Awesome
CycleMorph
This is an official repository of CycleMorph.
Paper
- CycleMorph: Cycle consistent unsupervised deformable image registration (Medical Image Analysis, Boah Kim et al.) [paper]
- Unsupervised Deformable Image Registration Using Cycle-Consistent CNN (MICCAI 2019, Boah Kim et al.)[paper]
Implementation
A PyTorch implementation of deep-learning-based registration. We implemented this code based on voxelMorph and original cycleGAN code. (*Thanks for voxelMorph.) (*Thanks for Jun-Yan Zhu and Taesung Park, and Tongzhou Wang.)
- Requirements
- OS : Ubuntu
- Python 3.6
- PyTorch 1.4.0
Data
To download the atlas brain and a sample data, visit the Data. The data should be in folder ./data.
Training
- train.py which is handled by scripts/Brain_train.sh
- You can run the code by running ./scripts/Brain_train.sh
- A code for CycleMorph is in models/cycleMorph_model.py.
Testing
- test.py which is handled by scripts/Brain_test.sh
- You can run the code by running ./scripts/Brain_test.sh
Citations
@article{kim2021cyclemorph,
title={CycleMorph: cycle consistent unsupervised deformable image registration},
author={Kim, Boah and Kim, Dong Hwan and Park, Seong Ho and Kim, Jieun and Lee, June-Goo and Ye, Jong Chul},
journal={Medical Image Analysis},
volume={71},
pages={102036},
year={2021},
publisher={Elsevier}
}
@inproceedings{kim2019unsupervised,
title={Unsupervised deformable image registration using cycle-consistent cnn},
author={Kim, Boah and Kim, Jieun and Lee, June-Goo and Kim, Dong Hwan and Park, Seong Ho and Ye, Jong Chul},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={166--174},
year={2019},
organization={Springer}
}