Comparison of methods for spectral estimation from 1D NMR time signals

Keith A. Wear; Kyle J. Myers; Robert F. Wagner; Sunder S. Rajan; Laurence W. Grossman

doi:10.1117/12.130905

9 December 1992 Comparison of methods for spectral estimation from 1D NMR time signals

Keith A. Wear, Kyle J. Myers, Robert F. Wagner, Sunder S. Rajan, Laurence W. Grossman

Proceedings Volume 1768, Mathematical Methods in Medical Imaging; (1992) https://doi.org/10.1117/12.130905
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

Various algorithms for spectral estimation were compared for the task of estimating spectra of NMR signals. These algorithms were the fast Fourier transform, maximum entropy, and an autoregressive model. Both simulated and real data were investigated. The simulated radio frequency (rf) data was designed to mimic data from the human liver using ³¹P NMR spectroscopy. All algorithms exhibited similar bias and variance of estimates in the simulation. Data from a solution containing water and ethanol was also acquired. Here, the FFT and autoregressive methods exhibited similar bias and variance. Investigations involving maximum entropy are currently underway.

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Keith A. Wear, Kyle J. Myers, Robert F. Wagner, Sunder S. Rajan, and Laurence W. Grossman "Comparison of methods for spectral estimation from 1D NMR time signals", Proc. SPIE 1768, Mathematical Methods in Medical Imaging, (9 December 1992); https://doi.org/10.1117/12.130905

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