MCTrans
Multi-Compound Transformer for Accurate Biomedical Image Segmentation
Introduction
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This repository provides code for "Multi-Compound Transformer for Accurate Biomedical Image Segmentation" [paper].
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The MCTrans repository heavily references and uses the packages of MMSegmentation, MMCV, and MONAI. We thank them for their selfless contributions
Highlights
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A comprehensive toolbox for medical image segmentation, including flexible data loading, processing, modular network construction, and more.
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Supports representative and popular medical image segmentation methods, e.g. UNet, UNet++, CENet, AttentionUNet, etc.
Changelog
The first version was released on 2021.7.16.
Model Zoo
Supported backbones:
- [x] VGG
- [x] ResNet
Supported methods:
- [x] UNet
- [x] UNet++
- [x] AttentionUNet
- [x] CENet
- [x] TransUNet
- [x] NonLocalUNet
Installation and Usage
Please see the guidance.md.
Citation
If you find this project useful in your research, please consider cite:
@article{ji2021multi,
title={Multi-Compound Transformer for Accurate Biomedical Image Segmentation},
author={Ji, Yuanfeng and Zhang, Ruimao and Wang, Huijie and Li, Zhen and Wu, Lingyun and Zhang, Shaoting and Luo, Ping},
journal={arXiv preprint arXiv:2106.14385},
year={2021}
}