Schuck Jr., A., Lemke, C. , Suvichakorn, A. and Antoine, J.-P. (2010) Analysis of Magnetic Resonance Spectroscopic Signals with Data-based Autocorrelation Wavelets. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, 31 Aug - 04 Sep 2010, pp. 855-858. ISBN 9781424441235 (doi: doi10.1109/iembs.2010.5628034)
Full text not currently available from Enlighten.
Abstract
A new class of wavelet functions called data-based autocorrelation wavelets is developed for analyzing Magnetic Resonance Spectroscopic (MRS) signals by means of the continuous wavelet transform (CWT), instead of the traditional wavelet like Morlet wavelet. These new wavelets are derived from the normalized autocorrelation function from metabolite data and then used for detecting the presence of a given metabolite in a signal with a presence of many different components and finally for quantifying some of its parameters.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Lemke, Dr Christina |
| Authors: | Schuck Jr., A., Lemke, C., Suvichakorn, A., and Antoine, J.-P. |
| College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
| ISSN: | 1094-687X |
| ISBN: | 9781424441235 |
| Published Online: | 11 November 2010 |
University Staff: Request a correction | Enlighten Editors: Update this record
Deposit and Record Details
Deposit and Record Details