Marie Curie Fellows :: Partner 7 - Louvain, Belgium

Marie-Curie Fellow
Research & Training Network
C. Lemke (ER)

Marie Curie Fellow (ER) of the FAST project
Université Catholique de Louvain, Belgium
Contact
 

Christina Lemke left the FAST network in February 2010 for a permanent position in Germany. She continued, however, to present the work on behalf of FAST in talks and articles.  

• T4 Signal processing
  Task 4 focuses on MRSI signal processing proper of Gigabytes of data. The ultimate goal is reliable quantitation of metabolites. The required computing times are long and will eventually need grid-computing.

  • T4.1 led by KU Leuven, concerns time-domain processing. This is a daunting task for many reasons:
    1. MRSI signals contain a strong non-parametric part from `macromolecules' that perturbs the wanted, parametric, part from metabolites. This requires a semi-parametric approach which is still under development, worldwide.
    2. Many spectral peaks of the parametric part overlap strongly.
    3. All processing needs to be fully automatic and numerically stable. Reliance on starting values will be reduced by development of genetic algorithms.
    4. Reliable error bars on metabolite concentrations that accommodate the non-parametric part must be provided.

Metabolite-based continuous wavelet analysis

The heart of the research is the derivation of metabolite-based wavelets for the analysis of MRS signals. From a given set of metabolite profiles new mother wavelets are constructed, each of them sensitive to one metabolite. One problem to solve was that both the profiles and thus the mother wavelets are discrete, too. As there is no analytical function to describe the mother wavelets, dilation of the mother wavelets has to be made possible by interpolation followed by up- and downsampling. Results of the CWT (continuous wavelet transform) show that that the existence of a metabolite hidden in a MRS signal can be indicated using the metabolite-based wavelets. Once a complete algorithm is derived from our network, it will contribute worthy input information to quantitation methods.

• Ellaboration of CW basis sets with M. I. Osorio Garcia and F. Nielsen (KUL, Leuven)
• Measurement on human scanners with C. Labadie (ULeipzig)
  

C. Lemke and J-P.Antoine, Data-based Wavelet Analysis for Magnetic Resonance Spectroscopy, talk, meeting of FNRS Contact Group Wavelets and Applications, Gembloux, Belgium, 4 December 2009

C. Lemke, A. Schuck Jr., D. Sima, M.I. Osorio Garcia, S. van Huffel and J-P.Antoine, MRS Signal Analysis by metabolite-based Wavelets, poster presentation, 2nd annual meeting of the ISMRM Benelux Chapter, Utrecht, Netherlands, 18 January 2010

C. Lemke, A. Schuck Jr., J-P.Antoine, D. Sima and M.I. Osorio Garcia, Metabolite-based wavelets for analyzing magnetic resonance spectroscopic signals, in Proc. of the 2010 IEEE Conference on Imaging Systems and Techniques (IST 2010), Thessaloniki, Greece, July 2010

A. Schuck,  C. Lemke, A. Suvichakorn and J.-P. Antoine, Analysis of magnetic resonance spectroscopic signals with data-based autocorrelation wavelets, in Proc.  IEEE EMBC 2010, Buenos Aires, Argentina pp. 855-8, September 2010