Polyps Recognition using Fuzzy Trees

Orlando Luis Chuquimia Camacho1, Andrea Pinna, Dray Xavier2, Bertrand Granado3

  • 1UPMC - LIP6
  • 2Unité d'endoscopie digestive, Hôpital Saint-Antoine
  • 3LIP6 UMR 7606, Université Pierre et Marie Curie, CNRS, Paris



Contributed Paper (Poster)


5. Imaging Informatics


09:05 - 09:55 | Thu 16 Feb | Ballroom D | ThRAF

Rapid Fire Session 01: Imaging Informatics


In this article, we present our work on classifier to realize a Wireless Capsule Endoscopy (WCE) including a Smart Vision Chip (SVC). Our classifier is based on fuzzy tree and forest of fuzzy trees. We obtain a sensitivity of 92.80% and a specificity of 91.26% with a false detection rate of 8.74% on a large database, that we have constructed, composed of 18910 images containing 3895 polyps from 20 different video-colonoscopies.

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