[Neuroimaging] [dipy] Resampling in bundle registration with uneven stepsize

[Samuel St-Jean]

While looking at the example over here [1], one important step is to
resample everything to the same size. Unfortunately, the why is not
mentioned in the example, so I was wondering if it is for performance
reason (quickbundle needs that, and it is used internally or at least if
uses the same distance metric) or for theoretical reasons?

Would it still work well on uneven stepsize bundles (fancy
tracking/compressed fibers) as long as they have the same number of points
or would something break in the theory by doing that? Should one aim to
resample to an even number of points and even stepsize or only the number
of points matter for this algorithm?


[1]
http://nipy.org/dipy/examples_built/bundle_registration.html#example-bundle-registration
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