Technical performance of a dual-energy CT system with a novel deep-learning based reconstruction process: Evaluation using an abdomen protocol.

Journal: Medical physics
Published Date: Mar 1, 2023

Abstract

BACKGROUND: A new tube voltage-switching dual-energy (DE) CT system using a novel deep-learning based reconstruction process has been introduced. Characterizing the performance of this DE approach can help demonstrate its benefits and potential drawbacks.

Authors

  • Luuk J Oostveen
    Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101 (route 766), 6500 HB, Nijmegen, The Netherlands. Luuk.Oostveen@radboudumc.nl.
  • Kirsten L Boedeker
    Canon Medical Systems Corporation, Otawara, Japan.
  • Christiana Balta
    Canon Medical Systems Corporation, Otawara, Japan.
  • Daniel Shin
    Center for Robotic Simulation & Education, Catherine & Joseph Aresty Department of Urology, University of Southern California Institute of Urology, Los Angeles, California.
  • Frank de Lange
    Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101 (route 766), 6500 HB, Nijmegen, The Netherlands.
  • Mathias Prokop
    Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Ioannis Sechopoulos
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.

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