Abstract:Image segmentation plays a crucial role in many medical imaging applications. The use of the conventional Chan-Vese algorithm for medical image analysis is widespread because of its ability to produce a complete division of the image. However, its drawbacks include over-segmentation and sensitivity to false edges. In this paper, we present a novel algorithm that incorporates k-means clustering and improved Chan-Vese algorithm. The improved Chan-Vese algorithm is based on the similarity between each point and c… Show more
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