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**Authors** : Rakshit Dadarwal
**Description** : These Jupyter notebooks showcase an example of diffusion MRI preprocessing and analysis with python. They include steps for basic preprocessing (denoising, susceptibility-induced distortion correction, eddy current-induced distortion and motion correction), model fitting (DTI, DKI, NODDI) and calculation of parametric maps. These steps use functions from [DIPY](https://dipy.org/), [FSL](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/), and [AMICO](https://github.com/daducci/AMICO).
**Documentation** : [Jupyter notebooks on GitHub](https://github.com/RDadarwal/Diffusion-MRI)
**Link** : [GitHub link](https://github.com/RDadarwal/Diffusion-MRI)
**Language** : Python
**Publication** : -
**Communication** : [GitHub profile](https://github.com/RDadarwal)
**Restrictions** : None
**Authors** : Rogier B. Mars, Lennart Verhagen, and the members and collaborators of the Cognitive Neuroecology Lab
**Description** : A collection of tools for processing of multi-species neuroimaging data.
**Documentation** : [Online doc](http://www.neuroecologylab.org)
**Link** : [www.neuroecologylab.org](http://www.neuroecologylab.org)
**Language** : shell, matlab
**Publication** : [Mars et al. 2016](http://www.rbmars.dds.nl/pubs/Mars2016NBR.pdf), among others
**Communication** : [www.neuroecologylab.org](http://www.neuroecologylab.org)
**Restrictions** : None
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