This website describes the functionality of QMRITools, a toolbox for analysis of quantitative magnetic resonance imaging data. QMRITools is a collection of tools and functions for processing quantitative MRI data, runs in the latest version of Wolfram Mathematica and is developed and maintained by Martijn Froeling. The toolbox was initially developed for the analysis of diffusion imaging data of skeletal muscle. Over the years it has grown in its functionality and is currently used for the analysis, processing and simulations of quantitative muscle, nerve and cardiac magnetic resonance imaging and spectroscopy data. The library of functions grows along with the research it is used for.
QMRITools 5 is live!
Deep learning muscle segmentation now has a full train-and-deploy workflow and supports Dixon derivatives (source, water, fat, in-phase and out-phase) and DWI/DTI data on both 2D and 3D data for multiple body regions.
New in this release are end-to-end Muscle-BIDS processing from DICOM to per-muscle results, statistical shape models, AMARES spectroscopy fitting, and command line scripts for installation and segmentation. QMRITools can also call MuscleMap for segmentation. All muscle labels are standardized and grouped by anatomical function.
What’s new in QMRITools 5 ›› Manuals and scripts ››
QMRITools contains various toolboxes for the quantitative analysis muscle, nerve and cardiac MRI data.
QMRITools contains functions for the simulation of diffusion, dixon, EPG T2 mapping and spectroscopy data.
For all functions extended documentation and demonstrations are available. It also includes various example data sets.