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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 55974 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Shamsollahi, Mohammad Bagher; Hajipour Sardouei, Sepideh
- Abstract:
- In most of brain studies, the primary objective is to find dipole activities, an underdetermined problem that requires additional constraints. Adequate constraints can be added by using information from other modalities. This research aims to develop a platform that combines various noninvasive modalities to improve localization accuracy. To accomplish this, two novel general approaches to combining modalities are proposed. In the first approach, the result of localizing by different methods and in different modalities are processed and combined in intervals by Dempster Shaffer's combination law. The final amount of bipolar activity is obtained by cumulating the activities obtained at smaller intervals. The second approach is based on the creation of a suitable weight matrix for localization using the WMNE method. This matrix is created in two forms: single-step and consecutive repetitions. In the single-step method, after independent localization in two modalities using the WMNE method, dipoles with the highest amount of activity are selected and form a cluster of active dipoles. By applying the k-means algorithm, the main foci of activity is determined and localization is performed with the modified weight matrix proportional to the distance from the main foci of activity. In the method with successive iterations, in each iteration, the dipoles having the most activity in each bimodality are selected. In the next iteration, localization is performed with the modified weight matrix having less weight for selected dipoles. After several consecutive repetitions, the largest connected area is selected from dipoles with the highest activity, the final weight matrix is adjusted according to these dipoles, and the final localization is performed in both modalities. In order to evaluate the performance of the proposed methods, realistic synthetic data has been used. The effectiveness of the proposed methods was measured by the AUC criterion and the results of the simulations show that the use of the proposed approaches will lead to more accurate positioning
- Keywords:
- Electroencephalography ; Brain Source Localization ; Epilepsy ; Dempster-Shafer Theory ; Multimodal Images ; Magnetoencephalography (MEG) ; Weighted Minimum Norm Error
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