Global 3D rigid registration of medical images

We present in this paper an iterative algorithm for the simultaneous registration of multiple 3D medical images. The proposed algorithm is a point-based registration method and is based on global registration techniques rather than the traditional pair-wise registration methods. Corresponding feature points, known as extremal points, are first automatically extracted from the 3D images and are used as the matching features in the registration process. These extremal points are stable landmarks, as the relative positions of these points are known to be invariant according to 3D rigid transformations. The registration algorithm is based on a novel weighted least squares formulation and it also incorporates 3D noise models on the extracted feature points. Results will be presented for the 3D rigid registration of three successive images of the same patient taken at different periods of time.