3D/2D Registration of Angiograms using Silhouette-based Differentiable Rendering

Fuente: arXiv
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Autores principales: Lee, Taewoong, Frisken, Sarah, Haouchine, Nazim
Formato: Preprint
Publicado: 2025
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author Lee, Taewoong
Frisken, Sarah
Haouchine, Nazim
author_facet Lee, Taewoong
Frisken, Sarah
Haouchine, Nazim
contents We present a method for 3D/2D registration of Digital Subtraction Angiography (DSA) images to provide valuable insight into brain hemodynamics and angioarchitecture. Our approach formulates the registration as a pose estimation problem, leveraging both anteroposterior and lateral DSA views and employing differentiable rendering. Preliminary experiments on real and synthetic datasets demonstrate the effectiveness of our method, with both qualitative and quantitative evaluations highlighting its potential for clinical applications. The code is available at https://github.com/taewoonglee17/TwoViewsDSAReg.
format Preprint
id arxiv_https___arxiv_org_abs_2501_14918
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle 3D/2D Registration of Angiograms using Silhouette-based Differentiable Rendering
Lee, Taewoong
Frisken, Sarah
Haouchine, Nazim
Computer Vision and Pattern Recognition
We present a method for 3D/2D registration of Digital Subtraction Angiography (DSA) images to provide valuable insight into brain hemodynamics and angioarchitecture. Our approach formulates the registration as a pose estimation problem, leveraging both anteroposterior and lateral DSA views and employing differentiable rendering. Preliminary experiments on real and synthetic datasets demonstrate the effectiveness of our method, with both qualitative and quantitative evaluations highlighting its potential for clinical applications. The code is available at https://github.com/taewoonglee17/TwoViewsDSAReg.
title 3D/2D Registration of Angiograms using Silhouette-based Differentiable Rendering
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2501.14918