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Abstract #3390

Data-Driven non-Cartesian trajectory correction based on Cartesian reference data

Felix Horger1, Mathias Nittka1, and Gregor Körzdörfer1
1Siemens Healthcare, Erlangen, Germany

Trajectory deformations in non-Cartesian scans can lead to significant image artifacts, while in comparison the effect on Cartesian scans is evidentially minor. We propose a novel approach for trajectory correction relying on the minimization of a suitable measure between a non-Cartesian image and a Cartesian reference image, given a trajectory deformation model. Our proof of concept is applied on simulated as well as measured data. The approach is fast, accurate and easily extendable. Given the right use-case, no extra scan time is required (e.g. mixed spiral-Cartesian MR Fingerprinting).

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