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Abstract #2521

Density Adapted Stack of Stars Sequence for 23Na using Dictionary Learning Compressed Sensing Reconstruction

Fabian J. Kratzer1, Sebastian Flassbeck1, Armin M. Nagel1,2, Peter Bachert1, Mark E. Ladd1, and Nicolas G. R. Behl1

1German Cancer Research Center (DKFZ), Heidelberg, Germany, 2University Hospital Erlangen, Erlangen, Germany

Sodium plays important roles in many cellular processes, which motivates imaging of the 23Na distribution. Short relaxation times and low in-vivo signal result in the need of sequences with short echo times and techniques to improve the SNR. Therefore, we present a stack of stars (SOS) sequence with density adapted readout gradients to increase SNR. We combine this sequence with an anisotropic dictionary learning compressed sensing reconstruction to further reduce noise in the images.

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