Skip to content

lkpengcs/DCDA

Repository files navigation

Unsupervised Domain Adaptation for Cross-Modality Retinal Vessel Segmentation via Disentangling Representation Style Transfer and Collaborative Consistency Learning

Pytorch implementation for our unsupervised domain adaptation framework with application to retinal vessel segmentation. We use style transfer and collaborative consistency learning to train a segmentation model on the target domain.

image

Paper

Please cite our paper if you find the code useful for your research.

@article{peng2022unsupervised,
  title={Unsupervised Domain Adaptation for Cross-Modality Retinal Vessel Segmentation via Disentangling Representation Style Transfer and Collaborative Consistency Learning},
  author={Peng, Linkai and Lin, Li and Cheng, Pujin and Huang, Ziqi and Tang, Xiaoying},
  journal={arXiv preprint},
  url={arXiv:2201.04812},
  year={2022}
}

Example Results

image

Usage

Prerequisite

  • Python 3.7+
  • Pytorch 1.4.0

Acknowledgement

Code adapted from DRIT.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages