DocumentCode :
3125597
Title :
A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data
Author :
Calhoun, V. ; Adali, T. ; Liu, J.
Author_Institution :
Olin Neuropsychiatry Res. Center, Yale Univ., New Haven, CT
fYear :
2006
fDate :
Aug. 30 2006-Sept. 3 2006
Firstpage :
3672
Lastpage :
3675
Abstract :
The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups
Keywords :
biomedical MRI; data visualisation; electroencephalography; feature extraction; independent component analysis; medical image processing; sensor fusion; EEG brain imaging data; Kullback-Leibler divergence; data fusion; feature-based approach; functional MRI data; healthy controls; image modalities; joint histogram visualization technique; joint independent component analysis; schizophrenia; structural MRI data; Brain modeling; Computed tomography; Data visualization; Electric variables measurement; Electroencephalography; Enterprise resource planning; Independent component analysis; Low pass filters; Magnetic resonance imaging; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
ISSN :
1557-170X
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2006.259810
Filename :
4462595
Link To Document :
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