We are excited to announce a new release of Diffusion Imaging in Python
DIPY 0.15 (Wednesday, 12 December 2018)
This release received contributions from 30 developers (the full release
notes are at: http://dipy.org/release0.15.html
Highlights of this release include:
Updated RecoBundles for automatic anatomical bundle segmentation.
New Reconstruction Model: qtau-dMRI signal representation.
New command line interfaces (e.g., dipy_slr).
New continuous integration with AppVeyor CI.
Nibabel Streamlines API now used almost everywhere for better memory
Compatibility with Python 3.7.
Many tutorials added or updated (5 New).
Large overall documentation update.
Moved visualization module to a new library: FURY.
Closed 287 issues and merged 93 pull requests.
Want to learn more?
The DIPY project is hosting an educational workshop March 11-15 at Indiana
University, USA. The event is sponsored by the National Institute of Health
(NIH). See topics and detailed information here:
The workshop will include tutorials on tracking, microstructure, and
statistical analysis. The workshop will also include a data accelerator
where you will be able to analyze your own data together with the DIPY
<http://dipy.org/> developers. More than 15 DIPY developers will be
available this year on site to help. All tutorials will run on 3 levels:
novice, intermediate and advanced. Register here <https://workshop.dipy.org>
To upgrade or install <http://dipy.org/release0.10.html> DIPY
Run the following command in your terminal:
pip install --upgrade dipy
conda install -c conda-forge dipy
This version of DIPY depends on nibabel (2.3.0+).
Questions or suggestions?
For any questions go to http://dipy.org, or send an e-mail to
We also have an instant messaging service and chat room available at
On behalf of the DIPY developers,
Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro