Paper
20 March 2014 Quantitative analysis of stain variability in histology slides and an algorithm for standardization
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Abstract
This paper presents data on the sources of variation of the widely used hematoxylin and eosin (H&E) histological staining, as well as a new algorithm to reduce these variations in digitally scanned tissue sections. Experimental results demonstrate that staining protocols in different laboratories and staining on different days of the week are the major factors causing color variations in histopathological images. The proposed algorithm for standardizing histology slides is based on an initial clustering of the image into two tissue components having different absorption characteristics for different dyes. The color distribution for each tissue component is standardized by aligning the 2D histogram of color distribution in the hue-saturation-density (HSD) model. Qualitative evaluation of the proposed standardization algorithm shows that color constancy of the standardized images is improved. Quantitative evaluation demonstrates that the algorithm outperforms competing methods. In conclusion, the paper demonstrates that staining variations, which may potentially hamper usefulness of computer assisted analysis of histopathological images, can be reduced considerably by applying the proposed algorithm.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Babak Ehteshami Bejnordi, Nadya Timofeeva, Irene Otte-Höller, Nico Karssemeijer, and Jeroen A. W. M. van der Laak "Quantitative analysis of stain variability in histology slides and an algorithm for standardization", Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 904108 (20 March 2014); https://doi.org/10.1117/12.2043683
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CITATIONS
Cited by 25 scholarly publications and 2 patents.
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KEYWORDS
Tissues

Data modeling

RGB color model

Image segmentation

Expectation maximization algorithms

Image processing algorithms and systems

Absorption

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