PuSH - Publication Server of Helmholtz Zentrum München: Abstract: Recognition of AML blast cells in a curated single-cell dataset of leukocyte morphologies using deep convolutional neural networks.

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Matek, C. ; Schwarz, S.* ; Spiekermann, K.* ; Marr, C.

Abstract: Recognition of AML blast cells in a curated single-cell dataset of leukocyte morphologies using deep convolutional neural networks.

In: Bildverarbeitung für die Medizin 2020. Switzerland: 2020. 53-54 (Inf. aktuell)

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Reliable recognition and microscopic differentiation of malignant and non-malignant leukocytes from peripheral blood smears is a key task of cytological diagnostics in hematology [1]. Having been practised for well over a century, cytomorphological analysis is still today routinely performed by human examiners using optical microscopes, a process that can be tedious, time-consuming, and suffering from considerable intra-and inter-rater variability [2]. Our work aims to provide a more quantitative and robust decision-aid for the differentiation of single blood cells in general and recognition of blast cells characteristic for Acute Myeloid Leukemia (AML) in particular.

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Publication type Article: Edited volume or book chapter

Corresponding Author

ISSN (print) / ISBN 1431-472X

e-ISSN 1431-472X

Book Volume Title Bildverarbeitung für die Medizin 2020

Journal Informatik aktuell

Quellenangaben Pages: 53-54

Publishing Place Switzerland

Non-patent literature Publications

Institute(s) Institute of Computational Biology (ICB)