Automatic Segmentation of Lumen in Intravascular Ultrasound Images Using Fuzzy Clustering and Active Contours
نویسندگان
چکیده
Intravascular ultrasound (IVUS) imaging constitutes a widely used technique for coronary heart disease diagnosis and management of arterial atherosclerosis. The identification of lumen and media-adventitia boundaries in IVUS images is necessary for an efficient quantitative assessment of atherosclerotic plaques. In this paper, a new automated approach for lumen border detection is proposed. This method is based on fuzzy c-means algorithm and active contours model. First, the fuzzy c-means with spatial constraint algorithm is used to efficiently extract the regions of interest information of the IVUS image. Secondly, a novel level-set active contours algorithm is used to refine the segmentation and detect the lumen boundary. Experimented results achieved on textured IVUS images revealed that the proposed method gave good results. Keywords— Intravascular ulrasound, Lumen detection, Segmentation, Level-sets, Spatial fuzzy clustering
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