tianyu0207 / CCD

Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]

CCD

This repo contains the Pytorch implementation of our paper:

Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images

Yu Tian, Guansong Pang, Fengbei Liu, Seon Ho Shin, Johan W Verjans, Rajvinder Singh, Gustavo Carneiro.

• Accepted at MICCAI 2021.

Dataset

Please download the Hyper-Kvasir Anomaly Detection Dataset from this link.

Training

The code is build based on the SCAN.

Modify the dataloader (data/lag_loader.py) code for your own medical images, then simply run the following command:

python simclr.py --config_env configs/env.yml --config_exp configs/pretext/simclr_cifar10.yml

Citation

If you find this repo useful for your research, please consider citing our paper:

@inproceedings{tian2021constrained,
  title={Constrained contrastive distribution learning for unsupervised anomaly detection and localisation in medical images},
  author={Tian, Yu and Pang, Guansong and Liu, Fengbei and Chen, Yuanhong and Shin, Seon Ho and Verjans, Johan W and Singh, Rajvinder and Carneiro, Gustavo},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={128--140},
  year={2021},
  organization={Springer}
}

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