Magnetic resonance spectroscopy has many important applications in bio-engineering while the acquisition of high dimensional spectroscopy is usually time consuming. Non-uniformly sampling can speed up the data acquisition but the missing data points have to be restored with proper signal models. In this work, a specific two dimensional magnetic resonance signal, of which the first dimension lies in time domain while the second dimension lies in frequency domain, is reconstructed with a proposed low rank enhanced Hankel matrix method. Results on realistic magnetic resonance spectroscopy shows that proposed method outperform the state-of-art compressed sensing method on recovering low intensities spectral peaks.
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