Skip to content

DMRITool is an open souce toolbox for reconstruction, processing and visualization of diffusion MRI data (DWI, tensor, ODF,EAP, fibers etc.).

License

Notifications You must be signed in to change notification settings

computational-neuroimaging-lab/dmritool

 
 

Repository files navigation

DMRITool

Build Status Codacy Badge

Introduction

DMRITool is a free and open source toolbox for diffusion MRI data processing. It is written in C++ with matlab interface.

With DMRITool, you can:

  • perform reconstruction/estimation of diffusion data, including diffusion weighted signal, ensemble average propagator (EAP), diffusion orientation distribution function (dODF), and some meaningful scalar maps, etc.
  • generate spherically uniform sampling schemes for single or multiple shells.
  • perform diffusion MRI data simulation.
  • visualize spherical function fields (e.g. dODF fields, EAP profile fields)

Website

Please check the DMRITool website for documentation and more information.

Download

You can download the latest source codes from github:

git clone https://github.com/DiffusionMRITool/dmritool

Building

See this page for building the source codes.

Citation

Citations will help us support the continued development of DMRITool.

If you use the methods and codes released in DMRITool, please cite the related references. See the citation page for details.

Acknowledgements

DMRITool is/was supported by the following research groups:

License

DMRITool is a free open source software. It is currently under the GNU General Public License, because it uses GSL for mathematical special functions and SPAMS for some optimization problems.

The software under the license is distributed on an "as is" basis, without warranties. It is user's responsibility to validate the behavior of the routines and their accuracy using the released source code.

About

DMRITool is an open souce toolbox for reconstruction, processing and visualization of diffusion MRI data (DWI, tensor, ODF,EAP, fibers etc.).

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 90.9%
  • MATLAB 3.4%
  • CMake 2.9%
  • C 1.5%
  • Python 1.2%
  • Dockerfile 0.1%