Minimizing prostate diffusion weighted MRI examination time through deep learning reconstruction.

Journal: Clinical imaging
PMID: 39532043

Abstract

PURPOSE: To study the diagnostic image quality of high b-value diffusion weighted images (DWI) derived from standard and variably reduced datasets reconstructed with a commercially available deep learning reconstruction (DLR) algorithm.

Authors

  • Rory L Cochran
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States. Electronic address: rcochran@mgh.harvard.edu.
  • Eugene Milshteyn
    GE HealthCare, Boston, MA, United States. Electronic address: Eugene.Milshteyn@ge.com.
  • Soumyadeep Ghosh
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States. Electronic address: sghosh18@mgh.harvard.edu.
  • Nabih Nakrour
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States. Electronic address: nnakrour1@mgh.harvard.edu.
  • Nathaniel D Mercaldo
    Massachusetts General Hospital Institute for Technology Assessment, Boston, MA, United States of America.
  • Arnaud Guidon
    GE HealthCare, Boston, MA, United States. Electronic address: arnaud.guidon@ge.com.
  • Mukesh G Harisinghani
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States. Electronic address: mharisinghani@mgh.harvard.edu.

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