Mirco Grosser1,2 and Tobias Knopp1,2
1Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
1Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
We
propose a fast algorithm for the reconstruction of non-cartesian
acquisitions with
B0-inhomogeneity.
The
proposed method uses a
new
SVD-based approximation of
the
B0-aware
imaging
operator in
combination with diagonal k-space preconditioning.
Figure 4: Two reconstructed slices of
the brain dataset. Reconstructions were performed using TS with $$$L=10$$$
(second column), TS with $$$L=20$$$ (third column) and the proposed
SVD-based method (fourth
column).
Figure 5: The upper part of the
figure shows the normalized root mean squared deviation (NRMSD) of
the reconstructed slices. The middle
part displays the number of basis functions $$$L$$$ employed by the
SVD based approximation. The bottom plot shows the NRMSD in
dependence of the iterations of the PDHG solver.