TY - JOUR
T1 - Improved reconstruction for MR spectroscopic imaging
AU - Yufang, Bao
AU - Maudsley, Andrew A.
N1 - Funding Information:
Manuscript received October 30, 2006; revised January 12, 2007. This work was supported by PHS Grant R01 NS041946. This paper was presented in part at the IEEE Workshop on Statistical Signal Processing, St. Louis, MO, September 2003. Asterisk indicates corresponding author. *Y. Bao is with the MR Center (R308), 1115 NW 14th Street, Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL 33136 USA (e-mail: ybao2@med.miami.edu).
PY - 2007/5
Y1 - 2007/5
N2 - Sensitivity limitations of in vivo magnetic resonance spectroscopic imaging (MRSI) require that the extent of spatialfrequency (k-space) sampling be limited, thereby reducing spatial resolution and increasing the effects of Gibbs ringing that is associated with the use of Fourier transform reconstruction. Additional problems occur in the spectral dimension, where quantitation of individual spectral components is made more difficult by the typically low signal-to-noise ratios, variable lineshapes, and baseline distortions, particularly in areas of significant magnetic field inhomogeneity. Given the potential of in vivo MRSI measurements for a number of clinical and biomedical research applications, there is considerable interest in improving the quality of the metabolite image reconstructions. In this report, a reconstruction method is described that makes use of parametric modeling and MRI-derived tissue distribution functions to enhance the MRSI spatial reconstruction. Additional preprocessing steps are also proposed to avoid difficulties associated with image regions containing spectra of inadequate quality, which are commonly present in the in vivo MRSI data.
AB - Sensitivity limitations of in vivo magnetic resonance spectroscopic imaging (MRSI) require that the extent of spatialfrequency (k-space) sampling be limited, thereby reducing spatial resolution and increasing the effects of Gibbs ringing that is associated with the use of Fourier transform reconstruction. Additional problems occur in the spectral dimension, where quantitation of individual spectral components is made more difficult by the typically low signal-to-noise ratios, variable lineshapes, and baseline distortions, particularly in areas of significant magnetic field inhomogeneity. Given the potential of in vivo MRSI measurements for a number of clinical and biomedical research applications, there is considerable interest in improving the quality of the metabolite image reconstructions. In this report, a reconstruction method is described that makes use of parametric modeling and MRI-derived tissue distribution functions to enhance the MRSI spatial reconstruction. Additional preprocessing steps are also proposed to avoid difficulties associated with image regions containing spectra of inadequate quality, which are commonly present in the in vivo MRSI data.
KW - Brain metabolite images
KW - Image reconstruction
KW - Magnetic resonance spectroscopic imaging (MRSI)
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U2 - 10.1109/TMI.2007.895482
DO - 10.1109/TMI.2007.895482
M3 - Article
C2 - 17518063
AN - SCOPUS:34247629723
VL - 26
SP - 686
EP - 695
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
SN - 0278-0062
IS - 5
ER -