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

Qiu Guan, Bin Du, Zhongzhao Teng, Jonathan Gillard, Shengyong Chen
2012 Computational and Mathematical Methods in Medicine  
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.
doi:10.1155/2012/549102 pmid:23365619 pmcid:PMC3536030 fatcat:mlnao2bx55d6tky4g53bv5qs7q