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International Conference on Computer Aided Systems Theory

EUROCAST 2019: Computer Aided Systems Theory – EUROCAST 2019 pp 281–288Cite as

Autoencoder Features for Differentiation of Leukocytes Based on Digital Holographic Microscopy (DHM)

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12014))

Abstract

The differentiation and counting of leukocytes is essential for the diagnosis of leukemia. This work investigates the suitability of Deep Convolutional Autoencoders and Principal Component Analysis (PCA) to generate robust features from the 3D image data of a digital holographic microscope (DHM). The results show that the feature space is not trivially separable in both cases. A terminal classification by a Support Vector Machine (SVM) favors the uncorrelated PCA features.

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Author information

Authors and Affiliations

  1. Chair for Data Processing, Department of Electrical and Computer Engineering, Technical University of Munich, Arcisstr. 21, 80333, Munich, Germany

    Stefan Röhrl & Klaus Diepold

  2. Heinz-Nixdorf-Chair of Biomedical Electronics, Department of Electrical and Computer Engineering, TranslaTUM, Campus Klinikum rechts der Isar, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany

    Matthias Ugele, Christian Klenk, Dominik Heim & Oliver Hayden

Authors
  1. Stefan Röhrl
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  2. Matthias Ugele
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  3. Christian Klenk
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  4. Dominik Heim
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  5. Oliver Hayden
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  6. Klaus Diepold
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Corresponding author

Correspondence to Stefan Röhrl .

Editor information

Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Röhrl, S., Ugele, M., Klenk, C., Heim, D., Hayden, O., Diepold, K. (2020). Autoencoder Features for Differentiation of Leukocytes Based on Digital Holographic Microscopy (DHM). In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2019. EUROCAST 2019. Lecture Notes in Computer Science(), vol 12014. Springer, Cham. https://doi.org/10.1007/978-3-030-45096-0_35

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  • DOI: https://doi.org/10.1007/978-3-030-45096-0_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45095-3

  • Online ISBN: 978-3-030-45096-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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