title: Spectral Quantification for High-Resolution MR Spectroscopic Imaging With Spatiospectral Constraints.
abstract: To obtain reliable spectral estimation from magnetic resonance spectroscopic imaging (MRSI) data.
  
  
  
  The proposed method takes advantage of prior knowledge: 1) along the spectral dimension in the form of spectral bases, and 2) along the spatial dimensions in the form of spatial regularizations (e.g., smoothness or transform sparsity) and jointly estimates parameters from all the voxels.
  
  
  
  Simulation and in vivo studies have been performed to demonstrate the performance of the proposed method. A Cramér-Rao-bound-based analysis is also provided.
  
  
  
  Incorporation of both spatial and spectral constraints can significantly improve spectral quantification of MRSI data.
  
  
  
  The proposed method is expected to be useful for various quantitative MRSI studies.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Ning
authors.forename: Chao
authors.initials: C
authors.lastname: Ma
authors.forename: Fan
authors.initials: F
authors.lastname: Lam
authors.forename: Zhi-Pei
authors.initials: ZP
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D057054:Molecular Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D062211:Spatio-Temporal Analysis