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Hindawi, Computational and Mathematical Methods in Medicine, (2012), p. 1-6, 2012

DOI: 10.1155/2012/549102

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Bayes Clustering and Structural Support Vector Machines for Segmentation of Carotid Artery Plaques in Multicontrast MRI

Journal article published in 2012 by Qiu Guan, Bin Du, Zhongzhao Teng ORCID, Jonathan Gillard, Shengyong Chen ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Accurate segmentation of carotid artery plaque in MR images is not only a key part but also an essential step for in vivo plaque analysis. Due to the indistinct MR images, it is very difficult to implement the automatic segmentation. Two kinds of classification models, that is, Bayes clustering and SSVM, are introduced in this paper to segment the internal lumen wall of carotid artery. The comparative experimental results show the segmentation performance of SSVM is better than Bayes.