Automatic Detection and Classification of Modic Changes in MRI Images Using Deep Learning: Intelligent Assisted Diagnosis System.

Journal: Orthopaedic surgery
Published Date: Nov 7, 2023

Abstract

OBJECTIVE: Modic changes (MCs) are the most prevalent classification system for describing intravertebral MRI signal intensity changes. However, interpreting these intricate MRI images is a complex and time-consuming process. This study investigates the performance of single shot multibox detector (SSD) and ResNet18 network-based automatic detection and classification of MCs. Additionally, it compares the inter-observer agreement and observer-classifier agreement in MCs diagnosis to validate the feasibility of deep learning network-assisted detection of classified MCs.

Authors

  • Gang Liu
    Department of Interventional Radiology, Qinghai Red Cross Hospital, Xining, Qinghai, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Sheng-Nan You
    State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences & Biomedical Engineering, Hebei University of Technology, Tianjin, China.
  • Zhi Wang
    Department of Pharmacy, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Shan Zhu
    Tianjin Hospital, Tianjin 300211, P.R. China.
  • Chao Chen
    Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Xin-Long Ma
    Department of Spine Surgery, Tianjin Hospital, Tianjin University, Tianjin, China.
  • Lei Yang
    George Mason University.
  • Shuai Zhang
    School of Information, Zhejiang University of Finance and Economics, Hangzhou, China.
  • Qiang Yang

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