Table 1.
A list of current, mature, open-source MRI image processing and ML frameworks as well as the general MRI community portals.
| General | ||
|---|---|---|
| NIF | https://neuinfo.org/ | Neuroscience Information Framework - a neuroscience community portal |
| Open fMRI | https://www.openfmri.org/ | Community portal for free and open sharing of raw magnetic resonance imaging (MRI) datasets |
| Open source imaging | http://www.opensourceimaging.org | Developers of open hardware imaging devices and image processing techniques |
| ANDI | http://adni.loni.usc.edu/ | The Alzheimer's disease neuroimaging initiative (ADNI) |
| Open source frameworks | ||
| 3D Slicer | https://www.slicer.org | Rich on features, open source, extendable, multi-platform |
| Brain Voyager | http://www.brainvoyager.com/ | Analysis and visualization of structural and functional MRI data combined with EEG or MEG distributed source imaging |
| Freesufter | http://freesurfer.net/ | Both low and high level processing and analyzing of brain MRI images |
| BrainSuite | http://brainsuite.org/ | Software tools for automated processing of brain MRIs |
| SlicerDMRI | Diffusion MRI Software for Brain Cancer Research | |
| Brain Atlas | http://www.brain-map.org/ | A collection of tools for segmentation, registration, and volumetric analysis of the functional brain centers |
| Fiber Navigator | http://scilus.github.io/fibernavigator/ | Fiber visualization and reconstruction toolbox from DTI data |
| TrackVis | http://trackvis.org/ | Fiber visualization and reconstruction toolbox from DTI data |
| Camino | http://camino.cs.ucl.ac.uk/ | DTI image processing and fuber reconstruction |
| DTI-tk | dti-tk.sourceforge.net | DTI image processing with spatial normalization and atlas construction for white matter morphometry measurements |
| ANTS | http://stnava.github.io/ANTs/ | Advanced Normalization Tools (ANTs) |
| http://picsl.upenn.edu/software/ants/ | ||
| ITK-Snap | http://www.itksnap.org | Segmentation of 3D structures from medical images using active contours |
| MITK | http://mitk.org/ | A toolbox for development of interactive medical image processing software |
| Elastix | http://elastix.isi.uu.nl/ | A toolbox for rigid and nonrigid registration of images |
| Gadgetgron | http://gadgetron.github.io/ | NIH framework for medical image reconstruction |
| gpuNUFFT | http://cai2r.net/resources/software | Accelerator gridding library with Matlab interface |
| BART | http://mrirecon.github.io/bart/ | Berkeley Advanced Reconstruction Toolbox |
| https://lists.eecs.berkeley.edu/sympa/info/mrirecon | ||
| Pulseq | http://pulseq.github.io/ | Open-source pulse sequences |
| JEMRIS | http://www.jemris.org/ | Multi-purpose MRI sequence development and simulation environment |
| MARIE | https://github.com/thanospol/MARIE | Magnetic Resonance Integral Equation Suite |
| NiftyRec | https://sourceforge.net/projects/niftyrec/ | Reconstruction library |
| General MRI, imaging or ML libraries | ||
| GIMIAS | http://www.gimias.org/ | A workflow-oriented environment for solving advanced, biomedical image computing and individualized simulation problems |
| SPM | https://www.fil.ion.ucl.ac.uk/spm/ | The analysis of brain imaging data sequences using Statistical Parametric Mapping as an assessment of spatially extended statistical processes used to test hypotheses about functional imaging data |
| FSL | https://fsl.fmrib.ox.ac.uk | A collection of analysis tools for FMRI, MRI and DTI brain imaging data |
| PyBrain | http://pybrain.org/ | Reinforcement Learning, Artificial Intelligence and Neural Network Library |
| TensorFlow: | http://tensorflow.org | ML and AI frameworks |
| Caffe | http://caffe.berkeleyvision.org/ | A deep ML framework |
| PyMVPA | http://www.pymvpa.org/ | Statistical learning analysis platform |
| Weka | https://www.cs.waikato.ac.nz/ml/weka/ | Data mining platform |
| Shogun | http://www.shogun-toolbox.org/ | Machine learning framework |
| SciKit Learn | http://scikit-learn.org | Scientific computation libraries |
| PRoNTo | http://www.mlnl.cs.ucl.ac.uk/pronto/ | Machine learning framework |
The table includes the standalone, purpose built packages as well as the extendable frameworks for the MRI image processing and machine learning.