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1
Spectral Quantification for High-Resolution MR Spectroscopic Imaging With Spatiospectral Constraints.
IEEE Trans Biomed Eng. 2017 May;64(5):1178-1186. doi: 10.1109/TBME.2016.2594583. Epub 2016 Jul 27.
2
A Subspace Approach to Spectral Quantification for MR Spectroscopic Imaging.
IEEE Trans Biomed Eng. 2017 Oct;64(10):2486-2489. doi: 10.1109/TBME.2017.2741922. Epub 2017 Aug 18.
3
Spatio-spectral regularization to improve magnetic resonance spectroscopic imaging quantification.
NMR Biomed. 2016 Jul;29(7):918-31. doi: 10.1002/nbm.3532. Epub 2016 May 11.
4
A semiadiabatic spectral-spatial spectroscopic imaging (SASSI) sequence for improved high-field MR spectroscopic imaging.
Magn Reson Med. 2016 Oct;76(4):1071-82. doi: 10.1002/mrm.26025. Epub 2015 Oct 31.
5
High-resolution (1) H-MRSI of the brain using SPICE: Data acquisition and image reconstruction.
Magn Reson Med. 2016 Oct;76(4):1059-70. doi: 10.1002/mrm.26019. Epub 2015 Oct 28.
6
Improved reconstruction for MR spectroscopic imaging.
IEEE Trans Med Imaging. 2007 May;26(5):686-95. doi: 10.1109/TMI.2007.895482.
7
8
Fast nosologic imaging of the brain.
J Magn Reson. 2007 Feb;184(2):292-301. doi: 10.1016/j.jmr.2006.10.017. Epub 2006 Nov 22.
9
Correction of field inhomogeneity effects on limited k-space MRSI data using anatomical constraints.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:883-6. doi: 10.1109/IEMBS.2010.5627873.
10
An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation.
Comput Biol Med. 2017 Feb 1;81:121-129. doi: 10.1016/j.compbiomed.2016.12.017. Epub 2016 Dec 27.

引用本文的文献

1
Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment-based manifold learning.
Magn Reson Med. 2023 Apr;89(4):1297-1313. doi: 10.1002/mrm.29526. Epub 2022 Nov 20.
3
High-resolution, 3D multi-TE H MRSI using fast spatiospectral encoding and subspace imaging.
Magn Reson Med. 2022 Mar;87(3):1103-1118. doi: 10.1002/mrm.29015. Epub 2021 Nov 9.
4
Accelerated J-resolved H-MRSI with limited and sparse sampling of ( -space.
Magn Reson Med. 2021 Jan;85(1):30-41. doi: 10.1002/mrm.28413. Epub 2020 Jul 29.
5
A Subspace Approach to Spectral Quantification for MR Spectroscopic Imaging.
IEEE Trans Biomed Eng. 2017 Oct;64(10):2486-2489. doi: 10.1109/TBME.2017.2741922. Epub 2017 Aug 18.

本文引用的文献

1
Removal of nuisance signals from limited and sparse 1H MRSI data using a union-of-subspaces model.
Magn Reson Med. 2016 Feb;75(2):488-97. doi: 10.1002/mrm.25635. Epub 2015 Mar 11.
3
Using spatial prior knowledge in the spectral fitting of MRS images.
NMR Biomed. 2012 Jan;25(1):1-13. doi: 10.1002/nbm.1704. Epub 2011 Apr 28.
4
Anatomically constrained reconstruction from noisy data.
Magn Reson Med. 2008 Apr;59(4):810-8. doi: 10.1002/mrm.21536.
5
Sparse MRI: The application of compressed sensing for rapid MR imaging.
Magn Reson Med. 2007 Dec;58(6):1182-95. doi: 10.1002/mrm.21391.
8
GAVA: spectral simulation for in vivo MRS applications.
J Magn Reson. 2007 Apr;185(2):291-9. doi: 10.1016/j.jmr.2007.01.005. Epub 2007 Jan 12.
10
Time-domain semi-parametric estimation based on a metabolite basis set.
NMR Biomed. 2005 Feb;18(1):1-13. doi: 10.1002/nbm.895.

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