Document Detail


Activation detection in functional MRI using model-free technique based on CCA-ICA analysis.
MedLine Citation:
PMID:  18002734     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The model-based approach for detecting the fMRI activations involves assumptions about the hemodynamic response function. If such assumptions are incorrect or incomplete, this may result in biased estimates of the true response, posing a significant obstacle to the practicality of the technique. In this work, a simple yet robust model-free technique is proposed for detecting the fMRI activations. The idea of the proposed model is to convert one of the model-based fMRI tools, namely canonical correlation analysis (CCA), to model-free with help of independent component analysis (ICA). In particular, ICA provides accurate reference functions for CCA instead of the harmonics originally used. This combination enables the elimination of the limitations of both techniques and provides a model-free approach for data analysis. Results from both numerical simulations and real fMRI data sets confirm the practicality and robustness of the proposed method.
Authors:
Nour El-Shabrawy; Ahmed S Mohamed; Abou-Bakr M Youssef; Yasser M Kadah
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Publication Detail:
Type:  Evaluation Studies; Journal Article    
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:  2007     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2007  
Date Detail:
Created Date:  2007-11-16     Completed Date:  2008-03-27     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:  3430-3     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Brain Mapping / methods*
Evoked Potentials, Motor / physiology*
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Models, Neurological
Motor Cortex / physiology*
Pattern Recognition, Automated / methods*
Principal Component Analysis
Reproducibility of Results
Sensitivity and Specificity
Statistics as Topic

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


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