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Classification of colorectal polyp regions in optical projection tomography

Classification of colorectal polyp regions in optical projection tomography

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Original languageEnglish
Title of host publicationISBI 2013
Subtitle of host publicationIEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Place of PublicationPiscataway, N.J.
PublisherIEEE
Pages736-739
Number of pages4
ISBN (Print)9781467364560
DOIs
StatePublished - 2013
Event10th International Symposium on Biomedical Imaging: From Nano to Macro - San Francisco, CA., United States

Conference

Conference10th International Symposium on Biomedical Imaging: From Nano to Macro
Abbreviated titleISBI 2013
CountryUnited States
CitySan Francisco, CA.
Period7/04/1311/04/13
Internet address

Abstract

The potential of optical projection tomography (OPT) to enhance colorectal polyp diagnosis is beginning to be explored. This paper presents, to the best of our knowledge, the first study on automatic image analysis of OPT images of colorectal polyps. 3D regions are classified using the bag of visual words framework and support vector machines. Independent subspace analysis is used to learn a domain-specific feature dictionary. This is compared to the use of raw patches (after random projection) and local binary patterns. Classification experiments (across patients) at the patch level and at the region level are presented using a set of 30 expert-annotated OPT images. Results show that accurate classification of 3D OPT image regions is feasible using this approach; regions of low-grade dysplasia and invasive cancer were discriminated with approximately 90% accuracy.

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