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Abstract #0127

Nonrigid Motion-corrected Reconstruction Using Image-space Gridding for Free-breathing Cardiac MRI

Kwang Eun Jang1,2, Mario O. Malavé1, Dwight G. Nishimura1, and Shreyas S. Vasanawala3
1Magnetic Resonance Systems Research Lab (MRSRL), Department of Electrical Engineering, Stanford University, Stanford, CA, United States, 2Department of Bioengineering, Stanford University, Stanford, CA, United States, 3Department of Radiology, Stanford University, Stanford, CA, United States

Motion remains a major challenge in MRI. Many motion-corrected reconstruction methods are available, yet models are often simplified. We propose image-space gridding that resamples images onto arbitrary grids, which provides a pair of operators that represents the forward and adjoint of a nonrigid transform. This allows existing nonrigid image registration techniques to be incorporated into model-based reconstructions. We apply this method to correct for respiratory motion in free-breathing cardiac MRI. Data from individual heartbeats are binned to reconstruct image-based self-navigators. Nonrigid motion is estimated using a diffeomorphic demons algorithm, and corrected by solving an optimization problem with image-space gridding operators.

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