Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T.

Abstract

Authors

• Teresa Lemainque
  Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany. Electronic address: tlemainque@ukaachen.de.
• Masami Yoneyama
  Philips Japan, Konan 2-13-37, Minato-ku, Tokyo 108-8507, Japan.
• Chiara Morsch
  Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany.
• Elene Iordanishvili
  Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany.
• Alexandra Barabasch
  Department of Diagnostic and Interventional Radiology, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany.
• Maximilian Schulze-Hagen
  Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany.
• Johannes M Peeters
  Philips Healthcare, Veenpluis 4-6, Building QR-0.113, 5684, Best, PC, Netherlands.
• Christiane Kuhl
  Department of Diagnostic and Interventional Radiology, University Hospital Düsseldorf, Düsseldorf, Germany (J.S., D.B.A., S.N.); Institute of Computer Vision and Imaging, RWTH University Aachen, Pauwelsstrasse 30, 52072 Aachen, Germany (J.S., D.M.); Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany (D.T., M.P., F.M., C.K., S.N.); and Faculty of Mathematics and Natural Sciences, Institute of Informatics, Heinrich Heine University Düsseldorf, Düsseldorf, Germany (S.C.).
• Shuo Zhang
  Ph.D. Program in Computer Science, The City University of New York, New York, NY, United States.

Keywords

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