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https://scholarbank.nus.edu.sg/handle/10635/70157
Title: | Embedding EEG data on 3D head modeled using MRI data | Authors: | Mangalapallil, A.T. Puthusserypady, S. |
Keywords: | EEG ICA Infomax Modeling MRI Multi-modal registration |
Issue Date: | 2004 | Citation: | Mangalapallil, A.T.,Puthusserypady, S. (2004). Embedding EEG data on 3D head modeled using MRI data. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 26 III : 1833-1837. ScholarBank@NUS Repository. | Abstract: | Current 3D head modeling techniques from magnetic resonance imaging (MRI) data fall short of what is needed by clinicians and scientists to study the head anatomy both in terms of accuracy and speed of rendering. This paper proposes a novel direct modeling approach (DMA), which successfully and accurately models the 3D head with minimum processing requirements. A method for embedding the electroencephalogram (EEG) dipole source location into this modeled head is also demonstrated. The infomax algorithm is used for performing the independent component analysis (ICA) to obtain temporally independent stationary sources from multi-channel EEG data. The dipole source location is then found by using the downhill simplex algorithm on the activation maps of each independent source. Finally a transformation matrix is derived that maps the dipole location onto the 3D head. | Source Title: | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings | URI: | http://scholarbank.nus.edu.sg/handle/10635/70157 | ISSN: | 05891019 |
Appears in Collections: | Staff Publications |
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