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

arXiv: https://arxiv.org/abs/1806.07125 · HTML: https://mlsanity.com/paper/1806.07125/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2018.

## Built on by (most cited first, 2 of 2)

- [ReMiDi: Reconstruction of Microstructure Using a Differentiable Diffusion MRI Simulator](https://mlsanity.com/paper/2502.01988/) (2025)
- [A Streaming Volumetric Image Generation Framework for Development and Evaluation of Out-of-Core Methods](https://mlsanity.com/paper/2112.09809/) (2021)

## Abstract (arXiv)

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.