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

Abstract:

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. Provided image data comprise a) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at four channels corresponding to CD14, CD163, Pax5 and DAPI; b) cartoon-filtered versions of these images, generated by Rudin-Osher-Fatemi (ROF) denoising; c) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel, and d) automatically generated segmentation masks for macrophages, B-cells and the total of cell nuclei, using information from CD14, CD163, Pax5 and DAPI channels, respectively.

DOI: 10.1093/gigascience/giaa016

Projects: MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demon...

Publication type: Journal article

Journal: GigaScience

Publisher: Oxford University Press (OUP)

Human Diseases: Diffuse large b-cell lymphoma

Citation: GigaScience,9(3)

Date Published: 12th Mar 2020

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Registered Mode: manually

Authors: Marcus Wagner, Sarah Reinke, René Hänsel, Wolfram Klapper, Ulf-Dietrich Braumann

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Citation
Wagner, M., Reinke, S., Hänsel, R., Klapper, W., & Braumann, U.-D. (2020). An image dataset related to automated macrophage detection in immunostained lymphoma tissue samples. In GigaScience (Vol. 9, Issue 3). Oxford University Press (OUP). https://doi.org/10.1093/gigascience/giaa016
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Created: 3rd Sep 2019 at 11:15

Last updated: 7th Dec 2021 at 17:58

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