Rigid image registration by General Adaptive Neighborhood matching

Non-Rigid Image Registration

An important hypothesis of the research reported in this paper is that dynamic space warping (DSW), a dynamic programming (DP) technique (Bellman 1965, Brown 1996), can be effectively used for object matching and for inference of the image registration warping function. For this end, a novel, robust, and efficient method for non-rigid image registration using DSW in the “length–code” domain is ...

A General Learning Framework for Non-rigid Image Registration

This paper presents a general learning framework for non-rigid registration of MR brain images. Given a set of training MR brain images, three major types of information are particularly learned, and further incorporated into a HAMMER registration algorithm for improving the performance of registration. First, the best features are learned from different types of local image descriptors for eac...

Non-Rigid Morphological Image Registration

Volume image registration by template matching

A template-matching approach to registration of volumetric images is introduced. The process automatically selects a dozen highly detailed and unique templates (cubic or spherical subvolumes) from one image and locates the templates in another image of the same scene. The centroids of the corresponding templates are used as corresponding control points and the best four correspondences that min...

Image registration by local histogram matching

We previously presented an image registration method, referred to hierarchical attribute matching mechanism for elastic registration (HAMMER), which demonstrated relatively high accuracy in inter-subject registration of MR brain images. However, the HAMMER algorithm requires the pre-segmentation of brain tissues, since the attribute vectors used to hierarchically match the corresponding pairs o...