Coder Social home page Coder Social logo

md-dmri-data's Introduction

Multidimensional diffusion MRI data

This repository contains some simple data sets suitable for getting acquainted with the MD-dMRI framework for processing multidimensional diffusion MRI data.1 The data was acquired on a Bruker microimaging system with a custom diffusion-encoded RARE sequence2 using gradient waveforms and q-trajectories3 giving axisymmetric b-tensors.4 The data was originally reported in

How to start

  • Download the MD-dMRI framework and add to the Matlab search path.
  • Download this repository and locate a pdata_mddmri folder within for instance the Topgaard_NMRBiomed2019/SmallSpheres_BigSpheres_OrderedSticks data set.
  • Run step1_recon.m to convert the raw Bruker data to nifti images and experimental parameters to matlab format.
  • Run step2_fit.m to process the data with gamma,2 covariance,5 and 4D diffusion tensor distribution.6
  • View the images in the indata and fitdata/maps folders with the GUI started by typing mgui in the Matlab command window.
  • Run step3_dtdbootstrap.m to perform uncertainty estimation for the 4D diffusion tensor distributions.6
  • Run step4_dtdfigs.m to generate figures corresponding to Figs 3-7 in Topgaard_NMRBiomed2019.

References

  1. D. Topgaard. Multidimensional diffusion MRI. J. Magn. Reson. 275, 98-113 (2017).
  2. S. Lasič, F. Szczepankiewicz, S. Eriksson, M. Nilsson, D. Topgaard. Microanisotropy imaging: quantification of microscopic diffusion anisotropy and orientational order parameter by diffusion MRI with magic-angle spinning of the q-vector. Front. Physics 2, 11 (2014).
  3. S. Eriksson, S. Lasič, D. Topgaard. Isotropic diffusion weighting by magic-angle spinning of the q-vector in PGSE NMR. J. Magn. Reson. 226, 13-18 (2013).
  4. S. Eriksson, S. Lasič, M. Nilsson, C.-F. Westin, D. Topgaard. NMR diffusion encoding with axial symmetry and variable anisotropy: Distinguishing between prolate and oblate microscopic diffusion tensors with unknown orientation distribution. J. Chem. Phys. 142, 104201 (2015).
  5. C.-F. Westin, H. Knutsson, O. Pasternak, F. Szczepankiewicz, E. Özarslan, D. van Westen, C. Mattisson, M. Bogren, L. O'Donnell, M. Kubicki, D. Topgaard, M. Nilsson. Q-space trajectory imaging for multidimensional diffusion MRI of the human brain. Neuroimage 135, 345-362 (2016).
  6. D. Topgaard. Diffusion tensor distribution imaging. NMR Biomed., e4066 (2019).

md-dmri-data's People

Contributors

daniel-topgaard avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.