Forward problem solution of ESI using FEM and BEM with quadratic isoparametric elements

Acar, C.E.; Gençer, N.G.

doi:10.1109/iembs.1999.802515

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…While FEM potentially allows more accurate head models using more tissue types and allowing specification of tissue anisotropy, generating these models requires extra information such as direction anisotropy information gleaned from diffusion tensor (DT) images. For isotropic head models, BEM is at least as accurate as FEM and also provides better control over source dipole locations (Acar and Gençer, 1999). …”

Section: Conclusion and Discussionmentioning

confidence: 99%

Neuroelectromagnetic Forward Head Modeling Toolbox

Acar

Makeig

2010

Journal of Neuroscience Methods

114

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This paper introduces a Neuroelectromagnetic Forward Head Modeling Toolbox (NFT) running under MATLAB (The Mathworks, Inc.) for generating realistic head models from available data (MRI and/or electrode locations) and for computing numerical solutions for the forward problem of electromagnetic source imaging. The NFT includes tools for segmenting scalp, skull, cerebrospinal fluid (CSF) and brain tissues from T1-weighted magnetic resonance (MR) images. The Boundary Element Method (BEM) is used for the numerical solution of the forward problem. After extracting segmented tissue volumes, surface BEM meshes can be generated. When a subject MR image is not available, a template head model can be warped to measured electrode locations to obtain an individualized head model. Toolbox functions may be called either from a graphic user interface compatible with EEGLAB (http://sccn.ucsd.edu/eeglab), or from the MATLAB command line. Function help messages and a user tutorial are included. The toolbox is freely available under the GNU Public License for noncommercial use and open source development.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Neuroelectromagnetic Forward Head Modeling Toolbox

Acar

Makeig

2010

Journal of Neuroscience Methods

114

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“…The model is based on the concentric three-spheres model with an additional inhomogeneity intersecting the outer-skull layer to model a single eye. Since an analytical solution is not possible for such a head geometry, the numerical solutions are compared with the results obtained by FEM ( Özdemir and Genc ¸er 1997, Acar and Genc ¸er 1999, Genc ¸er et al 2003.…”

Section: Validation Of the Intersecting Meshesmentioning

confidence: 99%

An advanced boundary element method (BEM) implementation for the forward problem of electromagnetic source imaging

Akalin-Acar

Gençer

2004

Phys. Med. Biol.

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The forward problem of electromagnetic source imaging has two components: a numerical model to solve the related integral equations and a model of the head geometry. This study is on the boundary element method (BEM) implementation for numerical solutions and realistic head modelling. The use of second-order (quadratic) isoparametric elements and the recursive integration technique increase the accuracy in the solutions. Two new formulations are developed for the calculation of the transfer matrices to obtain the potential and magnetic field patterns using realistic head models. The formulations incorporate the use of the isolated problem approach for increased accuracy in solutions. If a personal computer is used for computations, each transfer matrix is calculated in 2.2 h. After this pre-computation period, solutions for arbitrary source configurations can be obtained in milliseconds for a realistic head model. A hybrid algorithm that uses snakes, morphological operations, region growing and thresholding is used for segmentation. The scalp, skull, grey matter, white matter and eyes are segmented from the multimodal magnetic resonance images and meshes for the corresponding surfaces are created. A mesh generation algorithm is developed for modelling the intersecting tissue compartments, such as eyes. To obtain more accurate results quadratic elements are used in the realistic meshes. The resultant BEM implementation provides more accurate forward problem solutions and more efficient calculations. Thus it can be the firm basis of the future inverse problem solutions.

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Forward problem solution of ESI using FEM and BEM with quadratic isoparametric elements

Cited by 2 publications

References 4 publications

Neuroelectromagnetic Forward Head Modeling Toolbox

Neuroelectromagnetic Forward Head Modeling Toolbox

An advanced boundary element method (BEM) implementation for the forward problem of electromagnetic source imaging

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