A unifying approach to registration, segmentation, and intensity correction

Pohl KM, Fisher J, Levitt JJ, Shenton ME, Kikinis R, Grimson WE, Wells WM

Med Image Comput Comput Assist Interv 2005;8(Pt 1):310-8

PMID: 16685860


We present a statistical framework 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 inhomogeneities, anatomical labelmap, and a mapping from the atlas to the image space. An example of the approach is given for a brain structure-dependent affine mapping approach. The algorithm produces high quality segmentations for brain tissues as well as their substructures. We demonstrate the approach on a set of 22 magnetic resonance images. In addition, we show that the approach performs better than similar methods which separate the registration and segmentation problems.