Minimum-norm reconstruction for sensitivity-encoded magnetic resonance spectroscopic imaging.

In this work we propose minimum-norm reconstruction as a means to enhance the spatial response behavior in parallel spectroscopic MRI. By directly optimizing the shape of the spatial response function (SRF), the new method accounts for coil sensitivity variation across individual voxels and their side lobes. In this fashion, it mitigates the signal contamination and side-lobe aliasing, to which previous techniques are susceptible at low resolution. Although the computational burden is higher, minimum-norm reconstruction is shown to be feasible using an iterative algorithm. Benefits in terms of SRF shape and artifact suppression are demonstrated.