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 1.0.0 is now available. New features include:
Critical API changes
Large refactoring of tracking API.
New denoising algorithm: MP-PCA.
New Gibbs ringing removal.
New interpolation module:
New reconstruction models: MTMS-CSD, Mean Signal DKI.
Increased coordinate systems consistency.
New object to manage safely tractography data: StatefulTractogram
New command line interface for downloading datasets: FetchFlow
Horizon updated, medical visualization interface powered by QuickBundlesX.
Removed all deprecated functions and parameters.
Removed compatibility with Python 2.7.
Updated minimum dependencies version (Numpy, Scipy).
All tutorials updated to API changes and 3 new added.
Large documentation update.
Closed 289 issues and merged 98 pull requests.
See Older Highlights.
Mon Aug 19
RT @garyfallidis: A historic moment! DIPY 1.0.0 is released with new tools and new website. Visit https://t.co/tqOmbkbCdV for more.
Wed Jun 26
Wed Jun 12
RT @furranko: Dan Bullock developed a new #whitematter segmentation with with 60 tracts available on @BrainLifeio for #reuse see his poster…
Wed Jun 12
RT @kirstie_j: 10:30: Towards DIPY 1.0: new user-friendly tools for visualization, tractometry and statistical analysis in diffusion MRI da…
Tue Jun 11
RT @skoudoro: Getting ready for #OHBM2019 !!! @garyfallidis @JulioVillaln1 @dipymri @arokem https://t.co/4ayBaC8NF6
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.