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Please note that Mac support is experimental due to the unstable nature of the OpenCL drivers in Mac, that is, users running MDT with the GPU as selected device may experience crashes. Open a terminal and type: pip install mdt.Open an Anaconda shell and type: pip install mdt.The installation on Windows is a little bit more complex and the following is only a quick reference guide.įor complete instructions please view the complete documentation. for containerized deployment on a CPU cluster).įor example, to install using Docker use docker build -f containers/Dockerfile.intel. These dockers come with Intel OpenCL drivers pre-loaded (e.g. An alternative is to use pip3 install nibabel instead.Ī Dockerfile and Singularity recipe were kindly provided by Ali Khan (on github: akhanf). Note that python3-nibabel may need NeuroDebian to be available on your machine. sudo apt-get install python3 python3-pip python3-pyopencl python3-numpy python3-nibabel python3-pyqt5 python3-matplotlib python3-yaml python3-argcomplete libpng-dev libfreetype6-dev libxft-dev.sudo apt-get install python3-mdt python3-pipįor Debian users and Ubuntu sudo add-apt-repository ppa:robbert-harms/cbclab.OpenCL 1.2 (or higher) support in GPU driver or CPU runtime.To run, after installing MDT, go to the folder where you downloaded your (pre-processed) HCP data (MGH or WuMinn) and execute:Īnd it will autodetect the study in use and fit your selected model to all the subjects. MDT comes pre-installed with Human Connectome Project (HCP) compatible pipelines for the MGH and the WuMinn 3T studies. Runs on Intel, Nvidia and AMD GPU's and CPU's.Runs on Windows, Mac and Linux operating systems.Free Open Source Software: LGPL v3 license.Computations are parallelized over voxels and over volumes.Offers Graphical, command line and python interfaces.Supports volume weighted objective function.Supports gradient deviations per voxel and per voxel per volume.Includes multiple (adaptive) MCMC sampling algorithms.Includes Powell, Levenberg-Marquardt and Nelder-Mead Simplex optimization routines.Includes Gaussian, Offset-Gaussian and Rician likelihood models.Includes CHARMED, NODDI, BinghamNODDI, NODDIDA, NODDI-DTI, ActiveAx, AxCaliber, Ball&Sticks, Ball&Rackets, Kurtosis, Tensor, VERDICT, qMT, and relaxometry (T1, T2) models. Human Connectome Project (HCP) pipelines.MDT combines flexible modeling with fast processing, targeting both model developers and data analysts. The aim of MDT is to provide reproducible and comparable model fitting for MRI microstructure analysis.Īs such, we provide a common platform for microstructure modeling including many models that can all be processed using the same optimization routines.įor maximum performance all models and algorithms were implemented to make use of all parallel processing capabilities of modern computers. The Microstructure Diffusion Toolbox (MDT) is a framework and library for microstructure modeling of magnetic resonance imaging (MRI) data.
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