QMRITools is written in Mathematica using Wolfram Workbench and Eclipse and contains a collection of tools and functions for processing quantitative MRI data. The toolbox does not provide a GUI and its primary goal is to allow for fast and batch data processing, and facilitate development and prototyping of new functions. The core of the toolbox contains various functions for data manipulation and restructuring.
The toolbox contains some basic functionality such as DICOM and Nifti import, and 2D, 3D and 4D data visualization. The advanced features comprise data registration using Elastix, noise suppression , diffusion drift correction , DTI and IVIM processing, gradient direction optimization , simulation framework, EPG based T2 fitting and IDEAL Dixon reconstruction, and more.
Froeling M, Nederveen AJAJ, Nicolay K, Strijkers GJGJ: DTI of human skeletal muscle: The effects of diffusion encoding parameters, signal-to-noise ratio and T2 on tensor indices and fiber tracts. NMR Biomed 2013; 26:1339–1352.
Froeling M, Tax CMWCMW, Vos SBSB, Luijten PRPR, Leemans A: “MASSIVE” brain dataset: Multiple acquisitions for standardization of structural imaging validation and evaluation. Magn Reson Med 2017; 77:1797–1809.
1University Medical Center (UMC) Utrecht, Netherlands