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INTERACTIVE SEGMENTATION OF MEDICAL IMAGES USING GRABCUTKeywords: Endoscopy , interactive image segmentation , foreground extraction , Convergence of iterative minimization , Gaussian Mixture Model labeling , image editing. Abstract: Medical images do not contain sharp edges. Therefore segmentation of these images is a challenging. In this paper we propose the algorithm for interactive segmentation of endoscopic images using extension of original graph-cut method. In this work a more powerful, iterative version of the optimization is used; the power of the iterative algorithm is used to simplify substantially the user interaction and a robust algorithm for "border matting" has been developed to estimate simultaneously the alpha-matte around an object boundary and the colors of foreground pixels. This method is expected to be successful on a wide variety of images with foreground objects. The proposed algorithm is tested on endoscopic images containing tumors. The results of the proposed algorithm are encouraging.
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