# 3D-TransUNet

**Repository Path**: mkhuang/3D-TransUNet

## Basic Information

- **Project Name**: 3D-TransUNet
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-01-19
- **Last Updated**: 2024-01-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README



This is the official repository of our project ["3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers"](https://arxiv.org/abs/2310.07781). 

## 📰 News

We release the code.

## Usage

### Installation

See scripts/install.sh for installation. See [nnUNet](https://github.com/MIC-DKFZ/nnUNet) for self-configuring data preprocessing.

### Train

See scripts/train.sh

### Inference & Eval

See scripts/inference.sh


## Acknowledgements

This work is partially supported by TPU Research Cloud program, Google Cloud Research Credits program, and AWS Cloud Credit for Research program. Thanks for the codebase from [Mask2former](https://github.com/facebookresearch/Mask2Former), [nnUNet](https://github.com/MIC-DKFZ/nnUNet) and [TransUNet](https://github.com/Beckschen/TransUNet)


If you find 3D-TransUNet useful for your research and applications, please cite using this BibTeX:

```
@article{chen2023transunet3d,
  title={3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers},
  author={Chen, Jieneng and Mei, Jieru and Li, Xianhang and Lu, Yongyi and Yu, Qihang and Wei, Qingyue and Luo, Xiangde and Xie, Yutong and Adeli, Ehsan and Wang, Yan and Lungren, Matthew and Xing, Lei and Lu, Le and Yuille, Alan L and Zhou, Yuyin},
  journal={arXiv preprint arXiv:2310.07781},
  year={2023}
}
```