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Proceedings Paper

Entropy based quantification of Ki-67 positive cell images and its evaluation by a reader study
Author(s): M. Khalid Khan Niazi; Michael Pennell; Camille Elkins; Jessica Hemminger; Ming Jin; Sean Kirby; Habibe Kurt; Barrie Miller; Elizabeth Plocharczyk; Rachel Roth; Rebecca Ziegler; Arwa Shana’ah; Fred Racke; Gerard Lozanski; Metin N. Gurcan
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Paper Abstract

Presence of Ki-67, a nuclear protein, is typically used to measure cell proliferation. The quantification of the Ki-67 proliferation index is performed visually by the pathologist; however, this is subject to inter- and intra-reader variability. Automated techniques utilizing digital image analysis by computers have emerged. The large variations in specimen preparation, staining, and imaging as well as true biological heterogeneity of tumor tissue often results in variable intensities in Ki-67 stained images. These variations affect the performance of currently developed methods. To optimize the segmentation of Ki-67 stained cells, one should define a data dependent transformation that will account for these color variations instead of defining a fixed linear transformation to separate different hues. To address these issues in images of tissue stained with Ki-67, we propose a methodology that exploits the intrinsic properties of CIE Lab color space to translate this complex problem into an automatic entropy based thresholding problem. The developed method was evaluated through two reader studies with pathology residents and expert hematopathologists. Agreement between the proposed method and the expert pathologists was good (CCC = 0.80).

Paper Details

Date Published: 29 March 2013
PDF: 9 pages
Proc. SPIE 8676, Medical Imaging 2013: Digital Pathology, 86760I (29 March 2013); doi: 10.1117/12.2007909
Show Author Affiliations
M. Khalid Khan Niazi, The Ohio State Univ. (United States)
Michael Pennell, The Ohio State Univ. (United States)
Camille Elkins, The Ohio State Univ. (United States)
Jessica Hemminger, The Ohio State Univ. (United States)
Ming Jin, The Ohio State Univ. (United States)
Sean Kirby, The Ohio State Univ. (United States)
Habibe Kurt, The Ohio State Univ. (United States)
Barrie Miller, The Ohio State Univ. (United States)
Elizabeth Plocharczyk, The Ohio State Univ. (United States)
Rachel Roth, The Ohio State Univ. (United States)
Rebecca Ziegler, The Ohio State Univ. (United States)
Arwa Shana’ah, The Ohio State Univ. (United States)
Fred Racke, The Ohio State Univ. (United States)
Gerard Lozanski, The Ohio State Univ. (United States)
Metin N. Gurcan, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 8676:
Medical Imaging 2013: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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