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Proceedings Paper

Comparison of methods for spectral estimation from 1D NMR time signals
Author(s): Keith A. Wear; Kyle J. Myers; Robert F. Wagner; Sunder S. Rajan; Laurence W. Grossman
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Paper 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.

Paper Details

Date Published: 9 December 1992
PDF: 9 pages
Proc. SPIE 1768, Mathematical Methods in Medical Imaging, (9 December 1992); doi: 10.1117/12.130905
Show Author Affiliations
Keith A. Wear, Ctr. for Devices and Radiological Health/FDA (United States)
Kyle J. Myers, Ctr. for Devices and Radiological Health/FDA (United States)
Robert F. Wagner, Ctr. for Devices and Radiological Health/FDA (United States)
Sunder S. Rajan, Georgetown Univ. (United States)
Laurence W. Grossman, Ctr. for Devices and Radiological Health/FDA (United States)

Published in SPIE Proceedings Vol. 1768:
Mathematical Methods in Medical Imaging
David C. Wilson; Joseph N. Wilson, Editor(s)

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