Trends and hotspots in research on medical images with deep learning: a bibliometric analysis from 2013 to 2023.

Journal: Frontiers in artificial intelligence
Published Date:

Abstract

BACKGROUND: With the rapid development of the internet, the improvement of computer capabilities, and the continuous advancement of algorithms, deep learning has developed rapidly in recent years and has been widely applied in many fields. Previous studies have shown that deep learning has an excellent performance in image processing, and deep learning-based medical image processing may help solve the difficulties faced by traditional medical image processing. This technology has attracted the attention of many scholars in the fields of computer science and medicine. This study mainly summarizes the knowledge structure of deep learning-based medical image processing research through bibliometric analysis and explores the research hotspots and possible development trends in this field.

Authors

  • Borui Chen
    First School of Clinical Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
  • Jing Jin
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
  • Haichao Liu
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
  • Zhengyu Yang
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
  • Haoming Zhu
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
  • Yu Wang
    Clinical and Technical Support, Philips Healthcare, Shanghai, China.
  • Jianping Lin
    The School of Health, Fujian Medical University, Fuzhou, China.
  • Shizhong Wang
    The School of Health, Fujian Medical University, Fuzhou, China.
  • Shaoqing Chen
    College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.

Keywords

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