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Localisation of luminal epithelium edge in digital histopathology images of IHC stained slides of endometrial biopsies

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Li, Guannan, Sanchez Silva, Victor, Quenby, Siobhan, Patel, Gauranga Jeram and Rajpoot, Nasir M. (2015) Localisation of luminal epithelium edge in digital histopathology images of IHC stained slides of endometrial biopsies. Computerized Medical Imaging and Graphics, 42 . pp. 56-63. doi:10.1016/j.compmedimag.2014.11.007

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Official URL: http://dx.doi.org/10.1016/j.compmedimag.2014.11.00...

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Abstract

Diagnosis of recurrent miscarriage due to abnormally high number of uterine natural killer (uNK) cells has recently been made possible by a protocol devised by Quenby et al. Hum Reprod 2009;24(1):45–54. The diagnosis involves detection and counting of stromal and uNK cell nuclei in endometrial biopsy slides immunohistochemically stained with haematoxylin for staining cell nuclei and CD56 as a marker for the uNK cells. However, manual diagnosis is a laborious process, fraught with subjective errors. In this paper, we present a novel method for detection of uterine natural killer (uNK) cells in the human female uterus lining and localisation of the luminal epithelium edge in endometrial biopsies. Specifically, we employ a local phase symmetry based method to detect stromal cell nuclei and propose an adaptive background removal method that significantly eases the segmentation of uNK cell nuclei regions. We also propose a novel method using alpha shapes for the identification of epithelial cell nuclei and B-Spline curve fitting on identified cell nuclei to localise the luminal epithelium edge. The objective of edge localisation is to avoid cell nuclei near the luminal epithelium edge being counted in the diagnosis process due to their non-relevance to the calculation of stromal to uNK cell ratio that determines the diagnosis of recurrent miscarriages in the end. The resulting algorithm offers a promising potential for computer-assisted diagnosis of recurrent miscarriage due to its high accuracy.

Item Type: Journal Article
Divisions: Faculty of Medicine > Warwick Medical School > Biomedical Sciences > Translational & Experimental Medicine > Reproductive Health ( - until July 2016)
Faculty of Medicine > Warwick Medical School
Journal or Publication Title: Computerized Medical Imaging and Graphics
Publisher: Pergamon
ISSN: 0895-6111
Official Date: June 2015
Dates:
DateEvent
June 2015Published
18 November 2014Available
10 November 2014Accepted
4 April 2014Submitted
Volume: 42
Page Range: pp. 56-63
DOI: 10.1016/j.compmedimag.2014.11.007
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access

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