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A stochastic polygons model for glandular structures in colon histology images
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Sirinukunwattana, Korsuk, Snead, David R. J. and Rajpoot, Nasir M. (2015) A stochastic polygons model for glandular structures in colon histology images. IEEE Transactions on Medical Imaging, 34 (11). 2366 -2378. doi:10.1109/TMI.2015.2433900
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WRAP_0070699-cs-070715-sirinukunwattana_tmiinpress2015.pdf - Accepted Version - Requires a PDF viewer. Download (9Mb) | Preview |
Official URL: http://dx.doi.org/10.1109/TMI.2015.2433900
Abstract
In this paper, we present a stochastic model for glandular structures in histology images of tissue slides stained with Hematoxylin and Eosin, choosing colon tissue as an example. The proposed Random Polygons Model (RPM) treats each glandular structure in an image as a polygon made of a random number of vertices, where the vertices represent approximate locations of epithelial nuclei. We formulate the RPM as a Bayesian inference problem by defining a prior for spatial connectivity and arrangement of neighboring epithelial nuclei and a likelihood for the presence of a glandular structure. The inference is made via a Reversible-Jump Markov chain Monte Carlo simulation. To the best of our knowledge, all existing published algorithms for gland segmentation are designed to mainly work on healthy samples, adenomas, and low grade adenocarcinomas. One of them has been demonstrated to work on intermediate grade adenocarcinomas at its best. Our experimental results show that the RPM yields favorable results, both quantitatively and qualitatively, for extraction of glandular structures in histology images of normal human colon tissues as well as benign and cancerous tissues, excluding undifferentiated carcinomas.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QM Human anatomy R Medicine > R Medicine (General) R Medicine > RC Internal medicine T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science > Computer Science | ||||||||
| Library of Congress Subject Headings (LCSH): | Colon (Anatomy), Diagnostic imaging--Digital techniques, Image analysis, Imaging systems in medicine | ||||||||
| Journal or Publication Title: | IEEE Transactions on Medical Imaging | ||||||||
| Publisher: | IEEE | ||||||||
| ISSN: | 0278-0062 | ||||||||
| Official Date: | November 2015 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 29 March 2016 | ||||||||
| Volume: | 34 | ||||||||
| Number: | 11 | ||||||||
| Page Range: | 2366 -2378 | ||||||||
| DOI: | 10.1109/TMI.2015.2433900 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Funder: | Qatar National Research Fund (QNRF), Department of Computer Science, University of Warwick | ||||||||
| Grant number: | NPRP5-1345-1-228 (QNRF) |
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