[Insight-users] Curvature in ShapeDetectionLevelSetImageFilter
Joshua Cates
cates at sci . utah . edu
Tue, 5 Aug 2003 13:57:32 -0600 (MDT)
Sorry, a typo: make that itkLevelSetFunction.txx.
Josh.
On Tue, 5 Aug 2003, Joshua Cates wrote:
> Hi Lydia and Nils,
>
> I have just checked in some changes to itkLevelSetImageFunction.txx that I
> think will address this. The function now takes the entire curvature into
> account when computing the time step. Let me know if you continue to have
> problems with this.
>
> Josh.
>
> ______________________________
> Josh Cates
> School of Computer Science
> University of Utah
> Email: cates at sci . utah . edu
> Phone: (801) 587-7697
> URL: http://www . sci . utah . edu/~cates
>
>
> On Thu, 10 Jul 2003, Lydia Ng wrote:
>
> > Hi Josh and Nils,
> >
> > Actually I did tried to get one of my Examples to illustrate this
> > problem but I actually couldn't since in the Examples the
> > CurvatureSpeed() is between 0 and 1.
> >
> > I believe Nils derived his own classes and set the CurvatureSpeed() to a
> > high value.
> >
> > Nils: would you be able to post your code/test illustrating the
> > numerical instability problem?
> >
> > - Lydia
> >
> > > -----Original Message-----
> > > From: Joshua Cates [mailto:cates at sci . utah . edu]
> > > Sent: Thursday, July 10, 2003 3:28 PM
> > > To: Lydia Ng
> > > Cc: Luis Ibanez; Nils Hanssen; Insight-users at public . kitware . com
> > > Subject: RE: [Insight-users] Curvature in
> > > ShapeDetectionLevelSetImageFilter
> > >
> > > Hi Lydia,
> > >
> > > Can you send Ross and I an example of data/parameters which cause
> > problems
> > > in (ideally) one of the Example applications? We'll hack on this next
> > > week.
> > >
> > > thanks,
> > >
> > > Josh.
> > >
> > > ______________________________
> > > Josh Cates
> > > School of Computer Science
> > > University of Utah
> > > Email: cates at sci . utah . edu
> > > Phone: (801) 587-7697
> > > URL: http://www . sci . utah . edu/~cates
> > >
> > >
> > > On Thu, 10 Jul 2003, Lydia Ng wrote:
> > >
> > > > Hi Nils and Luis,
> > > >
> > > > There is issue in the current implementation of the level set
> > framework
> > > > in that the curvature term is not taken into account when computing
> > the
> > > > time step. Ideally, the time step should computed to maintain
> > numerical
> > > > stability.
> > > >
> > > > Thus, setting the curvature weight is high relative to the
> > propagation
> > > > term will cause problem most likely due to the time step being too
> > > > large.
> > > >
> > > > This is a known problem - computing the time step to meet the CFL
> > > > criterion is not widely reported in the literature - a few of us is
> > > > still trying to figure out what is the mathematically sound thing to
> > do
> > > > here.
> > > >
> > > > BTW - I have also fixed the problem of when the propagation weight
> > is
> > > > zero - it shouldn't crash now - but you will still get the numerical
> > > > instability issue as above.
> > > >
> > > > - Lydia
> > > >
> > > > > -----Original Message-----
> > > > > From: Luis Ibanez [mailto:luis . ibanez at kitware . com]
> > > > > Sent: Thursday, July 10, 2003 6:58 AM
> > > > > To: Nils Hanssen
> > > > > Cc: Insight-users at public . kitware . com
> > > > > Subject: Re: [Insight-users] Curvature in
> > > > > ShapeDetectionLevelSetImageFilter
> > > > >
> > > > >
> > > > > Hi Nils,
> > > > >
> > > > > I just performed a couple of tests, and the
> > > > > ShapeDetectionLSIF is behaving as expected.
> > > > > (Note that I did this with the current CVS
> > > > > version, not ITK 1.2).
> > > > >
> > > > > A couple of sample images that help to test
> > > > > your case were checked in under:
> > > > >
> > > > > - Insight/Examples/Data/Circle.png
> > > > > - Insight/Examples/Data/CircleSpikes.png
> > > > >
> > > > > http://www . itk . org/cgi-
> > > > > bin/cvsweb.cgi/Insight/Examples/Data/Circle.png?cvsroot=Insight
> > > > > http://www . itk . org/cgi-
> > > > >
> > bin/cvsweb.cgi/Insight/Examples/Data/CircleSpikes.png?cvsroot=Insight
> > > > >
> > > > > CircleSpikes.png simulates the conditions of your
> > > > > tube but in 2D.
> > > > >
> > > > > The example ShapeDetectionLevelSetImageFilter
> > > > > was also slightly modified in order to take the
> > > > > scaling parameter from the command line arguments.
> > > > >
> > > > > http://www . itk . org/cgi-
> > > > >
> > > >
> > bin/cvsweb.cgi/Insight/Examples/Segmentation/ShapeDetectionLevelSetFilte
> > > > r.
> > > > > cxx?cvsroot=Insight&sortby=date
> > > > >
> > > > > Running this example with the parameters below
> > > > > succeded to segment the internal circle without
> > > > > taking the spikes (bridges). Note that although
> > > > > the segmentation doesn't goes into the spikes, they
> > > > > excert some influence on the shape of the final
> > > > > contour.
> > > > >
> > > > > Here are the parameters:
> > > > >
> > > > > ShapeDetectionLevelSetFilter
> > > > >
> > > > > input image: CirclesSpikes.png
> > > > > output image: SegmentedCircle.png
> > > > > seed point: 50 50
> > > > > distance: 20
> > > > > sigma: 1.0
> > > > > sigmoid alpha: -40
> > > > > sigmoid beta: 128
> > > > > curvatureScaling: 3.1
> > > > > propagationScaling: 0.97
> > > > >
> > > > > The overlay of the segmented circle, on top
> > > > > of the CircleSpikes.png image is shown in
> > > > > the attachement.
> > > > >
> > > > > ---
> > > > >
> > > > > The balance between the curvatureScaling and the
> > > > > propagationScaling parameters is quite delicate.
> > > > >
> > > > > For example:
> > > > >
> > > > > keeping curvature scaling = 3.1
> > > > > propagation scaling = 0.98 will overflow the whole image
> > > > > while prop. scaling = 0.96 will grow just to half the circle
> > > > >
> > > > > OR
> > > > >
> > > > > keeping propagation scaling = 0.97
> > > > > curvature scaling = 3.0 will overflow the image
> > > > > curvature scaling = 3.2 will fall short on reaching the edges
> > > > >
> > > > >
> > > > >
> > > > > My guess is that it may be possible to find a
> > > > > continuous function F():
> > > > >
> > > > > curvatureScaling = F( propagationScaling )
> > > > >
> > > > > for which the segmentation grabs on the circle edges,
> > > > > but at some threshold of "PropagationScaling" the
> > > > > computation will start presenting numerical
> > > > > instabilities.
> > > > >
> > > > >
> > > > >
> > > > >
> > > > > Regards,
> > > > >
> > > > >
> > > > >
> > > > > Luis
> > > > >
> > > > >
> > > > >
> > > > > ---------------------
> > > > > Nils Hanssen wrote:
> > > > > > Hi Luis,
> > > > > >
> > > > > > thank you for the detailed answer.
> > > > > >
> > > > > >
> > > > > > My initial level set conforms to the "negative inside"
> > convention.
> > > > > > Now, I am using a curvature weighting of 1000 (just to see what
> > > > happens
> > > > > in
> > > > > > the extreme case) and a propagation weighting of 0.001. When
> > running
> > > > the
> > > > > > ShapeDetectionLSIF, the contour is not collapsing at all. Maybe
> > > > that's
> > > > > > because of the feature image that dictates the curvature speed
> > (==
> > > > > > propagation speed in the ShapeDetectionLSIF)?
> > > > > >
> > > > > > Since the curvature speed in the ShapeDetectionLSF equals the
> > > > > propagation
> > > > > > speed, I derived my own classes called "TubularLevelSetFunction"
> > and
> > > > > > "TubularLevelSetImageFilter". These are basically clones of the
> > > > > > ShapeDetection* classes, but with the difference that I set the
> > > > > curvature
> > > > > > speed to (constant) one in the Level-set function.
> > > > > > Now, the contour is collapsing according to the mean curvature
> > but
> > > > all
> > > > > this
> > > > > > happens _very_ slowly (the curvature weighting is 1000!).
> > > > > >
> > > > > > In itk::LevelSetFunction::ComputeUpdate(...) I see the
> > following:
> > > > > > ---
> > > > > > curvature_term = curve;
> > > > > > curvature_term *= m_CurvatureWeight * this->CurvatureSpeed(it,
> > > > > offset);
> > > > > > ---
> > > > > > so it should make no difference when I set the curvature weight
> > to 1
> > > > and
> > > > > the
> > > > > > curvature speed to (constant) 1000 (and not vice versa), right?
> > But
> > > > when
> > > > > I
> > > > > > do this, I get numerical instabilities during the evolution.
> > What is
> > > > > wrong
> > > > > > with my assumption?
> > > > > >
> > > > > > Luis, what was the curvature weighting and curvature speed when
> > you
> > > > > tested
> > > > > > the collapsing contour with the syntethic sphere image? Was the
> > > > > curvature
> > > > > > speed constant or dependent on the image?
> > > > > >
> > > > > > For now, I do all calculations in 2D. Could that be a problem? I
> > > > have
> > > > > > installed a observer that shows me the progress of the contour
> > after
> > > > > each
> > > > > > update event.
> > > > > >
> > > > > >
> > > > > > Regards,
> > > > > > Nils
> > > > > >
> > > > > >
> > > > > >
> > > > > >>-----Original Message-----
> > > > > >>From: Luis Ibanez [mailto:luis . ibanez at kitware . com]
> > > > > >>Sent: Wednesday, July 09, 2003 6:14 PM
> > > > > >>To: Nils Hanssen
> > > > > >>Cc: Insight-users at public . kitware . com
> > > > > >>Subject: Re: [Insight-users] Crash in
> > > > > >>ShapeDetectionLevelSetImageFilter
> > > > > >>
> > > > > >>
> > > > > >>
> > > > > >>Hi Nils,
> > > > > >>
> > > > > >>You are right in your interpretation of the
> > > > > >>behavior for the ShapeDetectionLevelSetFilter.
> > > > > >>
> > > > > >>Increasing the curvature scaling while decreasing
> > > > > >>the propagation scaling should make the contour
> > > > > >>collapse (contract).
> > > > > >>
> > > > > >>I just verified this behavior using a syntethic
> > > > > >>image of a sphere.
> > > > > >>
> > > > > >>Note that in version 1.2 this filter is expecting
> > > > > >>the input level set to conform to the convention
> > > > > >>of "negative inside" which means that the level
> > > > > >>set has negative values 'inside' the contour and
> > > > > >>positive values outside the contour.
> > > > > >>
> > > > > >>You may have to push the curvature scaling to
> > > > > >>a value higher than 1.0. (e.g. 5.0 or so).
> > > > > >>
> > > > > >>I would avoid to use 0.0 for the propagation
> > > > > >>scaling ( in part just for superstition against
> > > > > >>zeros values as parameters). You may want to
> > > > > >>try something like 0.1 for the propagation
> > > > > >>scaling.
> > > > > >>
> > > > > >>Please verify the convention used by your initial
> > > > > >>level set. That may be the cause for the contour
> > > > > >>not behaving as expected.
> > > > > >>
> > > > > >>
> > > > > >>Regards,
> > > > > >>
> > > > > >>
> > > > > >> Luis
> > > > > >>
> > > > > >>
> > > > > >>
> > > > > >>---------------------
> > > > > >>Nils Hanssen wrote:
> > > > > >>
> > > > > >>>Hi Luis,
> > > > > >>>
> > > > > >>>I am using the 1.2.0 web release.
> > > > > >>>
> > > > > >>>Regards,
> > > > > >>>Nils
> > > > > >>>
> > > > > >>>
> > > > > >>>
> > > > > >>>>-----Original Message-----
> > > > > >>>>From: insight-users-admin at itk . org
> > > > > >>>>[mailto:insight-users-admin at itk . org]On
> > > > > >>>>Behalf Of Luis Ibanez
> > > > > >>>>Sent: Tuesday, July 08, 2003 3:55 PM
> > > > > >>>>To: Nils Hanssen
> > > > > >>>>Cc: Insight-users at public . kitware . com
> > > > > >>>>Subject: Re: [Insight-users] Crash in
> > > > > >>>>ShapeDetectionLevelSetImageFilter
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>Hi Nils,
> > > > > >>>>
> > > > > >>>>Are you using a very recent checkout of ITK ?
> > > > > >>>>
> > > > > >>>>The level set filters have been reworked in
> > > > > >>>>recent days, so it will help us to know if you
> > > > > >>>>are experiencing this behavior with the current
> > > > > >>>>version or with the version as it was two weeks
> > > > > >>>>ago (or before that).
> > > > > >>>>
> > > > > >>>>Please let us know,
> > > > > >>>>
> > > > > >>>> Thanks
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> Luis
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>------------------------
> > > > > >>>>Nils Hanssen wrote:
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>>Hi,
> > > > > >>>>>
> > > > > >>>>>I am trying to understand the behaviour of the
> > > > ShapeDetectionLSIF.
> > > > > >>>>>Therefore, I set the propagation-weighting to zero. By
> > setting
> > > > the
> > > > > >>>>>curvature-weighting to a value of one I would expect that
> > > > > >>>>
> > > > > >>>>the inital
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>>surface is shrinking to a point (I set the MaxRMSError to
> > > > > >>>>
> > > > > >>>>zero) and the
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>>number of iterations very high.
> > > > > >>>>>
> > > > > >>>>>The filter is crashing in
> > > > > >>>>>SegmentationLevelSetFunction<TImageType, TFeatureImageType>
> > > > > >>>>>::PropagationSpeed(const NeighborhoodType &neighborhood,
> > const
> > > > > >>>>>FloatOffsetType &offset) const
> > > > > >>>>>[...]
> > > > > >>>>>--> else return (
> > > > > >>>>
> > > > > >>>>static_cast<ScalarValueType>(m_SpeedImage->GetPixel(idx)) );
> > > > > >>>>// crashing here
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>>[...]
> > > > > >>>>>
> > > > > >>>>>When I set the propagation-weighting to - for instance -
> > > > > >>>>
> > > > > >>0.0001 the
> > > > > >>
> > > > > >>>>>filter is not crashing, but the contour is not shrinking
> > > > > >>>>
> > > > > >>>>according to
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>>the mean curvature.
> > > > > >>>>>
> > > > > >>>>>Is that the correct behaviour of the filter?
> > > > > >>>>>
> > > > > >>>>>I would appreciate any suggestions. Thanks!
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>>Regards,
> > > > > >>>>>Nils
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>>-------------------------
> > > > > >>>>>Nils Hanssen
> > > > > >>>>>Surgical Systems Laboratory
> > > > > >>>>>research center c ae sa r
> > > > > >>>>>Ludwig-Erhard-Allee 2
> > > > > >>>>>53175 Bonn
> > > > > >>>>>fon: +49-228-9656-197
> > > > > >>>>>fax: +49-228-9656-117
> > > > > >>>>>___http://www . caesar . de/ssl_
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>_______________________________________________
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> > > > > >>>>
> > > > > >>>
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> > > > > >>
> > > > > >>
> > > > > >
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