Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination

Aimamorn Suvichakorn; Hélène Ratiney; Adriana Bucur; Sophie Cavassila; Jean-Pierre Antoine

doi:10.1109/IEMBS.2008.4649754

Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination

Aimamorn Suvichakorn, Hélène Ratiney, Adriana Bucur, Sophie Cavassila, Jean-Pierre Antoine

Division of Neuroscience

Universite Catholique de Louvain (Catholic University of Louvain)

Research output: Contribution to journal › Article › peer-review

Abstract

We study the Morlet wavelet transform on characterizing Magnetic Resonance Spectroscopic (MRS) signals acquired at short echo-time. These signals contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline signal decays faster than the metabolite ones. Therefore, by making use of the time-scale representation of the wavelet, the two signals can be distinguished without any additional pre-processing. This is confirmed by the experimental results which show that the Morlet wavelet can correctly quantify the metabolite contributions even when a baseline is embedded in the MRS signals.

Original language	English
Pages (from-to)	2681-4
Number of pages	4
Journal	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Volume	2008
DOIs	https://doi.org/10.1109/IEMBS.2008.4649754
Publication status	Published - 2008

Keywords

Algorithms
Creatine
Fourier Analysis
Humans
Image Enhancement
Image Interpretation, Computer-Assisted
Lipids
Macromolecular Substances
Magnetic Resonance Spectroscopy
Models, Statistical
Phantoms, Imaging
Regression Analysis
Reproducibility of Results
Signal Processing, Computer-Assisted
Journal Article
Research Support, Non-U.S. Gov't

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10.1109/IEMBS.2008.4649754

Cite this

Suvichakorn, A., Ratiney, H., Bucur, A., Cavassila, S., & Antoine, J.-P. (2008). Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2008, 2681-4. https://doi.org/10.1109/IEMBS.2008.4649754

Suvichakorn, Aimamorn ; Ratiney, Hélène ; Bucur, Adriana et al. / Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination. In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2008 ; Vol. 2008. pp. 2681-4.

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title = "Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination",

abstract = "We study the Morlet wavelet transform on characterizing Magnetic Resonance Spectroscopic (MRS) signals acquired at short echo-time. These signals contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline signal decays faster than the metabolite ones. Therefore, by making use of the time-scale representation of the wavelet, the two signals can be distinguished without any additional pre-processing. This is confirmed by the experimental results which show that the Morlet wavelet can correctly quantify the metabolite contributions even when a baseline is embedded in the MRS signals.",

keywords = "Algorithms, Creatine, Fourier Analysis, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Lipids, Macromolecular Substances, Magnetic Resonance Spectroscopy, Models, Statistical, Phantoms, Imaging, Regression Analysis, Reproducibility of Results, Signal Processing, Computer-Assisted, Journal Article, Research Support, Non-U.S. Gov't",

author = "Aimamorn Suvichakorn and H{\'e}l{\`e}ne Ratiney and Adriana Bucur and Sophie Cavassila and Jean-Pierre Antoine",

year = "2008",

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language = "English",

volume = "2008",

pages = "2681--4",

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Suvichakorn, A, Ratiney, H, Bucur, A, Cavassila, S & Antoine, J-P 2008, 'Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, vol. 2008, pp. 2681-4. https://doi.org/10.1109/IEMBS.2008.4649754

Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination. / Suvichakorn, Aimamorn; Ratiney, Hélène; Bucur, Adriana et al.
In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Vol. 2008, 2008, p. 2681-4.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination

AU - Suvichakorn, Aimamorn

AU - Ratiney, Hélène

AU - Bucur, Adriana

AU - Cavassila, Sophie

AU - Antoine, Jean-Pierre

PY - 2008

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N2 - We study the Morlet wavelet transform on characterizing Magnetic Resonance Spectroscopic (MRS) signals acquired at short echo-time. These signals contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline signal decays faster than the metabolite ones. Therefore, by making use of the time-scale representation of the wavelet, the two signals can be distinguished without any additional pre-processing. This is confirmed by the experimental results which show that the Morlet wavelet can correctly quantify the metabolite contributions even when a baseline is embedded in the MRS signals.

AB - We study the Morlet wavelet transform on characterizing Magnetic Resonance Spectroscopic (MRS) signals acquired at short echo-time. These signals contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline signal decays faster than the metabolite ones. Therefore, by making use of the time-scale representation of the wavelet, the two signals can be distinguished without any additional pre-processing. This is confirmed by the experimental results which show that the Morlet wavelet can correctly quantify the metabolite contributions even when a baseline is embedded in the MRS signals.

KW - Algorithms

KW - Creatine

KW - Fourier Analysis

KW - Humans

KW - Image Enhancement

KW - Image Interpretation, Computer-Assisted

KW - Lipids

KW - Macromolecular Substances

KW - Magnetic Resonance Spectroscopy

KW - Models, Statistical

KW - Phantoms, Imaging

KW - Regression Analysis

KW - Reproducibility of Results

KW - Signal Processing, Computer-Assisted

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

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DO - 10.1109/IEMBS.2008.4649754

M3 - Article

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SN - 1557-170X

VL - 2008

SP - 2681

EP - 2684

JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

ER -

Suvichakorn A, Ratiney H, Bucur A, Cavassila S, Antoine JP. Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2008;2008:2681-4. doi: 10.1109/IEMBS.2008.4649754

Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination

Abstract

Keywords

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