title: Fourier registration of three-dimensional brain MR images: exploiting the axis of rotation.
abstract: We have developed a novel algorithm to register three-dimensional MR images that have undergone rigid body motion. The most interesting feature of the algorithm is that it reduces a general three-dimensional rotation to a simple planar rotation by finding the axis of rotation. The algorithm, which is a nontrivial three-dimensional extension of existing Fourier registration algorithms, has been tested on 30 artificially misaligned MR images of a phantom, four artificially misaligned MR images of a brain, and one case of actual patient motion. The algorithm successfully registered every image. The registration error for a voxel 10 cm from the origin for the artificially misaligned phantom images was 2.8 mm at most and had a mean of 1.2 mm and standard deviation of .7 mm. The registration parameters for the images contaminated by actual patient motion were similar to that from an established image registration algorithm. The results indicate that the algorithm is accurate, reliable, and fast. The rigid body model requires the brain to be segmented from MR images of the head before registration.
authors.affiliation: Department of Medical Biophysics, University of Toronto, Ontario, Canada.
authors.forename: A
authors.initials: A
authors.lastname: Kassam
authors.forename: M L
authors.initials: ML
authors.lastname: Wood
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D005583:Fourier Analysis; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012399:Rotation