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: <http://dipy.org/release0.10.html> 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 neuroimag...@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 -- https://mail.python.org/mailman/listinfo/python-list