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A Quantitative Assessment of Image Normalization for Classifying Histopathological Tissue of the Kidney

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Pattern Recognition (GCPR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10496))

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Abstract

The advancing pervasion of digital pathology in research and clinical practice results in a strong need for image analysis techniques in the field of histopathology. Due to diverse reasons, histopathological imaging generally exhibits a high degree of variability. As automated segmentation approaches are known to be vulnerable, especially to unseen variability, we investigate several stain normalization methods to compensate for variations between different whole slide images. In a large experimental study, we investigate all combinations of five image normalization (not only stain normalization) methods as well as five image representations with respect to the classification performance in two application scenarios in kidney histopathology. Finally, we also pose the question, if color normalization is sufficient to compensate for the changed properties between whole slide images in an application scenario with few training data.

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Acknowledgments

This work was supported by the German Research Foundation (DFG), grant no. ME3737/3-1.

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Authors and Affiliations

  1. Aachen Center for Biomedical Image Analysis, Visualization and Exploration (ACTIVE), Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

    Michael Gadermayr, Sean Steven Cooper & Dorit Merhof

  2. Institute of Pathology, University Hospital Aachen, RWTH Aachen University, Aachen, Germany

    Barbara Klinkhammer & Peter Boor

Authors
  1. Michael Gadermayr
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  2. Sean Steven Cooper
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  3. Barbara Klinkhammer
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  4. Peter Boor
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  5. Dorit Merhof
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Corresponding author

Correspondence to Michael Gadermayr .

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Editors and Affiliations

  1. University of Basel, Basel, Switzerland

    Volker Roth

  2. University of Basel, Basel, Switzerland

    Thomas Vetter

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Gadermayr, M., Cooper, S.S., Klinkhammer, B., Boor, P., Merhof, D. (2017). A Quantitative Assessment of Image Normalization for Classifying Histopathological Tissue of the Kidney. In: Roth, V., Vetter, T. (eds) Pattern Recognition. GCPR 2017. Lecture Notes in Computer Science(), vol 10496. Springer, Cham. https://doi.org/10.1007/978-3-319-66709-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-66709-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66708-9

  • Online ISBN: 978-3-319-66709-6

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