An Accurate and Generalised Approach to Plaque Characterisation in Ultrasound Scan of Atherosclerosis Diseases
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of athermanous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic. Modern medical ultrasound equipment performs real-time high resolution imaging without the use of ionizing radiation. The costeffectiveness and portability of this facility are particularly important in small-scale hospitals, in which the equipment is useful in conducting complex medical imaging in a timely manner. The use of ultrasonic images to analyze the homogeneity of an internal echo is important to physicians in making diagnostic decisions. However, medical ultrasound images contain significant speckles, noises and ultrasound examination is operator dependent owing to experiences of the interpreter. A computer-aided diagnosis (CAD) system will provide a second beneficial opinion and avoid inter-observer variation. Hence CAD has become a major research topic in medical ultrasound imaging and diagnosis. The artificial neural networks and support vector machines (SVMs) models are extensively used in classification for its ability to model the complex system. Various Atherosclerosis ultrasound CAD systems using the neural network and SVM algorithms have been proposed and the results demonstrated that the classification models have their potential effectiveness. So that patient at risk of stroke can be identified.
Authors and Affiliations
A. Selvii, A. Dinesh Kumar, S. Arockya Selphine, N. Famitha Banu
Keywords
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