Subtype classification of malignant lymphoma using immunohistochemical staining pattern.

Journal: International journal of computer assisted radiology and surgery
Published Date: Feb 11, 2022

Abstract

PURPOSE: For the image classification problem, the construction of appropriate training data is important for improving the generalization ability of the classifier in particular when the size of the training data is small. We propose a method that quantitatively evaluates the typicality of a hematoxylin-and-eosin (H&E)-stained tissue slide from a set of immunohistochemical (IHC) stains and applies the typicality to instance selection for the construction of classifiers that predict the subtype of malignant lymphoma to improve the generalization ability.

Authors

  • Noriaki Hashimoto
    Graduate School of Medicine, Yamaguchi University, Tokiwadai 2-16-1, Ube, Yamaguchi, 755-8611, Japan.
  • Kaho Ko
    Department of Computer Science, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan.
  • Tatsuya Yokota
    Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan; Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Aichi, Japan. Electronic address: t.yokota@nitech.ac.jp.
  • Kei Kohno
    Department of Pathology, Kurume University School of Medicine, Kurume, Japan.
  • Masato Nakaguro
    Department of Pathology and Laboratory Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8560, Japan.
  • Shigeo Nakamura
    Department of Pathology and Laboratory Medicine, Nagoya University Hospital, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8560, Japan.
  • Ichiro Takeuchi
    RIKEN Center for Advanced Intelligent Project, Chuo-ku, Tokyo, 103-0027, Japan; Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi, 466-8555, Japan; and Center for Materials Research by Information Integration, National Institute for Material Science, Sengen, Tsukuba, Ibaraki, 305-0047, Japan takeuchi.ichiro@nitech.ac.jp.
  • Hidekata Hontani
    Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan; Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Aichi, Japan. Electronic address: hontani@nitech.ac.jp.

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