This repo is the PyTorch implementation for the paper:
The code is developed using Python 3.8 with PyTorch 1.11.0. All experiments in our paper were conducted on a single NVIDIA A40 GPU with 48G GPU memory.
Install the main packages:
pytorch == 1.11.0
torchvision == 0.12.0
The datasets can be downloaded from the following links:
PS: Please cite the original dataset papers when using these datasets in your publications.
Follow the list files (within the "data" folders) to split the datasets
python train_stycona.py
python eval.py
If you find this project useful, please consider citing:
@inproceedings{shen2026style,
title = {Style Content Decomposition-based Data Augmentation for Domain Generalizable Medical Image Segmentation},
author = {Shen, Zhiqiang and Cao, Peng and Yang, Jinzhu and Zaiane, Osmar R. and Chen, Zhaolin},
booktitle = {Proceedings of The 9th International Conference on Medical Imaging with Deep Learning},
volume = {315},
pages = {21--35},
year = {2026},
publisher = {PMLR}
}
If you have any questions or suggestions, please feel free to contact me (xxszqyy@gmail.com).
Thanks to the authors for providing the processed data.