Abstract #1968
A Lorentzian-Function-Sparsity Approach for Fast High-Dimensional Magnetic Resonance Spectroscopy
Boyu Jiang 1 , Xiaoping Hu 2 , and Hao Gao 1,3
1
School of Biomedical Engineering, Shanghai
Jiao Tong University, Shanghai, Shanghai, China,
2
Department
of Biomedical Engineering, Emory University and Georgia
Institute of Technology, Atlanta, GA, United States,
3
Department
of Mathematics, Shanghai Jiao Tong University, Shanghai,
Shanghai, China
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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