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An image dataset related to automated macrophage detection in immunostained lymphoma tissue samples

: Wagner, Markus; Reinke, Sarah; Hänsel, René; Klapper, Wolfram; Braumann, Ulf-Dietrich

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GigaScience 9 (2020), No.3, Art. giaa016, 7 pp.
ISSN: 2047-217X
Journal Article, Electronic Publication
Fraunhofer IZI ()
Lymphoma; Diffuses großzelliges B-Zell-Lymphom; Makrophage; Multiple immunohistochemical staining; Automated cell counting; ROF filtering; Floating threshold; Rule-based detection; Image dataset

Background: We present an image dataset related to automated segmentation and counting of macrophages in diffuselarge B-cell lymphoma (DLBCL) tissue sections. For the classification of DLBCL subtypes, as well as for providing a prognosisof the clinical outcome, the analysis of the tumor microenvironment and, particularly, of the different types and functionsof tumor-associated macrophages is indispensable. Until now, however, most information about macrophages has beenobtained 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 adifficult task. In an accompanying publication, a reliable approach to this problem has been established, and a large set ofrelated images has been generated and analyzed. Results: Provided image data comprise (i) fluorescence microscopyimages 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-Fatemidenoising; (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: Alarge set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populationsgenerated by a reference method for automated image analysis, thus featuring considerable reuse potential.