MICCAI 2020 Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network

This repo is the official implementation of Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network

I. Experiment Results:

II. Usage:

Using the train3d.py and predict3d.py to train and test the model on your own dataset, respectively.

The proposed network model RE-Net is defined in the model.py in models folder. It can be easily edited and embed in your own code.

III. Requirements:

• PyTorch = 1.2.0
• tqdm
• SimpleITK
• visdom

IV. Citation：

If our paper or code is helpful to you, please cite our paper. If you have any questions, please feel free to ask me.

@inproceedings{zhang2020cerebrovascular,
  title={Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network},
  author={Zhang, Hao and Xia, Likun and Song, Ran and Yang, Jianlong and Hao, Huaying and Liu, Jiang and Zhao, Yitian},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={66--75},
  year={2020},
  organization={Springer}
}