title: Spatial transformations of diffusion tensor magnetic resonance images.
abstract: We address the problem of applying spatial transformations (or "image warps") to diffusion tensor magnetic resonance images. The orientational information that these images contain must be handled appropriately when they are transformed spatially during image registration. We present solutions for global transformations of three-dimensional images up to 12-parameter affine complexity and indicate how our methods can be extended for higher order transformations. Several approaches are presented and tested using synthetic data. One method, the preservation of principal direction algorithm, which takes into account shearing, stretching and rigid rotation, is shown to be the most effective. Additional registration experiments are performed on human brain data obtained from a single subject, whose head was imaged in three different orientations within the scanner. All of our methods improve the consistency between registered and target images over naïve warping algorithms.
authors.affiliation: Department of Computer Science, University College London, UK. daniel.alexander@cs.ucl.ac.uk
authors.forename: D C
authors.initials: DC
authors.lastname: Alexander
authors.forename: C
authors.initials: C
authors.lastname: Pierpaoli
authors.forename: P J
authors.initials: PJ
authors.lastname: Basser
authors.forename: J C
authors.initials: JC
authors.lastname: Gee
mesh_terms: D000328:Adult; D000465:Algorithms; D001331:Automation; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D004058:Diffusion; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008962:Models, Theoretical; D011859:Radiography; D012016:Reference Values