title: Streamline flows for white matter fibre pathway segmentation in diffusion MRI.
abstract: We introduce a fibre tract segmentation algorithm based on the geometric coherence of fibre orientations as indicated by a streamline flow model. The inference of local flow approximations motivates a pairwise consistency measure between fibre ODF maxima. We use this measure in a recursive algorithm to cluster consistent ODF maxima, leading to the segmentation of white matter pathways. The method requires minimal seeding compared to streamline tractography-based methods, and allows multiple tracts to pass through the same voxels. We illustrate the approach with a segmentation of the corpus callosum and one of the cortico-spinal tract, with each example seeded at a single voxel.
authors.affiliation: McGill University, Montréal, QC, Canadal.
authors.forename: Peter
authors.initials: P
authors.lastname: Savadjiev
authors.forename: Jennifer S W
authors.initials: JS
authors.lastname: Campbell
authors.forename: G Bruce
authors.initials: GB
authors.lastname: Pike
authors.forename: Kaleem
authors.initials: K
authors.lastname: Siddiqi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003337:Corpus Callosum / 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*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011712:Pyramidal Tracts / Q000033:anatomy & histology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity