Investigation of stratum corneum cell morphology and content using novel machine-learning image analysis.

Journal: Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
PMID: 38279539

Abstract

BACKGROUND: The morphology and content of stratum corneum (SC) cells provide information on the physiological condition of the skin. Although the morphological and biochemical properties of the SC are known, no method is available to fully access and interpret this information. This study aimed to develop a method to comprehensively decode the physiological information of the skin, based on the SC. Therefore, we established a novel image analysis technique based on artificial intelligence (AI) and multivariate analysis to predict skin conditions.

Authors

  • Takeshi Tohgasaki
    FANCL Research Institute, FANCL Corporation, Yokohama, Kanagawa, Japan.
  • Saki Aihara
    FANCL Research Institute, FANCL Corporation, Yokohama, Kanagawa, Japan.
  • Mariko Ikeda
    FANCL Research Institute, FANCL Corporation, Yokohama, Kanagawa, Japan.
  • Minako Takahashi
    FANCL Research Institute, FANCL Corporation, Yokohama, Kanagawa, Japan.
  • Masaya Eto
    Software and AI Technology Center, Toshiba Digital Solutions Corporation, Kawasaki, Kanagawa, Japan.
  • Riki Kudo
    Software and AI Technology Center, Toshiba Digital Solutions Corporation, Kawasaki, Kanagawa, Japan.
  • Hiroshi Taira
    Software and AI Technology Center, Toshiba Digital Solutions Corporation, Kawasaki, Kanagawa, Japan.
  • Ai Kido
    Software and AI Technology Center, Toshiba Digital Solutions Corporation, Kawasaki, Kanagawa, Japan.
  • Shinya Kondo
    FANCL Research Institute, FANCL Corporation, Yokohama, Kanagawa, Japan.
  • Shioji Ishiwatari
    FANCL Research Institute, FANCL Corporation, Yokohama, Kanagawa, Japan.

Keywords

External Resources

Popular Topics
Recent Journals