What is DIPY?
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.
DIPY is easy to install:
Available on many operating systems
Pre-Processing
Registration
Reconstruction
Single Shell: DTI, CSD, SDT, SFM, Q-Ball CSA...
Multi Shell: GQI, DTI, DKI, SHORE and MAPMRI...
Tractography
Tissue Classification
Many tracking algorithms
Apply different operations on streamlines
Simplify large datasets via streamlines clustering.
Calculate distances/correspondences between streamlines.
Visualization
Simple interactive visualization of ODFs
Streamlines interactive visualization
Advanced widget
Command Line Interfaces
Announcements
DIPY Workshop - Titanium Edition (March 11-15, 2019) is now open for registration:
DIPY 1.0 released August 5, 2019.
DIPY 0.16 released March 10, 2019.
DIPY 0.15 released December 12, 2018.
See some of our Past Announcements
Highlights
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:
dipy.core.interpolation.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.
Tweets
Tue Dec 03 |
Congratulations to our own @GabrielPGirard for winning the IronTract competition! Another epic win for DIPY! Gabrie… https://t.co/HevNeRBjVJ |
Fri Nov 15 |
RT @garyfallidis: Early bird registration deadline ending in 7 hours and 41 minutes! Looking forward to see you @IUBloomington! https://t.c… |
Fri Nov 15 |
Here is a quick sneak-peek at the representation so far, for the @dipymri #workshop 16-20 March 2020!! Make sure to… https://t.co/aeTl4ZosGi |
Thu Nov 14 |
RT @dipymri: Upcoming DIPY 1.1.0 will provide access to @TensorFlow 2.0.🤩See PRs here https://t.co/MvDs1Vd3yw If you have DL methods that… |
Thu Nov 14 |
Upcoming DIPY 1.1.0 will provide access to @TensorFlow 2.0.🤩See PRs here https://t.co/MvDs1Vd3yw If you have DL me… https://t.co/doH3upgUlU |
Cite Us !
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.
Sponsors
