PROCEEDINGS ARTICLE | March 27, 2009
Proc. SPIE. 7259, Medical Imaging 2009: Image Processing
KEYWORDS: Electrodes, Magnetic resonance imaging, Image registration, Tomography, Monte Carlo methods, Electroencephalography, Neuroimaging, Positron emission tomography, Functional magnetic resonance imaging, Brain
Integration and correlation of brain's electrical (EEG) and physiological activity (PET, fMRI) is crucial for the
early evaluation of patients with neurophysiological disorders, such as epilepsy. Based on the scalp-recorded
EEG signals, the source image of brain's electrical activity can be reconstructed and spatially correlated with
tomographic functional images, thereby aiding to the characterization and localization of epileptic foci. However,
mis-localization of the electrode positions, with respect to the underlying anatomy, adversely affects the
localization precision performed by the interpretation of the source image. In this paper, a novel method for
registration of EEG electrode positions to tomographic functional images of the brain is proposed. Accuracy
and robustness of the registration were evaluated on three databases of real and simulated PET and real fMRI
images. The registration method showed good convergence properties for both PET [>10 mm] and especially
fMRI images [>30 mm]. Based on Monte Carlo simulations, the obtained mean registration error of electrode
positions in tomographic functional images was in the range of 1-2 corresponding voxel size. In this way, the
constant bias in the reconstructed source image, that is due to the mis-registration of EEG electrode positions,
can be suppressed with respect to the random errors induced by EEG signal noise. Finally, we aim to improve,
or at all enable, the integration and application of the many functional modalities involved in the analysis and
evaluation of clinical neurophysiological disorders.
