Abstract #0792

To be Dispersed or Not to be Dispersed: A Study Using HCP Data

Aurobrata Ghosh¹, Daniel C Alexander¹, and Hui Zhang¹

¹Centre for Medical Image Computing, University College London, London, United Kingdom

We conduct model comparison experiments on the widely available HCP dataset to assess the importance of fibre-dispersion when modelling the brain’s tissue-microstructure from diffusion MRI (dMRI). Although many fibre dispersion configurations have been identified in the brain, most dMRI methods only model parallel or crossing fibres. To highlight the importance of dispersion, we design k-fold cross-validation experiments, on two HCP subjects, and compare ten compartment-based models using three metrics. We find that up to 50% of the brain-voxels, including white matter regions, support dispersion models over crossing models. Hence we conclude that it is important to model dispersion in dMRI.

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