Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI.

Journal: Abdominal radiology (New York)
Published Date: Mar 23, 2024

Abstract

PURPOSE: To compare a previous model-based image reconstruction (MBIR) with a newly developed deep learning (DL)-based image reconstruction for providing improved signal-to-noise ratio (SNR) in high through-plane resolution (1 mm) T2-weighted spin-echo (T2SE) prostate MRI.

Authors

  • Stephen J Riederer
    Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA. riederer@mayo.edu.
  • Eric A Borisch
    Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA.
  • Adam T Froemming
    Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA.
  • Akira Kawashima
    Department of Radiology, Mayo Clinic in Arizona, Phoenix, Arizona.
  • Naoki Takahashi
    1 Department of Radiology, Radiology Informatics Laboratory, Mayo Clinic, 3507 17th Ave NW, Rochester, MN 55901.

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