Making algorithms at least 3D, preferably nD

[Ankit Agrawal]

Hi Juan,

I think this is all a bit off-topic anyway. The whole idea of making the
> algorithms nD is to apply them to 3D volumetric data, not 2D+t. That they
> *sometimes* apply to 2D+t is merely a happy accident.
>
> Thanks again. I somehow thought that the nD algorithms that are going to
be implemented in scikit should also generalize for 2D x t and hence my
previous concern. Dealing just with volumetric data makes the whole picture
clear.


> But scikit-image is part of scikits, an "index of add-on toolkits that
> complement SciPy, a library of *scientific* computing routines."
> (emphasis mine). One of the goals is (/should be; @stefanv can weigh in)
> the analysis of scientific images, many of which are 3D volumetric. And
> many such algorithms can be applied as-is whether the data is 2D or 3D.
> This includes filters, edge detectors, segmentation methods, convex hulls,
> and more.
>

Yes, all the functions in scipy.ndimage can be genralized for volumetric
3D.
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