Dipy is a free and open source software project for computational neuroanatomy, focusing mainly on diffusion magnetic resonance imaging (dMRI) analysis. It implements a broad range of algorithms for denoising, registration, reconstruction, tracking, clustering, visualization, and statistical analysis of MRI data.
Dipy 0.10 is now available. New features in this release include:
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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 what a slice should look like.
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