Application of deep learning-based image reconstruction in MR imaging of the shoulder joint to improve image quality and reduce scan time.

Journal: European radiology
Published Date: Mar 1, 2023

Abstract

OBJECTIVES: To compare the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) MRI sequences with post-processed PROPELLER MRI sequences using deep learning-based (DL) reconstructions.

Authors

  • Malwina Kaniewska
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Raemistrasse 100, CH-8091, Zurich, Switzerland. malwina.kaniewska@usz.ch.
  • Eva Deininger-Czermak
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Raemistrasse 100, CH-8091, Zurich, Switzerland.
  • Jonas M Getzmann
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Raemistrasse 100, CH-8091, Zurich, Switzerland.
  • Xinzeng Wang
    MR Clinical Solutions and Research Collaborations, GE Healthcare, Houston, TX, USA.
  • Maelene Lohezic
    Applications & Workflow, GE Healthcare, Manchester, UK.
  • Roman Guggenberger
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Ramistrasse 100, 8091, Zurich, Switzerland.

Keywords

External Resources

Popular Topics
Recent Journals