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2008 21st IEEE International Symposium on Computer-Based Medical Systems
Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing
June 17-June 19
ISBN: 978-0-7695-3165-6
ASCII Text
x 
 
Hyung-Won Koh, Sasidhar Maddula, J? Lambert, Roland Hergenr?der, Lars Hildebrand, "Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing," Computer-Based Medical Systems, IEEE Symposium on, pp. 608-613, 2008 21st IEEE International Symposium on Computer-Based Medical Systems, 2008.
 
 
BibTex
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@article{ 10.1109/CBMS.2008.43,
author = {Hyung-Won Koh and Sasidhar Maddula and J? Lambert and Roland Hergenr?der and Lars Hildebrand},
title = {Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing},
journal ={Computer-Based Medical Systems, IEEE Symposium on},
volume = {0},
year = {2008},
issn = {1063-7125},
pages = {608-613},
doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2008.43},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer-Based Medical Systems, IEEE Symposium on
TI - Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing
SN - 1063-7125
SP608
EP613
A1 - Hyung-Won Koh,
A1 - Sasidhar Maddula,
A1 - J? Lambert,
A1 - Roland Hergenr?der,
A1 - Lars Hildebrand,
PY - 2008
KW - Feature Selection
KW - NMR Data Processing
KW - Parameter Fitting
VL - 0
JA - Computer-Based Medical Systems, IEEE Symposium on
ER -
 
In recent years, Nuclear Magnetic Resonance spectroscopy (NMR) has become more and more popular in the field of metabolomic analysis. Analyzing and interpreting the obtained data is thus still challenging due to its complex and nontrivial characteristics. Further analysis of the obtained data is still mainly based on manual assignment, manual analysis and expert knowledge, and therefore time consuming. Common approaches towards automated post processing methods are often based on binning, which leads to loss of information in any case. This paper addresses an approach for reconstructing a one-dimensional NMR spectrum into a set of distinct lorentzian peak lines as an impressive feature selection and data reduction method and evaluates the performance on a real-world as well as on different simulated spectra.
Index Terms:
Feature Selection, NMR Data Processing, Parameter Fitting
Citation:
Hyung-Won Koh, Sasidhar Maddula, J? Lambert, Roland Hergenr?der, Lars Hildebrand, "Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing," cbms, pp.608-613, 2008 21st IEEE International Symposium on Computer-Based Medical Systems, 2008
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