Current Applications and Future Impact of Machine Learning in Radiology.

Journal: Radiology
Published Date: Jun 26, 2018

Abstract

Recent advances and future perspectives of machine learning techniques offer promising applications in medical imaging. Machine learning has the potential to improve different steps of the radiology workflow including order scheduling and triage, clinical decision support systems, detection and interpretation of findings, postprocessing and dose estimation, examination quality control, and radiology reporting. In this article, the authors review examples of current applications of machine learning and artificial intelligence techniques in diagnostic radiology. In addition, the future impact and natural extension of these techniques in radiology practice are discussed.

Authors

  • Garry Choy
  • Omid Khalilzadeh
    From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, Mass 02114 (G.C., O.K., M.M., S.D., A.E.S., O.S.P., P.V.P., J.A.B., K.J.D.); and Department of Radiology, University of Colorado School of Medicine, Aurora, Colo (J.R.G.).
  • Mark Michalski
    From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, Mass 02114 (G.C., O.K., M.M., S.D., A.E.S., O.S.P., P.V.P., J.A.B., K.J.D.); and Department of Radiology, University of Colorado School of Medicine, Aurora, Colo (J.R.G.).
  • Synho Do
    Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. sdo@mgh.harvard.edu.
  • Anthony E Samir
    Division of Ultrasound, Department of Radiology, Center for Ultrasound Research & Translation, Massachusetts General Hospital, Boston, MA, 02114, USA.
  • Oleg S Pianykh
    Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts. Electronic address: opianykh@mgh.harvard.edu.
  • J Raymond Geis
    4 Department of Radiology, University of Colorado School of Medicine, Fort Collins, CO.
  • Pari V Pandharipande
    From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, Mass 02114 (G.C., O.K., M.M., S.D., A.E.S., O.S.P., P.V.P., J.A.B., K.J.D.); and Department of Radiology, University of Colorado School of Medicine, Aurora, Colo (J.R.G.).
  • James A Brink
  • Keith J Dreyer
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States; Mass General Brigham Data Science Office (DSO), Boston, MA, United States.

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