[Insight-users] Watershed and Ultimate Erode Points on 3D MicroCT
Bradley Lowekamp
blowekamp at mail.nih.gov
Wed Nov 7 13:26:12 EST 2012
Hello,
The classic gray scale watershed segmentation takes a gradient magnitude as an input, where the binary watershed takes a distance map. I put the filters together for the binary watershed method recently with SimpleITK. The basics of the SimpleITK python code was this:
l = sitk.BinaryThreshold( labelImage, labelID, labelID, 1, 0 )
d = sitk.SignedMaurerDistanceMap( l,
inInsideIsPositive = False,
inSquaredDistance = False,
inUseImageSpacing = True )
d = sitk.Threshold( d, -1e23, 0, 0 )
ws = sitk.MorphologicalWatershed( d, inMarkWatershedLine=True, inLevel = level )
It should be fairly straight forward to use ITK proper and create a pipeline based on the above.
Regarding the Ultimate Erode points. I don't believe we have a direct morphological filter to compute that. But it can be simply computed as the RegionalMaxima of a distance field from you binary image.
Brad
On Nov 6, 2012, at 3:11 PM, Ruben Neves <ruben.m.neves at gmail.com> wrote:
> Greetings,
>
> I have a 16-bit (signed short) vtk image of a MicroCT that I have already filtered and binarized.
>
> I have been playing with some samples (taken from the original) in ImageJ and I reached the point were I really need to apply the Ultimate Erode Points and the Watershed segmentation to my binary original. To be clear, I want the separate outputs from each process, no mixes...
>
> As for the watershed segmentation, I've got the algorithm taken from the examples of ITK, but I'm not very sure how to work with the input parameters. In my binary original I have shapes that are "overlapping", and became a single shape with the binary threshold, hence my need for watershed. I just need to separate them like ImageJ does.
>
> As for the Ultimate Erode Points, I'm a bit clueless...
>
> Can Anyone shed some light over these two issues?
>
> Thanks in advance,
> Best regards
>
> Ruben Neves
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