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| Paper IPM / Cognitive / 14229 |
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INTRODUCTION: Long acquisition times of 2D and 3D 1H MR Spectroscopic Imaging (1H-MRSI) are a major obstacle to its widespread clinical application. Compressed Sensing (CS) allows accelerated 1H-MRSI acquisitions through reconstruction of nonuniform randomly subsampled k-space [1]. CS can reliably reconstruct the subsampled MRSI data with meaningful selection of regularizers that consider spars and compressible nature of MR spectra. In this study, we implemented CS directly based on the
spectral-spatial sparsity of spectra for reconstruction [2]. The efficiency of the CS method was evaluated by calculating the difference in NAA, Creatine (Cr) and Choline (Cho) estimation across all voxels compared to full k-space acquisition as determined by LCModel.
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