Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics.

Journal: European radiology
Published Date: May 9, 2024

Abstract

OBJECTIVE: Deep learning (DL) MRI reconstruction enables fast scan acquisition with good visual quality, but the diagnostic impact is often not assessed because of large reader study requirements. This study used existing diagnostic DL to assess the diagnostic quality of reconstructed images.

Authors

  • Quintin van Lohuizen
    University Medical Centre Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands. q.y.van.lohuizen@umcg.nl.
  • Christian Roest
    Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Meditech Building, Room 305, Hanzeplein 1, 9700 RB, Groningen, The Netherlands.
  • Frank F J Simonis
    Technical University Twente, TechMed Centre, Hallenweg 5, 7522 NH, Enschede, the Netherlands.
  • Stefan J Fransen
    University Medical Centre Groningen, Department of Radiology, Hanzeplein 1, 9713 GZ, Groningen, the Netherlands. Electronic address: S.j.fransen@umcg.nl.
  • Thomas C Kwee
    Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Derya Yakar
    Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. Electronic address: d.yakar@umcg.nl.
  • Henkjan Huisman
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.

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