Deep learning-based MR-to-CT synthesis: The influence of varying gradient echo-based MR images as input channels.

Abstract

Authors

• Mateusz C Florkow
  Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
• Frank Zijlstra
  Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
• Koen Willemsen
  Department of Orthopedics, University Medical Center Utrecht, Utrecht, Netherlands.
• Matteo Maspero
  Department of Radiation Oncology, Imaging and Cancer Division, University Medical Center Utrecht, Utrecht, The Netherlands; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
• Cornelis A T van den Berg
  Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
• Linda G W Kerkmeijer
  Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, Netherlands.
• René M Castelein
  Department of Orthopedics, University Medical Center Utrecht, Utrecht, Netherlands.
• Harrie Weinans
  Department of Biomechanical Engineering, Faculty of Mechanical, Maritime, and Materials Engineering, Delft University of Technology (TU Delft), Mekelweg 2, 2628CD Delft, The Netherlands; Department of Orthopedics, UMC Utrecht, Heidelberglaan 100, 3584CX Utrecht, The Netherlands; Department of Rheumatology, UMC Utrecht, Heidelberglaan 100, 3584CX Utrecht, The Netherlands.
• Max A Viergever
• Marijn van Stralen
  Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
• Peter R Seevinck
  Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.

Keywords

External Resources