Registration of a 3D mesh derived from MRA, CTA or 3d DSA onto two images of 2D DSA using silhouette-based differentiable rendering.

• Inputs: 3D Mesh + Two DSA images, antero-posterior and lateral
• Outputs: Camera pose Rotation and translation

If you find this code useful for your research, please cite the following paper (to be submitted):

@article{Lee2024,
author = {Taewoong Lee, Sarah Frisken and Nazim Haouchine},
title = {3D/2D Registration of Angiograms using Silhouette-based Differentiable Rendering}
journal={arXiv preprint arXiv:xxxxx},
year = {2024},
}

The pose estimation is based on PyTorch3D differentiable rendering. The visualizer is based on PyVitsa.

• Python 3.9.19
• Pytorch 2.3.1
• Pytorch3D 0.7.7
• CUDA 11.8
• PyVista 0.44.1

We used this dataset of paired 3D/2D DSA images: https://lit.fe.uni-lj.si/en/research/resources/3D-2D-GS-CA/

For a differentiable DSA renderer and 3D/2D registration, check DiffPose by Vivek Gopalakrishnan

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.