title: Registration and analysis of white matter group differences with a multi-fiber model.
abstract: Diffusion magnetic resonance imaging has been used extensively to probe the white matter in vivo. Typically, the raw diffusion images are used to reconstruct a diffusion tensor image (DTI). The incapacity of DTI to represent crossing fibers leaded to the development of more sophisticated diffusion models. Among them, multi-fiber models represent each fiber bundle independently, allowing the direct extraction of diffusion features for population analysis. However, no method exists to properly register multi-fiber models, seriously limiting their use in group comparisons. This paper presents a registration and atlas construction method for multi-fiber models. The validity of the registration is demonstrated on a dataset of 45 subjects, including both healthy and unhealthy subjects. Morphometry analysis and tract-based statistics are then carried out, proving that multi-fiber models registration is better at detecting white matter local differences than single tensor registration.
authors.affiliation: Computational Radiology Laboratory, Children's Hospital Boston, Harvard, USA.
authors.forename: Maxime
authors.initials: M
authors.lastname: Taquet
authors.forename: Benoit
authors.initials: B
authors.lastname: Scherrer
authors.forename: Olivier
authors.initials: O
authors.lastname: Commowick
authors.forename: Jurriaan
authors.initials: J
authors.lastname: Peters
authors.forename: Mustafa
authors.initials: M
authors.lastname: Sahin
authors.forename: Benoît
authors.initials: B
authors.lastname: Macq
authors.forename: Simon K
authors.initials: SK
authors.lastname: Warfield
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology*; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008959:Models, Neurological; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014402:Tuberous Sclerosis / Q000473:pathology*