Abstract
This paper compares the effects of colour pre-processing on the classification performance of H&E-stained images. Variations in the tissue preparation procedures, acquisition systems, stain conditions and reagents are all source of artifacts that can affect negatively computer-based classification. Pre-processing methods such as colour constancy, transfer and deconvolution have been proposed to compensate the artifacts. In this paper we compare quantitatively the combined effect of six colour pre-processing procedures and 12 colour texture descriptors on patch-based classification of H&E-stained images. We found that colour pre-processing had negative effects on accuracy in most cases – particularly when used with colour descriptors. However, some pre-processing procedures proved beneficial when employed in conjunction with classic texture descriptors such as co-occurrence matrices, Gabor filters and Local Binary Patterns.
F. Bianconi—Performed this work as an Academic Visitor at City, University of London.
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Acknowledgements
This work was partially supported by the Italian Ministry of Education, University and Research (MIUR) under the Individual Funding Scheme for Fundamental Research (‘FFABR 2017’) and by the Department of Engineering at the University of Perugia, Italy, under the Fundamental Research programme 2018.
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Bianconi, F., Kather, J.N., Reyes-Aldasoro, C.C. (2019). Evaluation of Colour Pre-processing on Patch-Based Classification of H&E-Stained Images. In: Reyes-Aldasoro, C., Janowczyk, A., Veta, M., Bankhead, P., Sirinukunwattana, K. (eds) Digital Pathology. ECDP 2019. Lecture Notes in Computer Science(), vol 11435. Springer, Cham. https://doi.org/10.1007/978-3-030-23937-4_7
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