DIPY is a free and open source software project for computational neuroanatomy, focusing mainly on diffusion magnetic resonance imaging (dMRI) analysis. It implements a broad range of algorithms for denoising, registration, reconstruction, tracking, clustering, visualization, and statistical analysis of MRI data.
Available on many operating systems
Denoising : NLmeans, Local PCA
SNR estimation / Reslice Datasets
Streamlines based Registration
Diffeomorphic 2D/3D Registration
Single Shell: DTI, CSD, SDT, SFM, Q-Ball CSA...
Multi Shell: GQI, DTI, DKI, SHORE and MAPMRI...
Many tracking algorithms
Apply different operations on streamlines
Simplify large datasets via streamlines clustering.
Calculate distances/correspondences between streamlines.
Simple interactive visualization of ODFs
Streamlines interactive visualization
Many algorithms available via command line
Create your owns command line!
DIPY 1.1.1 is now available. New features include:
New module for deep learning
DIPY.NN (uses TensorFlow 2.0).
Improved DKI performance and increased utilities.
Non-linear and RESTORE fits from DTI compatible now with DKI.
Numerical solutions for estimating axial, radial and mean kurtosis.
Added Kurtosis Fractional Anisotropy by Glenn et al. 2015.
Added Mean Kurtosis Tensor by Hansen et al. 2013.
Nibabel minimum version is 3.0.0.
Azure CI added and Appveyor CI removed.
New command line interfaces for LPCA, MPPCA and Gibbs Unringing.
New MTMS CSD tutorial added.
Horizon refactored and updated to support StatefulTractograms.
Speeded up all cython modules by using a smarter configuration setting.
All tutorials updated to API changes and 2 new tutorials added.
Large documentation update.
Closed 126 issues and merged 50 pull requests.
See Older Highlights.
Tue Jan 21
Did you notice DIPY Release 1.1.1😁? Here some Highlights: New module for deep learning DIPY.NN, Added Mean Kurtosis… https://t.co/rUOWr5CzUi
Fri Jan 17
Given the large growth of DIPY and the large need for sub-projects, DIPY moved to its own organization in Github. L… https://t.co/4qoYRNTQve
Thu Jan 09
RT @arokem: The tentative schedule for the @dipymri workshop @IULuddy in March is up: https://t.co/CRMh7crxbe and it is super! Looking forw…
Thu Jan 02
RT @arokem: New software for the new year! The first release of pyAFQ: https://t.co/KPLwbNnF4h. This is a Python reimplementation of the tr…
Thu Dec 19
RT @reiinakano: At #NeurIPS2019, talking to a guy from DeepMind about how I can't reproduce their results because it's so resource intensiv…
Garyfallidis E, Brett M, Amirbekian B, Rokem A, van der Walt S, Descoteaux M, Nimmo-Smith I and Dipy Contributors (2014). DIPY, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, vol.8, no.8.