Automatic prosthetic-parameter estimation from anteroposterior pelvic radiographs after total hip arthroplasty using deep learning-based keypoint detection.

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS
Published Date: Apr 4, 2022

Abstract

BACKGROUND: X-ray is a necessary tool for post-total hip arthroplasty (THA) check-ups; however, parameter measurements are time-consuming. We proposed a deep learning tool, BKNet that automates localization of landmarks with parameter measurements.

Authors

  • Tsung-Wei Tseng
    Department of Orthopaedic Surgery, Chang Gung Memorial Hospital (CGMH), Taoyuan, Taiwan.
  • Yueh-Peng Chen
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital at Linkou, No. 5, Fuxing St., Guishan Dist., Taoyuan City, 333, Taiwan. yuepengc@gmail.com.
  • Yu-Cheng Yeh
    Spine Division, Department of Orthopaedic Surgery, Bone and Joint Research Center, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 5, Fuxing St., Guishan Dist., Taoyuan, 333, Taiwan. yehchrist2@gmail.com.
  • Chang-Fu Kuo
    Department of Rheumatology, Allergy, and Immunology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC.
  • Tzuo-Yau Fan
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital at Linkou, No. 5, Fuxing St., Guishan Dist., Taoyuan City, 333, Taiwan.
  • Yu-Chih Lin
    Department of Orthopaedic Surgery, Chang Gung Memorial Hospital (CGMH), Taoyuan, Taiwan.

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