📄 Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation ($C^2SDG$ )
We use the public available RIGA+ dataset for our experiments. You should download the dataset and unzip it.
cd CCSDG # Python Preparation virtualenv .env --python=3 source .env/bin/activate # Install PyTorch, compiling PyTorch on your own workstation is suggested but not needed. # Follow the instructions on https://pytorch.org/get-started/locally/ pip install torch torchvision torchaudio # or other command to match your CUDA version # Install CCSDG pip install -e .# Path Preparation export OUTPUT_FOLDER="YOUR OUTPUT FOLDER" export RIGAPLUS_DATASET_FOLDER="RIGA+ DATASET FOLDER" # BinRushed as source domain ccsdg_train --model unet_ccsdg --gpu 0 --tag source_BinRushed \ --log_folder $OUTPUT_FOLDER \ --batch_size 8 \ --initial_lr 0.01 \ -r $RIGAPLUS_DATASET_FOLDER \ --tr_csv $RIGAPLUS_DATASET_FOLDER/BinRushed.csv \ --ts_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base1.csv \ $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base2.csv \ $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base3.csv # Magrabia as source domain ccsdg_train --model unet_ccsdg --gpu 0 --tag source_Magrabia \ --log_folder $OUTPUT_FOLDER \ --batch_size 8 \ --initial_lr 0.01 \ -r $RIGAPLUS_DATASET_FOLDER \ --tr_csv $RIGAPLUS_DATASET_FOLDER/Magrabia.csv \ --ts_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base1.csv \ $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base2.csv \ $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base3.csvIf you find this repo useful for your research, please consider citing the paper as follows:
@inproceedings{hu2023devil, title={Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation}, author={Shishuai Hu and Zehui Liao and Yong Xia}, booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention}, year={2023}, organization={Springer} }