Analysis of Human Brain NMR Spectra in Vivo Using Artificial Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03145662" target="_blank" >RIV/68407700:21230/08:03145662 - isvavai.cz</a>
Alternative codes found
RIV/00023001:_____/08:00001909
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Analysis of Human Brain NMR Spectra in Vivo Using Artificial Neural Networks
Original language description
Magnetic resonance has proven to be a successful method of in-vivo imaging. Although MRI can help detect various pathologies, its ability to classify the nature of the pathological tissue is limited. Magnetic resonance spectroscopy allows identifying metabolite content of the tissue and estimating the metabolite concentration. Map of metabolite concentration along with the MR image allows proper classification of many pathologies, for example progressive tumorous tissue identification in brain. Standardmethods used to analyze nuclear magnetic resonance spectra such as singular value decomposition or curve fitting algorithms are very time consuming taking several minutes to analyze spectrum from a single voxel. To analyze the spectra from a chemical shift imagine sequence (CSI) in maximal resolution hundreds of spectra need to be processed. The suggested ANN framework proved to be much faster. Networks were trained on the outputs of LCModel curve fitting algorithm.
Czech name
Analýza lidského mozku pomocí NMR spektra a neuronových sítích
Czech description
Článek popisuje analýza lidského mozku pomocí NMR spektra a neuronových sítích.
Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Neural Networks - ICANN 2008
ISBN
978-3-540-87558-1
ISSN
0302-9743
e-ISSN
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Number of pages
10
Pages from-to
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Publisher name
Springer
Place of publication
Heidelberg
Event location
Prague
Event date
Sep 3, 2008
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000259567200054