English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Coronary angiography is the gold standard imaging technique for studying anddiagnosing coronary artery disease. However, the resulting 2D X-ray projectionslose 3D information and exhibit visual ambiguities. In this work, we aim toestablish dense correspondence in multi-view angiography, serving as afundamental basis for various clinical applications and downstream tasks. Toovercome the challenge of unavailable annotated data, we designed a datasimulation pipeline using 3D Coronary Computed Tomography Angiography (CCTA).We formulated the problem of dense correspondence estimation as a querymatching task over all points of interest in the given views. We establishedpoint-to-point query matching and advanced it to curve-to-curve correspondence,significantly reducing errors by minimizing ambiguity and improving topologicalawareness. The method was evaluated on a set of 1260 image pairs from differentviews across 8 clinically relevant angulation groups, demonstrating compellingresults and indicating the feasibility of establishing dense correspondence inmulti-view angiography.

Towards Establishing Dense Correspondence on Multiview Coronary Angiography: From Point-to-Point to Curve-to-Curve Query Matching