Abstract #4644

Data-consistent Retrospective Motion Correction and Co-Registration

Michael Fieseler¹, Georg Schramm², Johan Nuyts², Klaus P. Schäfers¹, and Fernando E. Boada³

¹European Institute for Molecular Imaging, University of Muenster, Muenster, Germany, ²Department of Imaging and Pathology, Division of Nuclear Medicine, UZ Leuven and KU Leuven, Leuven, Belgium, ³Radiological Sciences Laboratory, Standford University, Stanford, CA, United States

Synopsis

Keywords: Motion Correction, Motion Correction

Motivation: Motion correction algorithms based on Image-based co-registration of retrospectively ordered motion states have limited effectiveness for highly accelerated scans.

Goal(s): To develop a robust motion correction algorithm for highly accelerated dynamic MRI scans.

Approach: We developed an approach that jointly, and data-consistently, estimates motion-corrected images and motion fields.

Results: Simulated and experimental results demonstrate that the proposed approach yields improved motion-corrected images at high acceleration factors during dynamic MRI scans.

Impact: The proposed approach could remove previously reported limitations on the use of retrospectively re-ordered dynamic MRI scans.

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