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Scalable HEVC for Histological Whole-Slide Image Compression

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Bildverarbeitung für die Medizin 2020

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

Zusammenfassung

Digital whole-slide images (WSI) are scanned representations of histological tissue at microscopic scale, enabling computer aided diagnosis and remote pathology applications. However, the data sizes may hinder a widespread use, as raw files can easily exceed 10-20GB. In this work, we explore the Scalable High Effciency Video Coding (SHVC) as a replacement for the JPEG standard currently found in most vendor formats. Besides a comparison of the compression rates, this work comprises a user-study to estimate SHVC quantization parameters (QP) and JPEG quality level that threshold the just-noticeable distortions (JND) for a compression below the JND.

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Literatur

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Author information

Authors and Affiliations

  1. Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Deutschland

    Daniel Bug, Felix Bartsch, Mathias Wien & Dorit Merhof

  2. Institute for Pathology, Hannover Medical School, Hannover, Deutschland

    Nadine Sarah Schaadt & Friedrich Feuerhake

  3. Institute for Neuropathology, University Clinic Freiburg im Breisgau, Freiburg im Breisgau, Deutschland

    Friedrich Feuerhake

  4. Charles River Discover Research Services Germany GmbH, Freiburg im Breisgau, Deutschland

    Julia Schüler & Eva Oswald

Authors
  1. Daniel Bug
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  2. Felix Bartsch
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  3. Nadine Sarah Schaadt
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  4. Mathias Wien
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  5. Friedrich Feuerhake
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  6. Julia Schüler
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  7. Eva Oswald
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  8. Dorit Merhof
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Corresponding author

Correspondence to Daniel Bug .

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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Bug, D. et al. (2020). Scalable HEVC for Histological Whole-Slide Image Compression. 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_71

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