Removal of Nuisance Lipid Signals from Limited k -Space Data in 1H MRSI of the Brain
Chao Ma 1 , Fan Lam 1,2 , Curtis L. Johnson 1 , and Zhi-Pei Liang 1,2
Beckman Institute, University of Illinois at
Urbana-Champaign, Urbana, Illinois, United States,
of Electrical and Computer Engineering, University of
Illinois at Urbana-Champaign, Urbana, Illinois, United
data are often acquired in conventional 1H MRSI
experiments. However, the strong leakage of nuisance
lipid signals from the subcutaneous lipid layer of the
brain can significantly complicate spectrum quantitation
in brain MRSI. Removal of such lipid signals is
desirable but challenging, because they appear as
strong, multiple-peak, and broad spectra, overlapping
with the spectra of other important brain metabolites.
In this work, we propose a novel method to solve this
classical problem using a new spatial-spectral model.
at 3T showed that the proposed method is very effective
in removing lipid signals from brain MRSI data.
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