Chao Ma1,
2, Fan Lam1, 3, Ryan Larsen3, Bradley
P. Sutton, 34, Zhi-Pei Liang, 35
1Department
of Electrical and Computer Engineering , University of Illinois at
Urbana-Champaign, Urbana, IL, United States; 2Beckman
Institute, University of Illinois at
Urbana-Champaign, Urbana, IL, United States; 3Beckman Institute,
University of Illinois at Urbana-Champaign, Urbana, IL, United States; 4Department
of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL,
United States; 5Department of Electrical and Computer Engineering,
University of Illinois at Urbana-Champaign, Urbana, IL, United States
Nuisance lipid signals from the subcutaneous lipid layer of the brain often cause significant difficulties for spectral quantification of the brain metabolites. Removal of the lipid signals in brain MRSI is desirable but challenging because they appear as multiple-peak, broad spectra that overlap with the spectra of important brain metabolites (e.g., lactate and NAA). In this work, we introduce a model-based post-processing method for effective removal of the lipid signals.