Abstract #2005

Generative statistical models of white matter microstructure for MRI simulations in virtual tissue blocks

Leandro Beltrachini¹ and Alejandro Frangi¹

¹The University of Sheffield, Sheffield, United Kingdom

In silico studies of diffusion MRI are becoming a standard tool for testing the sensitivity of the technique to changes in white matter (WM) structures. To perform such simulations, realistic models of brain tissue microstructure are needed. However, most of the computational results are obtained considering straight and parallel cylinders models, which are known to be too simplistic for representing real-scenario situations. We present a statistical-driven approach for obtaining random models of WM tissue samples based on histomorphometric data available in the literature. We show the versatility of the method for characterising WM voxels representing bundles and disordered structures.

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