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 builbots and can be monitored online here.