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Abstract #0474

Nonrigid Motion Correction using 3D iNAVs with Generalized Motion Compensated Reconstruction and Autofocusing

Srivathsan Prabu Koundinyan1, Corey Allan Baron1, Nicholas Dwork1, Joseph Yitan Cheng1, and Dwight George Nishimura1

1Electrical Engineering, Stanford University, Stanford, CA, United States

We present a novel framework to combine two well-known methods for motion correction: generalized motion compensated reconstruction (GMCR) and autofocusing. In this hybrid technique, 3D image-based navigators (3D iNAVs) are utilized for motion tracking. The beat-to-beat and voxel-by-voxel motion information within the 3D iNAVs are directly inputted into GMCR to mitigate motion artifacts. To reduce computation time, an autofocusing step is incorporated. The overall correction scheme is evaluated in free-breathing coronary magnetic resonance angiography and renal magnetic resonance angiography exams. In all six in vivo studies, images reconstructed with the proposed strategy outperform those generated with beat-to-beat 3D translational correction.

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