Spectral Quantification of MRSI Data Using Spatiospectral Constraints
Qiang Ning1,2, Chao Ma2, Fan Lam2, Bryan Clifford1,2, and Zhi-Pei Liang1,2
1Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, United States, 2Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, Urbana, IL, United States
A new method is proposed for spectral quantitation of MRSI data. The method has two main features: 1) incorporation of prior spectral knowledge in the form of basis functions obtained by quantum simulation, and 2) incorporation of prior spatial knowledge by penalizing smoothness within each type of tissue. An efficient algorithm is also proposed to solve the underlying optimization problem, and its effectiveness for extracting quantitative spectral information from noisy MRSI data is demonstrated by comparing it with one of the state-of-the-art methods.
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