Abstract
Quantification of MRS spectra is a challenging problem when a large baseline is present along with a low signal to noise ratio. This work investigates a robust fitting technique that yields accurate peak areas under these conditions. Using simulated long echo time 1H MRS spectra with low signal to noise ratio and a large baseline component, both the accuracy and reliability of the fit in the frequency domain were greatly improved by reducing the number of fitted parameters and making full use of all the known information concerning the Voigt lineshape. Using an appropriate first order approximation to a popular approximation of the Voigt lineshape, a significant improvement in the estimate of the area of a known spectral peak was obtained with a corresponding reduction in the residual. Furthermore, this improved parameter choice resulted in a large reduction in the number of iterations of the least-squares fitting routine. On the other hand, making use of the known centre frequency differences of the component resonances gave negligible improvement. A wavelet filter was used to remove the baseline component. In addition to performing a Monte Carlo study, these fitting techniques were also applied to a set of 10 spectra acquired from healthy human volunteers.Again, the same reduced parameter model gave the lowest value for X2 in each case. Copyright © 2006 John Wiley & Sons, Ltd.
Original language | English |
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Pages (from-to) | 617-626 |
Number of pages | 10 |
Journal | NMR in Biomedicine |
Volume | 19 |
Issue number | 5 |
DOIs | |
Publication status | Published - Aug 2006 |
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Keywords
- Baseline
- Lineshape
- MRS
- Spectroscopy
- Voigt
- Wavelet
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Quantification of MRS data in the frequency domain using a wavelet filter, an approximated Voigt lineshape model and prior knowledge. / Gillies, P.; Marshall, Ian; Asplund, M.; Winkler, P.; Higinbotham, J.
In: NMR in Biomedicine, Vol. 19, No. 5, 08.2006, p. 617-626.Research output: Contribution to journal › Article
TY - JOUR
T1 - Quantification of MRS data in the frequency domain using a wavelet filter, an approximated Voigt lineshape model and prior knowledge
AU - Gillies, P.
AU - Marshall, Ian
AU - Asplund, M.
AU - Winkler, P.
AU - Higinbotham, J.
PY - 2006/8
Y1 - 2006/8
N2 - Quantification of MRS spectra is a challenging problem when a large baseline is present along with a low signal to noise ratio. This work investigates a robust fitting technique that yields accurate peak areas under these conditions. Using simulated long echo time 1H MRS spectra with low signal to noise ratio and a large baseline component, both the accuracy and reliability of the fit in the frequency domain were greatly improved by reducing the number of fitted parameters and making full use of all the known information concerning the Voigt lineshape. Using an appropriate first order approximation to a popular approximation of the Voigt lineshape, a significant improvement in the estimate of the area of a known spectral peak was obtained with a corresponding reduction in the residual. Furthermore, this improved parameter choice resulted in a large reduction in the number of iterations of the least-squares fitting routine. On the other hand, making use of the known centre frequency differences of the component resonances gave negligible improvement. A wavelet filter was used to remove the baseline component. In addition to performing a Monte Carlo study, these fitting techniques were also applied to a set of 10 spectra acquired from healthy human volunteers.Again, the same reduced parameter model gave the lowest value for X2 in each case. Copyright © 2006 John Wiley & Sons, Ltd.
AB - Quantification of MRS spectra is a challenging problem when a large baseline is present along with a low signal to noise ratio. This work investigates a robust fitting technique that yields accurate peak areas under these conditions. Using simulated long echo time 1H MRS spectra with low signal to noise ratio and a large baseline component, both the accuracy and reliability of the fit in the frequency domain were greatly improved by reducing the number of fitted parameters and making full use of all the known information concerning the Voigt lineshape. Using an appropriate first order approximation to a popular approximation of the Voigt lineshape, a significant improvement in the estimate of the area of a known spectral peak was obtained with a corresponding reduction in the residual. Furthermore, this improved parameter choice resulted in a large reduction in the number of iterations of the least-squares fitting routine. On the other hand, making use of the known centre frequency differences of the component resonances gave negligible improvement. A wavelet filter was used to remove the baseline component. In addition to performing a Monte Carlo study, these fitting techniques were also applied to a set of 10 spectra acquired from healthy human volunteers.Again, the same reduced parameter model gave the lowest value for X2 in each case. Copyright © 2006 John Wiley & Sons, Ltd.
KW - Baseline
KW - Lineshape
KW - MRS
KW - Spectroscopy
KW - Voigt
KW - Wavelet
U2 - 10.1002/nbm.1060
DO - 10.1002/nbm.1060
M3 - Article
VL - 19
SP - 617
EP - 626
JO - NMR in Biomedicine
JF - NMR in Biomedicine
SN - 0952-3480
IS - 5
ER -