Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Jan 18, 2023

Abstract

BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI).

Authors

  • Angela Tong
    Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.
  • Barun Bagga
    Department of Radiology, NYU Langone Health, New York, New York, USA.
  • Robert Petrocelli
    Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York, USA.
  • Paul Smereka
    Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.
  • Abhinav Vij
    Department of Radiology, NYU Langone Health, New York, New York, USA.
  • Kun Qian
    Key Laboratory of Brain Health Intelligent Evaluation and Intervention (Beijing Institute of Technology), Ministry of Education, Beijing, China.
  • Robert Grimm
    Computational Linguistics & Psycholinguistics Research Center, Department of Linguistics, University of Antwerp, Antwerp, Belgium.
  • Ali Kamen
    755 College Road East, Digital Technology and Innovation Division, Siemens Healthineers, Princeton, NJ, 08540.
  • Mahesh B Keerthivasan
    Department of Medical Imaging, University of Arizona, Tucson, AZ, United States of America; Siemens Healthcare, Tucson, AZ, USA.
  • Marcel Dominik Nickel
    MR Application Predevelopment, Siemens Healthineers AG, Erlangen, Germany.
  • Heinrich von Busch
    Digital Health, Siemens Healthineers, Erlangen, Germany.
  • Hersh Chandarana
    Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.

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