📄 Domain Specific Convolution and High Frequency Reconstruction based Unsupervised Domain Adaptation for Medical Image Segmentation (DoCR)
The dataset used in this study (RIGA+) can be downloaded from Zenodo.
You should download the dataset and unzip it.
cd DoCR
# 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 # or other command to match your CUDA version
# Install DoCR
pip install -e .# Path Preparation
export OUTPUT_FOLDER="YOUR OUTPUT FOLDER" # cannot be ended with '/'
export RIGAPLUS_DATASET_FOLDER="RIGA+ DATASET FOLDER" # cannot be ended with '/'
# Target Domain - Base 1
DoCR_train --model DoCR --gpu 0 --tag Base1 \
--log_folder $OUTPUT_FOLDER \
--root $RIGAPLUS_DATASET_FOLDER \
--tr_csv $RIGAPLUS_DATASET_FOLDER/BinRushed_train.csv \
$RIGAPLUS_DATASET_FOLDER/BinRushed_test.csv \
$RIGAPLUS_DATASET_FOLDER/Magrabia_train.csv \
$RIGAPLUS_DATASET_FOLDER/Magrabia_test.csv \
--tu_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base1_unlabeled.csv \
--ts_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base1_test.csv
# Target Domain - Base 2
DoCR_train --model DoCR --gpu 0 --tag Base2 \
--log_folder $OUTPUT_FOLDER \
--root $RIGAPLUS_DATASET_FOLDER \
--tr_csv $RIGAPLUS_DATASET_FOLDER/BinRushed_train.csv \
$RIGAPLUS_DATASET_FOLDER/BinRushed_test.csv \
$RIGAPLUS_DATASET_FOLDER/Magrabia_train.csv \
$RIGAPLUS_DATASET_FOLDER/Magrabia_test.csv \
--tu_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base2_unlabeled.csv \
--ts_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base2_test.csv
# Target Domain - Base 3
DoCR_train --model DoCR --gpu 0 --tag Base3 \
--log_folder $OUTPUT_FOLDER \
--root $RIGAPLUS_DATASET_FOLDER \
--tr_csv $RIGAPLUS_DATASET_FOLDER/BinRushed_train.csv \
$RIGAPLUS_DATASET_FOLDER/BinRushed_test.csv \
$RIGAPLUS_DATASET_FOLDER/Magrabia_train.csv \
$RIGAPLUS_DATASET_FOLDER/Magrabia_test.csv \
--tu_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base3_unlabeled.csv \
--ts_csv $RIGAPLUS_DATASET_FOLDER/MESSIDOR_Base3_test.csv If you find this repo useful for your research, please consider citing the paper as follows:
@inproceedings{hu2022domain,
title={Domain Specific Convolution and High Frequency Reconstruction based Unsupervised Domain Adaptation 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={2022},
organization={Springer}
}
- The code of Fourier Transform is adopted from FDA.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent