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Proceedings Paper

Automatic identification of origins of left and right coronary arteries in CT angiography for coronary arterial tree tracking and plaque detection
Author(s): Chuan Zhou; Heang-Ping Chan; Aamer Chightai; Jun Wei; Lubomir M. Hadjiiski; Prachi Agarwal; Jean W. Kuriakose; Ella A. Kazerooni
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Paper Abstract

Automatic tracking and segmentation of the coronary arterial tree is the basic step for computer-aided analysis of coronary disease. The goal of this study is to develop an automated method to identify the origins of the left coronary artery (LCA) and right coronary artery (RCA) as the seed points for the tracking of the coronary arterial trees. The heart region and the contrast-filled structures in the heart region are first extracted using morphological operations and EM estimation. To identify the ascending aorta, we developed a new multiscale aorta search method (MAS) method in which the aorta is identified based on a-priori knowledge of its circular shape. Because the shape of the ascending aorta in the cCTA axial view is roughly a circle but its size can vary over a wide range for different patients, multiscale circularshape priors are used to search for the best matching circular object in each CT slice, guided by the Hausdorff distance (HD) as the matching indicator. The location of the aorta is identified by finding the minimum HD in the heart region over the set of multiscale circular priors. An adaptive region growing method is then used to extend the above initially identified aorta down to the aortic valves. The origins at the aortic sinus are finally identified by a morphological gray level top-hat operation applied to the region-grown aorta with morphological structuring element designed for coronary arteries. For the 40 test cases, the aorta was correctly identified in 38 cases (95%). The aorta can be grown to the aortic root in 36 cases, and 36 LCA origins and 34 RCA origins can be identified within 10 mm of the locations marked by radiologists.

Paper Details

Date Published: 29 March 2013
PDF: 7 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86703L (29 March 2013); doi: 10.1117/12.2008046
Show Author Affiliations
Chuan Zhou, Univ. of Michigan Health System (United States)
Heang-Ping Chan, Univ. of Michigan Health System (United States)
Aamer Chightai, Univ. of Michigan Health System (United States)
Jun Wei, Univ. of Michigan Health System (United States)
Lubomir M. Hadjiiski, Univ. of Michigan Health System (United States)
Prachi Agarwal, Univ. of Michigan Health System (United States)
Jean W. Kuriakose, Univ. of Michigan Health System (United States)
Ella A. Kazerooni, Univ. of Michigan Health System (United States)


Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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