Patcher

Pytorch Implementation for our MICCAI 2022 paper: Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation .

Overview

Installation

Environment

• Tested OS: Linux
• Python >= 3.7

Dependencies:

1. Install PyTorch 1.6.0 with the correct CUDA version.
2. Install the dependencies:

   pip install pytorch_lightning==1.5.2
   pip install mmcv-full==1.2.2 -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html
   pip install -r requirements.txt
   
   

Datasets

Kvasir-SEG is available online. Download, put it under data/ and run:

python pre_process.py 

We will also release the stroke lesion segmentation data soon.

Training

You can try our models on Kvasir-SEG. For example:

python train.py --cfg patchformer_kvasir_moe_2_strct_adam_aug2 --gpu 0,1

Or you can train our models on your customized data, just put them under data/ and follow the same scheme.

Acknowledgment

This repo borrows code from

• SETR
• Another implementation of SETR

Citation

If you find our work useful in your research, please cite our paper:

@article{ou2022patcher,
  title={Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation},
  author={Ou, Yanglan and Yuan, Ye and Huang, Xiaolei and Wong, Stephen TC and Volpi, John and Wang, James Z and Wong, Kelvin},
  journal={arXiv preprint arXiv:2206.01741},
  year={2022}
}