2019 JRNL PP Patryk Szwargulski - 1.pdf
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
Due to peripheral nerve stimulation, the magnetic
particle imaging (MPI) method is limited in the maximumapplicableexcitation-
fieldamplitude. This in turn leads
to a limitation of the size of the covered field of view (FoV)
to few millimeters. In order to still capture a larger FoV,
MPI is capable to rapidly acquire volumes in a multi-patch
fashion. To this end, the small excitation volume is shifted
through space using the magnetic focus fields. Recently,
it has been shown that the individual patches are preferably
reconstructed in a joint fashion by solving a single linear
system of equations taking the coupling between individual
patches into account. While this improves the image
quality, it is computationally and memory demanding since
the size of the linear system increases in the best case
quadratically with the number of patches. In this paper,
we will develop a reconstruction algorithm for MPI multipatch
data exploiting the sparsity of the joint systemmatrix.
A highly efficient implicit matrix format allows for rapid onthe-
fly calculations of linear algebra operations involving
the system matrix. Using this approach, the computational
effort can be reduced to a linear dependence on the number
of used patches. The algorithm is validated on 3-D multipatch
phantom data sets and shown to reconstruct large
data sets with 15 patches in less than 22 s.