NDLI: Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing

Content Provider	IEEE Xplore Digital Library
Author	Hyung-Won Koh Maddula, S. Lambert, J. Hergenroder, R. Hildebrand, L.
Copyright Year	2008
Description	Author affiliation: ISAS - Inst. for Anal. Sci., Dortmund (Hyung-Won Koh)
Abstract	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.
Starting Page	608
Ending Page	613
File Size	916513
Page Count	6
File Format	PDF
ISBN	9780769531656
ISSN	10637125
DOI	10.1109/CBMS.2008.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-17
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nuclear magnetic resonance Magnetic analysis Instruction sets Spectroscopy Principal component analysis Artificial neural networks Probes Medical diagnostic imaging Metabolomics Biological system modeling Parameter Fitting Feature Selection NMR Data Processing
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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