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We evaluate a new method, called VAMPIRE, for automated definition of a center lumen line in vessels in cardiovascular image data. VAMPIRE is based on detection of vessel-like structures by analyzing first-order and second-order image derivatives combined with a minimal cost path algorithm. The image derivatives are obtained using Canny edge detection and an improved ridge filter for detecting elongated structures. We compared VAMPIRE with an established technique in a multi-observer evaluation study involving 40 tracings in slabbed MIP images of multislice CTA datasets of atherosclerotic carotid arteries. The results show that VAMPIRE, in comparison with the established technique, presents considerably more successful tracings and improved handling of stenosis, calcifications, multiple vessels and nearby bone structures. We conclude that VAMPIRE is highly suitable for automated path definition in vessels in (clinical) cardiovascular image data and we expect to improve VAMPIRE to yield paths that are adequate enough to directly serve as center lumen lines in accordance with standards provided by clinicians.

VAMPIRE: Improved Method for Automated Center Lumen Line Definition in Atherosclerotic Carotid Arteries in CTA Data