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Proceedings Paper

A novel texture descriptor for detection of glandular structures in colon histology images
Author(s): Korsuk Sirinukunwattana; David R.J. Snead; Nasir M. Rajpoot
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Paper Abstract

The first step prior to most analyses on most histopathology images is the detection of area of interest. In this work, we present a superpixel-based approach for glandular structure detection in colon histology images. An image is first segmented into superpixels with the constraint on the presence of glandular boundaries. Texture and color information is then extracted from each superpixel to calculate the probability of that superpixel belonging to glandular regions, resulting in a glandular probability map. In addition, we present a novel texture descriptor derived from a region covariance matrix of scattering coefficients. Our approach shows encouraging results for the detection of glandular structures in colon tissue samples.

Paper Details

Date Published: 19 March 2015
PDF: 9 pages
Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 94200S (19 March 2015); doi: 10.1117/12.2082010
Show Author Affiliations
Korsuk Sirinukunwattana, Qatar Univ. (Qatar)
The Univ. of Warwick (United Kingdom)
David R.J. Snead, Univ. Hospitals Coventry and Warwickshire NHS Trust (United Kingdom)
Nasir M. Rajpoot, Qatar Univ. (Qatar)

Published in SPIE Proceedings Vol. 9420:
Medical Imaging 2015: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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