title: A viscous fluid model for multimodal non-rigid image registration using mutual information.
abstract: We propose a multimodal free-form registration algorithm based on maximization of mutual information. The warped image is modeled as a viscous fluid that deforms under the influence of forces derived from the gradient of the mutual information registration criterion. Parzen windowing is used to estimate the joint intensity probability of the images to be matched. The method is evaluated for non-rigid inter-subject registration of MR brain images. The accuracy of the method is verified using simulated multi-modal MR images with known ground truth deformation. The results show that the root mean square difference between the recovered and the ground truth deformation is smaller than 1 voxel. We illustrate the application of the method for atlas-based brain tissue segmentation in MR images in case of gross morphological differences between atlas and patient images.
authors.affiliation: Faculties of Medicine and Engineering, Medical Image Computing (Radiology-ESAT/PSI), Katholieke Universiteit Leuven, University Hospital Gasthuisberg, Herestraat 49, B-3000 Leuven, Belgium. emiliano.dagostino@uz.kuleuven.ac.be
authors.forename: Emiliano
authors.initials: E
authors.lastname: D'Agostino
authors.forename: Frederik
authors.initials: F
authors.lastname: Maes
authors.forename: Dirk
authors.initials: D
authors.lastname: Vandermeulen
authors.forename: Paul
authors.initials: P
authors.lastname: Suetens
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D014783:Viscosity