Hi Luca,
Once again, thanks for the helpful information.
The example is a good start, however I think the curvatureweight doesn't
belong to this script.
I couldn't find it in the parameters list at:
http://www.vmtk.org/VmtkScripts/vmtkpotentialfit and when I tried to use it
I got a crash.
Thanks,
Ido
On Wed, Aug 3, 2011 at 2:31 AM, Luca Antiga <luca.ant...@gmail.com> wrote:
> Hi Ido,
> this script takes an image (actually, a feature image, i.e. the output of
> vmtkimagefeatures) and a surface in input,
> and moves the vertices of the surface so that they converge on the minimum
> of the potential defined by the image.
> For instance, you can extract an isosurface from the image and let it
> converge to the ridges of the gradient magnitude
> of the image, like with level sets (this is just one use case, you can of
> course start from any surface, not necessarily
> an isosurface).
> Here is the pipe to do it:
>
> vmtkimagereader -ifile foo.vti --pipe vmtkmarchingcubes -l 200.0 --pipe
> vmtkimagefeatures --pipe vmtkpotentialfit -potentialweight 1
> -curvatureweight 0.1 -iterations 100 -ofile foo.vtp
>
> Here potentialweight is the analogous of level set advection.
>
> Hope this will get you started.
>
> Luca
>
>
>
> On Jul 31, 2011, at 12:00 PM, ido yerushalmy wrote:
>
> Hi,
> I'm having a similar problem and want to try using vmtkpotentialfit.
> I tried using it the following way:
>
> vmtkpotentialfit -imagefile foo.vti -ofile foo_potentialfit.vtk
>
> but it seems that the output is empty (no file is created). If I try to
> view the surface, I see nothing, just a black screen.
> Does anyone know if there's an example I can follow for this script?
>
> Regards,
> Ido
>
> On Fri, Jul 29, 2011 at 11:28 AM, Luca Antiga <luca.ant...@gmail.com>wrote:
>
>> Hi Yap,
>> if you are on a 64 bit system, and assuming you compiled vmtk from
>> scratch (correct me if I'm wrong)
>> make sure that vmtk and its dependencies are compiled for a 64 bit
>> architecture (amd64 or x86_64).
>> You should find a reference to these two in your CMakeCache.txt in the
>> build directories.
>> If you are running on a 64 bit system, your build should already be 64
>> bits anyway...
>>
>> In any case, there is a possibility that memory is not sufficient if you
>> are running, for instance, level
>> sets on very large images. Running level sets means that your image has to
>> be replicated several
>> times in memory (to compute gradients, etc), and converted to "expensive"
>> numerical representations,
>> so it's totally possible that you run out of memory.
>>
>> Just so you know, you can for instance segment individual VOIs and merge
>> them after segmentation,
>> or you can work on a subsampled image and then optimize your segmentation
>> on the full image.
>> Or you could rely on less expensive deformable models - an explicit
>> deformable model such as the
>> one provided by vmtkpotentialfit. Or a bit of all the above.
>>
>> What's the right way to go really depends on the problem at hand and what
>> you're trying to achieve.
>>
>> What is the size of your images and what algorithms are you trying to run
>> on them?
>>
>> Luca
>>
>>
>> On Jul 21, 2011, at 9:05 PM, Yap, Choon Hwai wrote:
>>
>> > Hi,
>> >
>> > I would like to segment very high resolution images, and keep
>> encountering memory error as such:
>> >
>> > ERROR: In /build/buildd/vtk-5.4.2/Common/vtkDataArrayTemplate.txx, line
>> 141
>> > vtkFloatArray (0x1d582b0): Unable to allocate 186212691 elements of size
>> 4 bytes.
>> >
>> > Is there a way to increase the memory allocation for vmtk?
>> > I'm using Ubuntu v11.04
>> >
>> > Any advice will be greatly appreciated..!
>> > Thanks!
>> >
>> > regards,
>> > Yap
>> >
>> >
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