Share Email Print

Proceedings Paper

Patient specific coronary territory maps
Author(s): Pascale Beliveau; Randolph Setser; Farida Cheriet; Thomas O'Donnell
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

It is standard practice for physicians to rely on empirical, population based models to define the relationship between regions of left ventricular (LV) myocardium and the coronary arteries which supply them with blood. Physicians use these models to infer the presence and location of disease within the coronary arteries based on the condition of the myocardium within their distribution (which can be established non-invasively using imaging techniques such as ultrasound or magnetic resonance imaging). However, coronary artery anatomy often varies from the assumed model distribution in the individual patient; thus, a non-invasive method to determine the correspondence between coronary artery anatomy and LV myocardium would have immediate clinical impact. This paper introduces an image-based rendering technique for visualizing maps of coronary distribution in a patient-specific approach. From an image volume derived from computed tomography (CT) images, a segmentation of the LV epicardial surface, as well as the paths of the coronary arteries, is obtained. These paths form seed points for a competitive region growing algorithm applied to the surface of the LV. A ray casting procedure in spherical coordinates from the center of the LV is then performed. The cast rays are mapped to a two-dimensional circular based surface forming our coronary distribution map. We applied our technique to a patient with known coronary artery disease and a qualitative evaluation by an expert in coronary cardiac anatomy showed promising results.

Paper Details

Date Published: 29 March 2007
PDF: 10 pages
Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 65111J (29 March 2007); doi: 10.1117/12.711786
Show Author Affiliations
Pascale Beliveau, École Polytechnique Montréal (Canada)
Siemens Corporate Research (United States)
Randolph Setser, Cleveland Clinic Foundation (United States)
Farida Cheriet, École Polytechnique Montréal (Canada)
Thomas O'Donnell, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 6511:
Medical Imaging 2007: Physiology, Function, and Structure from Medical Images
Armando Manduca; Xiaoping P. Hu, Editor(s)

© SPIE. Terms of Use
Back to Top