title: Registering a non-rigid multi-sensor ensemble of images.
abstract: The majority of image registration methods deal with registering only two images at a time. Recently, a clustering method that concurrently registers more than two multi-sensor images was proposed, dubbed ensemble clustering. In this paper, we apply the ensemble clustering method to a deformable registration scenario for the first time. Non-rigid deformation is implemented by a free-form deformation model based on B-splines with a regularization term. However, the increased degrees of freedom in the transformations caused the Newton-type optimization process to become ill-conditioned. This made the registration process unstable. We solved this problem by using the matrix approximation afforded by the singular value decomposition (SVD). Experiments show that the method is successfully applied to non-rigid multi-sensor ensembles and overall yields better registration results than methods that register only two images at a time.
authors.affiliation: David R. Cheriton School of Computer Science, University of Waterloo, ON, Canada, N2L3G1.
authors.forename: Hwa Young
authors.initials: HY
authors.lastname: Kim
authors.forename: Jeff
authors.initials: J
authors.lastname: Orchard
mesh_terms: D001921:Brain / Q000033:anatomy & histology; D016000:Cluster Analysis; D016208:Databases, Factual; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging