Non-rigid image registration on brain magnetic resonance images using graph-cuts

Abstract

We present a graph-cuts based method for non-rigid medical image registration on brain magnetic resonance images. In this thesis, the non-rigid image registration problem is reformulated as a discrete labeling problem. According to a voxel-to-voxel similarity measure, each voxel in the source image is assigned a displacement label, which represents a displacement vector, indicating which position in the floating image it is spatially corresponding to. A smoothness constraint based on the first derivatives is used to penalize sharp changes in the displacement labels across voxels. The image registration problem is therefore modeled by two energy terms based on intensity similarity and smoothness of the displacement field. These energy terms are submodular and can be optimized by using th...[ Read more ]