Automatic polyp detection: A comparative study

Alaa El Khatib, Naoufel Werghi, Hussain Al-Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

In this work we present a performance comparison between a set of different state-of-the-art image descriptors for the automatic detection of polyps in colonoscopy videos. This set includes: Local binary patterns, 2-dimensional Gabor filters, wavelet-based texture, and histogram of oriented gradients. We use these descriptors in conjunction with support vector machine or nearest neighbor classifiers to classify candidate regions, which in turn are selected using the maximally stable extremal regions algorithm. We present performance scores on the ASU-Mayo Clinic polyp database.

Original languageBritish English
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2669-2672
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - 4 Nov 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 25 Aug 201529 Aug 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period25/08/1529/08/15

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