Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics.

Journal: Investigative radiology
Published Date: Apr 1, 2021

Abstract

OBJECTIVES: The aims of this study were to present a deep learning approach for the automated classification of multiple sclerosis and its mimics and compare model performance with that of 2 expert neuroradiologists.

Authors

  • Maria A Rocca
    Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
  • Nicoletta Anzalone
  • Loredana Storelli
    From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience.
  • Anna Del Poggio
    Neuroradiology Unit, IRCCS San Raffaele Scientific Institute.
  • Laura Cacciaguerra
  • Angelo A Manfredi
  • Alessandro Meani
    From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience.
  • Massimo Filippi
    Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Scientific Institute and University Vita-Salute San Raffaele, Milan, Italy.

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