Registration and analysis of white matter group differences with a multi-fiber model.

Taquet, Maxime [UCL] Scherrer, Benoit [Harvard Medical School] Commowick, Olivier [INRIA] Peters, Jurriaan [Harvard Medical School] Sahin, Mustafa [Harvard Medical School] Macq, Benoît [UCL] Warfield, Simon [Harvard Medical School] et al.

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.