CoPAS: learning Co-Plane Attention across MRI Sequences for diagnosing twelve types of knee abnormalities: A multi-center retrospective study

Introduction

This is the official repository of

Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities

by Zelin Qiu, Zhuoyao Xie, Yanwen Li, Huangjing Lin, Qiang Ye, Menghong Wang, Shisi Li, Yinghua Zhao, and Hao Chen

Installation Guide:

The code is based on Python 3.8.0

1. Download the repository

git clone https://github.com/zqiuak/CoPAS

2. Go to the main folder and install requested libarary.

cd main
pip install -r requirements.txt

Typically, it will take few minutes to complete the installation.

Run

1. Fill the data path in PathDict.py, the sample is given in the file.
2. Change parameters in Args.py to fit your data.

Run the following command for training:

python run.py

Run the following command for testing:

python run.py --test --weight_path PATH_TO_WEIGHT

Other useful command line arguments:

--epochs: Maximum number of epoches in training.
--batch_size: Batch size.
--lr: Initial learning rate.
--gpu: GPU card number.
--augment: bool, use augmentation or not.

We have prepared sample data for test, click here to download.

If you have any special requests, please send a email to Zelin Qiu (zqiuak@connect.ust.hk).

License & Citation

This project is covered under the Apache 2.0 License.

If you find this work useful, please cite our paper:

@article{qiu2024learning,
  title={Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities},
  author={Qiu, Zelin and Xie, Zhuoyao and Lin, Huangjing and Li, Yanwen and Ye, Qiang and Wang, Menghong and Li, Shisi and Zhao, Yinghua and Chen, Hao},
  journal={Nature Communications},
  volume={15},
  number={1},
  pages={7637},
  year={2024},
  publisher={Nature Publishing Group UK London}
}