Deep learning-based automatic measurement system for patellar height: a multicenter retrospective study.

Journal: Journal of orthopaedic surgery and research
Published Date: May 31, 2024

Abstract

BACKGROUND: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patellar height and evaluated its performance and generalization ability to accurately measure the patellar height index.

Authors

  • Zeyu Liu
    Department of Aerospace and Mechanical Engineering , University of Notre Dame , Notre Dame , Indiana 46556 , United States.
  • Jiangjiang Wu
    College of Information and Communication Engineering, Harbin Engineering University, Heilongjiang, Harbin, China.
  • Xu Gao
    National Research Base of Intelligent Manufacturing Service, School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, China; Chongqing Water Group Co. Ltd., Chongqing, 400042, China. Electronic address: hughgao@outlook.com.
  • Zhipeng Qin
    Department of Orthopedics, The Second Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
  • Run Tian
    Department of Bone and Joint Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • ChunSheng Wang
    Department of Cardiovascular Surgery, Zhongshan Hospital Fudan University.

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