Polyps Recognition Using Fuzzy Trees

Orlando Chuquimia 1 Andrea Pinna 1 Xavier Dray 2 Bertrand Granado 1
1 SYEL - Systèmes Electroniques
LIP6 - Laboratoire d'Informatique de Paris 6
2 ASTRE [Cergy-Pontoise]
ETIS - Equipes Traitement de l'Information et Systèmes
Abstract : 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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Orlando Chuquimia, Andrea Pinna, Xavier Dray, Bertrand Granado. Polyps Recognition Using Fuzzy Trees. BHI-2017 International Conference on Biomedical and Health Informatics, Feb 2017, Orlando, FL, United States. pp.9-12, ⟨10.1109/BHI.2017.7897192⟩. ⟨hal-01896834⟩

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