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

被引：0
|
作者：
Kyriacou, E. [1 ,3 ]
Pattichis, C. S. [1 ]
Pattichis, M. S. [2 ]
Mavrommatis, A. [1 ]
Panagiotou, S. [1 ]
Christodoulou, C. I. [1 ,3 ]
Kakkos, S. [4 ]
Nicolaides, A. [1 ,4 ,5 ]
机构：
[1] Univ Cyprus, Dept Comp Sci, 75 Kallipoleos Str,POB 20578, CY-1678 Nicosia, Cyprus
[2] Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM USA
[3] Cyprus Inst Neurol & Genet, Nicosia, Cyprus
[4] Univ London, Imperial Coll, Fac Med, Dept Vasc Surg, London, England
[5] Vasc Screening & Diagnost Ctr, Nicosia, Cyprus
来源：
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS | 2006年 / 204卷
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D O I：
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中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 -TIA, 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.
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页码：737 / +
页数：2
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