Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PMID: 38700592

Abstract

PURPOSE: To investigate the possibility of distinguishing between IgG4-related ophthalmic disease (IgG4-ROD) and orbital MALT lymphoma using artificial intelligence (AI) and hematoxylin-eosin (HE) images.

Authors

  • Mizuki Tagami
    Department of Ophthalmology and Visual Sciences, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
  • Mizuho Nishio
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Atsuko Yoshikawa
    Ophthalmology Department and Eye Center, Kobe Kaisei Hospital, Kobe, Hyogo, Japan.
  • Norihiko Misawa
    Department of Ophthalmology and Visual Sciences, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
  • Atsushi Sakai
    Department of Ophthalmology and Visual Sciences, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
  • Yusuke Haruna
    Department of Ophthalmology and Visual Sciences, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
  • Mami Tomita
    Department of Ophthalmology and Visual Sciences, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
  • Atsushi Azumi
    Ophthalmology Department and Eye Center, Kobe Kaisei Hospital, Kobe, Hyogo, Japan.
  • Shigeru Honda
    Department of Ophthalmology and Visual Sciences, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.

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