Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip.

Journal: BMC musculoskeletal disorders
Published Date: Nov 13, 2024

Abstract

OBJECTIVES: Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radiographs of the hip. The assessment seeks to demonstrate the efficacy of the artificial intelligence model in diagnosing both developmental dysplasia of the hip and borderline developmental dysplasia of the hip through the analysis of pelvic radiographs.

Authors

  • Ruixin Li
    Liaoning Provincial Key Laboratory of Carbohydrates, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. liruixinlndl@163.com.
  • Xiao Wang
    Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
  • Tianran Li
    Department of Radiology, The Fourth Medical Center of Chinese PLA General Hospital, No. 51, Fucheng Road, Haidian District, Beijing, China. ltranmd@yeah.net.
  • Beibei Zhang
    School of Statistics, Capital University of Economics and Business, Beijing, China.
  • Xiaoming Liu
    College of Agriculture, Northeast Agricultural University, Harbin, China.
  • Wenhua Li
    Ultrasound in Cardiac Electrophysiology and Biomechanics Key Laboratory of Sichuan Province, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32# W. Sec 2, 1st Ring Rd., Chengdu, 610072, China.
  • Qirui Sui
    Department of Radiology, The Fourth Medical Center of Chinese PLA General Hospital, No. 51, Fucheng Road, Haidian District, Beijing, China.

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