A semi-supervised learning-based quality evaluation system for digital chest radiographs.

Journal: Medical physics
Published Date: Nov 1, 2023

Abstract

BACKGROUND: Digital radiography is the most commonly utilized medical imaging technique worldwide, and the quality of radiographs plays a crucial role in accurate disease diagnosis. Therefore, evaluating the quality of radiographs is an essential step in medical examinations. However, manual evaluation can be time-consuming, labor-intensive, and prone to interobserver differences, making it less reliable.

Authors

  • Shuoyang Wei
    Department of Engineering Physics, Tsinghua University, Beijing, China.
  • Rui Qiu
    Department of Engineering Physics, Tsinghua University, Beijing, China.
  • Yanheng Pu
    Department of Engineering Physics, Tsinghua University, Beijing, China.
  • Ankang Hu
    Department of Engineering Physics, Tsinghua University, Beijing, China.
  • Yantao Niu
    Beijing Tongren Hospital, CMU, Beijing, China.
  • Zhen Wu
    Department of Neurosurgery/China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, China.
  • Hui Zhang
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Junli Li
    School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650093, China.

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