A Deep-Learning-Based, Fully Automated Program to Segment and Quantify Major Spinal Components on Axial Lumbar Spine Magnetic Resonance Images.

Journal: Physical therapy
PMID: 33517461

Abstract

OBJECTIVE: The paraspinal muscles have been extensively studied on axial lumbar magnetic resonance imaging (MRI) for better understanding of back pain; however, the acquisition of measurements mainly relies on manual segmentation, which is time consuming. The study objective was to develop and validate a deep-learning-based program for automated acquisition of quantitative measurements for major lumbar spine components on axial lumbar MRIs, the paraspinal muscles in particular.

Authors

  • Haotian Shen
  • Jiawei Huang
    Spine Lab, Department of Orthopedic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, The Second Floor of Building 3, 79# Qingchun Road, Hangzhou 310003, China.
  • Qiangqiang Zheng
    Spine Lab, Department of Orthopedic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Zhiwei Zhu
    Department of Radiology, Dongyang People's Hospital, Dongyang, China.
  • Xiaoqiang Lv
    Department of Orthopedic Surgery, Dongyang People's Hospital, Dongyang, China.
  • Yong Liu
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Yue Wang
    Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

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