Relationship between a deep learning model and liquid-based cytological processing techniques.

Journal: Cytopathology : official journal of the British Society for Clinical Cytology
Published Date: Jul 1, 2023

Abstract

OBJECTIVE: Artificial intelligence (AI)-based cytopathology studies conducted using deep learning have enabled cell detection and classification. Liquid-based cytology (LBC) has facilitated the standardisation of specimen preparation; however, cytomorphology varies according to the LBC processing technique used. In this study, we elucidated the relationship between two LBC techniques and cell detection and classification using a deep learning model.

Authors

  • Katsuhide Ikeda
    Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Nanako Sakabe
    Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Sayumi Maruyama
    Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Chihiro Ito
    Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Yuka Shimoyama
    Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Wataru Oboshi
    Department of Medical Technology and Sciences, School of Health Sciences at Narita, International University of Health and Welfare, Narita, Japan.
  • Tetsuya Komene
    Department of Medical Technology and Sciences, School of Health Sciences at Narita, International University of Health and Welfare, Narita, Japan.
  • Yoshitaka Yamaguchi
    Department of Medical Technology and Sciences, School of Health Sciences at Narita, International University of Health and Welfare, Narita, Japan.
  • Shouichi Sato
    Clinical Engineering, Faculty of Medical Sciences, Juntendo University, Urayasu, Japan.
  • Kohzo Nagata
    Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.

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