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Abstract: Recognition of AML Blast Cells in a Curated Single-Cell Dataset of Leukocyte Morphologies Using Deep Convolutional Neural Networks

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Bildverarbeitung für die Medizin 2020

Part of the book series: Informatik aktuell ((INFORMAT))

Zusammenfassung

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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Literatur

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  2. Fuentes-Arderiu X, Dot-Bach D. Measurement uncertainty in manual differential leukocyte counting. Clin Chem Lab Med. 2009;47:112–115.

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  3. Matek C, Schwarz S, Marr C, et al.. A Single-cell morphological dataset of leukocytes from AML patients and non-malignant controls.; 2019. Cancer Imaging Archive.

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Author information

Authors and Affiliations

  1. Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Deutschland

    Christian Matek & Carsten Marr

  2. Laboratory of Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Deutschland

    Christian Matek, Simone Schwarz & Karsten Spiekermann

  3. German Cancer Consortium (DKTK), Heidelberg, Deutschland

    Karsten Spiekermann

  4. German Cancer Research Center (DKFZ), Heidelberg, Deutschland

    Karsten Spiekermann

Authors
  1. Christian Matek
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  2. Simone Schwarz
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  3. Karsten Spiekermann
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  4. Carsten Marr
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Corresponding author

Correspondence to Christian Matek .

Editor information

Editors and Affiliations

  1. Institut für Medizinische Informatik, Charité - Universitätsmedizin Berlin, Berlin, Germany

    Thomas Tolxdorff

  2. Peter L. Reichertz Institut für Medizinische Informatik, Technische Universität Braunschweig, Braunschweig, Germany

    Thomas M. Deserno

  3. Institut für Medizinische Informatik, Universität zu Lübeck, Lübeck, Germany

    Heinz Handels

  4. Lehrstuhl für Mustererkennung, Friedrich-Alexander-Universität, Erlangen, Germany

    Andreas Maier

  5. Medical Image Computing, E230, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany

    Klaus H. Maier-Hein

  6. Fakultät für Informatik und Mathematik, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany

    Christoph Palm

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© 2020 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Matek, C., Schwarz, S., Spiekermann, K., Marr, C. (2020). Abstract: Recognition of AML Blast Cells in a Curated Single-Cell Dataset of Leukocyte Morphologies Using Deep Convolutional Neural Networks. In: Tolxdorff, T., Deserno, T., Handels, H., Maier, A., Maier-Hein, K., Palm, C. (eds) Bildverarbeitung für die Medizin 2020. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-29267-6_11

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