Automatic segmentation of dura for quantitative analysis of lumbar stenosis: A deep learning study with 518 CT myelograms.

Journal: Journal of applied clinical medical physics
Published Date: Jul 1, 2024

Abstract

BACKGROUND: The diagnosis of lumbar spinal stenosis (LSS) can be challenging because radicular pain is not often present in the culprit-level localization. Accurate segmentation and quantitative analysis of the lumbar dura on radiographic images are key to the accurate differential diagnosis of LSS. The aim of this study is to develop an automatic dura-contouring tool for radiographic quantification on computed tomography myelogram (CTM) for patients with LSS.

Authors

  • Guoxin Fan
    Department of Spine Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; Department of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China. Electronic address: fangx35@mail.sysu.edu.cn.
  • Yufeng Li
    Department of Sports Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
  • Dongdong Wang
    Department of Radiology, Huashan Hospital Affiliated to Fudan University, 12 Wulumuqi Rd. Middle, Shanghai 200040, China.
  • Jianjin Zhang
    Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China.
  • Xiaokang Du
    Department of Orthopedics, The People's Hospital of Wenshang County, Wenshang, Shandong, China.
  • Huaqing Liu
    Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, 510735, China.
  • Xiang Liao
    Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China.

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