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Abstract #1308

Dictionary-Learning Compressed Sensing Reconstruction for an Anisotropic 3D Density-Adapted Radial Acquisition Sequence

Matthias Utzschneider1,2, Nicolas G. R. Behl 3, Sebastian Lachner1, Andreas Maier2,4, Michael Uder1, and Armin M. Nagel1,3

1Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 2Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 3Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 4Erlangen Graduate School in Advanced Optical Technologies, Erlangen, Germany

Sodium magnetic resonance imaging requires dedicated acquisition techniques and reconstruction approaches due to the low in-vivo signal and ultra-short relaxation times. For this purpose a compressed sensing reconstruction technique using dictionary learning is applied to raw data acquired with an anisotropic 3D density-adapted radial acquisition sequence. The anisotropic acquisition allows an adjustment of projections in different directions to increase the in-plane resolution. In the following evaluation the possible benefits of the compressed sensing reconstruction using the increased in-plane resolution are shown for in-vivo sodium magnetic resonance imaging and quantification of 23Na.

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