Diffusion Imaging In Python - Documentation¶
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.
DIPY is part of the NiPy ecosystem.
Quick links¶
New to DIPY? Start with our installation guide and DIPY key concepts.
Browse our tutorials gallery.
How do I do X in DIPY? This dedicated section will provide you quick and direct answer.
Not comfortable with coding? we have command line interfaces for you. An easy way to use DIPY via a terminal.
Back to the basics. Learn the theory behind the methods implemented in DIPY.
Saw a typo? Found a bug? Want to improve a function? Learn how to contribute to DIPY!
A detailed description of DIPY public Python API.
A detailed description of all the DIPY workflows command line.
Upgrading from a previous version? See what’s new and changed between each release of DIPY.
Need help with your processing? Ask us and a large neuroimaging community.
Highlights¶
DIPY 1.11.0 is now available. New features include:
NF: Refactoring of the tracking API.
Deprecation of Tensorflow backend in favor of PyTorch.
Performance improvements of multiple functionalities.
DIPY Horizon improvements and minor features added.
Added support for Python 3.13.
Drop support for Python 3.9.
Multiple Workflows updated and added (15 workflows).
Documentation update.
Closed 73 issues and merged 47 pull requests.
See Older Highlights.
Announcements¶
DIPY 1.11.0 released March 15, 2025.
DIPY 1.10.0 released December 12, 2024.
DIPY 1.9.0 released March 8, 2024.
See some of our Past Announcements