Artificial Intelligence in Neuroradiology: Current Status and Future Directions.

Journal: AJNR. American journal of neuroradiology
Published Date: Aug 1, 2020

Abstract

Fueled by new techniques, computational tools, and broader availability of imaging data, artificial intelligence has the potential to transform the practice of neuroradiology. The recent exponential increase in publications related to artificial intelligence and the central focus on artificial intelligence at recent professional and scientific radiology meetings underscores the importance. There is growing momentum behind leveraging artificial intelligence techniques to improve workflow and diagnosis and treatment and to enhance the value of quantitative imaging techniques. This article explores the reasons why neuroradiologists should care about the investments in new artificial intelligence applications, highlights current activities and the roles neuroradiologists are playing, and renders a few predictions regarding the near future of artificial intelligence in neuroradiology.

Authors

  • Y W Lui
    From the Department of Radiology (Y.W.L.), New York University Langone Medical Center, New York, New York.
  • P D Chang
    From the Departments of Radiology (P.D.C., E.K., M.T., R.H., M.-Y.S., D.C.).
  • G Zaharchuk
    From the Departments of Radiology (G.Z., M.W., D.R., C.P.L.) gregz@stanford.edu.
  • D P Barboriak
    Department of Radiology (D.P.B.), Duke University Medical Center, Durham, North Carolina.
  • A E Flanders
    Department of Radiology (A.E.F.), Thomas Jefferson University Hospital, Philadelphia, Pennsylvania.
  • M Wintermark
    From the Departments of Radiology (G.Z., M.W., D.R., C.P.L.).
  • C P Hess
    Department of Radiology and Biomedical Imaging (C.P.H.), University of California, San Francisco, San Francisco, California.
  • C G Filippi
    Department of Radiology (C.G.F.), North Shore University Hospital, Long Island, New York.

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