title: Diffusion k-tensor estimation from Q-ball imaging using discretized principal axes.
abstract: A reoccurring theme in the diffusion tensor imaging literature is the per-voxel estimation of a symmetric 3 x 3 tensor describing the measured diffusion. In this work we attempt to generalize this approach by calculating 2 or 3 or up to k diffusion tensors for each voxel. We show that our procedure can more accurately describe the diffusion particularly when crossing fibers or fiber-bundles are present in the datasets.
authors.affiliation: Laboratory of Mathematics in Imaging, Harvard Medical School, Boston MA, USA.
authors.forename: Orjan
authors.initials: O
authors.lastname: Bergmann
authors.forename: Gordon
authors.initials: G
authors.lastname: Kindlmann
authors.forename: Arvid
authors.initials: A
authors.lastname: Lundervold
authors.forename: Carl-Fredrik
authors.initials: CF
authors.lastname: Westin
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D009434:Neural Pathways / Q000033:anatomy & histology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted