DocumentCode
2192651
Title
Source Inversion Technique using Bayesian Inference: Combined MEG/fMRI
Author
Jun, Sung C. ; George, John S. ; Kim, Woohan ; Plis, Sergey M. ; Ranken, Doug M. ; Schmidt, David M.
Author_Institution
Los Alamos Nat. Lab., Los Alamos
fYear
2007
fDate
12-14 Oct. 2007
Firstpage
144
Lastpage
147
Abstract
As a way to integrate multi-modal brain imaging data in the Bayesian frame, we propose a spatiotemporal Bayesian inference multi-dipole analysis for MEG and fMRI data. We formulate a Bayesian integration of MEG and fMRI data, and its usefulness and feasibility are verified through testing simulated data.
Keywords
Bayes methods; biomedical MRI; magnetoencephalography; medical image processing; MEG; fMRI; multidipole analysis; multimodal brain imaging; source inversion technique; spatiotemporal Bayesian inference; Bayesian methods; Brain modeling; Electroencephalography; Information analysis; Laboratories; Physics; Position measurement; Probability distribution; Spatiotemporal phenomena; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging, 2007. NFSI-ICFBI 2007. Joint Meeting of the 6th International Symposium on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-0949-5
Electronic_ISBN
978-1-4244-0949-5
Type
conf
DOI
10.1109/NFSI-ICFBI.2007.4387710
Filename
4387710
Link To Document