Keywords: Spectroscopy, Image Reconstruction, MRSI quantificationConventional MRSI methods perform MRSI image reconstruction and spectral quantification in two separate steps. This work presents a novel direct estimation method for MRSI that reconstructs high-resolution metabolite concentration maps from undersampled k-space data, leveraging a linear tangent space alignment (LTSA) model for spectral quantification and a low-rank (LR) model for denoising. Furthermore, the proposed framework allows estimating the temporal basis functions of the LR model from the undersampled, noise-corrupted k-space data, thus eliminating the need for experiment-dependent or pre-acquired spectral training data. The performance of the proposed method was validated using numerical simulation phantom and in vivo MRSI data.
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