title: Inference of a HARDI fiber bundle atlas using a two-level clustering strategy.
abstract: This paper presents a method inferring a model of the brain white matter organisation from HARDI tractography results computed for a group of subjects. This model is made up of a set of generic fiber bundles that can be detected in most of the population. Our approach is based on a two-level clustering strategy. The first level is a multiresolution intra-subject clustering of the million tracts that are computed for each brain. This analysis reduces the complexity of the data to a few thousands fiber bundles for each subject. The second level is an intersubject clustering over fiber bundle centroids from all the subjects using a pairwise distance computed after spatial normalization. The resulting model includes the large bundles of anatomical literature and about 20 U-fiber bundles in each hemisphere.
authors.affiliation: Neurospin, CEA, Gif-sur-Yvette, France.
authors.forename: Pamela
authors.initials: P
authors.lastname: Guevara
authors.forename: Cyril
authors.initials: C
authors.lastname: Poupon
authors.forename: Denis
authors.initials: D
authors.lastname: Rivière
authors.forename: Yann
authors.initials: Y
authors.lastname: Cointepas
authors.forename: Linda
authors.initials: L
authors.lastname: Marrakchi
authors.forename: Maxime
authors.initials: M
authors.lastname: Descoteaux
authors.forename: Pierre
authors.initials: P
authors.lastname: Fillard
authors.forename: Bertrand
authors.initials: B
authors.lastname: Thirion
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Mangin
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D008959:Models, Neurological; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity