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Proceedings Paper

A comparison of blood vessel features and local binary patterns for colorectal polyp classification
Author(s): Sebastian Gross; Thomas Stehle; Alexander Behrens; Roland Auer; Til Aach; Ron Winograd; Christian Trautwein; Jens Tischendorf
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Paper Abstract

Colorectal cancer is the third leading cause of cancer deaths in the United States of America for both women and men. By means of early detection, the five year survival rate can be up to 90%. Polyps can to be grouped into three different classes: hyperplastic, adenomatous, and carcinomatous polyps. Hyperplastic polyps are benign and are not likely to develop into cancer. Adenomas, on the other hand, are known to grow into cancer (adenoma-carcinoma sequence). Carcinomas are fully developed cancers and can be easily distinguished from adenomas and hyperplastic polyps. A recent narrow band imaging (NBI) study by Tischendorf et al. has shown that hyperplastic polyps and adenomas can be discriminated by their blood vessel structure. We designed a computer-aided system for the differentiation between hyperplastic and adenomatous polyps. Our development aim is to provide the medical practitioner with an additional objective interpretation of the available image data as well as a confidence measure for the classification. We propose classification features calculated on the basis of the extracted blood vessel structure. We use the combined length of the detected blood vessels, the average perimeter of the vessels and their average gray level value. We achieve a successful classification rate of more than 90% on 102 polyps from our polyp data base. The classification results based on these features are compared to the results of Local Binary Patterns (LBP). The results indicate that the implemented features are superior to LBP.

Paper Details

Date Published: 28 February 2009
PDF: 8 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72602Q (28 February 2009); doi: 10.1117/12.810996
Show Author Affiliations
Sebastian Gross, RWTH Aachen (Germany)
Univ. Hospital Aachen (Germany)
Thomas Stehle, RWTH Aachen (Germany)
Alexander Behrens, RWTH Aachen (Germany)
Roland Auer, RWTH Aachen (Germany)
Til Aach, RWTH Aachen (Germany)
Ron Winograd, Univ. Hospital Aachen (Germany)
Christian Trautwein, Univ. Hospital Aachen (Germany)
Jens Tischendorf, Univ. Hospital Aachen (Germany)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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