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A hybrid approach for stain normalisation in digital histopathological images

Bukenya, Faiza

A hybrid approach for stain normalisation in digital histopathological images Thumbnail


Authors

Faiza Bukenya



Abstract

Stain in-homogeneity adversely affects segmentation and quantifi-cation of tissues in histology images. Stain normalisation techniques have been used to standardise the appearance of images. However, most the available stain normalisation techniques only work on a particular kind of stain images. In addition, some of these techniques fail to utilise both the spatial and tex-tural information in histology images, leading to image tissue distortion. In this paper, a hybrid approach has been developed, based on an octree colour quantisation algorithm combined with the Beer-Lambert law, a modified blind source separation algorithm, and a modified colour transfer approach. The hybrid method consists of two stages the stain separation stage and colour transfer stage. An octree colour quantisation algorithm combined with Beer-Lambert law, and a modified blind source separation algorithm are used during the stain separation stage to computationally estimate the amount of stain in an histology image based on its chromatic and luminous response. A modified colour transfer algorithm is used during the colour transfer stage to minimise the effect of varying staining and illumination. The hybrid method addresses the colour variation problem in both H&DAB (Haemotoxylin and Diaminoben-zidine) and H&E (Haemotoxylin and Eosin) stain images. The stain normali-sation method is validated against ground truth data. It is widely known that the Beer-Lambert law applies to only stains (such as haematoxylin, eosin) that absorb light. We demonstrate that the Beer-Lambert law applies is applicable to images containing a DAB stain. Better stain normalisation results are obtained in both H&E and H&DAB images.

Citation

Bukenya, F. (2020). A hybrid approach for stain normalisation in digital histopathological images. Multimedia Tools and Applications, 79(3-4), 2339-2362. https://doi.org/10.1007/s11042-019-08262-0

Journal Article Type Article
Acceptance Date Sep 16, 2019
Online Publication Date Nov 19, 2019
Publication Date 2020-01
Deposit Date Jan 14, 2020
Publicly Available Date Mar 28, 2024
Journal Multimedia Tools and Applications
Print ISSN 1380-7501
Electronic ISSN 1573-7721
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 79
Issue 3-4
Pages 2339-2362
DOI https://doi.org/10.1007/s11042-019-08262-0
Keywords Media Technology; Computer Networks and Communications; Hardware and Architecture; Software
Public URL https://nottingham-repository.worktribe.com/output/3723747
Publisher URL https://link.springer.com/article/10.1007/s11042-019-08262-0
Additional Information Received: 29 November 2018; Revised: 25 June 2019; Accepted: 16 September 2019; First Online: 19 November 2019; : ; : There is no competing interests or exclusive licenses used in preparing this manuscript.

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