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Bayes clustering and structural support vector machines for segmentation of carotid artery plaques in multicontrast MRI.


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Authors

Guan, Qiu 
Du, Bin 
Teng, Zhongzhao 
Chen, Shengyong 

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.

Description

Keywords

Bayes Theorem, Carotid Arteries, Carotid Stenosis, Cluster Analysis, Contrast Media, Humans, Image Enhancement, Magnetic Resonance Imaging, Models, Statistical, Software, Support Vector Machine

Journal Title

Comput Math Methods Med

Conference Name

Journal ISSN

1748-670X
1748-6718

Volume Title

Publisher

Hindawi Limited