Computer based analysis of ultrasound images for assessing carotid artery plaque risk

This paper presents the design and implementation of a computer based image analysis system, employing pattern recognition methods on ultrasound images, for assessing carotid plaque risk of causing brain infarcts. Sixty-one ultrasound images displaying carotid artery stenosis were selected by an HDI-3000 ATL digital ultrasound system. Thirty-eight textural features were calculated from the carotid plaque's image, 4 from the image histogram, 28 from the cooccurrence matrix, and 10 from the run-length matrix. Two classifiers, the least squares minimum distance (LSMD) and the support vector machines (SVM) were employed for comparison reasons. The proposed image analysis system, employing textural features and the SVM classifier, may be indicative of carotid plaque risk of causing brain infarcts and may be of value to patient management.