| 1. |
- Edelvik, Fredrik, 1972, et al.
(författare)
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An improved method for dipole modeling in EEG-based source localization
- 2009
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Ingår i: International Federation for Medical and Biological Engineering Proceedings. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1680-0737. - 9783642038884 ; 25:9, s. 146-149
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Konferensbidrag (refereegranskat)abstract
- The inverse problem in EEG-based source localizationis to determine the location of the brain sources that areresponsible for the measured potentials at the scalp electrodes.The brain sources are usually modeled as current dipoles whichlead to a singularity in the right-hand side of the governing Poisson’sequation. Subtraction methods have been proposed as aremedy and in this paper an improved subtraction method formodeling the dipoles is presented. The accuracy is demonstratedfor radial and tangential sources in layered sphere models and isto the best of the authors’ knowledge superior to previous methodsfor superficial sources. An additional advantage is that itproduces a right hand side with few non-zeros which is beneficialfor efficient solution of the inverse problem.
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| 2. |
- Persson, Mikael, 1959, et al.
(författare)
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Advances in Neuro Diagnostic based on Microwave Technology, Transcranial Magnetic Stimulation and EEG source localization
- 2011
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Ingår i: Asia Pacific Microwave Conference, (APMC 2011;Melbourne, VIC; 5 - 8 December 2011). - 9780858259744 ; , s. 469-472
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Konferensbidrag (refereegranskat)abstract
- Advances in neuro diagnostics based on microwave antenna system in terms of a helmet including a set of broad band patch antennas is presented. It is shown that classification algorithms can be used to detect internal bleeding in stroke patients. Transcranial magnetic stimulation has traditionally been used for brain mapping and treatment of depression. In this paper we discuss the use of the method for neuro diagnostics with the help of integrated image guidance. Surgical therapy has become an important therapeutic alternative for some patients with medically intractable epilepsy. Electroencephalography and the associated model based diagnostics as a non-invasive diagnostic tool is also discussed.
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| 3. |
- Qaiser, Mahmood, 1981, et al.
(författare)
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On the Fully Automatic Construction of a Realistic Head Model for EEG Source Localization
- 2013
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Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Osaka, Japan, 3-7 July 2013. - 1557-170X. - 9781457702167 ; , s. 3331-3334
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Konferensbidrag (refereegranskat)abstract
- Accurate multi-tissue segmentation of magnetic resonance (MR) images is an essential first step in the construction of a realistic finite element head conductivity model (FEHCM) for electroencephalography (EEG) source localization. All of the segmentation approaches proposed to date for this purpose require manual intervention or correction and are thus laborious, time-consuming, and subjective. In this paper we propose and evaluate a fully automatic method based on a hierarchical segmentation approach (HSA) incorporating Bayesian-based adaptive mean-shift segmentation (BAMS). An evaluation of HSA-BAMS, as well as two reference methods, in terms of both segmentation accuracy and the source localization accuracy of the resulting FEHCM is also presented. The evaluation was performed using (i) synthetic 2D multi-modal MRI head data and synthetic EEG (generated for a prescribed source), and (ii) real 3D T1-weighted MRI head data and real EEG data (with expert determined source localization). Expert manual segmentation served as segmentation ground truth. The results show that HSA-BAMS outperforms the two reference methods and that it can be used as a surrogate for manual segmentation for the construction of a realistic FEHCM for EEG source localization.
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| 4. |
- Shirvany, Yazdan, 1980, et al.
(författare)
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Application of particle swarm optimization in epileptic spike EEG source localization
- 2013
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Ingår i: Applied Soft Computing Journal. - : Elsevier BV. - 1568-4946. ; 13:5, s. 2515-2525
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Tidskriftsartikel (refereegranskat)abstract
- Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy. Correct and anatomically precise localization of an epileptic focus is essential to decide if resection of brain tissue is possible. The inverse problem in EEG-based source localization is to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes. We propose a new global optimization method based on particle swarm optimization (PSO) to solve the epileptic spike EEG source localization inverse problem. In a forward problem a modified subtraction method is proposed to reduce the computational time. The good accuracy and fast convergence are demonstrated for 2D and 3D cases with realistic head models. The results from the new method are promising for use in the pre-surgical clinic in the future
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| 5. |
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| 6. |
- Shirvany, Yazdan, 1980, et al.
(författare)
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Evaluation of a finite-element reciprocity method for epileptic EEG source localization: Accuracy, computational complexity and noise robustness
- 2013
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Ingår i: Biomedical Engineering Letters. - : Springer Science and Business Media LLC. - 2093-985X .- 2093-9868. ; 3:1, s. 8-16
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSEThe aim of this paper is to evaluate the performance of an EEG source localization method that combines a finite element method (FEM) and the reciprocity theorem.METHODSThe reciprocity method is applied to solve the forward problem in a four-layer spherical head model for a large number of test dipoles. To benchmark the proposed method, the results are compared with an analytical solution and two state-of-the-art methods from the literature. Moreover, the dipole localization error resulting from utilizing the method in the inverse procedure for a realistic head model is investigated with respect to EEG signal noise and electrode misplacement.RESULTSThe results show approximately 3% relative error between numerically calculated potentials done by the reciprocity theorem and the analytical solutions. When adding EEG noise with SNR between 5 and 10, the mean localization error is approximately 4.3 mm. For the case with 10 mm electrode misplacement the localization error is 4.8 mm. The reciprocity EEG source localization speeds up the solution of the inverse problem with more than three orders of magnitude compared to the state-of-the-art methods.CONCLUSIONSThe reciprocity method has high accuracy for modeling the dipole in EEG source localization, is robust with respect to noise, and faster than alternative methods.
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| 7. |
- Shirvany, Yazdan, 1980, et al.
(författare)
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Influence of Different Sources of Noise on Epileptic Spike EEG Source Localization
- 2013
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Ingår i: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. - : SPIE. - 1605-7422. - 9780819494467 ; 8672
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Konferensbidrag (refereegranskat)abstract
- Spike EEG source localization results are influenced by different errors and approximations, e.g., head-model complexity, EEG signal noise, electrode misplacements, tissue anisotropy, tissue conductivity noise as well as numerical errors. For accurate source localization, understanding the affects of these errors on the source localization is very crucial. Six finite element head models are selected for a head-model complexity study. A reference head model is used to create the synthetic EEG signals by placing a dipole inside the model to mimic the epileptic spike activity. To understand the influence of EEG signal noise, tissue conductivity noise and electrode misplacements on the EEG source localization, different level of noises are added to EEG signals, tissue conductivities and electrode positions, independently. To investigate the influence of white matter anisotropy, a realistic head model generated from T1-weighted MRI is used and the conductivity anisotropy for the white matter is calculated from diffusion tensor imaging (DTI). Major findings of the study include (1) the CSF layer plays an important role to achieve an accurate source localization result, (2) the source localization is very sensitive to the tissue conductivity noises, (3) one centimeter electrode misplacement cause approximately 8 mm localization error, (4) the source localization is robust with respect to the EEG signal noise and (5) the model with white matter anisotropy has small source localization error but large amplitude and orientation errors compared to the isotropic head model.
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