Dipy is an international, free and open soure software project for diffusion magnetic resonance imaging analysis.
Depends on a few standard libraries: python (the core language), numpy (for numerical computation), scipy (for more specific mathematical operations), cython (for extra speed) and nibabel (for file formats). Optionally, it can use python-vtk (for visualisation), pytables (for handling large datasets), matplotlib (for scientific plotting), and ipython (for interaction with the code and its results).
Dipy is multiplatform and will run under any standard operating systems such as Windows, Linux, Mac OS X.
Just some of our state-of-the-art applications are:
Join in the fun and enjoy the video we made for the Summer Exhibition in London for the celebration of the 350 years of the Royal Society.
Here is a tiny usage example for dipy
>>> import numpy as np
>>> from dipy.reconst.dti import Tensor
>>> from dipy.data import get_data
>>> fimg,fbval,fbvec=get_data('small_101D')
>>> import nibabel as nib
>>> img=nib.load(fimg)
>>> data=img.get_data()
>>> bvals=np.loadtxt(fbvals)
>>> gradients=np.loadtxt(fbvecs).T
>>> ten=dti.Tensor(data,bvals,gradients,thresh=50)
>>> FA=ten.fa()
>>> MASK = FA < 0.2
In this code snippet we loaded a small diffusion dataset with their data, b-vectors and b-values, calculated the Tensors and fractional anisotropy (FA) and then created a mask to remove the regions with low anisotropy. Download dipy and try it for yourself.
This is a depiction of a tractography skeleton created using dipy.