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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.

Original publication

DOI

10.1007/978-3-642-33454-2_39

Type

Journal article

Journal

Med Image Comput Comput Assist Interv

Publication Date

2012

Volume

15

Pages

313 - 320

Keywords

Algorithms, Brain, Computer Simulation, Diffusion Tensor Imaging, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Models, Neurological, Nerve Fibers, Myelinated, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique, Tuberous Sclerosis