DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
Available on many operating systems
All Algorithms available via CLI
Create your Own
K-Fold cross validation
Single Shell: DTI, CSA, SFM, SDT, Q-Ball, CSD, ...
Multi-Shell: GQI, DTI, DKI, SHORE, MAPMRI, MSMT-CSD, ...
Diffeomorphic 2D/3D Registration
Streamlines based Registration
High resolution DWI
LPCA - MPPCA
Non Local Means
interactive tractogram visualization
Advanced UI and Shaders
DIPY 1.7.0 released April 23, 2023.
DIPY 1.6.0 released January 16, 2023.
DIPY 1.5.0 released March 11, 2022.
See some of our Past Announcements
DIPY 1.7.0 is now available. New features include:
NF: BundleWarp - Streamline-based nonlinear registration method for bundles added.
NF: DKI+ - Diffusion Kurtosis modeling with advanced constraints added.
NF: Synb0 - Synthetic b0 creation added using deep learning added.
NF: New Parallel Transport Tractography (PTT) added.
NF: Fast Streamline Search algorithm added.
NF: New denoising methods based on 1D CNN added.
Handle Asymmetric Spherical Functions.
Large update of DIPY Horizon features.
Multiple Workflows updated
Large codebase cleaning.
Large documentation update. Integration of Sphinx-Gallery.
Closed 53 issues and merged 34 pull requests.
See Older Highlights.
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.