Deep Learning in Diagnosis of Maxillary Sinusitis Using Conventional Radiography.

Journal: Investigative radiology
Published Date: Jan 1, 2019

Abstract

OBJECTIVES: The aim of this study was to compare the diagnostic performance of a deep learning algorithm with that of radiologists in diagnosing maxillary sinusitis on Waters' view radiographs.

Authors

  • Youngjune Kim
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Kyong Joon Lee
    Department of Radiology, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, Republic of Korea.
  • Leonard Sunwoo
    Department of Radiology, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, Republic of Korea.
  • Dongjun Choi
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Chang-Mo Nam
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Jungheum Cho
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Jihyun Kim
    Quality Evaluation Team, Samsung Bioepis Co., Ltd, Incheon, Republic of Korea.
  • Yun Jung Bae
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Roh-Eul Yoo
    Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Byung Se Choi
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Cheolkyu Jung
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Jae Hyoung Kim
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.

Keywords

External Resources

Popular Topics
Recent Journals