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Erschienen in:
2020 | OriginalPaper | Buchkapitel
Abstract: Recognition of AML Blast Cells in a Curated Single-Cell Dataset of Leukocyte Morphologies Using Deep Convolutional Neural Networks
verfasst von : Christian Matek, Simone Schwarz, Karsten Spiekermann, Carsten Marr
Erschienen in: Bildverarbeitung für die Medizin 2020
Verlag: Springer Fachmedien Wiesbaden
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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.