title: Reorientation of fiber orientation distributions using apodized point spread functions.
abstract: Using high angular resolution diffusion-weighted images, spherical deconvolution enables multiple white matter fiber populations to be resolved within a single voxel by computing the fiber orientation distribution (FOD). Higher order information provided by FODs could improve several methods for investigating population differences in white matter, including image registration, voxel-based analysis, atlas-based segmentation and labeling, and group average fiber tractography. All of these methods require spatial normalization of FODs. In this article, a novel method to reorient the FOD is presented, which is an important step required for FOD spatial normalization. The proposed method was assessed using both qualitative and quantitative experiments, with numerical simulations and in vivo human data. Results demonstrate that the proposed method improves FOD reorientation accuracy, removes undesired artefacts, and decreases computation time compared to a previous approach. The utility of the proposed method is illustrated by nonlinear FOD spatial normalization of 10 human subjects. Accurate reorientation and normalization of FODs is a critical step toward investigating white matter tissue in the context of multiple fiber orientations.
authors.affiliation: CSIRO Preventative Health National Research Flagship ICTC, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia. david.raffelt@csiro.au
authors.forename: David
authors.initials: D
authors.lastname: Raffelt
authors.forename: J-Donald
authors.initials: JD
authors.lastname: Tournier
authors.forename: Stuart
authors.initials: S
authors.lastname: Crozier
authors.forename: Alan
authors.initials: A
authors.lastname: Connelly
authors.forename: Olivier
authors.initials: O
authors.lastname: Salvado
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*