Kuse, Manohar, Wang, Yi-Fang, Kalasannavar, V, Khan, Michael and Rajpoot, Nasir M. (Nasir Mahmood) (2012) Local isotropic phase symmetry measure for detection of beta cells and lymphocytes. Journal of Pathology Informatics, Vol.2 (No.2). doi:10.4103/2153-3539.92028

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Abstract

Diabetes can be associated with a reduction in functional β cell mass, which must be restored if the disease is to be cured or progress is to be arrested. To study the cell count, it is also necessary to determine the number of nuclei within the insulin stained area. It can take a single experimentalist several months to complete a single study of this kind, results of which may still be quite subjective. In this paper, we propose a framework based on a novel measure of local symmetry for detection of cells. The local isotropic phase symmetry measure (LIPSyM) is designed to give high values at or near the cell centers. We demonstrate the effectiveness of our algorithm for detection of two types of specific cells in histology images, cells in mouse pancreatic sections and lymphocytes in human breast tissue. Experimental results for these two problems show that our algorithm performs better than human experts for the former problem, and outperforms the best reported results for the latter.

Item Type:	Journal Article
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Library of Congress Subject Headings (LCSH):	Pancreatic beta cells -- Counting, Cell nuclei -- Counting, Cytology -- Technique
Journal or Publication Title:	Journal of Pathology Informatics
Publisher:	Medknow Publications and Media Pvt. Ltd.
ISSN:	2229-5089
Official Date:	19 January 2012
Dates:	Date Event 19 January 2012 Published
Volume:	Vol.2
Number:	No.2
DOI:	10.4103/2153-3539.92028
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Funder:	University of Warwick. Dept. of Computer Science

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