AGMN: Association Graph-based Graph Matching Network for Coronary Artery Semantic Labeling on Invasive Coronary Angiograms

Understand

Semantic labeling of coronary arterial segments in invasive coronary angiography (ICA) is important for automated assessment and report generation of coronary artery stenosis in the computer-aided diagnosis of coronary artery disease (CAD).

• Inspired by the training procedure of interventional cardiologists for interpreting the structure of coronary arteries, we propose an association graph-based graph matching network (AGMN) for coronary arterial semantic labeling.
• We first extract the vascular tree from invasive coronary angiography (ICA) and convert it into multiple individual graphs.
• Then, an association graph is constructed from two individual graphs where each vertex represents the relationship between two arterial segments.