<p>Localized Magnetic Resonance Spectroscopy is a non-invasive tool that offers insight into physiological status via signals arising from biological compounds. Unambiguous evaluation of said signals, however; is intrinsically limited by self interference through signal overlap. J Resolved Spectroscopy introduces an additional dimension to the measured signal which reduces overlap at the cost of increasing the scan duration. Compressed Sensing is a growing mathematical framework that asserts that under certain conditions, if a signal admits a sparse representation then it can be recovered from fewer measurements than required by classical signal theory. This framework has been successfully applied in high resolution Nuclear Magnetic Resonance experiments, justifying the investigation into its applicability in the realm of localized Magnetic Resonance Spectroscopy. The problem is addressed by optimizing the Compressed Sensing recovery on model spectra and evaluated in vitro through a parametric approach.</p> / <p>Localized Magnetic Resonance Spectroscopy is a non-invasive tool that o↵ers insight into physiological status via signals arising from biological compounds. Unambiguous evaluation of said signals, however; is intrinsically limited by self interference through signal overlap. J Resolved Spectroscopy introduces an additional dimension to the measured signal which reduces overlap at the cost of increasing the scan duration. Compressed Sensing is a growing mathematical framework that asserts that under certain conditions, if a signal admits a sparse representation then it can be recovered from fewer measurements than required by classical signal theory. This framework has been successfully applied in high resolution Nuclear Magnetic Resonance experiments, justifying the investigation into its applicability in the realm of localized Magnetic Resonance Spectroscopy. The problem is addressed by optimizing the Compressed Sensing recovery on model spectra and evaluated in vitro through a parametric approach.</p> / Master of Applied Science (MASc)