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Abstract #3702

Multidimensional Gradient Encoding: Artifacts Resulting from Destructive Signal Interference

Gerrit Schultz1, Stefan Kroboth2, Daniel Gallichan3, Jrgen Hennig1, Maxim Zaitsev1

1University Medical Center Freiburg, Freiburg, Germany; 2Graz University of Technology, Graz, Austria; 3Center for Biomedical Imaging (CIBM), Lausanne, Switzerland

The researcher or engineer who is working with nonlinear gradient fields is addressed. Maybe the most challenging problem with multi-dimensional trajectories is that they tend to be extremely sensitive to calibration errors. In this abstract a band-shaped artifact that may result from miscalibration is investigated and explained. The analysis reveals how such an artifact can be avoided when designing new multi-dimensional encoding schemes.

Keywords

acquisition actually affected affects appear argument arrow artifact artifacts audience avoided banding bands behavior biomedical black calibrated calibration cancellations caption cause central channels closely come comes components congruence congruent consider constructive controlled corresponds count derive designing despite destructive dimensional distortions education encoding energy engineers equation error errors evaluations eventually exactly example exists explaining explains explanation expression extensive extremely field fields five fold forward function generalized generated gradient hardly hardware heavily heavy helpful helps hence illustrates important increasing indeed intensity interference introduced introduces known local location long loss magma maps match maybe misplacements modified multidimensional neglected nonlinear notice novel object obvious occur occurs offers opposite organ overlapping particularly perfect previous prior problem project proportional qualitative question rather reasonable reconstructed reconstruction related relevant rotated rotating rotation scheme schemes seems shape similarity simulation simulations situation space spatial special superimposing symmetry target tend topic trajectories trajectory true twice typically understanding unique vicinity visited voids whose