Document Detail


Identification and attenuation of physiological noise in fMRI using kernel techniques.
MedLine Citation:
PMID:  22255425     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Functional magnetic resonance imaging (fMRI) techniques enable noninvasive studies of brain functional activity under task and resting states. However, the analysis of brain activity could be significantly affected by the cardiac- and respiration-induced physiological noise in fMRI data. In most multi-slice fMRI experiments, the temporal sampling rates are not high enough to critically sample the physiological noise, and the noise is aliased into frequency bands where useful brain functional signal exists, compromising the analysis. Most existing approaches cannot distinguish between the aliased noise and signal if they overlap in the frequency domain. In this work, we further developed a kernel principal component analysis based physiological removal method based on our previous work. Specifically, two kernel functions were evaluated based on a newly proposed criterion that can measure the capability of a kernel to separate the aliased physiological noise from fMRI signal. In addition, a mutual information based criterion was designed to select principal components for noise removal. The method was evaluated by human experimental fMRI studies, and the results demonstrate that the proposed method can effectively identify and attenuate the aliased physiological noise in fMRI data.
Authors:
Xiaomu Song; Nan-Kuei Chen; Pooja Gaur
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Publication Detail:
Type:  Journal Article; Review    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2011     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2011  
Date Detail:
Created Date:  2012-01-18     Completed Date:  2012-07-09     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  4852-5     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Humans
Magnetic Resonance Imaging / methods*
Models, Theoretical

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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