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Picro-Sirius-HTX Stain for Blind Color Decomposition of Histopathological Prostate Tissue
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
2014 (English)In: Proc, IEEE 11th International Symposium on Biomedical Imaging (ISBI) 2014, 2014, 282-285 p.Conference paper, Published paper (Refereed)
Abstract [en]

Gleason grading is the most widely used system for determining the severity of prostate cancer. The Gleason grade is determined visually under a microscope from prostate tissue that is most often stained with Hematoxylin-Eosin (H&E). In an earlier study we demonstrated that this stain is not ideal for machine learning applications, but that other stains, such as Sirius-hematoxylin (Sir-Htx), may perform better. In this paper we illustrate the advantages of this stain over H&E for blind color decomposition. When compared to ground truth defined by an experienced pathologist, the relative root-mean-square errors of the color decomposition mixing matrices for Sir-Htx are better than those for H&E by a factor of two, and the Pearson correlation coefficients of the density maps resulting from the decomposition of Sir-Htx-stained tissue gives a 99% correlation with the ground truth. Qualitative examples of the density maps confirm the quantitative findings and illustrate that the density maps will allow accurate segmentation of morphological features that determine the Gleason grade.

Place, publisher, year, edition, pages
2014. 282-285 p.
Keyword [en]
Microscopy, histological stains, image color decomposition, prostate cancer, Gleason grading
National Category
Medical Image Processing
Research subject
Pathology
Identifiers
URN: urn:nbn:se:uu:diva-238511ISBN: 978-1-4673-1959-1 (print)OAI: oai:DiVA.org:uu-238511DiVA: diva2:771305
Conference
IEEE 11th International Symposium on Biomedical Imaging (ISBI) 2014
Funder
Swedish Research Council, 621-2009-5418Swedish Research Council, 621-2012-3667
Available from: 2014-12-12 Created: 2014-12-12 Last updated: 2014-12-12

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Division of Visual Information and InteractionComputerized Image Analysis and Human-Computer InteractionDepartment of Immunology, Genetics and Pathology
Medical Image Processing

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