Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study.

Journal: Diagnostic and interventional imaging
Published Date: Nov 8, 2023

Abstract

PURPOSE: The purpose of this study was to compare the performance of Precise IQ Engine (PIQE) and Advanced intelligent Clear-IQ Engine (AiCE) algorithms on image-quality according to the dose level in a cardiac computed tomography (CT) protocol.

Authors

  • Joël Greffier
    Department of Medical Imaging, CHU Nimes, Medical Imaging Group Nimes, Univ Montpellier, EA 2415, Bd Prof Robert Debré, 30029, Nîmes Cedex 9, France. joel.greffier@chu-nimes.fr.
  • Maxime Pastor
    IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
  • Salim Si-Mohamed
    Department of Radiology, Hospices Civils de Lyon, 69500 Lyon, France.
  • Cynthia Goutain-Majorel
    Department of Medical Imaging, Centre Hospitalier de Perpignan, 66000 Perpignan, France.
  • Aude Peudon-Balas
    Department of Medical Imaging, Centre Hospitalier de Perpignan, 66000 Perpignan, France.
  • Mourad Zoubir Bensalah
    Department of Medical Imaging, Centre Hospitalier de Perpignan, 66000 Perpignan, France.
  • Julien Frandon
    Department of Medical Imaging, CHU Nimes, Medical Imaging Group Nimes, Univ Montpellier, EA 2415, Bd Prof Robert Debré, 30029, Nîmes Cedex 9, France.
  • Jean-Paul Beregi
    DRIM France IA, 75013 Paris, France; Collège des Enseignants en Radiologie de France (CERF), 75013 Paris, France; Medical Imaging Group Nîmes, Nîmes University Hospital, 34000 Nîmes, France.
  • Djamel Dabli
    Department of Medical Imaging, CHU Nimes, Univ Montpellier, Medical Imaging Group Nimes, EA 2992, 30029 Nîmes, France.

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