Main Article Content
In magnetic particle imaging, the time consuming measurement of a system matrix is required before image reconstruction.
Reduction of measurement time can be achieved with the help of compressed sensing, which is based on the sparsity of the system
matrix in a suitable transform domain. In this work, we propose regularization functions to exploit the additional correlations in multi-
patch system matrices. Experiments show that the resulting recovery method allows successful matrix recovery at higher
undersampling factors than a standard compressed sensing recovery.
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009035, DOI: 10.18416/IJMPI.2020.2009035