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

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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

  1. Dataset
  2. 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).
  3. Training

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

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

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