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Abstract #3639

Towards a more realistic and flexible white matter numerical phantom generator for diffusion MRI simulation

Ross Callaghan1, Noam Shemesh2, Daniel Alexander1, Hui Zhang1, and Marco Palombo1

1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal

We present a novel method for the generation of realistic white matter numerical phantoms with controllable morphology, and more realistic orientation-dispersion and packing-density. A shift of paradigm is proposed: rather than ‘packing fibres’, our algorithm ‘grows fibres’ contextually and efficiently, avoiding intersection between fibres. The potential of the method is demonstrated by reaching the highest orientation-dispersion and packing-density ever. The flexibility of the method is demonstrated with simulations of diffusion-weighted MR signal in three example substrates with differing orientation-dispersions, packing-densities and permeabilities. A proof-of-concept application is presented to investigate the impacts of undulation and beading on the intra-axonal axial diffusivity.

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