Disimpy
Disimpy: A massively parallel Monte Carlo simulator for generating diffusion-weighted MRI data in Python - Published in JOSS (2020)
KomaMRI
Koma is a Pulseq-compatible framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in pulse sequence development.
dmriprep
dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
dmipy
The open source toolbox for reproducible diffusion MRI-based microstructure estimation
https://github.com/dipy/dipy
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
https://github.com/bids-apps/mrtrix3_connectome
Generate subject connectomes from raw BIDS data & perform inter-subject connection density normalisation, using the MRtrix3 software package.
https://github.com/bids-apps/tracula
implements Freesurfer's TRACULA (TRActs Constrained by UnderLying Anatomy) tool for cross-sectional as well as longitudinal (multi session) input data.
https://github.com/aramis-lab/clinica_pipeline_noddi
NODDI pipeline used for [Wen et al., 2018]
mri-on-bear-edu
Repository for the Magnetic Resonance Imaging in Cognitive Neuroscience (MRICN) course, University of Birmingham
https://github.com/bids-apps/ndmg
BIDS app for NeuroData's MRI to Graphs pipeline