Elastic Registration of Geodesic Vascular Graphs

TL;DR

This paper introduces a novel 3D elastic registration method for vascular graphs that aligns complex networks without relying on anatomical priors, enabling improved clinical analysis.

Contribution

It presents an end-to-end registration approach using overconnected geodesic graphs and advanced graph matching, advancing vascular network analysis.

Findings

Successful registration on synthetic and real angiography data

Potential for improved clinical vascular analysis

No anatomical priors needed for alignment

Abstract

Vascular graphs can embed a number of high-level features, from morphological parameters, to functional biomarkers, and represent an invaluable tool for longitudinal and cross-sectional clinical inference. This, however, is only feasible when graphs are co-registered together, allowing coherent multiple comparisons. The robust registration of vascular topologies stands therefore as key enabling technology for group-wise analyses. In this work, we present an end-to-end vascular graph registration approach, that aligns networks with non-linear geometries and topological deformations, by introducing a novel overconnected geodesic vascular graph formulation, and without enforcing any anatomical prior constraint. The 3D elastic graph registration is then performed with state-of-the-art graph matching methods used in computer vision. Promising results of vascular matching are found using graphs from synthetic and real angiographies. Observations and future designs are discussed towards potential clinical applications.