Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy\nis currently the ââ?¬Å?gold standardââ?¬Â technique for diagnosis of different pathologies of the intestinal tract. Wireless capsule\nendoscopy (WCE) has been developed in the 1990s as an alternative to videoendoscopy to allow direct examination of the\ngastrointestinal tractwithout any need for sedation.Nevertheless, the systematic postexamination by the specialist of the 50,000 (for\nthe small bowel) to 150,000 images (for the colon) of a complete acquisition usingWCE remains time-consuming and challenging\ndue to the poor quality ofWCE images. In this paper, a semiautomatic segmentation for analysis ofWCE images is proposed. Based\non active contour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that\ngives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are\nshown on different types of real-case examinations, from (multi)polyp(s) segmentation, to radiation enteritis delineation.
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