This is the official PyTorch implementation of ContrastPool from the paper "Contrastive Graph Pooling for Explainable Classification of Brain Networks" published in IEEE Transactions on Medical Imaging (TMI) 2024.
Link: Arxiv.
All Preprocessed data used in this paper are published in this paper.
Data splits and configurations are stored in ./data/ and ./configs/. If you want to process your own data, please check the dataloader script ./data/BrainNet.py.
Please check baseline.sh on how to run the project.
If you find this code useful, please consider citing our paper:
@ARTICLE{10508252,
author={Xu, Jiaxing and Bian, Qingtian and Li, Xinhang and Zhang, Aihu and Ke, Yiping and Qiao, Miao and Zhang, Wei and Sim, Wei Khang Jeremy and Gulyás, Balázs},
journal={IEEE Transactions on Medical Imaging},
title={Contrastive Graph Pooling for Explainable Classification of Brain Networks},
year={2024},
volume={},
number={},
pages={1-1},
keywords={Functional magnetic resonance imaging;Feature extraction;Task analysis;Data mining;Alzheimer's disease;Message passing;Brain modeling;Brain Network;Deep Learning for Neuroimaging;fMRI Biomarker;Graph Classification;Graph Neural Network},
doi={10.1109/TMI.2024.3392988}}
If you have any questions, please feel free to reach out at jiaxing003@e.ntu.edu.sg.