Statistical atlas-based sub-voxel segmentation of 3D brain MRI

We present a 3D brain MRI segmentation method in which a high resolution label image evolves under the influence of multiple constraints. The constraints are expressed in a versatile energy minimization framework which allows for evolutions only at label boundaries, effectively making it a surface evolution system. Constraints are defined using atlas-mapped parameters. The atlas, composed of a reference image and parameter values, is mapped onto the source image using a multiresolution deformable image matching method. Variable scale image constraints are considered. The prior model currently includes: a relative distribution constraint, which gives the probability of observing a label at a given distance from another label, a thickness constraint and a surface regularization constraint. Issues related to partial volumes are addressed by the use of a high resolution label image and an accurate model of the acquisition process. High resolution segmentations are thus obtained from standard (eventually low resolution) MRIs.