Assessment of deep learning-based reconstruction on T2-weighted and diffusion-weighted prostate MRI image quality.

Journal: European journal of radiology
Published Date: Jul 28, 2023

Abstract

PURPOSE: To evaluate the impact of a commercially available deep learning-based reconstruction (DLR) algorithm with varying combinations of DLR noise reduction settings and imaging parameters on quantitative and qualitative image quality, PI-RADS classification and examination time in prostate T2-weighted (T2WI) and diffusion-weighted (DWI) imaging.

Authors

  • Kang-Lung Lee
    Department of Radiology, University of Cambridge, United Kingdom; Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Dimitri A Kessler
    Department of Radiology, University of Cambridge, Cambridge, United Kingdom. Electronic address: dak50@cam.ac.uk.
  • Simon Dezonie
    GE HealthCare, Amersham, United Kingdom.
  • Wellington Chishaya
    Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom.
  • Christopher Shepherd
    Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom.
  • Bruno Carmo
    Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom.
  • Martin J Graves
    Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom.
  • Tristan Barrett
    Department of Radiology, University of Cambridge, Cambridge, UK.

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