- Cycle-consistent adversarial denoising network for multiphase coronary CT angiography
- Authors: Eunhee Kang, Hyun Jung Koo, Dong Hyun Yang, Joon Bum Seo, and Jong Chul Ye
- published in Medical Physics (2018): [https://doi.org/10.1002/mp.13284]
A PyTorch implementation of cycleGAN for multiphase coronary CT angiography based on original cycleGAN code. [https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix] (*Thanks for Jun-Yan Zhu and Taesung Park, and Tongzhou Wang.)
- Requirements
- OS: The package development version is tested on Windows operating systems with Anaconda.
- Python 3.5.5
- PyTorch 0.3.1.post2
- The whole data used in the paper are private data from ASAN medical center, so only 3 test samples are uploaded.
- CT image files are formated in *.mat.
- Training: train.py which is handled by scripts/train_for_cardiac.sh
- Test: test_for_cardiac.py which is handled by scripts/test_for_cardiac.sh
- Learned network for Paper is uploaded.