@Article{JorgeBernal2012,
author="Jorge Bernal
and F. Javier Sanchez
and Fernando Vilari{\~n}o",
title="Towards Automatic Polyp Detection with a Polyp Appearance Model",
journal="Pattern Recognition",
year="2012",
publisher="Elsevier",
volume="45",
number="9",
pages="3166--3182",
optkeywords="Colonoscopy",
optkeywords="PolypDetection",
optkeywords="RegionSegmentation",
optkeywords="SA-DOVA descriptot",
abstract="This work aims at the 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.",
optnote="MV;SIAI",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1997), last updated on Fri, 14 Mar 2014 15:55:39 +0100",
issn="0031-3203",
doi="10.1016/j.patcog.2012.03.002",
opturl="http://dx.doi.org/10.1016/j.patcog.2012.03.002",
file=":http://refbase.cvc.uab.es/files/BSV2012a.pdf:PDF"
}