Contribution of an artificial intelligence deep-learning reconstruction algorithm for dose optimization in lumbar spine CT examination: A phantom study.

Journal: Diagnostic and interventional imaging
Published Date: Sep 11, 2022

Abstract

PURPOSE: The purpose of this study was to assess the impact of the new artificial intelligence deep-learning reconstruction (AI-DLR) algorithm on image quality and radiation dose compared with iterative reconstruction algorithm in lumbar spine computed tomography (CT) examination.

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.
  • 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.
  • Quentin Durand
    Department of Medical Imaging, CHU Nîmes, Univ Montpellier, Nîmes Medical Imaging Group, EA 2992, Bd. Prof Robert Debré, 30029, Nîmes Cedex 9, France.
  • Tarek Kammoun
    IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
  • Maeliss Loisy
    IMAGINE, UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, 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.

Keywords

External Resources

Popular Topics
Recent Journals