[Insight-users] Performance of 3D Watershed?

[Joshua Cates]

Hi again,

One more critial thing I forgot to mention:

Be very conservative in setting the Level parameter of the
WatershedImageFilter.  Try using only 0.01 (i.e. 1%) or so as a first
test, just to see what sort of results you are getting.  

The Lower threshold parameter is usually set very low (in my experience, 
less than 1%).

Josh.


______________________________
 Josh Cates			
 School of Computer Science	
 University of Utah
 Email: cates@sci.utah.edu
 Phone: (801) 587-7697
 URL:   www.cs.utk.edu/~cates


On Tue, 22 Oct 2002, Harri Tapio Jaalinoja wrote:

> 
> Hi!
> 
> I am running code based on the watershed example to segment a 101^3 cube
> of electron microscopy density data (type = short).
> 
> The problem is that the code seems to stall my machine.
> The progress command meter writes first 3 dots almost right away, the 4th
> after a while, but the 5th I never saw.
> 
> I am not using the gradient magnitude image filter because the density
> values as such should be a valid height function.
> 
> I don't have a smaller data cube at the moment I could experiment with.
> I can simply read data from the existing file, to fill in a smaller cube.
> This of course messes up the structure, but might give some idea about the
> processing. A cube of 33^3 already stalls the machine, 32^3 is processed
> fairly quickly.
> 
> My processor:
> model name      : AMD Athlon(TM) XP2200+
> stepping        : 0
> cpu MHz         : 1800.110
> 
> Available memory:
> [hajaalin@gene work]$ free -m
>              total       used       free     shared    buffers     cached
> Mem:          1008        170        837          0         15         77
> -/+ buffers/cache:         77        931
> Swap:          243         11        231
> 
> I am running Mandrake Linux 9.0.
> 
> Here's some info about the data
> Number of images:               1
> Dimensions:                     101 101 101 voxels
> Page dimensions:                101 101 101 voxels
> Channels:                       1
> Data type:                      short (size = 2)
> Color model:                    Gray scale
> Voxel units/sampling:           8.89903 8.89903 8.89903 A/voxel
> Min, max, ave, std:             -1813.35 2149.04 11.9238 0
> 
> I have tried various values for the anisotropic diffusion filter. At all
> values a cube size can be found that is no longer processed (at least
> nowhere as quickly as the one step smaller cube). The biggest cube (32^3)
> was in fact processed without the filter.
> 
> With some values I get this:
> ..........Exception caught during processing.
> Unknown
> itk::ERROR: itk::watershed::SegmentTreeGenerator::MergeSegments:: An
> unexpected and fatal error has occurred. This is probably the result of
> overthresholding of the input image.
> 
> which at least clearly tells that something is going wrong.
> 
> Based on your experience, what do you make of the numbers and ramblings
> above? Any ideas I could experiment with?
> 
> Thanks for your help!
> 
> Harri
> 
> _______________________________________________
> Insight-users mailing list
> Insight-users@public.kitware.com
> http://public.kitware.com/mailman/listinfo/insight-users
>