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https://github.com/kerkelae/disimpy
Massively parallel Monte Carlo diffusion MR simulator written in Python.
https://github.com/kerkelae/disimpy
cuda diffusion-mri gpu-computing monte-carlo-simulation
Last synced: about 8 hours ago
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Massively parallel Monte Carlo diffusion MR simulator written in Python.
- Host: GitHub
- URL: https://github.com/kerkelae/disimpy
- Owner: kerkelae
- License: mit
- Created: 2020-04-05T16:57:18.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2024-11-02T14:20:15.000Z (3 months ago)
- Last Synced: 2025-01-03T15:16:09.493Z (about 1 month ago)
- Topics: cuda, diffusion-mri, gpu-computing, monte-carlo-simulation
- Language: Python
- Homepage: https://disimpy.readthedocs.io/
- Size: 11.2 MB
- Stars: 25
- Watchers: 3
- Forks: 9
- Open Issues: 5
-
Metadata Files:
- Readme: README.rst
- License: license.txt
Awesome Lists containing this project
README
*******
Disimpy
*******
Disimpy is a Python package for generating simulated diffusion-weighted MR
signals that can be useful in the development and validation of data
acquisition and analysis methods. The data is generated by Monte Carlo random
walk simulations that run massively parallel on Nvidia CUDA-capable GPUs. If
you use Disimpy in work that leads to a scientific publication, please cite
[1]_, where the details about signal generation can also be found.
Requirements and installation
#############################
Follow the `installation instructions
`_.
Usage example
#############
Read the `tutorial `_
to learn how to use Disimpy.
Validation
##########
Disimpy's functionality has been validated by comparing its results to
analytical solutions and to results from other simulators (e.g., `Camino
`_ and `MISST
`_), and by automated
testing (:code:`disimpy.tests`). Examples of simulations used for validation
are provided `here
`_. However, Disimpy
is research software and some bugs undoubtedly remain. If you find any of them
or encounter unexpected behaviour, please open an `issue on GitHub
`_.
Contribute
##########
If you want to contribute to the development of Disimpy, start by reading the
`contributing guidelines
`_.
Support
#######
If you have questions or need help, open an `issue on Github
`_.
References
##########
.. [1] Kerkelä et al., (2020). Disimpy: A massively parallel Monte Carlo
simulator for generating diffusion-weighted MRI data in Python. Journal
of Open Source Software, 5(52), 2527.
https://doi.org/10.21105/joss.02527
Sponsors
########
|
.. image:: https://disimpy.readthedocs.io/en/latest/_static/nihr_gosh_brc_logo.png
:width: 418
:alt: National Institute of Health Research Great Ormond Street Biomedical Research Centre
:align: center
:target: https://www.gosh.nhs.uk/our-research/our-research-infrastructure/nihr-great-ormond-street-hospital-brc/
|
.. image:: https://disimpy.readthedocs.io/en/latest/_static/gsoc_logo.png
:width: 200
:alt: Google Summer of Code
:align: center
:target: https://summerofcode.withgoogle.com/
|
.. image:: https://disimpy.readthedocs.io/en/latest/_static/rh_logo.png
:width: 300
:alt: ResearchHub
:align: center
:target: https://www.researchhub.com/