12 February 2011 Automatic segmentation of intravascular optical coherence tomography images for facilitating quantitative diagnosis of atherosclerosis
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Proceedings Volume 7889, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XV; 78890N (2011); doi: 10.1117/12.876003
Event: SPIE BiOS, 2011, San Francisco, California, United States
Abstract
Quantitative diagnosis of atherosclerosis can be facilitated by automatic segmentation of intravascular Optical Coherence Tomography (OCT) images. We report an automatic method of lumen and calcified plaque segmentation for commercial intravascular OCT systems. Lumen segmentation is based on a dynamic programming scheme. Calcified plaque is localized by edge detection and finely traced using an active contour model. The proposed methods yield promising results when applied to clinical images as validated by manual tracing. Lumen segmentation is useful for estimating the coronary artery stenosis and guiding stent implantation. Calcified plaque segmentation can be used to estimate the distribution of superficial calcification and inform strategies for coronary stenting.
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Zhao Wang, Hiroyuki Kyono, Hiram G. Bezerra, David L. Wilson, Marco A. Costa, Andrew M. Rollins, "Automatic segmentation of intravascular optical coherence tomography images for facilitating quantitative diagnosis of atherosclerosis", Proc. SPIE 7889, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XV, 78890N (12 February 2011); doi: 10.1117/12.876003; https://doi.org/10.1117/12.876003
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KEYWORDS
Image segmentation

Optical coherence tomography

Arteries

Computer programming

Binary data

Calcium

Databases

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