1. An image dataset related to automated macrophage detection in immunostained lymphoma tissue samples.
- Author
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Wagner M, Reinke S, Hänsel R, Klapper W, and Braumann UD
- Subjects
- Antigens, CD metabolism, Antigens, Differentiation, Myelomonocytic metabolism, Datasets as Topic, Fluorescent Antibody Technique standards, Image Interpretation, Computer-Assisted standards, Lipopolysaccharide Receptors metabolism, Lymphoma, Large B-Cell, Diffuse classification, Macrophages metabolism, PAX5 Transcription Factor metabolism, Receptors, Cell Surface metabolism, Fluorescent Antibody Technique methods, Image Interpretation, Computer-Assisted methods, Lymphoma, Large B-Cell, Diffuse pathology, Macrophages pathology
- Abstract
Background: We present an image dataset related to automated segmentation and counting of macrophages in diffuse large B-cell lymphoma (DLBCL) tissue sections. For the classification of DLBCL subtypes, as well as for providing a prognosis of the clinical outcome, the analysis of the tumor microenvironment and, particularly, of the different types and functions of tumor-associated macrophages is indispensable. Until now, however, most information about macrophages has been obtained either in a completely indirect way by gene expression profiling or by manual counts in immunohistochemically (IHC) fluorescence-stained tissue samples while automated recognition of single IHC stained macrophages remains a difficult task. In an accompanying publication, a reliable approach to this problem has been established, and a large set of related images has been generated and analyzed., Results: Provided image data comprise (i) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at 4 channels corresponding to CD14, CD163, Pax5, and DAPI; (ii) "cartoon-like" total variation-filtered versions of these images, generated by Rudin-Osher-Fatemi denoising; (iii) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel; and (iv) automatically generated segmentation masks for macrophages (using information from CD14 and CD163 channels), B-cells (using information from Pax5 channel), and all cell nuclei (using information from DAPI channel)., Conclusions: A large set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populations generated by a reference method for automated image analysis, thus featuring considerable reuse potential., (© The Author(s) 2020. Published by Oxford University Press.)
- Published
- 2020
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