Performance of deep learning technology for evaluation of positioning quality in periapical radiography of the maxillary canine.

Journal: Oral radiology
Published Date: May 26, 2021

Abstract

OBJECTIVES: The aim of the present study was to create and test an automatic system for assessing the technical quality of positioning in periapical radiography of the maxillary canines using deep learning classification and segmentation techniques.

Authors

  • Mizuho Mori
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University School of Dentistry, Nagoya, Japan.
  • Yoshiko Ariji
    Department of Oral Radiology, School of Dentistry, Osaka Dental University, Osaka, Japan.
  • Motoki Fukuda
    Department of Oral Radiology, School of Dentistry, Osaka Dental University, Osaka, Japan.
  • Tomoya Kitano
    Department of Oral Radiology, Asahi University School of Dentistry, 1851 Hozumi, Mizuho-city, Gifu, 501-0296, Japan.
  • Takuma Funakoshi
    Department of Oral and Maxillofacial Radiology, Aichi-Gakuin University School of Dentistry, 2-11 Suemori-dori, Chikusa-ku, Nagoya, 464-8651, Japan.
  • Wataru Nishiyama
  • Kiyomi Kohinata
    Department of Oral Radiology, Asahi University School of Dentistry, 1851 Hozumi, Mizuho-city, Gifu, 501-0296, Japan.
  • Yukihiro Iida
    Department of Oral Radiology, Asahi University School of Dentistry, 1851 Hozumi, Mizuho-city, Gifu, 501-0296, Japan.
  • Eiichiro Ariji
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University School of Dentistry, Nagoya, Japan.
  • Akitoshi Katsumata

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