A statistical model is presented that combines the registration of an atlas with the segmentation of magnetic resonance images. We use an Expectation Maximization-based algorithm to find a solution within the model, which simultaneously estimates image artifacts, anatomical labelmaps, and a structure-dependent hierarchical mapping from the atlas to the image space. The algorithm produces segmentations for brain tissues as well as their substructures. We demonstrate the approach on a set of 22 magnetic resonance images. On this set of images, the new approach performs significantly better than similar methods which sequentially apply registration and segmentation.

%B Neuroimage %V 31 %P 228-39 %8 2006 May 15 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/16466677?dopt=Abstract %R 10.1016/j.neuroimage.2005.11.044