Trends in the application of deep learning networks in medical image analysis: Evolution between 2012 and 2020.

Journal: European journal of radiology
Published Date: Nov 24, 2021

Abstract

PURPOSE: To evaluate the general rules and future trajectories of deep learning (DL) networks in medical image analysis through bibliometric and hot spot analysis of original articles published between 2012 and 2020.

Authors

  • Lu Wang
    Department of Laboratory, Akesu Center of Disease Control and Prevention, Akesu, China.
  • Hairui Wang
    Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
  • Yingna Huang
    School of Health Management, China Medical University, Shenyang, Liaoning 110122, PR China.
  • Baihui Yan
    School of Health Management, China Medical University, Shenyang, Liaoning 110122, PR China.
  • Zhihui Chang
    Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
  • Zhaoyu Liu
    Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
  • Mingfang Zhao
    Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China.
  • Lei Cui
    School of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China.
  • Jiangdian Song
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Liaoning, Shenyang, 110819, China.
  • Fan Li
    Department of Instrument Science and Engineering, School of SEIEE, Shanghai Jiao Tong University, Shanghai 200240, China.

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