ANN: DIPY 0.12.0 release

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

or

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 neuroimaging@python.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
http://dipy.org/developers.html

MANAGED BY INCF