Abstract: Atherosclerosis is the leading underlying pathologic process that results in cardiovascular diseases, which represents the main cause of death and disability in the world. The atherosclerotic process is a complex degenerative condition mainly affecting the medium- and large-size arteries, which begins in childhood and may remain unnoticed during decades. The intima-media thickness (IMT) of the common carotid artery (CCA) has emerged as one of the most powerful tool for the evaluation of preclinical atherosclerosis. IMT is measured by means of B-mode ultrasound images, which is a non-invasive and relatively low-cost technique. This paper proposes an effective image segmentation method for the IMT measurement in an automatic way. With this purpose, segmentation technique based on machine learning and statistical pattern recognition to measure IMT from ultrasound CCA images. The pixels are classified by means of support vector machine (SVM) to identify the IMT boundaries. The suggested approach is tested on a set of 60 longitudinal ultrasound images of the CCA by comparing the automatic segmentation with four manual tracings.
Keywords: Automatic Detection, Ultrasound Images, (IMT), Common Carotid Artery, (SVM).
Title: Automatic Detection of Intima-Media Thickness in Ultrasound Images of the Common Carotid Artery Using SVM
Author: D.SASIKALA, M.NARGEESH BANU, B.NANDHINI
International Journal of Electrical and Electronics Research
ISSN 2348-6988 (online)
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