Reconstruction of 3D knee MRI using deep learning and compressed sensing: a validation study on healthy volunteers.

Abstract

Authors

• Thomas Dratsch
  Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany. t.dratsch@mac.comn.
• Charlotte Zäske
  Department of Diagnostic and Interventional Radiology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
• Florian Siedek
  Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
• Philip Rauen
  Department of Diagnostic and Interventional Radiology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
• Nils Große Hokamp
  Institute of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
• Kristina Sonnabend
  Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
• David Maintz
  Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
• Grischa Bratke
  Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
• Andra Iuga
  Department of Diagnostic and Interventional Radiology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.

Keywords

External Resources