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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)
Reliable recognition and microscopic differentiation of malignant and non-malignant leukocytes from peripheral blood smears is a key task of cytological diagnostics in hematology . 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 . 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
ISSN (print) / ISBN 1431-472X
Book Volume Title Bildverarbeitung für die Medizin 2020
Journal Informatik aktuell
Quellenangaben Pages: 53-54
Publishing Place Switzerland
Institute(s) Institute of Computational Biology (ICB)