title: Belief propagation based segmentation of white matter tracts in DTI.
abstract: This paper presents a belief propagation approach to the segmentation of the major white matter tracts in diffusion tensor images of the human brain. Unlike tractography methods that sample multiple fibers to be bundled together, we define a Markov field directly on the diffusion tensors to separate the main fiber tracts at the voxel level. A prior model of shape and direction guides a full segmentation of the brain into known fiber tracts; additional, unspecified fibers; and isotropic regions. The method is evaluated on various data sets from an atlasing project, healthy subjects, and multiple sclerosis patients.
authors.affiliation: Johns Hopkins University, Baltimore, USA.
authors.forename: Pierre-Louis
authors.initials: PL
authors.lastname: Bazin
authors.forename: John
authors.initials: J
authors.lastname: Bogovic
authors.forename: Daniel
authors.initials: D
authors.lastname: Reich
authors.forename: Jerry L
authors.initials: JL
authors.lastname: Prince
authors.forename: Dzung L
authors.initials: DL
authors.lastname: Pham
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000166:cytology*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique