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}
}