Automatic detection of calcified plaque with acoustic shadowing

Abstract

Intravascular ultrasound (IVUS) is one medical imaging technology using invasive ultrasound imaging modality, and has been widely used in the assessment of the extent and severity of the atherosclerosis. Automatic and accurate detection of the shape of the calcified plaque with acoustic shadowing can assist the evaluation and treatment of the pathological changes in the cardiovascular vessels. In this paper, we have developed a method to automatically detect the range of the calcified plaque with acoustic shadowing in IVUS images by combining of the Gaussian mixture model and Markov random field. The results of this study on In-Vivo IVUS images demonstrate that the proposedmethod has great potential for automatically detecting the calcified plaque with acoustic shadowing.