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Journal of Biomedical Optics

Offset-sparsity decomposition for automated enhancement of color microscopic image of stained specimen in histopathology
Author(s): Ivica Kopriva; Marijana Popović Hadžija; Mirko Hadžija; Gorana Aralica
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Paper Abstract

We propose an offset-sparsity decomposition method for the enhancement of a color microscopic image of a stained specimen. The method decomposes vectorized spectral images into offset terms and sparse terms. A sparse term represents an enhanced image, and an offset term represents a “shadow.” The related optimization problem is solved by computational improvement of the accelerated proximal gradient method used initially to solve the related rank-sparsity decomposition problem. Removal of an image-adapted color offset yields an enhanced image with improved colorimetric differences among the histological structures. This is verified by a no-reference colorfulness measure estimated from 35 specimens of the human liver, 1 specimen of the mouse liver stained with hematoxylin and eosin, 6 specimens of the mouse liver stained with Sudan III, and 3 specimens of the human liver stained with the anti-CD34 monoclonal antibody. The colorimetric difference improves on average by 43.86% with a 99% confidence interval (CI) of [35.35%, 51.62%]. Furthermore, according to the mean opinion score, estimated on the basis of the evaluations of five pathologists, images enhanced by the proposed method exhibit an average quality improvement of 16.60% with a 99% CI of [10.46%, 22.73%].

Paper Details

Date Published: 28 July 2015
PDF: 14 pages
J. Biomed. Opt. 20(7) 076012 doi: 10.1117/1.JBO.20.7.076012
Published in: Journal of Biomedical Optics Volume 20, Issue 7
Show Author Affiliations
Ivica Kopriva, Institut Ruder Boškovic (Croatia)
Marijana Popović Hadžija, Institut Ruder Boškovic (Croatia)
Mirko Hadžija, Institut Ruder Boškovic (Croatia)
Gorana Aralica, Klinička Bolnica Dubrava (Croatia)
Univ. of Zagreb (Croatia)


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