From 0d2d5a2c22a594852e5e0bce6ded046751c42bc2 Mon Sep 17 00:00:00 2001 From: heyufan1995 Date: Thu, 27 Jun 2024 11:27:54 -0400 Subject: [PATCH] Remove bone lesion --- configs/train/hyper_parameters_stage1.yaml | 2 +- configs/train/hyper_parameters_stage2.yaml | 4 ++-- configs/train/hyper_parameters_stage3.yaml | 2 +- configs/train/hyper_parameters_stage4.yaml | 2 +- scripts/utils/sample_utils.py | 1 + 5 files changed, 6 insertions(+), 5 deletions(-) diff --git a/configs/train/hyper_parameters_stage1.yaml b/configs/train/hyper_parameters_stage1.yaml index 896b7be..1c4e0a0 100644 --- a/configs/train/hyper_parameters_stage1.yaml +++ b/configs/train/hyper_parameters_stage1.yaml @@ -44,7 +44,7 @@ skip_iter_prob: 0 train_datasets: [CTPelvic1K-CLINIC, AbdomenCT-1K, AeroPath, AMOS22, BTCV-Abdomen, BTCV-Cervix, CT-ORG, FLARE22, Multi-organ-Abdominal-CT-btcv, Multi-organ-Abdominal-CT-tcia, Pancreas-CT, Task03, Task06, Task07, - Task08, Task09, Task10, VerSe, Bone-NIH, CRLM-CT, TotalSegmentatorV2, NLST, LIDC, StonyBrook-CT, TCIA_Colon, Covid19] + Task08, Task09, Task10, VerSe, CRLM-CT, TotalSegmentatorV2, NLST, LIDC, StonyBrook-CT, TCIA_Colon, Covid19] val_datasets: [TotalSegmentatorV2] transforms_train: _target_: Compose diff --git a/configs/train/hyper_parameters_stage2.yaml b/configs/train/hyper_parameters_stage2.yaml index 1da945f..abd566b 100644 --- a/configs/train/hyper_parameters_stage2.yaml +++ b/configs/train/hyper_parameters_stage2.yaml @@ -42,9 +42,9 @@ resample_to_spacing: [1.5, 1.5, 1.5] skip_iter_prob: 0 train_datasets: [CTPelvic1K-CLINIC, AbdomenCT-1K, AeroPath, AMOS22, BTCV-Abdomen, BTCV-Cervix, CT-ORG, FLARE22, Multi-organ-Abdominal-CT-btcv, Multi-organ-Abdominal-CT-tcia, - Pancreas-CT, Task03, Task06, Task07, Task08, Task09, Task10, VerSe, Bone-NIH, CRLM-CT, + Pancreas-CT, Task03, Task06, Task07, Task08, Task09, Task10, VerSe, CRLM-CT, TotalSegmentatorV2] -val_datasets: ['CRLM-CT', 'AeroPath', 'Task03','Task06','Task07','Task08','Task10','Bone-NIH'] +val_datasets: ['CRLM-CT', 'AeroPath', 'Task03','Task06','Task07','Task08','Task10'] transforms_train: _target_: Compose transforms: diff --git a/configs/train/hyper_parameters_stage3.yaml b/configs/train/hyper_parameters_stage3.yaml index db785b6..b7d7e69 100644 --- a/configs/train/hyper_parameters_stage3.yaml +++ b/configs/train/hyper_parameters_stage3.yaml @@ -43,7 +43,7 @@ resample_to_spacing: [1.5, 1.5, 1.5] skip_iter_prob: 1 train_datasets: [CTPelvic1K-CLINIC, AbdomenCT-1K, AeroPath, AMOS22, BTCV-Abdomen, BTCV-Cervix, CT-ORG, FLARE22, Multi-organ-Abdominal-CT-btcv, Multi-organ-Abdominal-CT-tcia, - Pancreas-CT, Task03, Task06, Task07, Task08, Task09, Task10, VerSe, Bone-NIH, CRLM-CT, + Pancreas-CT, Task03, Task06, Task07, Task08, Task09, Task10, VerSe, CRLM-CT, TotalSegmentatorV2, NLST, LIDC, StonyBrook-CT, TCIA_Colon] val_datasets: ['TotalSegmentatorV2'] transforms_train: diff --git a/configs/train/hyper_parameters_stage4.yaml b/configs/train/hyper_parameters_stage4.yaml index d6c9892..1b8a127 100644 --- a/configs/train/hyper_parameters_stage4.yaml +++ b/configs/train/hyper_parameters_stage4.yaml @@ -43,7 +43,7 @@ resample_to_spacing: [1.5, 1.5, 1.5] skip_iter_prob: 1 train_datasets: [CTPelvic1K-CLINIC, AbdomenCT-1K, AeroPath, AMOS22, BTCV-Abdomen, BTCV-Cervix, CT-ORG, FLARE22, Multi-organ-Abdominal-CT-btcv, Multi-organ-Abdominal-CT-tcia, - Pancreas-CT, Task03, Task06, Task07, Task08, Task09, Task10, VerSe, Bone-NIH, CRLM-CT, + Pancreas-CT, Task03, Task06, Task07, Task08, Task09, Task10, VerSe, CRLM-CT, TotalSegmentatorV2] val_datasets: ['CRLM-CT', 'AeroPath', 'Task03','Task06','Task07','Task08','Task10','Bone-NIH'] transforms_train: diff --git a/scripts/utils/sample_utils.py b/scripts/utils/sample_utils.py index a676957..24973f0 100644 --- a/scripts/utils/sample_utils.py +++ b/scripts/utils/sample_utils.py @@ -289,6 +289,7 @@ def organ_add(self, id, Np=1, Nn=0): self.label[self.label == id] = id + self.map_shift self.shifted[id] = id + self.map_shift self.read_only_id.append(id + self.map_shift) + print("organ add") return _point, _point_label return self.regular(id, Np, Nn)