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Proceedings Paper

Fully automatic detection and visualization of patient specific coronary supply regions
Author(s): Dominik Fritz; Alexander Wiedemann; Ruediger Dillmann; Michael Scheuering
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Paper Abstract

Coronary territory maps, which associate myocardial regions with the corresponding coronary artery that supply them, are a common visualization technique to assist the physician in the diagnosis of coronary artery disease. However, the commonly used visualization is based on the AHA-17-segment model, which is an empirical population based model. Therefore, it does not necessarily cope with the often highly individual coronary anatomy of a specific patient. In this paper we introduce a novel fully automatic approach to compute the patient individual coronary supply regions in CTA datasets. This approach is divided in three consecutive steps. First, the aorta is fully automatically located in the dataset with a combination of a Hough transform and a cylindrical model matching approach. Having the location of the aorta, a segmentation and skeletonization of the coronary tree is triggered. In the next step, the three main branches (LAD, LCX and RCX) are automatically labeled, based on the knowledge of the pose of the aorta and the left ventricle. In the last step the labeled coronary tree is projected on the left ventricular surface, which can afterward be subdivided into the coronary supply regions, based on a Voronoi transform. The resulting supply regions can be either shown in 3D on the epicardiac surface of the left ventricle, or as a subdivision of a polarmap.

Paper Details

Date Published: 12 March 2008
PDF: 9 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 691602 (12 March 2008); doi: 10.1117/12.769778
Show Author Affiliations
Dominik Fritz, Siemens Medical Solutions (Germany)
Alexander Wiedemann, Univ. of Karlsruhe (Germany)
Ruediger Dillmann, Univ. of Karlsruhe (Germany)
Michael Scheuering, Siemens Medical Solutions (Germany)

Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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