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Computer-Assisted Segmentation of Videocapsule Images Using Alpha-Divergence-Based Active Contour In The Framework of Intestinal Pathologies Detection

Leila Meziou 1 Aymeric Histace 2, * Frédéric Precioso 3 Olivier Romain 2 Xavier Dray 4 Bertrand Granado 5 Bogdan Matuszewski 6
* Corresponding author
1 ICI
ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes
2 ASTRE [Cergy-Pontoise]
ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes
3 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe KEIA
Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
4 Unité d'endoscopie
Hôpital Lariboisière, ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes
5 SYEL - Systèmes Electroniques
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy is currently the "gold standard" technique for diagnosis of different pathologies of the intestinal tract. Wireless Capsule Endoscopy (WCE) has been developed in the 1990's as an alternative to videoendoscopy to allow direct examination of the gastrointestinal tract without any need for sedation. Nevertheless, the systematic post-examination by the specialist of the 50,000 (for the small bowel) to 150,000 images (for the colon) of a complete acquisition using WCE remains time-consuming and challenging due to the poor quality of WCE images. In this article, a semiautomatic segmentation for analysis of WCE images is proposed. Based on active contour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that gives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are shown on different types of real-case examinations, from (multi-) polyp(s) segmentation, to radiation enteritis delineation.
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Submitted on : Wednesday, December 3, 2014 - 9:57:16 AM
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Leila Meziou, Aymeric Histace, Frédéric Precioso, Olivier Romain, Xavier Dray, et al.. Computer-Assisted Segmentation of Videocapsule Images Using Alpha-Divergence-Based Active Contour In The Framework of Intestinal Pathologies Detection. International Journal of Biomedical Imaging, Hindawi Publishing Corporation, 2014, 2014, 428583 (10 p.). ⟨10.1155/2014/428583⟩. ⟨hal-01090142⟩

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