Automatic screening of tear meniscus from lacrimal duct obstructions using anterior segment optical coherence tomography images by deep learning.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Published Date: Jun 1, 2021

Abstract

PURPOSE: We assessed the ability of deep learning (DL) models to distinguish between tear meniscus of lacrimal duct obstruction (LDO) patients and normal subjects using anterior segment optical coherence tomography (ASOCT) images.

Authors

  • Hitoshi Imamura
    Department of Ophthalmology, Tsukazaki Hospital, 68-1 Waku, Aboshi-ku, Himeji City, Hyogo, 671-1227, Japan.
  • Hitoshi Tabuchi
    Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.
  • Daisuke Nagasato
    Department of Ophthalmology, Tsukazaki Hospital, 68-1 Waku, Aboshi-ku, Himeji, 671-1227, Japan.
  • Hiroki Masumoto
    Department of Ophthalmology, Saneikai Tsukazaki Hospital, 68-1 Aboshi Waku, Himeji, 671-1227, Japan.
  • Hiroaki Baba
    Department of Ophthalmology, Tsukazaki Hospital, 68-1 Waku, Aboshi-ku, Himeji City, Hyogo, 671-1227, Japan.
  • Hiroki Furukawa
    Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.
  • Sachiko Maruoka
    Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.

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