A novel
compartmental low rank algorithm and data acquisition method for high
resolution MR spectroscopic imaging without the use of any lipid suppression
methods is introduced. The field inhomogeneity compensated data is modeled as
the sum of a lipid dataset and a metabolite dataset using the spatial
compartmental information obtained from the water reference data. These
datasets are modelled to be low-rank subspaces and are assumed to be mutually
orthogonal. The high resolution spiral acquisition method achieves in plane resolution of upto 1.8x1.8 mm2 in 7.2 mins. Recovery from these measurements
is posed as a low rank recovery problem. Experiments on in-vivo data
demonstrates comparable results for both lipid suppressed and lipid unsuppressed
data.
