Automatic hip osteoarthritis grading with uncertainty estimation from computed tomography using digitally-reconstructed radiographs.

Journal: International journal of computer assisted radiology and surgery
PMID: 38472690

Abstract

PURPOSE: Progression of hip osteoarthritis (hip OA) leads to pain and disability, likely leading to surgical treatment such as hip arthroplasty at the terminal stage. The severity of hip OA is often classified using the Crowe and Kellgren-Lawrence (KL) classifications. However, as the classification is subjective, we aimed to develop an automated approach to classify the disease severity based on the two grades using digitally-reconstructed radiographs from CT images.

Authors

  • Masachika Masuda
    Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan. masuda.masachika.mp2@is.naist.jp.
  • 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
  • Keisuke Uemura
    Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan. keisuke-uemura@is.naist.jp.
  • Sotaro Kono
    Department of Orthopaedics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Kazuma Takashima
    Department of Orthopaedics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Hidetoshi Hamada
    Department of Orthopaedic Medical Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Yi Gu
    Department of Electrical and Computer Engineering, University of California, San Diego, California.
  • Masaki Takao
  • Seiji Okada
    Department of Orthopaedic Surgery, Osaka University Graduate School of Medicine, Suita, Japan.
  • Nobuhiko Sugano
  • 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.

Keywords

External Resources

Popular Topics
Recent Journals