Preliminary study on the application of deep learning system to diagnosis of Sjögren's syndrome on CT images.

Journal: Dento maxillo facial radiology
Published Date: May 22, 2019

Abstract

OBJECTIVES: This study estimated the diagnostic performance of a deep learning system for detection of Sjögren's syndrome (SjS) on CT, and compared it with the performance of radiologists.

Authors

  • Yoshitaka Kise
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University School of Dentistry, Nagoya, Japan.
  • Haruka Ikeda
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University, Nagoya, Japan.
  • Takeshi Fujii
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University, Nagoya, Japan.
  • Motoki Fukuda
    Department of Oral Radiology, School of Dentistry, Osaka Dental University, Osaka, Japan.
  • Yoshiko Ariji
    Department of Oral Radiology, School of Dentistry, Osaka Dental University, Osaka, Japan.
  • Hiroshi Fujita
    Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.
  • Akitoshi Katsumata
  • Eiichiro Ariji
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University School of Dentistry, Nagoya, Japan.

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