title: A pointwise correspondence based DT-MRI fiber similarity measure.
abstract: Diffusion Tensor Magnetic Resonance Imaging (DTI) fiber tractography is a way to reconstruct fiber tracts underlying data according to local anisotropic diffusion characteristics. Reliability of fiber tracts as a result of tractography decreases due to noise in the data, error accumulation during integration and stochastic nature of the underlying data. We proposed a new similarity measure based on point-wise correspondence between tracts. Laplacian Eigenmaps are used to embed the fiber tracts into ℜ(3) based on the new similarity measure. We compared our method with a previously proposed method, on real and phantom data, that uses a 9D feature space to measure fiber similarity and showed that the new similarity measure results in a low dimensional manifold representing the fiber bundles. We presented preliminary results demonstrating that the fibers that fall far from this manifold correspond to outliers.
authors.affiliation: Department of Electrical and Electronics Engineering, Boğaziçi University, İstanbul, Turkey.
authors.forename: Sema
authors.initials: S
authors.lastname: Berkiten
authors.forename: Burak
authors.initials: B
authors.lastname: Acar
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D001921:Brain / Q000473:pathology; D016000:Cluster Analysis; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D015233:Models, Statistical; D016011:Normal Distribution; D010363:Pattern Recognition, Automated; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013269:Stochastic Processes