Automatic Pavlov ratio measurement method based on spinal landmarks identification by a deep-learning model.

Journal: Medical physics
PMID: 39715317

Abstract

BACKGROUND: Cervical canal stenosis is one of the important pathogenic factors of cervical spondylosis. The accuracy of the Pavlov ratio measurement is crucial for the diagnosis and treatment of cervical spinal stenosis. Manual measurement is influenced by observer variability, accompanied by its inefficiency, which affects clinical evaluation.

Authors

  • Yongli Wang
    Department of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
  • Chi Huang
    Department of Orthopedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001 Heilongjiang, China.
  • Junhao Zhou
    Second Affiliated Hospital (Changzheng Hospital) of Naval Medical University, Shanghai, China.
  • Xueyuan Zhang
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107# Yanjiang West Road, Guangzhou, China.
  • Fei Ren
    Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China; SKLP, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China. Electronic address: renfei@ict.ac.cn.
  • Benbo Zhang
    Second Affiliated Hospital (Changzheng Hospital) of Naval Medical University, Shanghai, China.
  • Xiaowen Wang
    Bioresources Green Transformation Collaborative Innovation Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan 430062, Hubei, China.
  • Xiyue Cheng
    School of Medicine, North China University of Science and Technology, Tangshan, China.
  • Kai Cao
  • Yibo Dou
    Department of Cervical Surgery, The Second Affiliated Hospital of the Naval Medical University, Shanghai, 200003, China.
  • Peng Cao
    Medical Image Computing Laboratory of Ministry of Education, Northeastern University, 110819, Shenyang, China.

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