DocumentCode :
2555540
Title :
Time-domain analysis of magnetic resonance spectra and chemical shift images
Author :
Canady, L.D. ; Jordan, R. ; Asgharzadeh, A. ; Abousleman, G. ; Koechner, D. ; Griffey, R.H.
Author_Institution :
New Mexico Univ., Albuquerque, NM, USA
fYear :
1990
fDate :
3-6 Jun 1990
Firstpage :
432
Lastpage :
437
Abstract :
The utility of adaptive prediction and filtering algorithms and the autocorrelation-based Yule-Walker algorithm to predict and filter complex NMR (nuclear magnetic resonance) data is demonstrated. The application of these methods improves the available signal-to-noise ratio using time-domain analysis, and increases the low resolution via prediction algorithms in data containing phase errors introduced by hardware limitations. The application of the complex least-mean-squares and the modified-least-mean-squares transversal and lattice algorithms to low- and high-resolution NMR data records is demonstrated. The resolution and windowing problems found in the discrete Fourier transform are overcome by these alternative methods
Keywords :
biomedical NMR; chemical shift; spectral analysis; autocorrelation-based Yule-Walker algorithm; chemical shift images; discrete Fourier transform; hardware limitations; lattice algorithms; magnetic resonance spectra; phase errors; prediction algorithms; signal-to-noise ratio; time-domain analysis; Adaptive filters; Autocorrelation; Chemical analysis; Filtering algorithms; Magnetic resonance; Magnetic separation; Nuclear magnetic resonance; Prediction algorithms; Signal resolution; Time domain analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems, 1990., Proceedings of Third Annual IEEE Symposium on
Conference_Location :
Chapel Hill, NC
Print_ISBN :
0-8186-9040-2
Type :
conf
DOI :
10.1109/CBMSYS.1990.109430
Filename :
109430
Link To Document :
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