A generative model of realistic brain cells with application to numerical simulation of diffusion-weighted MR signal

by   Marco Palombo, et al.

In this work, we introduce a novel computational framework that we developed to use numerical simulations to investigate the complexity of brain tissue at a microscopic level with a detail never realised before. Directly inspired by the advances in computational neuroscience for modelling brain cells, we propose a generative model that enables us to simulate molecular diffusion within realistic digitalised brain cells, such as neurons and glia, in a completely controlled and flexible fashion. We validate our new approach by showing an excellent match between the morphology and simulated DW-MR signal of the generated digital model of brain cells and those of digital reconstruction of real brain cells from available open-access databases. We demonstrate the versatility and potentiality of the framework by showing a select set of examples of relevance for the DW-MR community. Further development is ongoing, which will support even more realistic conditions like dense packing of numerous 3D complex cell structures and varying cell surface permeability.


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