Automatic detection of midfacial fractures in facial bone CT images using deep learning-based object detection models.

Journal: Journal of stomatology, oral and maxillofacial surgery
Published Date:

Abstract

BACKGROUND: Midfacial fractures are among the most frequent facial fractures. Surgery is recommended within 2 weeks of injury, but this time frame is often extended because the fracture is missed on diagnostic imaging in the busy emergency medicine setting. Using deep learning technology, which has progressed markedly in various fields, we attempted to develop a system for the automatic detection of midfacial fractures. The purpose of this study was to use this system to diagnose fractures accurately and rapidly, with the intention of benefiting both patients and emergency room physicians.

Authors

  • Daiki Morita
    Department of Plastic and Reconstructive Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan. Electronic address: d-morita@koto.kpu-m.ac.jp.
  • Ayako Kawarazaki
    Department of Plastic and Reconstructive Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan.
  • Mazen Soufi
    Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5, Takayama-cho, Ikoma, Nara, Japan.
  • Yoshito Otake
  • Yoshinobu Sato
    Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan. Electronic address: yoshi@is.naist.jp.
  • Toshiaki Numajiri
    Departments of Plastic and Reconstructive Surgery.