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Journal of Biomedical Optics

Semiautomatic segmentation and quantification of calcified plaques in intracoronary optical coherence tomography images
Author(s): Zhao Wang; Hiroyuki Kyono; Hiram G. Bezerra; Hui Wang; Madhusudhana Gargesha; Chadi Alraies; Chenyang Xu; Joseph M. Schmitt; David L. Wilson; Marco A. Costa; Andrew M. Rollins
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Paper Abstract

Coronary calcified plaque (CP) is both an important marker of atherosclerosis and major determinant of the success of coronary stenting. Intracoronary optical coherence tomography (OCT) with high spatial resolution can provide detailed volumetric characterization of CP. We present a semiautomatic method for segmentation and quantification of CP in OCT images. Following segmentation of the lumen, guide wire, and arterial wall, the CP was localized by edge detection and traced using a combined intensity and gradient-based level-set model. From the segmentation regions, quantification of the depth, area, angle fill fraction, and thickness of the CP was demonstrated. Validation by comparing the automatic results to expert manual segmentation of 106 in vivo images from eight patients showed an accuracy of 78±9%. For a variety of CP measurements, the bias was insignificant (except for depth measurement) and the agreement was adequate when the CP has a clear outer border and no guide-wire overlap. These results suggest that the proposed method can be used for automated CP analysis in OCT, thereby facilitating our understanding of coronary artery calcification in the process of atherosclerosis and helping guide complex interventional strategies in coronary arteries with superficial calcification.

Paper Details

Date Published: 1 November 2010
PDF: 10 pages
J. Biomed. Opt. 15(6) 061711 doi: 10.1117/1.3506212
Published in: Journal of Biomedical Optics Volume 15, Issue 6
Show Author Affiliations
Zhao Wang, Case Western Reserve Univ. (United States)
Hiroyuki Kyono, Univ. Hospitals of Cleveland (United States)
Hiram G. Bezerra, Univ. Hospitals of Cleveland (United States)
Hui Wang, Case Western Reserve Univ. (United States)
Madhusudhana Gargesha, Case Western Reserve Univ. (United States)
Chadi Alraies, Case Western Reserve Univ. (United States)
Chenyang Xu, LightLab Imaging Inc. (United States)
Joseph M. Schmitt, LightLab Imaging Inc. (United States)
David L. Wilson, Case Western Reserve Univ. (United States)
Marco A. Costa, Case Western Reserve Univ. (United States)
Andrew M. Rollins, Case Western Reserve Univ. (United States)


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