DS-TransUNet

This repository contains the official code of DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation

Requirements

Python==3.7.6
Pytorch==1.8.0 && CUDA 11.1
timm==0.4.5

Experiments

Kvasir-SEG

Dataset
- Downloading training dataset and move it into ./data, which can be found in this download link (Google Drive).
- Downloading testing dataset and move it into ./data , which can be found in this download link (Google Drive).
Testing
- Downloading our trained DS-TransUNet-B from Baidu Pan (dd79), and move it into ./checkpoints.
- run test_kvasir.py
- run criteria.py to get the DICE score, which uses EvaluateSegmentation. Or you can download our result images from Baidu Pan (dd79).
Training
- downloading Swin-T and Swin-B from Swin-Transformer or Baidu Pan (ji2g) to ./checkpoints.
- run train_kvasir.py

Code of other tasks will be comming soon.

Reference

Some of the codes in this repo are borrowed from:

Citation

Please consider citing us if you find this work helpful:

@article{lin2022ds,
  title={DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation},
  author={Lin, Ailiang and Chen, Bingzhi and Xu, Jiayu and Zhang, Zheng and Lu, Guangming and Zhang, David},
  journal={IEEE Transactions on Instrumentation and Measurement},
  year={2022},
  publisher={IEEE}
}

Questions

Please drop an email to tianbaoge24@gmail.com