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Abstract #0864

Pose-dependent field reconstruction enabled by prospective motion navigation and randomized sampling

Malte Riedel1, Thomas Ulrich2, and Klaas Pruessmann2
1ETH Zurich, Zurich, Switzerland, 2Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland

Synopsis

Keywords: Image Reconstruction, BrainHead motion is accompanied by a multitude of second order motion effects like changing coil sensitivity maps, background field inhomogeneities, and susceptibility-induced fields. While scan geometries and shims can be corrected in real-time, the scanner has no means to counteract changes of the coil sensitivity maps or the susceptibility-induced fields requiring data-driven retrospective motion correction algorithms for these issues. Randomized sampling can further be exploited to improve the problem conditioning of the parameter estimations on temporal sub-segments of the scan. In this work, we evaluate the combination prospective motion navigation with randomized sampling in a pose-dependent field correction algorithm.

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Keywords