  Increasing imaging speed is of utmost importance in in-vivo magnetic
resonance imaging (MRI). With simultaneous multi-slice (SMS) MRI we can
simultaneously acquire several slices of an object, which allows for higher
undersampling factors compared to single- or conventional multi-slice
measurements by exploiting axial coil sensitivity information. In this thesis,
we give a short introduction to the physical principles of MRI, cover the
basics of a FLASH based SMS MRI sequence and perform tests to verify its
accuracy: We check the fidelity of the slice distance as well as the flip angle
and confirm the square-root-like signal-to-noise ratio benefit of SMS compared
to conventional multi-slice experiments. A g-factor analysis is used to
determine a favorable Cartesian undersampling scheme for multi-slice data.
Common reconstruction strategies for SMS MRI make use of previously estimated
coil sensitivities to solve a linear equation. Here, we propose a new method of
SMS MRI based on Regularized Nonlinear Inversion (NLINV): SMS-NLINV. This
method does not require a priori knowledge about the coil sensitivities and is
attractive especially for real-time imaging where coil sensitivities may change
due to motion or interactive changes to the slice position. We characterize the
algorithm and present reconstructed phantom and in-vivo images.
