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Tensor-Based Method for Residual Water Suppression in H-1 Magnetic Resonance Spectroscopic Imaging

Tijdschriftbijdrage - Tijdschriftartikel

OBJECTIVE: Magnetic resonance spectroscopic imaging (MRSI) signals are often corrupted by residual water and artifacts. Residual water suppression plays an important role in accurate and efficient quantification of metabolites from MRSI. A tensor-based method for suppressing residual water is proposed. METHODS: A third-order tensor is constructed by stacking the Löwner matrices corresponding to each MRSI voxel spectrum along the third mode. A canonical polyadic decomposition is applied on the tensor to extract the water component and to, subsequently, remove it from the original MRSI signals. RESULTS: The proposed method applied on both simulated and in-vivo MRSI signals showed good water suppression performance. CONCLUSION: The tensor-based Löwner method has better performance in suppressing residual water in MRSI signals as compared to the widely used subspace-based Hankel singular value decomposition method. SIGNIFICANCE: A tensor method suppresses residual water simultaneously from all the voxels in the MRSI grid and helps in preventing the failure of the water suppression in single voxels.
Tijdschrift: IEEE Transactions on Biomedical Engineering
ISSN: 0018-9294
Issue: 2
Volume: 66
Pagina's: 584 - 594
Aantal pagina's: 11
Jaar van publicatie:2019