Advancements in supervised deep learning for metal artifact reduction in computed tomography: A systematic review.

Abstract

Authors

• Cecile E J Kleber
  Department of Clinical Technology, Faculty of Mechanical Engineering, Delft University of Technology, Delft, the Netherlands.
• Ramez Karius
  Department of Clinical Technology, Faculty of Mechanical Engineering, Delft University of Technology, Delft, the Netherlands.
• Lucas E Naessens
  Department of Clinical Technology, Faculty of Mechanical Engineering, Delft University of Technology, Delft, the Netherlands.
• Coen O Van Toledo
  Department of Clinical Technology, Faculty of Mechanical Engineering, Delft University of Technology, Delft, the Netherlands.
• Jochen A C van Osch
  Department of Radiology, Isala Hospital, Zwolle, the Netherlands.
• Martijn F Boomsma
  Department of Radiology and Nuclear Medicine, Isala, P.O. Box 10400, 8000 GK Zwolle, The Netherlands.
• Jan W T Heemskerk
  Department of Radiology C-2S, Leiden University Medical Center, Albinusdreef 2, NL-2333 ZA, Leiden, The Netherlands.
• Aart J van der Molen
  Department of Radiology C-2S, Leiden University Medical Center, Albinusdreef 2, NL-2333 ZA, Leiden, The Netherlands.

Keywords

External Resources