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Zeffiro User Interface for Electromagnetic Brain Imaging: a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab

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Zeffiro User Interface for Electromagnetic Brain Imaging : a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab. / He, Q.; Rezaei, A.; Pursiainen, S.

In: Neuroinformatics, 2019.

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@article{041f5ae186234fe58f0426de6fa74cc9,
title = "Zeffiro User Interface for Electromagnetic Brain Imaging: a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab",
abstract = "This article introduces the Zeffiro interface (ZI) version 2.2 for brain imaging. ZI aims to provide a simple, accessible and multimodal open source platform for finite element method (FEM) based and graphics processing unit (GPU) accelerated forward and inverse computations in the Matlab environment. It allows one to (1) generate a given multi-compartment head model, (2) to evaluate a lead field matrix as well as (3) to invert and analyze a given set of measurements. GPU acceleration is applied in each of the processing stages (1)–(3). In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography (EEG) and linearized electrical impedance tomography (EIT) as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM). We report the results of EEG and EIT inversion tests performed with real and synthetic data, respectively, and demonstrate numerically how the inversion parameters affect the EEG inversion outcome in HBM. The GPU acceleration was found to be essential in the generation of the FE mesh and the LF matrix in order to achieve a reasonable computing time. The code package can be extended in the future based on the directions given in this article.",
keywords = "Electrical Impedance Tomography (EIT), Electro-/Magnetoencephalography (EEG/MEG), Finite Element Method (FEM), Hierarchical Bayesian Model (HBM), Matlab Interface",
author = "Q. He and A. Rezaei and S. Pursiainen",
year = "2019",
doi = "10.1007/s12021-019-09436-9",
language = "English",
journal = "Neuroinformatics",
issn = "1539-2791",
publisher = "HUMANA PRESS INC",

}

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TY - JOUR

T1 - Zeffiro User Interface for Electromagnetic Brain Imaging

T2 - a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab

AU - He, Q.

AU - Rezaei, A.

AU - Pursiainen, S.

PY - 2019

Y1 - 2019

N2 - This article introduces the Zeffiro interface (ZI) version 2.2 for brain imaging. ZI aims to provide a simple, accessible and multimodal open source platform for finite element method (FEM) based and graphics processing unit (GPU) accelerated forward and inverse computations in the Matlab environment. It allows one to (1) generate a given multi-compartment head model, (2) to evaluate a lead field matrix as well as (3) to invert and analyze a given set of measurements. GPU acceleration is applied in each of the processing stages (1)–(3). In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography (EEG) and linearized electrical impedance tomography (EIT) as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM). We report the results of EEG and EIT inversion tests performed with real and synthetic data, respectively, and demonstrate numerically how the inversion parameters affect the EEG inversion outcome in HBM. The GPU acceleration was found to be essential in the generation of the FE mesh and the LF matrix in order to achieve a reasonable computing time. The code package can be extended in the future based on the directions given in this article.

AB - This article introduces the Zeffiro interface (ZI) version 2.2 for brain imaging. ZI aims to provide a simple, accessible and multimodal open source platform for finite element method (FEM) based and graphics processing unit (GPU) accelerated forward and inverse computations in the Matlab environment. It allows one to (1) generate a given multi-compartment head model, (2) to evaluate a lead field matrix as well as (3) to invert and analyze a given set of measurements. GPU acceleration is applied in each of the processing stages (1)–(3). In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography (EEG) and linearized electrical impedance tomography (EIT) as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM). We report the results of EEG and EIT inversion tests performed with real and synthetic data, respectively, and demonstrate numerically how the inversion parameters affect the EEG inversion outcome in HBM. The GPU acceleration was found to be essential in the generation of the FE mesh and the LF matrix in order to achieve a reasonable computing time. The code package can be extended in the future based on the directions given in this article.

KW - Electrical Impedance Tomography (EIT)

KW - Electro-/Magnetoencephalography (EEG/MEG)

KW - Finite Element Method (FEM)

KW - Hierarchical Bayesian Model (HBM)

KW - Matlab Interface

U2 - 10.1007/s12021-019-09436-9

DO - 10.1007/s12021-019-09436-9

M3 - Article

JO - Neuroinformatics

JF - Neuroinformatics

SN - 1539-2791

ER -