Towards Automatic Polyp Detection with a Polyp Appearance Model

This work aims at automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees...

ver descrição completa

Detalhes bibliográficos
Autores: Bernal del Nozal, Jorge|||0000-0001-8493-9514, Sánchez, F. Javier|||0000-0002-9364-3122, Vilariño, Fernando|||0000-0002-7705-4141
Formato: artículo
Fecha de publicación:2012
País:España
Recursos:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:326628
Acesso em linha:https://ddd.uab.cat/record/326628
https://dx.doi.org/urn:doi:10.1016/j.patcog.2012.03.002
Access Level:acceso abierto
Palavra-chave:Colonoscopy
Polyp detection
Region segmentation
SA-DOVA descriptor
Descrição
Resumo:This work aims at automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside.