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Proceedings Paper

Robust detection of bifurcations for vessel tree tracking
Author(s): Xin Wang; Tobias Heimann; Hans-Peter Meinzer; Ingmar Wegner
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Paper Abstract

Vessel tree tracking is an important and challenging task for many medical applications. This paper presents a novel bifurcation detection algorithm for Bayesian tracking of vessel trees. Based on a cylindrical model, we introduce a bifurcation metric that yields minimal values at potential branching points. This approach avoids searching for bifurcations in every iteration of the tracking process (as proposed by prior works) and is therefore computationally more efficient. We use the same geometric model for the bifurcation metric as for the tracking; no specific bifurcation model is needed. In a preliminary evaluation of our method on 8 CTA datasets of coronary arteries, all side branches and 95.8% of the main branches were detected correctly.

Paper Details

Date Published: 9 March 2011
PDF: 7 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 796327 (9 March 2011); doi: 10.1117/12.878882
Show Author Affiliations
Xin Wang, German Cancer Research Ctr. (Germany)
Tobias Heimann, German Cancer Research Ctr. (Germany)
Hans-Peter Meinzer, German Cancer Research Ctr. (Germany)
Ingmar Wegner, German Cancer Research Ctr. (Germany)


Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers; Bram van Ginneken, Editor(s)

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