Image Quality Control in Lumbar Spine Radiography Using Enhanced U-Net Neural Networks.

Journal: Frontiers in public health
Published Date: Apr 26, 2022

Abstract

PURPOSE: To standardize the radiography imaging procedure, an image quality control framework using the deep learning technique was developed to segment and evaluate lumbar spine x-ray images according to a defined quality control standard.

Authors

  • Xiao Chen
  • Qingshan Deng
    Department of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
  • Qiang Wang
    Ningbo Konfoong Bioinformation Tech Co., Ltd, Ningbo, China.
  • Xinmiao Liu
    School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China.
  • Lei Chen
    Department of Chemistry, Stony Brook University Stony Brook NY USA.
  • Jinjin Liu
    School of Public Health, Hengyang Medical School, University of South China, Hengyang 421001, P. R. China.
  • Shuangquan Li
    Department of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
  • Meihao Wang
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, PR China.
  • Guoquan Cao
    Department of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

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