Dipy is a free and open source software project for diffusion magnetic resonance imaging (dMRI) analysis.
Dipy 0.7.1 is now available for download with 3X more tutorials than 0.6.0! In addition, a journal paper focusing on teaching the fundamentals of Dipy is now available in Frontiers of Neuroinformatics.
So, how similar are your bundles to the real anatomy? Learn how to optimize your analysis as we did to create the fornix of the figure above, by reading the tutorials in our gallery.
See older highlights.
Here is a simple example showing how to calculate color FA. We use a single Tensor model to reconstruct the datasets which are saved in a Nifti file along with the b-values and b-vectors which are saved as text files. In this example we use only a few voxels with 101 gradient directions:
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() from dipy.io import read_bvals_bvecs bvals, bvecs = read_bvals_bvecs(fbval, fbvec) from dipy.core.gradients import gradient_table gtab = gradient_table(bvals, bvecs) from dipy.reconst.dti import TensorModel ten = TensorModel(gtab) tenfit = ten.fit(data) from dipy.reconst.dti import fractional_anisotropy fa = fractional_anisotropy(tenfit.evals) from dipy.reconst.dti import color_fa cfa = color_fa(fa, tenfit.evecs)
As an exercise try to calculate the color FA with your datasets. Here is how a slice should look like.