Candice A. Bookwalter1, Nicole Seiberlich2, Michael W. Harrell3, Philipp Ehses4, 5, Mark A. Griswold1, 6, Vikas Gulani1, 2
1Department of Radiology, University Hospitals Case Medical Center\Case Western Reserve University, Cleveland, OH, United States; 2Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; 3School of Medicine, Case Western Reserve University, Cleveland, OH, United States; 4Max Planck Institute for Biological Cybernetics, Tbingen, Germany; 5Department for Neuroimaging, University Hospital Tbingen, Tbingen, Germany; 6Department of Biomedical Engineering, Case Western Reserve University, Cleveland , OH, United States
While radial k-space trajectories are known to be inherently insensitive to motion due to the oversampling of the center of k-space, patient motion causes image degradation by object distortion and streaking artifacts. An algorithm called Motion Artifact Removal by Retrospective Resolution Reduction (MARs) for rectilinear trajectories has been previously described, which automatically and retrospectively identifies a transition between breath hold to free breathing and subsequently removes the corrupted data for a motion artifact free, yet lower resolution image. This work expands the MARs method to radial sequences demonstrated through volunteer and patient data.