Evaluating medical images using deep convolutional neural networks: A simulated CT phantom image study.

Journal: Technology and health care : official journal of the European Society for Engineering and Medicine
Published Date: Jan 1, 2020

Abstract

BACKGROUND: Applied research on artificial intelligence, mainly in deep learning, is widely performed. If medical images can be evaluated using artificial intelligence, this could substantially improve examination efficiency.

Authors

  • Norio Hayashi
    Department of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.
  • Tomoko Maruyama
    Department of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.
  • Yusuke Sato
    Graduate School of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.
  • Haruyuki Watanabe
    Department of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.
  • Toshihiro Ogura
    Department of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.
  • Akio Ogura
    Department of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan.

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