Disimpy: A massively parallel Monte Carlo simulator for generating diffusion-weighted MRI data in Python

@article{Kerkel2020DisimpyAM,
  title={Disimpy: A massively parallel Monte Carlo simulator for generating diffusion-weighted MRI data in Python},
  author={Leevi Kerkel{\"a} and Fabio Nery and Matt G. Hall and Chris A Clark},
  journal={J. Open Source Softw.},
  year={2020},
  volume={5},
  pages={2527}
}
Disimpy is a simulator for generating diffusion-weighted magnetic resonance imaging (dMRI) data that is useful in the development and validation of new methods for data acquisition and analysis. Diffusion of water is modelled as an ensemble of random walkers whose trajectories are generated on an Nvidia (Nvidia Corporation, Santa Clara, California, United States) CUDA-capable (Nickolls, Buck, Garland, & Skadron, 2008) graphical processing unit (GPU). The massive parallelization results in a… 
4 Citations

Figures from this paper

Unraveling micro-architectural modulations in neural tissue upon ischemia by Correlation Tensor MRI
TLDR
It is shown that CTI can resolve the sources of diffusional kurtosis, which in turn, provide dramatically enhanced specificity and sensitivity towards ischemia, which bodes well for future applications in biomedicine, basic neuroscience, and in the clinic.

References

SHOWING 1-10 OF 25 REFERENCES
Realistic voxel sizes and reduced signal variation in Monte-Carlo simulation for diffusion MR data synthesis
TLDR
The new method improves accuracy, precision, and reproducibility of synthetic measurements in Monte-Carlo simulation-based data synthesis, leading to reduced bias and variance in synthesised data, compared to existing implementation of MC simulations.
Convergence and Parameter Choice for Monte-Carlo Simulations of Diffusion MRI
TLDR
A general and flexible Monte- Carlo simulation framework for diffusing spins that generates realistic synthetic data for diffusion magnetic resonance imaging and achieves an optimal combination of spins and updates for a given run time by trading off number of updates in favor of number of spins.
SpinDoctor: A MATLAB toolbox for diffusion MRI simulation
Microstructure Imaging Sequence Simulation Toolbox
TLDR
A semi-analytical simulation software, which is based on a matrix method approach and computes diffusion signal for fully general, user specified pulse sequences and tissue models, to provide a deep understanding of the restricted diffusion MRI signal for a wide range of realistic, fully flexible scanner acquisition protocols, in practical computational time.
Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the Substrate Complexity and Parameter Choice on the Reproducibility of Results
TLDR
This work presents a general framework able to generate complex substrates and shows the framework's capability to overcome the aforementioned simplifications by generating a complex crossing substrate, which preserves the volume in the crossing area and achieves a high packing density.
Diffusion MRI: From Quantitative Measurement to In vivo Neuroanatomy: Second Edition
TLDR
The fundamental theory of diffusion imaging is covered, its most promising applications to basic and clinical neuroscience are discussed, and cutting-edge methodological developments that will shape the field in coming years are introduced.
High-Fidelity Meshes from Tissue Samples for Diffusion MRI Simulations
TLDR
The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.
...
1
2
3
...