 100644 model/msnet_en32_20000.ckpt.meta create mode 100644 model/msnet_en32cr_5000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_en32cr_5000.ckpt.index create mode 100644 model/msnet_en32cr_5000.ckpt.meta create mode 100644 model/msnet_en32sg_5000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_en32sg_5000.ckpt.index create mode 100644 model/msnet_en32sg_5000.ckpt.meta create mode 100644 model/msnet_tc32_20000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_tc32_20000.ckpt.index create mode 100644 model/msnet_tc32_20000.ckpt.meta create mode 100644 model/msnet_tc32cr_5000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_tc32cr_5000.ckpt.index create mode 100644 model/msnet_tc32cr_5000.ckpt.meta create mode 100644 model/msnet_tc32sg_5000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_tc32sg_5000.ckpt.index create mode 100644 model/msnet_tc32sg_5000.ckpt.meta create mode 100644 model/msnet_wt32_10000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_wt32_10000.ckpt.index create mode 100644 model/msnet_wt32_10000.ckpt.meta create mode 100644 model/msnet_wt32cr_5000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_wt32cr_5000.ckpt.index create mode 100644 model/msnet_wt32cr_5000.ckpt.meta create mode 100644 model/msnet_wt32sg_5000.ckpt.data-00000-of-00001 create mode 100644 model/msnet_wt32sg_5000.ckpt.index create mode 100644 model/msnet_wt32sg_5000.ckpt.meta create mode 100644 rename_variables.py create mode 100755 test_data.txt diff --git a/config/test_all_class.txt b/config/test_all_class.txt index f4de742..f55a35c 100755 --- a/config/test_all_class.txt +++ b/config/test_all_class.txt @@ -1,6 +1,7 @@ [data] -data_root = [data/Brats17ValidationData_renamed] -data_names = +data_root = [/home/guotwang/data/brats_docker_data/pre_process] +data_names = config/test_names.txt +modality_postfix = [Flair, T1, T1c, T2] [network1ax] net_type = MSNet @@ -9,7 +10,7 @@ downsample_twice = True data_shape = [19, 180, 160, 4] label_shape = [11, 180, 160, 1] class_num = 2 -model_file = model_pretrain/msnet_wt32_20000.ckpt +model_file = model/msnet_wt32_10000.ckpt [network1sg] net_type = MSNet @@ -18,7 +19,7 @@ downsample_twice = True data_shape = [19, 160, 180, 4] label_shape = [11, 160, 180, 1] class_num = 2 -model_file = model_pretrain/msnet_wt32sg_20000.ckpt +model_file = model/msnet_wt32sg_5000.ckpt [network1cr] net_type = MSNet @@ -27,7 +28,7 @@ downsample_twice = True data_shape = [19, 160, 160, 4] label_shape = [11, 160, 160, 1] class_num = 2 -model_file = model_pretrain/msnet_wt32cr_20000.ckpt +model_file = model/msnet_wt32cr_5000.ckpt [network2ax] @@ -37,7 +38,7 @@ downsample_twice = True data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] class_num = 2 -model_file = model_pretrain/msnet_tc32_20000.ckpt +model_file = model/msnet_tc32_20000.ckpt [network2sg] net_type = MSNet @@ -46,7 +47,7 @@ downsample_twice = True data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] class_num = 2 -model_file = model_pretrain/msnet_tc32sg_20000.ckpt +model_file = model/msnet_tc32sg_5000.ckpt [network2cr] net_type = MSNet @@ -55,7 +56,7 @@ downsample_twice = True data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] class_num = 2 -model_file = model_pretrain/msnet_tc32cr_20000.ckpt +model_file = model/msnet_tc32cr_5000.ckpt [network3ax] net_type = MSNet @@ -63,8 +64,8 @@ net_name = MSNet_EN32 downsample_twice = False data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] -class_num = 2 -model_file = model_pretrain/msnet_en32_20000.ckpt +class_num = 3 +model_file = model/msnet_en32_20000.ckpt [network3sg] net_type = MSNet @@ -72,8 +73,8 @@ net_name = MSNet_EN32sg downsample_twice = False data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] -class_num = 2 -model_file = model_pretrain/msnet_en32sg_20000.ckpt +class_num = 3 +model_file = model/msnet_en32sg_5000.ckpt [network3cr] net_type = MSNet @@ -81,11 +82,9 @@ net_name = MSNet_EN32cr downsample_twice = False data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] -class_num = 2 -model_file = model_pretrain/msnet_en32cr_20000.ckpt +class_num = 3 +model_file = model/msnet_en32cr_5000.ckpt [testing] test_slice_direction = all -label_convert_source = [0, 1, 2, 3] -label_convert_target = [0, 1, 2, 4] -save_folder = results +save_folder = result_all diff --git a/config/test_names.txt b/config/test_names.txt new file mode 100644 index 0000000..4d53103 --- /dev/null +++ b/config/test_names.txt @@ -0,0 +1,50 @@ +HGG_brats_tcia_pat417_0001 +HGG_brats_tcia_pat205_0001 +HGG_brats_tcia_pat455_0001 +HGG_brats_tcia_pat374_0356 +HGG_brats_tcia_pat473_0001 +HGG_brats_tcia_pat277_0001 +HGG_brats_tcia_pat396_0117 +LGG_brats_tcia_pat299_0001 +HGG_brats_tcia_pat332_0001 +HGG_brats_tcia_pat178_0002 +HGG_brats_tcia_pat199_0001 +HGG_brats_tcia_pat170_0002 +HGG_brats_tcia_pat156_0001 +HGG_brats_tcia_pat447_0313 +HGG_brats_tcia_pat198_0283 +HGG_brats_tcia_pat105_0001 +HGG_brats_2013_pat0002_1 +HGG_brats_tcia_pat406_0001 +LGG_brats_tcia_pat393_0001 +HGG_brats_tcia_pat274_0001 +LGG_brats_tcia_pat141_0001 +HGG_brats_tcia_pat138_0001 +LGG_brats_2013_pat0006_1 +HGG_brats_tcia_pat314_0001 +LGG_brats_2013_pat0014_1 +HGG_brats_tcia_pat447_0122 +HGG_brats_tcia_pat372_0001 +HGG_brats_tcia_pat230_0637 +HGG_brats_tcia_pat247_0001 +HGG_brats_tcia_pat171_0780 +LGG_brats_tcia_pat351_0001 +HGG_brats_tcia_pat399_0527 +HGG_brats_tcia_pat193_0002 +HGG_brats_tcia_pat374_0557 +HGG_brats_2013_pat0024_1 +HGG_brats_tcia_pat374_0909 +HGG_brats_tcia_pat278_0001 +HGG_brats_tcia_pat180_0001 +HGG_brats_tcia_pat399_0595 +HGG_brats_tcia_pat396_0217 +HGG_brats_tcia_pat257_0001 +HGG_brats_tcia_pat157_0001 +HGG_brats_tcia_pat165_0001 +HGG_brats_2013_pat0022_1 +HGG_brats_tcia_pat444_0001 +HGG_brats_tcia_pat399_0002 +HGG_brats_tcia_pat399_0156 +LGG_brats_tcia_pat428_0001 +HGG_brats_tcia_pat171_0950 +HGG_brats_tcia_pat399_0479 diff --git a/config/test_names_example.txt b/config/test_names_example.txt deleted file mode 100755 index fb12045..0000000 --- a/config/test_names_example.txt +++ /dev/null @@ -1,20 +0,0 @@ -HGG/Brats17_CBICA_ATX_1 -HGG/Brats17_CBICA_AXN_1 -HGG/Brats17_TCIA_491_1 -HGG/Brats17_CBICA_AOZ_1 -HGG/Brats17_TCIA_151_1 -HGG/Brats17_2013_25_1 -HGG/Brats17_TCIA_396_1 -HGG/Brats17_CBICA_AQN_1 -HGG/Brats17_TCIA_135_1 -HGG/Brats17_TCIA_603_1 -LGG/Brats17_2013_24_1 -LGG/Brats17_TCIA_630_1 -LGG/Brats17_TCIA_152_1 -LGG/Brats17_TCIA_620_1 -LGG/Brats17_TCIA_310_1 -LGG/Brats17_2013_29_1 -LGG/Brats17_TCIA_490_1 -LGG/Brats17_TCIA_449_1 -LGG/Brats17_TCIA_634_1 -LGG/Brats17_TCIA_346_1 \ No newline at end of file diff --git a/config/train_en_ax.txt b/config/train_en_ax.txt index 50eb304..7769393 100755 --- a/config/train_en_ax.txt +++ b/config/train_en_ax.txt @@ -1,22 +1,24 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all_lggx3.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 64, 64, 4] label_shape = [11, 64, 64, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 0, 0, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 0, 0, 2] batch_slice_direction = axial train_with_roi_patch = True -label_roi_mask = [1,4] +label_roi_mask = [1,3,4] roi_patch_margin = 5 [network] net_type = MSNet net_name = MSNet_EN32 downsample_twice = False -class_num = 2 +class_num = 3 [training] learning_rate = 1e-3 @@ -27,4 +29,4 @@ start_iteration = 0 test_iteration = 100 test_step = 10 model_pre_trained = -model_save_prefix = model/msnet_en32 \ No newline at end of file +model_save_prefix = model/msnet_en32 diff --git a/config/train_en_cr.txt b/config/train_en_cr.txt index e8095a5..e4be81e 100755 --- a/config/train_en_cr.txt +++ b/config/train_en_cr.txt @@ -1,30 +1,32 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all_lggx3.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 64, 64, 4] label_shape = [11, 64, 64, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 0, 0, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 0, 0, 2] batch_slice_direction = coronal train_with_roi_patch = True -label_roi_mask = [1,4] +label_roi_mask = [1,3,4] roi_patch_margin = 5 [network] net_type = MSNet net_name = MSNet_EN32cr downsample_twice = False -class_num = 2 +class_num = 3 [training] learning_rate = 1e-3 decay = 1e-7 -maximal_iteration = 20000 +maximal_iteration = 5000 snapshot_iteration = 5000 -start_iteration = 0 +start_iteration = 1 test_iteration = 100 test_step = 10 -model_pre_trained = +model_pre_trained = model/msnet_en32cr_init model_save_prefix = model/msnet_en32cr \ No newline at end of file diff --git a/config/train_en_sg.txt b/config/train_en_sg.txt index bb310b2..25fff42 100755 --- a/config/train_en_sg.txt +++ b/config/train_en_sg.txt @@ -1,30 +1,32 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all_lggx3.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 64, 64, 4] label_shape = [11, 64, 64, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 0, 0, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 0, 0, 2] batch_slice_direction = sagittal train_with_roi_patch = True -label_roi_mask = [1,4] +label_roi_mask = [1,3,4] roi_patch_margin = 5 [network] net_type = MSNet net_name = MSNet_EN32sg downsample_twice = False -class_num = 2 +class_num = 3 [training] learning_rate = 1e-3 decay = 1e-7 -maximal_iteration = 20000 +maximal_iteration = 5000 snapshot_iteration = 5000 -start_iteration = 0 +start_iteration = 1 test_iteration = 100 test_step = 10 -model_pre_trained = +model_pre_trained = model/msnet_en32sg_init model_save_prefix = model/msnet_en32sg \ No newline at end of file diff --git a/config/train_names.txt b/config/train_names.txt new file mode 100644 index 0000000..d80eba0 --- /dev/null +++ b/config/train_names.txt @@ -0,0 +1,224 @@ +HGG_brats_tcia_pat399_0369 +HGG_brats_tcia_pat448_0001 +HGG_brats_tcia_pat396_0294 +HGG_brats_tcia_pat335_0001 +HGG_brats_tcia_pat208_0001 +HGG_brats_tcia_pat230_0511 +HGG_brats_tcia_pat309_0243 +HGG_brats_tcia_pat242_0001 +HGG_brats_tcia_pat190_0001 +HGG_brats_tcia_pat290_0669 +HGG_brats_2013_pat0011_1 +HGG_brats_tcia_pat171_0387 +HGG_brats_tcia_pat439_0333 +HGG_brats_tcia_pat217_0001 +HGG_brats_2013_pat0015_1 +HGG_brats_tcia_pat290_0001 +LGG_brats_tcia_pat420_0001 +HGG_brats_tcia_pat260_0244 +HGG_brats_tcia_pat463_0001 +HGG_brats_tcia_pat153_0002 +HGG_brats_tcia_pat343_0001 +HGG_brats_tcia_pat260_0317 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LGG_brats_tcia_pat325_0001 LGG_brats_tcia_pat330_0001 LGG_brats_tcia_pat346_0001 LGG_brats_tcia_pat351_0001 LGG_brats_tcia_pat354_0001 LGG_brats_tcia_pat387_0001 LGG_brats_tcia_pat393_0001 LGG_brats_tcia_pat402_0001 LGG_brats_tcia_pat408_0001 LGG_brats_tcia_pat410_0001 LGG_brats_tcia_pat413_0001 LGG_brats_tcia_pat420_0001 LGG_brats_tcia_pat428_0001 LGG_brats_tcia_pat442_0001 LGG_brats_tcia_pat449_0001 LGG_brats_tcia_pat451_0001 LGG_brats_tcia_pat462_0001 LGG_brats_tcia_pat466_0001 LGG_brats_tcia_pat470_0001 LGG_brats_tcia_pat480_0001 LGG_brats_tcia_pat483_0001 LGG_brats_tcia_pat490_0001 LGG_brats_tcia_pat493_0001 \ No newline at end of file diff --git a/config/train_tc_ax.txt b/config/train_tc_ax.txt index c86f2dc..74ee70a 100755 --- a/config/train_tc_ax.txt +++ b/config/train_tc_ax.txt @@ -1,15 +1,17 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all_lggx3.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 1, 0, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 0, 1, 1] batch_slice_direction = axial train_with_roi_patch = True -label_roi_mask = [1,2,4] +label_roi_mask = [1,2,3,4] roi_patch_margin = 5 [network] diff --git a/config/train_tc_cr.txt b/config/train_tc_cr.txt index b5c0834..55782b4 100755 --- a/config/train_tc_cr.txt +++ b/config/train_tc_cr.txt @@ -1,15 +1,17 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] -data_names = config/train_names_all_lggx3.txt +data_root = [/home/guotwang/data/brats_docker_data/pre_process] +data_names = config/train_names_all_lggx3.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 1, 0, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 0, 1, 1] batch_slice_direction = coronal train_with_roi_patch = True -label_roi_mask = [1,2,4] +label_roi_mask = [1,2,3,4] roi_patch_margin = 5 [network] @@ -21,10 +23,10 @@ class_num = 2 [training] learning_rate = 1e-3 decay = 1e-7 -maximal_iteration = 20000 +maximal_iteration = 5000 snapshot_iteration = 5000 -start_iteration = 0 +start_iteration = 1 test_iteration = 100 test_step = 10 -model_pre_trained = +model_pre_trained = model/msnet_tc32cr_init model_save_prefix = model/msnet_tc32cr \ No newline at end of file diff --git a/config/train_tc_sg.txt b/config/train_tc_sg.txt index 7485567..5e5b3eb 100755 --- a/config/train_tc_sg.txt +++ b/config/train_tc_sg.txt @@ -1,15 +1,17 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] -data_names = config/train_names_all_lggx3.txt +data_root = [/home/guotwang/data/brats_docker_data/pre_process] +data_names = config/train_names_all_lggx3.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 96, 96, 4] label_shape = [11, 96, 96, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 1, 0, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 0, 1, 1] batch_slice_direction = sagittal train_with_roi_patch = True -label_roi_mask = [1,2,4] +label_roi_mask = [1,2,3,4] roi_patch_margin = 5 [network] @@ -21,10 +23,10 @@ class_num = 2 [training] learning_rate = 1e-3 decay = 1e-7 -maximal_iteration = 20000 +maximal_iteration = 5000 snapshot_iteration = 5000 -start_iteration = 0 +start_iteration = 1 test_iteration = 100 test_step = 10 -model_pre_trained = +model_pre_trained = model/msnet_tc32sg_init model_save_prefix = model/msnet_tc32sg \ No newline at end of file diff --git a/config/train_wt_ax.txt b/config/train_wt_ax.txt index dccfa42..0415f54 100755 --- a/config/train_wt_ax.txt +++ b/config/train_wt_ax.txt @@ -1,12 +1,14 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 144, 144, 4] label_shape = [11, 144, 144, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 1, 1, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 1, 1, 1] batch_slice_direction = axial train_with_roi_patch = False label_roi_mask = diff --git a/config/train_wt_cr.txt b/config/train_wt_cr.txt index b4c17ae..22ef56c 100755 --- a/config/train_wt_cr.txt +++ b/config/train_wt_cr.txt @@ -1,12 +1,14 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 144, 144, 4] label_shape = [11, 144, 144, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 1, 1, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 1, 1, 1] batch_slice_direction = coronal train_with_roi_patch = False label_roi_mask = @@ -21,10 +23,10 @@ class_num = 2 [training] learning_rate = 1e-3 decay = 1e-7 -maximal_iteration = 20000 -snapshot_iteration = 5000 -start_iteration = 0 +maximal_iteration = 5000 +snapshot_iteration = 1000 +start_iteration = 1 test_iteration = 100 test_step = 10 -model_pre_trained = -model_save_prefix = model/msnet_wt32cr \ No newline at end of file +model_pre_trained = model/msnet_wt32cr_init +model_save_prefix = model/msnet_wt32cr diff --git a/config/train_wt_sg.txt b/config/train_wt_sg.txt index 9e6bd59..2970c8e 100755 --- a/config/train_wt_sg.txt +++ b/config/train_wt_sg.txt @@ -1,12 +1,14 @@ [data] -data_root = [data/Brats17TrainingData_crop_renamed] +data_root = [/home/guotwang/data/brats_docker_data/pre_process] data_names = config/train_names_all.txt +modality_postfix = [Flair, T1, T1c, T2] +label_postfix = OT with_ground_truth = True batch_size = 5 data_shape = [19, 144, 144, 4] label_shape = [11, 144, 144, 1] -label_convert_source = [0, 1, 2, 4] -label_convert_target = [0, 1, 1, 1] +label_convert_source = [0, 1, 2, 3, 4] +label_convert_target = [0, 1, 1, 1, 1] batch_slice_direction = sagittal train_with_roi_patch = False label_roi_mask = @@ -21,10 +23,10 @@ class_num = 2 [training] learning_rate = 1e-3 decay = 1e-7 -maximal_iteration = 20000 +maximal_iteration = 5000 snapshot_iteration = 5000 -start_iteration = 0 +start_iteration = 1 test_iteration = 100 test_step = 10 -model_pre_trained = +model_pre_trained = model/msnet_wt32sg_init model_save_prefix = model/msnet_wt32sg \ No newline at end of file diff --git a/convert_brats_image.py b/convert_brats_image.py new file mode 100644 index 0000000..26b7e27 --- /dev/null +++ b/convert_brats_image.py @@ -0,0 +1,38 @@ +# -*- coding: utf-8 -*- +from __future__ import absolute_import, print_function +import os +import numpy as np +import SimpleITK as sitk +from util.parse_config import parse_config + +def convert_brats15_data(input_folder, output_folder, modalities): + """ + Copy the brats dataset to a single folder, and convert .mha files into .nii.gz files + inputs: + input_folder: the root folder of brats data, e.g. */BRATS2015_Training + output_folder: the folder where the converted files will be writen + modalities: modalities of files, e.g., ['Flair', 'T1c', 'T1', 'OT'] + """ + sub_folders = ['HGG', 'LGG'] + if(not os.path.isdir(output_folder)): + os.mkdir(output_folder) + for sub_folder in sub_folders: + sub_dir = input_folder + '/' + sub_folder + patients = os.listdir(sub_dir) + for patient in patients: + if 'brats' in patient: + patient_dir = sub_dir + '/' + patient + scan_dirs = os.listdir(patient_dir) + for mod in modalities: + for scan_dir in scan_dirs: + if mod + '.' in scan_dir: + input_name = patient_dir + '/' + scan_dir + '/' + scan_dir + ".mha" + img = sitk.ReadImage(input_name) + save_name = "{0:}/{1:}_{2:}_{3:}.nii.gz".format(output_folder, sub_folder, patient, mod) + sitk.WriteImage(img, save_name) + +if __name__ == "__main__": + brats15_data_root = "/mnt/shared/guotai/data/BRATS2015_Training" + data_save_root = "/home/guotai/data/brats_docker_data/origin" + modalities = ['Flair', 'T1c', 'T1', 'T2', 'OT'] + convert_brats15_data(brats15_data_root, data_save_root, modalities) diff --git a/evaluation.py b/evaluation.py index ee11daa..ca3e6b3 100644 --- a/evaluation.py +++ b/evaluation.py @@ -12,7 +12,7 @@ def dice_of_brats_data_set(s_folder, g_folder, patient_names_file, type_idx): dice_all_data = [] for i in range(len(patient_names)): s_name = os.path.join(s_folder, patient_names[i] + '.nii.gz') - g_name = os.path.join(g_folder, patient_names[i] + '_seg.nii.gz') + g_name = os.path.join(g_folder, patient_names[i] + '.nii.gz') s_volume = load_nifty_volume_as_array(s_name) g_volume = load_nifty_volume_as_array(g_name) dice_one_volume = [] @@ -25,16 +25,16 @@ def dice_of_brats_data_set(s_folder, g_folder, patient_names_file, type_idx): temp_dice = binary_dice3d(s_volume > 0, g_volume > 0) dice_one_volume = [temp_dice] else: - for label in [1, 2, 4]: # dice of each class + for label in [1, 2, 3, 4]: # dice of each class temp_dice = binary_dice3d(s_volume == label, g_volume == label) dice_one_volume.append(temp_dice) dice_all_data.append(dice_one_volume) return dice_all_data if __name__ == '__main__': - s_folder = 'results' - g_folder = 'data/Brats17TrainingData_crop_renamed' - patient_names_file = 'config/test_names_example.txt' + s_folder = 'result' + g_folder = '/home/guotai/data/brats_docker_data/pre_process' + patient_names_file = 'config_part/test_names.txt' test_types = ['whole','core', 'all'] for type_idx in range(3): dice = dice_of_brats_data_set(s_folder, g_folder, patient_names_file, type_idx) @@ -47,7 +47,7 @@ def dice_of_brats_data_set(s_folder, g_folder, patient_names_file, type_idx): np.savetxt(s_folder + '/dice_{0:}_std.txt'.format(test_type), dice_std) print('tissue type', test_type) if(test_type == 'all'): - print('tissue label', [1, 2, 4]) + print('tissue label', [1, 2, 3, 4]) print('dice mean ', dice_mean) print('dice std ', dice_std) diff --git a/model/checkpoint b/model/checkpoint new file mode 100644 index 0000000..1e8947c --- /dev/null +++ b/model/checkpoint @@ -0,0 +1,6 @@ +model_checkpoint_path: "msnet_wt32cr_5000.ckpt" +all_model_checkpoint_paths: "msnet_wt32cr_1000.ckpt" +all_model_checkpoint_paths: "msnet_wt32cr_2000.ckpt" +all_model_checkpoint_paths: "msnet_wt32cr_3000.ckpt" +all_model_checkpoint_paths: "msnet_wt32cr_4000.ckpt" +all_model_checkpoint_paths: "msnet_wt32cr_5000.ckpt" diff --git a/model/msnet_en32_20000.ckpt.data-00000-of-00001 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