Accelerated Diffusion-Weighted Magnetic Resonance Imaging of the Liver at 1.5 T With Deep Learning-Based Image Reconstruction: Impact on Image Quality and Lesion Detection.

Journal: Journal of computer assisted tomography
Published Date: May 6, 2024

Abstract

OBJECTIVE: To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI).

Authors

  • Luke A Ginocchio
    Department of Radiology, NYU Langone Medical Center, 660 First Avenue, 3rd Floor, New York, NY 10016.
  • Sonam Jaglan
    From the Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY.
  • Angela Tong
    Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.
  • Paul N Smereka
    Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, 660 First Avenue, 3rd Floor, New York, NY, 10016, USA.
  • Thomas Benkert
    Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Strasse 6, 97080 Würzburg, Germany (J.F.H., S.V., C.M., L.M.P., T.A.B., H.K., A.M.W.); and Department of Application Development, Siemens Healthcare, Erlangen, Germany (T.B., J.P.).
  • Hersh Chandarana
    Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.
  • Krishna P Shanbhogue
    Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, 660 First Avenue, 3rd Floor, New York, NY, 10016, USA.

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