Automated measurement of pelvic parameters using convolutional neural network in complex spinal deformities: overcoming challenges in coronal deformity cases.

Journal: The spine journal : official journal of the North American Spine Society
Published Date: Jan 31, 2025

Abstract

BACKGROUND CONTEXT: Accurate and consistent measurement of sagittal alignment is challenging, particularly in patients with severe coronal deformities, including degenerative lumbar scoliosis (DLS).

Authors

  • Dong-Ho Kang
    Department of Orthopedic Surgery, Samsung Medical Center, Seoul, Republic of Korea; College of Medicine, Seoul National University, Seoul, Republic of Korea.
  • Ye-Jin Jeong
    College of Mathematics, Korea University, Seoul, Republic of Korea; Research & Development Department, CONNECTEVE Co., Ltd, Seoul, Republic of Korea.
  • Sung Taeck Kim
    College of Medicine, Seoul National University, Seoul, Republic of Korea; Department of Orthopedic Surgery, Seoul National University Hospital, Seoul, Republic of Korea.
  • Younguk Kim
    Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, Republic of Korea.
  • Bong-Soon Chang
  • Hyoungmin Kim
    Healthcare AI Research Institute, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
  • Sam Yeol Chang
    Department of Orthopedic Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. hewl3102@gmail.com.
  • Du Hyun Ro
    Department of Orthopaedic Surgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. duhyunro@gmail.com.

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