Segmentation algorithms

[Emmanuelle Gouillart]

Hi Andy,

> @Emanuelle: Are there examples in scikit-image for using 3d images?
> I didn't find anything in the gallery.

no, there are no examples with 3-D images. The main reason why I didn't
write any such 3-D example is that visualization of the result would best
be done with Mayavi, and since the code of the examples is executed when
the doc is built, there will be errors if mayavi is not installed. But
the principle of a segmentation algorithm is often the same in 2-D and in
3-D. The example
http://scikits-image.org/docs/dev/auto_examples/plot_random_walker_segmentation.html
could have been done on a similar 3-D image.

I could, however, write a tutorial on how to deal with the processing of
3-D images with numpy/skimage/mayavi...

> I am not very familiar with this kind of data but if I have some "typical"
> case, I can see how it goes.

3-D data that I'm aware of are mostly medical images and materials science
image (MRI, CT, FIB). Compared to 2-D images, we usually do not have such
things as "natural 3-D images", and images are more "homogeneous". (I
hope I'm not saying too much nonsense -- what I mean is that usually you
do not try to detect people or faces in 3-D images! But I might have a
too limited viewpoint.). 

In Python/skimage, these 3-D images would be just 3-D arrays (usually 3-D
images are in grayscale and not in color), with the array values
corresponding to the pixel values (actually, a pixel is called voxel in
3-D). 

If you start working on 2-D algorithms, I can give you a hand to see
whether it would be relevant to have them in 3-D as well, and how to do it.

Cheers,
Emmanuelle