Quantification of MRS data in the frequency domain using a wavelet filter, an approximated Voigt lineshape model and prior knowledge

• 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.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

Nyckelord

Baseline

Lineshape

MRS

Spectroscopy

Voigt

Wavelet

Baseline component

Voigt lineshape

Wavelet filter

Computer simulation

Curve fitting

Frequency domain analysis

Least squares approximations

Monte Carlo methods

Wavelet transforms

Magnetic resonance spectroscopy

article

controlled study

data analysis

diagnostic accuracy

filter

frequency analysis

human

human experiment

Monte Carlo method

normal human

nuclear magnetic resonance spectroscopy

priority journal

proton nuclear magnetic resonance

radiological parameters

reference value

reliability

signal noise ratio

statistical model

volunteer

Humans

Image Enhancement

Mathematics

Models

Theoretical

Signal Processing

Computer-Assisted

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