A quick overview of features#

Here are just a few of the state-of-the-art technologies and algorithms which are provided in DIPY:

  • Reconstruction algorithms: CSD, DSI, GQI, DTI, DKI, QBI, SHORE and MAPMRI.

  • Fiber tracking algorithms: deterministic and probabilistic.

  • Simple interactive visualization of ODFs and streamlines.

  • Apply different operations on streamlines (selection, resampling, registration).

  • Simplify large datasets of streamlines using QuickBundles clustering.

  • Reslice datasets with anisotropic voxels to isotropic.

  • Calculate distances/correspondences between streamlines.

  • Deal with huge streamline datasets without memory restrictions (using the .dpy file format).

  • Visualize streamlines in the same space as anatomical images.

With the help of some external tools you can also:

  • Read many different file formats e.g. Trackvis or Nifti (with nibabel).

  • Examine your datasets interactively (with ipython).

For more information on specific algorithms we recommend starting by looking at DIPY’s gallery of examples.

For a full list of the features implemented in the most recent release cycle, check out the release notes.

Systems supported#

DIPY is multiplatform and will run under any standard operating systems such as Windows, Linux and Mac OS X. Every single new code addition is being tested on a number of different buildbots and can be monitored online here.