A Lorentzian-Function-Sparsity Approach for Fast High-Dimensional Magnetic Resonance Spectroscopy
Boyu Jiang 1 , Xiaoping Hu 2 , and Hao Gao 1,3
School of Biomedical Engineering, Shanghai
Jiao Tong University, Shanghai, Shanghai, China,
of Biomedical Engineering, Emory University and Georgia
Institute of Technology, Atlanta, GA, United States,
of Mathematics, Shanghai Jiao Tong University, Shanghai,
A new MRS reconstruction method has been proposed using
the Lorentzian-function-based sparsity, with
significantly reduced number of unknown variables. The
new method can achieve significantly better MRS
reconstruction results than FFT method or L1-based
sparsity method, e.g., even with 1% k-space data.
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