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.
Wed Feb 26
Getting ready for crazy visualization at the DIPY workshop 2020! 3 weeks to go! #Python #AI #Neurology #Medical… https://t.co/OC5LqBbXBh
Tue Feb 11
Present your poster at the DIPY Workshop 2020 and have your work integrated in DIPY! Poster sessions to present and… https://t.co/HbZLlUz7tZ
Tue Feb 04
RT @skoudoro: FURY will be part of #GSoC this year under the umbrella of @ThePSF. Check out our cool projects and be ready to apply! #grap…
Tue Feb 04
Congratulations to David who win the OHBM BrainArt (MELPOMENE category) by using DIPY and FURY!!! Really beautiful… https://t.co/9lClv1pyWi
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
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.