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.