A fast method to derive realistic BEM models for E/MEG source reconstruction

A fast method for segmentation of a subject´s skin, skull or brain compartment for electroencephalogram (EEG)/magnetoencephalogram (MEG) (E/MEG) source localization is proposed. The method is based on a description of volumes with spherical harmonics and a database of exact surfaces. Using the spherical harmonic coefficients, sets of basis surfaces are obtained for each compartment. New segmentations can be acquired by combining the appropriate basis surfaces to describe a delineation of the volume in a limited number of magnetic resonance (MR) slices. Alternatively, a representation of the skin can be derived from digitized head shape. Skull and brain then can be predicted from the skin representation with a prediction model also obtained from the segmentation database. Database segmentations were recomputed with the proposed method. Mean deviations from the originals were about 2 and 3 mm for compartments derived from MR and head shape. Dipole simulations with original surfaces for forward and computed segmentations for inverse calculations showed average dipole mislocalizations of 1.6 and 3.3 mm, respectively. With the proposed method highly accurate segmentation can be performed with much less effort and in much less time compared with other techniques. The method also is applicable when MR data is unavailable but a digitization of the head is