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Optimal Parameter Search for Colour Normalization Aiding Cell Nuclei Segmentation

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Book cover Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety (BDAS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 928))

Abstract

Automatic segmentation of biological images is necessary to allow faster diagnosis of several diseases. There are numerous methods addressing this problem, yet any general solution has been proposed. Probably it might result from the lacking standardization in tissue staining by hematoxylin and eosin, which is necessary to better visualize cell structure. The colour space normalization seems to be a perfect solution, but choosing adequate parameters is still a difficult task. Therefore, in this work, a Monte Carlo Simulation method is applied to search for a set of parameters assuring the best performance of colour transfer normalization technique. The segmentation accuracy is evaluated for each parameter set on a dataset containing colon tissue. Three accuracy metrics are computed to compare manually prepared masks with those achieved automatically: the Dice coefficient, specificity, and sensitivity. The analysis of the aggregated results proved that it is possible to find a sub-space where the worst results are placed, and depending on the accuracy measure it is possible to find a plane dividing those results.

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Acknowledgement

This work was supported by statutory fonds (02/020/BK_18/0128) and statutory funds for young researchers (BKM-509/RAU2/2017) of the Institute of Informatics, Silesian University of Technology, Poland.

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Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Karolina Nurzynska

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  1. Karolina Nurzynska
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Correspondence to Karolina Nurzynska .

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Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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Nurzynska, K. (2018). Optimal Parameter Search for Colour Normalization Aiding Cell Nuclei Segmentation. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety. BDAS 2018. Communications in Computer and Information Science, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-319-99987-6_27

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  • DOI: https://doi.org/10.1007/978-3-319-99987-6_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99986-9

  • Online ISBN: 978-3-319-99987-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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