Angio-Diff: Learning a Self-Supervised Adversarial Diffusion Model for Angiographic Geometry Generation
This repository provides the official PyTorch implementation of our model in the following papers:
Zhifeng Wang, Renjiao Yi, Xin Wen, Chenyang Zhu, Kai Xu, Kunlun He
We could ensure that the code is available in such environment.
- OS : Ubuntu 18.04
- Python >= 3.8
- PyTorch >= 1.13.0
In this paper, we used the XCAD dataset and the ARCADE dataset for training. In the Blood vessel simulation part, we used the RPCA-UNet dataset.
python main.py -p train -c config/train.json
python main.py -p test -c config/test.json