Khan, AM, Rajpoot, N, Treanor, D orcid.org/0000-0002-4579-484X et al. (1 more author) (2014) A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution. IEEE Transactions on Biomedical Engineering, 61 (6). pp. 1729-1738. ISSN 0018-9294
Abstract
Histopathology diagnosis is based on visual examination of the morphology of histological sections under a microscope. With the increasing popularity of digital slide scanners, decision support systems based on the analysis of digital pathology images are in high demand. However, computerized decision support systems are fraught with problems that stem from color variations in tissue appearance due to variation in tissue preparation, variation in stain reactivity from different manufacturers/batches, user or protocol variation, and the use of scanners from different manufacturers. In this paper, we present a novel approach to stain normalization in histopathology images. The method is based on nonlinear mapping of a source image to a target image using a representation derived from color deconvolution. Color deconvolution is a method to obtain stain concentration values when the stain matrix, describing how the color is affected by the stain concentration, is given. Rather than relying on standard stain matrices, which may be inappropriate for a given image, we propose the use of a color-based classifier that incorporates a novel stain color descriptor to calculate image-specific stain matrix. In order to demonstrate the efficacy of the proposed stain matrix estimation and stain normalization methods, they are applied to the problem of tumor segmentation in breast histopathology images. The experimental results suggest that the paradigm of color normalization, as a preprocessing step, can significantly help histological image analysis algorithms to demonstrate stable performance which is insensitive to imaging conditions in general and scanner variations in particular.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | histopathology images analysis; nonlinear mapping; principal color histograms (PCH); stain color descriptor; stain estimation; stain normalization |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cancer and Pathology (LICAP) |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Nov 2014 11:19 |
Last Modified: | 30 Mar 2021 14:40 |
Published Version: | http://dx.doi.org/10.1109/TBME.2014.2303294 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/TBME.2014.2303294 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:80820 |