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

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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.

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Taquet, M., Scherrer, B., Commowick, O., Peters, J., Sahin, M., Macq, B., & Warfield, S. K. (2012). Registration and analysis of white matter group differences with a multi-fiber model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7512 LNCS, pp. 313–320). Springer Verlag. https://doi.org/10.1007/978-3-642-33454-2_39

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