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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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