3D/2D Registration of Angiograms using Silhouette-based Differentiable Rendering
This addresses registration for clinical brain imaging, but appears incremental as it builds on existing differentiable rendering techniques.
The paper tackled 3D/2D registration of angiograms to analyze brain hemodynamics, using silhouette-based differentiable rendering on anteroposterior and lateral views, with preliminary experiments showing effectiveness on real and synthetic datasets.
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.