Automatic Identification and Segmentation of Orbital Blowout Fractures Based on Artificial Intelligence.

Journal: Translational vision science & technology
Published Date: Apr 3, 2023

Abstract

PURPOSE: The incidence of orbital blowout fractures (OBFs) is gradually increasing due to traffic accidents, sports injuries, and ocular trauma. Orbital computed tomography (CT) is crucial for accurate clinical diagnosis. In this study, we built an artificial intelligence (AI) system based on two available deep learning networks (DenseNet-169 and UNet) for fracture identification, fracture side distinguishment, and fracture area segmentation.

Authors

  • Xiao-Li Bao
    Department of Ophthalmology, The Second Norman Bethune Hospital of Jilin University, Changchun, China.
  • Xi Zhan
    The Army Engineering University of PLA, Nanjing, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Qi Zhu
    Medical Research Center, Southwestern Hospital, Army Medical University, Chongqing 400037, P.R. China.
  • Bin Fan
    National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R.China.
  • Guang-Yu Li
    Department of Ophthalmology, The Second Norman Bethune Hospital of Jilin University, Changchun, China.

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