Comparison of two versions of a deep learning image reconstruction algorithm on CT image quality and dose reduction: A phantom study.

Abstract

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.
• Djamel Dabli
  Department of Medical Imaging, CHU Nimes, Univ Montpellier, Medical Imaging Group Nimes, EA 2992, 30029 Nîmes, 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.
• Aymeric Hamard
  Department of Medical Imaging, CHU Nimes, Medical Imaging Group Nimes, Univ Montpellier, EA 2415, Bd Prof Robert Debré, 30029, Nîmes Cedex 9, France.
• Asmaa Belaouni
  Department of Medical Imaging, CHU Nimes, Univ Montpellier, Medical Imaging Group Nimes, EA 2992, 30029 Nîmes, France.
• Philippe Akessoul
  Department of Medical Imaging, CHU Nimes, Univ Montpellier, Medical Imaging Group Nimes, EA 2992, 30029 Nîmes, France.
• Yannick Fuamba
  Computed Tomography Division, Canon Medical Systems France, Suresnes, France.
• Julien Le Roy
  Medical Physics Department, Montpellier University Hospital, Montpellier, France.
• Boris Guiu
  Department of RadiologySt-Eloi University HospitalMontpellierFrance.
• 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.

Keywords

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