Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation(JBHI)

Introduction

Pytorch implementation of the paper "Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation", Accepted by JBHI. In this paper, we present a novel approach, the affinity feature strengthening network (AFN), which jointly models geometry and refines pixel-wise segmentation features using a contrast-insensitive, multiscale affinity approach. AFN outperforms the state-of-the-art methods in terms of both higher accuracy and topological metrics, while also being more robust to various contrast changes.

Citation

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@ARTICLE{10122604,
  author={Shi, Tianyi and Ding, Xiaohuan and Zhou, Wei and Pan, Feng and Yan, Zengqiang and Bai, Xiang and Yang, Xin},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation}, 
  year={2023},
  volume={},
  number={},
  pages={1-12},
  doi={10.1109/JBHI.2023.3274789}}

Prerequisities

• Datasets: [DRIVE], [XCAD]

Usage

1. Training scripts

sh train.sh

2. Evaluation scripts

sh test.sh

Contact

Thanks for your attention! If you have any suggestion or question, you can leave a message here or contact us directly:

• shitianyihust@hust.edu.cn
• dingxiaohuan@hust.edu.cn