Development of a model for measuring sagittal plane parameters in 10-18-year old adolescents with idiopathic scoliosis based on RTMpose deep learning technology.

Journal: Journal of orthopaedic surgery and research
Published Date: Jan 11, 2025

Abstract

PURPOSE: The study aimed to develop a deep learning model for rapid, automated measurement of full-spine X-rays in adolescents with Adolescent Idiopathic Scoliosis (AIS). A significant challenge in this field is the time-consuming nature of manual measurements and the inter-individual variability in these measurements. To address these challenges, we utilized RTMpose deep learning technology to automate the process.

Authors

  • Zhijie Kang
    Department of Human Anatomy, Graduate School, Inner Mongolia Medical University, Hohhot, 010010, Inner Mongolia, China.
  • Guopeng Shi
    Department of Human Anatomy, Graduate School, Inner Mongolia Medical University, Hohhot, 010010, Inner Mongolia, China.
  • Yong Zhu
    Jiangsu Key Laboratory of Regional Specific Resource Pharmaceutical Transformation, Huaiyin Institute of Technology, Huai'an 223003, Jiangsu, P. R. China.
  • Feng Li
    Department of General Surgery, Shanghai Traditional Chinese Medicine (TCM)-INTEGRATED Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
  • Xiaohe Li
    The Third People's Hospital of Shenzhen, Shenzhen, China.
  • Haiyan Wang
    College of Chemistry and Material Science, Shandong Agricultural University, Tai'an 271018, PR China.

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