Haoyu Zhai, Jin Huang, Lei Li, Hairong Tao, Jinwu Wang, Kang Li, Moyu Shao, Xiaomin Cheng, Jing Wang, Xiang Wu, Chuan Wu, Xiao Zhang, Hongkai Wang, Yan Xiong
OBJECTIVE: Precise hip joint morphometry measurement from CT images is crucial for successful preoperative arthroplasty planning and biomechanical simulations. Although deep learning approaches have been applied to clinical bone surgery planning, there is still a lack of relevant research on quantifying hip joint morphometric parameters from CT images. APPROACH: This paper proposes a deep learning workflow for CT-based hip morphometry measurement. For the first step, a coarse-to-fine deep learning model is designed for accurate reconstruction of the hip geometry (3D bone models and key landmark points)...
October 18, 2023: Physics in Medicine and Biology