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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...
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Published in: | Pattern recognition 2012-09, Vol.45 (9), p.3166-3182 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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.
► Definition of a general model of polyp appearance. ► Extension on the definition of the depth of valleys image. ► Development of an accurate region segmentation scheme. ► Integrate information from depth of valleys image in the novel SADOVA descriptor. ► Promising results on region-based and frame-based classification. |
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ISSN: | 0031-3203 1873-5142 |
DOI: | 10.1016/j.patcog.2012.03.002 |