Deep learning-based correction of cataract-induced influence on macular pigment optical density measurement by autofluorescence spectroscopy.

Journal: PloS one
PMID: 38349916

Abstract

PURPOSE: Measurements of macular pigment optical density (MPOD) using the autofluorescence spectroscopy yield underestimations of actual values in eyes with cataracts. Previously, we proposed a correction method for this error using deep learning (DL); however, the correction performance was validated through internal cross-validation. This cross-sectional study aimed to validate this approach using an external validation dataset.

Authors

  • Akira Obana
    Department of Ophthalmology, Seirei Hamamatsu General Hospital, Hamamatsu City, Shizuoka, Japan.
  • Kibo Ote
    Central Research Laboratory, Hamamatsu Photonics K. K., 5000 Hirakuchi, Hamakita-ku, Hamamatsu 434-8601, Japan.
  • Yuko Gohto
    Department of Ophthalmology, Seirei Hamamatsu General Hospital, Hamamatsu City, Shizuoka, Japan.
  • Hidenao Yamada
    Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, Shizuoka, Japan.
  • Fumio Hashimoto
    Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, 434-8601, Japan. fumio.hashimoto@crl.hpk.co.jp.
  • Shigetoshi Okazaki
    Department of Medical Spectroscopy, Institute for Medical Photonics Research, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Ryo Asaoka
    Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.

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