We are excited to announce a new public release of Diffusion Imaging in Python (DIPY).
DIPY 0.12 (Tuesday, 26 June 2017)
This release received contributions from 48 developers (the full release notes are at: http://nipy.org/dipy/release0.12.html)
Highlights of this release include:
- IVIM Simultaneous modeling of perfusion and diffusion.
- MAPL, tissue microstructure estimation using Laplacian-regularized MAP-MRI.
- DKI-based microstructural modelling.
- Free water diffusion tensor imaging.
- Denoising using Local PCA.
- Streamline-based registration (SLR).
- Fiber to bundle coherence (FBC) measures.
- Bayesian MRF-based tissue classification.
- New API for integrated user interfaces.
- New hdf5 file (.pam5) for saving reconstruction results.
- Interactive slicing of images, ODFs and peaks.
- Updated API to support latest numpy versions.
- New system for automatically generating command line interfaces.
- Faster computation of cross correlation for image registration.
To upgrade, run the following command in your terminal:
pip install --upgrade dipy
conda install -c conda-forge dipy
This version of DIPY depends on the latest version of nibabel (2.1.0).
For any questions go to http://dipy.org, or send an e-mail to firstname.lastname@example.org
We also have an instant messaging service and chat room available at https://gitter.im/nipy/dipy
On behalf of the DIPY developers,
Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro