Diagnostic Performance of a New Convolutional Neural Network Algorithm for Detecting Developmental Dysplasia of the Hip on Anteroposterior Radiographs.

Journal: Korean journal of radiology
Published Date: Nov 26, 2020

Abstract

OBJECTIVE: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs.

Authors

  • Hyoung Suk Park
    Division of Integrated Mathematics, National Institute for Mathematical Sciences, Daejeon, 34047, Korea.
  • Kiwan Jeon
  • Yeon Jin Cho
  • Se Woo Kim
    Department of Radiology, Seoul National University Hospital, Seoul, Korea.
  • Seul Bi Lee
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
  • Gayoung Choi
    Department of Radiology, Seoul National University Hospital, Seoul, Korea.
  • Seunghyun Lee
    Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA. Electronic address: seunghyun.lee.22@gmail.com.
  • Young Hun Choi
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea. iater@snu.ac.kr.
  • Jung Eun Cheon
    Department of Radiology, Seoul National University Hospital, Seoul, Korea.
  • Woo Sun Kim
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
  • Young Jin Ryu
    Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
  • Jae Yeon Hwang
    Department of Agricultural Biotechnology, Animal Biotechnology Major, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul 151-921, Korea.

Keywords

External Resources

Popular Topics
Recent Journals