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Abstract #2461

Blind Retrospective Motion Correction of MR Images

Alexander Loktyushin1, Hannes Nickisch2, Rolf Pohmann3, Bernhard Schlkopf1

1Max Planck Institute for Intelligent Systems, Stuttgart, Germany; 2Philips Research Laboratories, Hamburg, Germany; 3Max Planck Institute for Biological Cybernetics, Tbingen, Germany

Patient motion in the scanner is one of the most challenging problems in MRI. We propose a new retrospective motion correction method for which no tracking devices or specialized sequences are required. We seek the motion parameters such that the image gradients in the spatial domain become sparse. We then use these parameters to invert the motion and recover the sharp image. In our experiments we acquired 2D TSE images and 3D FLASH/MPRAGE volumes of the human head. Major quality improvements are possible in the 2D case and substantial improvements in the 3D case.

Keywords

acquisition adaptation additional affected artifacts assume avoid become belonging binary bingen biological blind blocks bottleneck brain cameras cause challenging coarse computational consider containing correction costing costs cubes currently cybernetics decomposed degradations degraded degrees depending details detect developing devices domain done equivalent evaluation expensive fast field fine fixed flash free frequencies general good gradient gradients grid grids growing hamburg head highest highly human ignore improve improvement induced institute intelligent intensity invert invertible iterations laboratories laird like linear little local major manner mask matrix meaningless medical millimeters minutes missing model morphological motion multiplication navigator noise nonlinear note objective offsets optimizer orientation orthonormal patient pipe pixels problems produce propose prospective quality ramp reconstruct recovery relatively remove render required restoration restored retrospective rigid rotated rotation rotations ruin running scale schemes seek sharp space sparse spatial speaking strictly strong subject subsequent substantial switch systems takes target tolerate tracking trajectories transactions transformation transforms translation unknown volume volumes