Classification of atherosclerotic carotid plaques using gray level morphological analysis on ultrasound images

Abstract

The aim of this study was to investigate the usefulness of gray scale morphological analysis in the assessment of atherosclerotic carotid plagues. Ultrasound images were recorded from 137 asymptomatic and 137 symptomatic plaques (Stroke, Transient Ischaemic Attack -TLA, Amaurosis Fugax-AF). The morphological pattern spectra of gray scale images were computed and two different classifiers named the Probabilistic Neural Network (PNN) and the Support Vector Machine (SVM) were evaluated for classifying these spectra into two classes: asymptomatic or symptomatic. The highest percentage of correct classifications score was 66,8% and was achieved using the SVM classifier. This score is slightly lower than texture analysis carried out on the same data set. © 2006 International Federation for Information Processing.