• Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning (ISBI-2021)
• • Framwork
  • Installation
  • Data
  • Training and Evaluation
  • Contact

Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning (ISBI-2021)

by Yang Yang, Jiancong Chen, Ruixuan Wang, Ting Ma, Lingwei Wang, Jie Chen, Wei-Shi Zheng, Tong Zhang.

This repo contains the official Pytorch implementation for Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning.

Framwork

@inproceedings{yang2021towards,
  title={Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning},
  author={Yang, Yang and Chen, Jiancong and Wang, Ruixuan and Ma, Ting and Wang, Lingwei and Chen, Jie and Zheng, Wei-Shi and Zhang, Tong},
  booktitle={IEEE International Symposium on Biomedical Imaging},
  pages={1966--1970},
  year={2021},
  organization={IEEE}
}

Installation

• Python 3.8+

• Pytorch 1.10+

• Torchvision 0.11.0

• GPU, such as a 1080Ti

  You can install require modules with following command.

pip install -r requirements.txt

Data

Data is stored in ./data, you can directory download it (~400M).

Training and Evaluation

You can train with following code, which save logs and models to /exp/exp-1.

python train.py -p ./exp/exp-1 -l 10 -s 0.01 -a 0.01 -g 200 -t 0 -i 15 -b 4 -e 120 --debug

Contact

If you have any questions about this paper, welcome to email to zhangt02@pcl.ac.cn