DocumentCode
2193116
Title
Head Modeling for E/MEG Source Analysis: Image Segmentation, Domain Decomposition and Solution of the Forward Problem
Author
Koles, Zoltan J.
Author_Institution
Alberta Univ., Edmonton
fYear
2007
fDate
12-14 Oct. 2007
Firstpage
213
Lastpage
214
Abstract
Issues in head modeling for E/MEG source analysis are discussed and some of the methods developed by our group are outlined. For image segmentation, a Kalman filter based edge tracing algorithm is described that performs well on noisy images and where intensity nonuniformity and partial volume effects are factors. For domain decomposition, a high resolution finite volume method is described that simplifies grid generation, meshing and source modeling. For the solution of the forward problem, a polynomial preconditioned conjugate gradient method is described that is efficient in terms of both computational speed and memory utilization.
Keywords
Kalman filters; biomedical MRI; electroencephalography; finite volume methods; image segmentation; magnetoencephalography; medical image processing; mesh generation; EEG; Kalman filter; MEG; domain decomposition; edge tracing algorithm; finite volume method; forward problem; grid generation; head modeling; image segmentation; intensity nonuniformity; magnetic resonance imaging; meshing; partial volume effects; polynomial preconditioned conjugate gradient method; source analysis; source modeling; Anisotropic magnetoresistance; Brain modeling; Conductivity; Finite volume methods; Image analysis; Image segmentation; Magnetic heads; Magnetic resonance imaging; Numerical models; Scalp;
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.2007.4387731
Filename
4387731
Link To Document