Segmentation of Brain Internal Structures Automatically Using Non-rigid Registration with Simultaneous Intensity and Geometric Match

Segmentation of the brain internal structures is an important and a challenging task due to their small size, partial volume effects, and anatomical variability. In this paper we propose a method that segments automatically the deep brain internal structures from brain MRI images. It uses a combination of local affine transformation and optical flow based non-rigid registration, which has the advantages of modifying the larger geometric deformation and intensity differences simultaneously. Meanwhile the residual subtle differences decrease due to the high degree of freedom. Both simulated data and real data are used to validate the proposed method and the results are encouraging. It can be concluded that the image gray level of the corresponding structures plays an important role in registration based segmentation using intensity metric.