Instantaneous frequency based spectral analysis of nuclear magnetic resonance spectroscopy data

Nuclear magnetic resonance spectroscopy signals are modelled as a sum of decaying complex exponentials in noise. The spectral analysis of these signals allowing for their decomposition and the estimation of the parameters of the components is crucial to the study of biochemical samples. This paper presents a novel Gabor filterbank/notch filtering instantaneous frequency (IF) estimator, that enables the extraction of weaker and shorter lived exponentials. This new approach is an iterative procedure where a Gabor filterbank is first employed to obtain a reliable estimate of the IF of the strongest component present. The estimated strongest component is then notch filtered, which un-masks weaker components, and the procedure repeated. The performance of this method was evaluated using an artificial signal and compared to the short time Fourier transform, reassigned STFT, and the original Gabor filterbank approach. The results clearly demonstrate its superiority in uncovering weaker signals and resolving components that are very close to one another in frequency. Furthermore, the new method is shown to be more robust than the ITCMP technique at low signal to noise ratios.

[1]  Patrick Flandrin,et al.  Improving the readability of time-frequency and time-scale representations by the reassignment method , 1995, IEEE Trans. Signal Process..

[2]  Victor A. N. Barroso,et al.  On the concept of instantaneous frequency , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[3]  Elias Aboutanios,et al.  Investigation of bat echolocation calls using high resolution spectrogram and instantaneous frequency based analysis , 2009, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing.

[4]  Yung-Ya Lin,et al.  A Novel Detection–Estimation Scheme for Noisy NMR Signals: Applications to Delayed Acquisition Data , 1997 .

[5]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. II. A/lgorithms and applications , 1992, Proc. IEEE.

[6]  Barry G. Quinn,et al.  The Estimation and Tracking of Frequency , 2001 .

[7]  Sabine Van Huffel,et al.  Using prior knowledge in SVD-based parameter estimation for magnetic resonance spectroscopy-the ATP example , 2004, IEEE Transactions on Biomedical Engineering.

[8]  P. Maragos,et al.  Speech formant frequency and bandwidth tracking using multiband energy demodulation , 1996 .

[9]  L. Mandel.  Interpretation of Instantaneous Frequencies , 1974 .

[10]  Elias Aboutanios,et al.  Instantaneous frequency based spectral analysis of nuclear magnetic spectroscopy data for metabolomics , 2010, 2010 3rd International Congress on Image and Signal Processing.

[11]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[12]  J. Griffin,et al.  Time-domain Bayesian detection and estimation of noisy damped sinusoidal signals applied to NMR spectroscopy. , 2007, Journal of magnetic resonance.

[13]  Elias Aboutanios,et al.  Estimation of the Frequency and Decay Factor of a Decaying Exponential in Noise , 2010, IEEE Transactions on Signal Processing.

[14]  Stephan Dahlke,et al.  Coorbit Theory, Multi--Modulation Frames, and the Concept of Joint Sparsity for Medical Multichannel Data Analysis , 2008, EURASIP J. Adv. Signal Process..

[15]  Pradip Sircar,et al.  Parametric modelling of non-stationary signals: a unified approach , 1997 .

[16]  G. C. Levy,et al.  Modern methods of N M R data processing and data evaluation , 1991 .

[17]  Petros Maragos,et al.  On amplitude and frequency demodulation using energy operators , 1993, IEEE Trans. Signal Process..

[18]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[19]  Steve McLaughlin,et al.  Improved EMD Using Doubly-Iterative Sifting and High Order Spline Interpolation , 2008, EURASIP J. Adv. Signal Process..

[20]  Sudhakar M. Pandit,et al.  Cramer-Rao lower bounds for a damped sinusoidal process , 1995, IEEE Trans. Signal Process..

[21]  Elias Aboutanios,et al.  Estimating the parameters of sinusoids and decaying sinusoids in noise , 2011, IEEE Instrumentation & Measurement Magazine.

[22]  Petros Maragos,et al.  A comparison of the energy operator and the Hilbert transform approach to signal and speech demodulation , 1994, Signal Process..

[23]  Elias Aboutanios,et al.  Time-frequency and advanced frequency estimation techniques for the investigation of bat echolocation calls. , 2010, The Journal of the Acoustical Society of America.

[24]  James H. McClellan,et al.  Instantaneous frequency estimation using linear prediction with comparisons to the DESAs , 1996, IEEE Signal Processing Letters.

[25]  S. Van Huffel,et al.  MRS signal quantitation: a review of time- and frequency-domain methods. , 2008, Journal of magnetic resonance.

[26]  Srinivasan Umesh,et al.  Estimation of parameters of exponentially damped sinusoids using fast maximum likelihood estimation with application to NMR spectroscopy data , 1996, IEEE Trans. Signal Process..

[27]  Yannis Kopsinis,et al.  An instantaneous frequency based algorithm for the processing of NMR data , 2011, 2011 17th International Conference on Digital Signal Processing (DSP).

[28]  J. Lindon,et al.  Metabonomics: a platform for studying drug toxicity and gene function , 2002, Nature Reviews Drug Discovery.

[29]  Jian Li,et al.  Parametric methods for frequency-selective MR spectroscopy-a review. , 2004, Journal of magnetic resonance.