Hello Carlos,
welcome to vmtk and sorry for the wait. I hope the timing won't stop you from
sending more questions in the future.
The level set code I used during my PhD was written by me, then ITK came along
and I was very happy to fully embrace it :-)
So right now level set implementation in vmtk is the one provided by ITK:
http://www.itk.org/Doxygen/html/classitk_1_1GeodesicActiveContourLevelSetFunction.html
which is a specialization of this general formulation
http://www.itk.org/Doxygen/html/classitk_1_1LevelSetFunction.html
As you see, the latter link includes a spatial modifier for the mean curvature
term (Z), which in the actually code is
returned by the CurvatureSpeed method. In the
GeodesicActiveContourLevelSetFunction such term is set equal to
G (the edge potential image).
So, long story short, yes, the current implementation follows equation 2.22.
> Correct me if i'm wrong: G and P depend on the so called featured Image ( |
> grad I(x) | on Luca's thesis), if executing the vmtklevelsetsegmentation
> filter as before (without specifying a -featureimagefile image) Is the
> featured image used by G and P calculated automatically (depending on the
> -featureimagetype parameter with gradient as default)?
Exactly. Good job!
Luca
On Nov 27, 2012, at 10:19 PM, Carlos Alberto Bulant wrote:
> Hi VMTK users,
> this is my first post in this mailing list (probably there will be more), i'm
> a new user just starting to use the toolkit.
> Now to my questions:
>
> When using the level set segmentation filter in the form of :
> vmtklevelsetsegmentation -ifile image_volume_voi.vti -ofile level_sets.vti
> assuming none-zero PropagationScaling (w1), CurvatureScaling (w2) and
> AdvectionScaling (w3) parameters, which of the Level Set formulation
> (proposed on Luca Antiga's PhD thesis) does the implementation use?
>
> (2.19) -w1 G(x) | grad F | + 2 w2 H(x) | grad F | + w3 <[grad P(x)] ,
> grad F >
> (2.22) -w1 G(x) | grad F | + 2 w2 G(x) H(x) | grad F | + w3 <[grad P(x)]
> , grad F >
>
>
> In the current implementation, are G(x) and P(x) the one proposed on Luca's
> thesis?
>
>
> Correct me if i'm wrong: G and P depend on the so called featured Image ( |
> grad I(x) | on Luca's thesis), if executing the vmtklevelsetsegmentation
> filter as before (without specifying a -featureimagefile image) Is the
> featured image used by G and P calculated automatically (depending on the
> -featureimagetype parameter with gradient as default)?
>
> Sorry for my English,
> Best of regards
> Carlos
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