We are excited to announce a new release of Diffusion Imaging in Python
(DIPY).
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
http://nipy.org/dipy/release0.12.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
management.
-
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:
https://workshop.dipy.org
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:
http://dipy.org/release0.10.html
pip install --upgrade dipy
or
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
dipy@python.org