Three-dimensional MR brain segmentation

rn MR brain images, segmentation using intensity values is severely limited owing to field inhomogeneities, susceptibility artifacts and partial volume effects. Edge based segmentation methods stiffer from spurious edges and gaps in boundaries. A method is presented which combines the advantages of edge based and region based segmentation. First a multiscale image representation is constructed which favors intra-tissue diffusion over inter-tissue diffusion by exploiting local contrast. Subsequently a multiscale linking model (the hyperstack) is used to group voxels into a number of segments. This facilitates segmentation of grey matter, white matter and cerebrospinal fluid with minimal user interaction. Using a supervised segmentation technique and MR simulations of a brain phantom as validation it is shown, that the errors are in the order of or smaller than reported in literature.