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scilus / scilpy

The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox
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DTI tensor, coeff order, saved for "fiberNav" #104

Open StongeEtienne opened 4 years ago

StongeEtienne commented 4 years ago

In the "scil_compute_dti_metrics.py" the script use the fiber Nav order for coef, should we simply use the default dipy (lower triangle order)


        # Get the Tensor values and format them for visualisation
        # in the Fibernavigator.
        tensor_vals = lower_triangular(tenfit.quadratic_form)
        correct_order = [0, 1, 3, 2, 4, 5]
        tensor_vals_reordered = tensor_vals[..., correct_order]
        fiber_tensors = nib.Nifti1Image(
            tensor_vals_reordered.astype(np.float32), affine)
        nib.save(fiber_tensors, args.tensor)```
frheault commented 4 years ago

I would need input from @jchoude and @arnaudbore on this. I think mostly no one use the FiberNav for Q/A tensor, but I also think mostly no one user Dipy to Q/A tensor too.

We look at the peaks (which are fine) and the recent local tracking support peaks. So I don't know what to do since both ways they aren't use...

arnaudbore commented 3 years ago

@GuillaumeTh I thinking about moving to dipy ordering but I want to make sure it won't affect other visualisation scripts. Do you have an idea of what would be effect of such modification ?