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Oleg Portniaguine and Dmitriy Pavlov

Oleg Portniaguine and Dmitriy Pavlov. Scientific Computing and Imaging Institute University of Utah. Convenient Modeling of Bioelectric Fields. 1. SCI. Outline. Introduction Computational Scheme Numerical Results Conclusion. 2. SCI. Introduction. EEG Modeling: Boundary Elements

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Oleg Portniaguine and Dmitriy Pavlov

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  1. Oleg Portniaguine and Dmitriy Pavlov Scientific Computing and Imaging Institute University of Utah Convenient Modeling of Bioelectric Fields 1 SCI

  2. Outline Introduction Computational Scheme Numerical Results Conclusion 2 SCI

  3. Introduction EEG Modeling: Boundary Elements Finite Elements Voxel grid based on MRI (Bonovas et al, 2001; Schinpf et al, 1998) - supercomputer needed 3 SCI

  4. Introduction ... We propose a computational scheme based on MRI voxel size cubic grid with ILU preconditioner to solve EEG problem on PC in a matter of seconds The modeling domain consists of regular cubic elements voxels with the same size as underlying MRI or CT 3-D image of the object 4 SCI

  5. Computational Scheme Scalar electric field potential within the voxel satisfies the Laplas-type equation: = 0 and can be approximated by a trilinear function:  = a1xyz+a2xy+a3xz+a4yz+a5x+a6y+a7z+a8 Assuming =const within the voxel: a1= 0 5 SCI

  6. Element Template 2 02 03 0 04 3 4 01 1 6 SCI

  7. Scheme Coefficients Current continuity contitions at the voxel edges: sn(n-0n)= s0(0n-00) Coefficient equation: 7 SCI

  8. ILU preconditioned BiCJ relaxation A= b A = DU+L-U, D = diag(A) L(DU+L-U)U-1ULb L(D+LU-1-I)m = c The Bi-conjugate gradient algoritm is used to find m 8 SCI

  9. Conductive Sphere Validation One dipole Grid size: 128x128x128 (2 mm MRI) 9 SCI

  10. Realistic Head Model One dipole Grid size: 112x128x128 (2 mm MRI) 10 SCI

  11. Conclusion The modeling code shows its reliability and fastness, while more validation is needed The code can be easily modified for anisotropic conductivity case The code will be modified to simulate magnetic field as well for the MEG modeling The ultimate goal is to use this computational scheme as a part of fast and accurate inversion code for EEG/MEG and other source localization problems 11 SCI

  12. Acknowledgments This project is supported by NIH/NCRR grant 1-P41-RR12553-01A1 12 SCI

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