dMRI-Lab: advanced diffusion MRI with Matlab

PURPOSE

This is a Work-In-Process toolbox designed for Matlab(R) and aimed at the computational analysis of diffusion MRI. It addresses basic concepts such as Diffusion Tensor Imaging (DTI), but also advanced topics like High Angular Resolution Diffusion Imaging (HARDI, including estimation and representation of Orientation Distribution Functions-ODF), multi-shell samplings, and computational diffusion MRI. We have tested the library for Matlab versions starting R2015b, but we advice using a more recent version. A working license for the Parallel Computing Toolbox is strongly recommended (but not necessary).

GET STARTED

  1. Download the package and unzip to a local folder at will.
  2. From the Matlab command window, cd to the home folder, i. e. that containing the setup script "setup__DMRIMatlab_toolbox.m".
  3. Run the setup script as either:
    • >> setup__DMRIMatlab_toolbox('useparallel',true);
    • >> setup__DMRIMatlab_toolbox('useparallel',false); or simply: >> setup__DMRIMatlab_toolbox;

    for using/avoid using the Parallel Computing Toolbox. In case you don't have a working license for it, the script will not throw an error. This will setup your Matlab path for the present session (it won't make any permanent change).

  4. Open/run some of the demo files in the "examples" folder to get started.

LICENSING

Copyright (c) 2021, Antonio Tristán Vega, Santiago Aja-Fernández, Guillem París. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  • Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

In case you use the package for your own research, we ask you to kindly cite it as: Antonio Tristán-Vega, Santiago Aja-Fernández and Guillem París "dMRI-Lab: advanced diffusion MRI with Matlab" [Online resource] https://www.lpi.tel.uva.es/dmrilab January 2022. Universidad de Valladolid. Spain

SEE ALSO

You might be as well interested in other related software products developed at the LPI.

PUBLICATIONS

Note this library is a compendium of many techniques delivered from the original research carried out at the LPI for more than a decade. As such, you will find implementations for the methods described in several papers listed in our publications site.

On DT-MRI:

https://www.lpi.tel.uva.es/node/107 (Noise propagation in DT-MRI)

https://www.lpi.tel.uva.es/node/113 (Noise propagation in DT-MRI; journal version)

https://www.lpi.tel.uva.es/node/210 (Discontinued Saturn software)

On dMRI denoising:

https://www.lpi.tel.uva.es/node/93 (Joint Wiener filter, jLMMSE)

https://www.lpi.tel.uva.es/node/85 (Joint Wiener filter, jLMMSE; journal version)

https://www.lpi.tel.uva.es/node/161 (Joint anisotropic Wiener filter - jaLMMSE)

On HARDI imaging and ODF estimation:

https://www.lpi.tel.uva.es/node/80 (HARDI-OPDT)

https://www.lpi.tel.uva.es/node/103 (HARDI - cQ-Balls, pQ-Balls)

https://www.lpi.tel.uva.es/node/89 (HARDI-cOPDT, pOPDT)

On computational dMRI:

https://www.lpi.tel.uva.es/node/844 (HARDI/multi-shell - AMURA)

https://www.lpi.tel.uva.es/node/899 (HARDI/multi-shell - AMURA-APA)

https://www.lpi.tel.uva.es/node/900 (Multi-shell imaging - MiSFIT)

http://www.lpi.tel.uva.es/node/934 (Multi-shell imaging - Free water estimation with spherical means)

http://www.lpi.tel.uva.es/node/954 (Multi-shell imaging - gAMURA)

Additionally, you will find implementations for the methods described in this paper currently under review:

Antonio Tristán-Vega, Tomasz Pieciak, Guillem París, Justion R. Rodríguez-Galván, and Santiago Aja-Fernández. "HYDI-DSI revisited: constrained non-parametric EAP imaging without q-space re-gridding" January 2021. Submitted to Medical Image Analysis.