Keywords: Diffusion Modeling, Simulations, White-Matter, Monte-Carlo simulations.
Motivation: This work addresses the sampling bias related to voxel size and boundary conditions in DW-MRI Monte-Carlo simulations.
Goal(s): The study aims to understand how voxel-size and boundary-conditions influence Monte-Carlo simulations in DW-MRI to ensure convergence and minimise errors.
Approach: It uses simulations with realistic synthetic white-matter substrates and calculates diffusion propagators and apparent diffusion coefficients to measure simulation accuracy.
Results: It underscores the significance of voxel-size and boundary conditions in Monte-Carlo simulation and offers insights for better simulation parameters in DW-MRI. It also highlights conditions where errors can reach 20% and shows the need for larger voxel-sizes to achieve convergence.
Impact: The analysis focuses on making Monte-Carlo simulations reliable, enabling model validation from DW-MRI techniques. This has the potential to substantially improve microstructure assessment precision in clinical practice, enabling more accurate DW-MRI analysis.
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