DocumentCode
1529892
Title
Computed Basis Functions for Finite Element Analysis Based on Tomographic Data
Author
Gu, Huanhuan ; Gotman, Jean ; Webb, Jon P.
Author_Institution
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Volume
58
Issue
9
fYear
2011
Firstpage
2498
Lastpage
2505
Abstract
In bioelectromagnetics, the structures in which the electromagnetic field is to be computed are sometimes defined by a fine grid of voxels (3-D cells) whose tissue types are obtained by tomography. A novel finite element method is proposed for such cases. A simple, regular mesh of cube elements is constructed, each containing the same, integer number of voxels. There may be several different tissues present within an element, but this is accommodated by computing element basis functions that approximately respect the interface conditions between different tissues. Results are presented for a test model of 1283 voxels, consisting of nested dielectric cubes, driven by specified charges. The electrostatic potential computed with the new method agrees well with that of a conventional finite element code: the rms difference along the sample line is 1.5% of the highest voltage. Results are also presented for the potential due to a current dipole placed in a brain model of 181 × 217 × 181 voxels, derived from MRI data. The new method gives potentials that are different to those obtained by treating each voxel as an element by 1% of the peak voltage, yet the global finite element matrix has a dimension which is more than 50 times smaller.
Keywords
biological tissues; biomedical MRI; brain models; cellular biophysics; data analysis; electrostatics; mesh generation; 3D cells; MRI data; bioelectromagnetics; biological tissues; brain model; computing element basis functions; electrostatic potential; finite element analysis; interface conditions; nested dielectric cubes; regular mesh construction; rms difference; tomographic data; voxels; Boundary conditions; Electric potential; Equations; Face; Finite element methods; Materials; Mathematical model; Bioelectromagnetism; MRI; computational modeling; electroencephalography; electrostatics; finite element method (FEM); Brain; Computer Simulation; Finite Element Analysis; Humans; Magnetic Resonance Imaging; Models, Biological; Signal Processing, Computer-Assisted; Static Electricity;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2011.2158212
Filename
5779710
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