Effects of dimension reduction of hyperspectral images in skin gross pathology.

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)
Published Date: Feb 1, 2023

Abstract

BACKGROUND: Hyperspectral imaging (HSI) is an emerging modality for the gross pathology of the skin. Spectral signatures of HSI could discriminate malignant from benign tissue. Because of inherent redundancies in HSI and in order to facilitate the use of deep-learning models, dimension reduction is a common preprocessing step. The effects of dimension reduction choice, training scope, and number of retained dimensions have not been evaluated on skin HSI for segmentation tasks.

Authors

  • Eleni Aloupogianni
    Department of Information and Communications Engineering, Tokyo Institute of Technology, Yokohama, Japan.
  • Masahiro Ishikawa
  • Takaya Ichimura
    Department of Pathology, Faculty of Medicine, Saitama Medical University Moroyama Campus, Moroyama, Japan.
  • Mei Hamada
    Department of Pathology, Faculty of Medicine, Saitama Medical University Moroyama Campus, Moroyama, Japan.
  • Takuo Murakami
    Department of Dermatology, Faculty of Medicine, Saitama Medical University Moroyama Campus, Moroyama, Japan.
  • Atsushi Sasaki
    Department of Pathology, Faculty of Medicine, Saitama Medical University Moroyama Campus, Moroyama, Japan.
  • Koichiro Nakamura
    Department of Dermatology, Saitama Medical University Hospital, 38 Morohongo Moroyama-machi, Iruma-gun, Saitama, Japan.
  • Naoki Kobayashi
    Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto 860-8556, Japan (T.N., N.Y., N.K., Y.N., H.U., M.K., S.O., T.H.).
  • Takashi Obi

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