Segmentation of Patient Specific Meg / Eeg Skull , Scalp , and Brain Models from Mri

Content Provider	Semantic Scholar
Author	Dogdas, Belma Shattuck, David W. Leahy, Richard M.
Copyright Year	2002
Abstract	We present an automated method for segmenting skull, scalp, and brain regions in T1-weighted MR images of the human head that are suitable for MEG and EEG source modeling. These segmentation results can be used to generate surface and volume tessellations suitable for finite element method (FEM) or boundary element method (BEM) forward field calculations. We first segment the brain from the head using our Brain Surface Extractor software. We then use a combination of thresholding and morphology to produce a scalp mask. The brain and scalp masks provide boundaries between which the skull must lie and allow us to quickly exclude exterior voxels with intensities similar to those of the skull. We find the inner and outer skull boundaries using thresholding and morphological operations. We then mask these results with the scalp and brain volumes to ensure closed and nonintersecting skull boundaries. We have applied our segmentation algorithm to several MR images and validated our method using coregistered CT-MR image data sets.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://neuroimage.usc.edu/paperspdf/dogdas_biomag_02.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article