SOURCE-LINKED INTELLIGENCE
Temporally Consistent Graph Extraction and Matching for Longitudinal Angiographic Images
Recent advances in angiographic imaging have enabled longitudinal visualization of the microvasculature. Image processing pipelines based on vessel graphs are able to resolve subtle temporal changes at the level of individual blood vessels. However, current strategies for graph extraction, refinement, and matching are highly sensitive, with even minuscule differences in the underlying segmentation map resulting in substantially different vessel graphs. These artifacts severely inhibit the ability to accurately match sequential vessel graphs of the same subject over time. To address this proble
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T09:22:44.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.