[Insight-users] Curvature in ShapeDetectionLevelSetImageFilter
Lydia Ng
lng at insightful . com
Thu, 10 Jul 2003 16:41:54 -0700
Hi Josh and Nils,
=20
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
>=20
> Hi Lydia,
>=20
> 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.
>=20
> thanks,
>=20
> Josh.
>=20
> ______________________________
> 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
>=20
>=20
> On Thu, 10 Jul 2003, Lydia Ng wrote:
>=20
> > 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=3DInsight
> > > http://www . itk . org/cgi-
> > >
bin/cvsweb.cgi/Insight/Examples/Data/CircleSpikes.png?cvsroot=3DInsight
> > >
> > > 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=3DInsight&sortby=3Ddate
> > >
> > > 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 =3D 3.1
> > > propagation scaling =3D 0.98 will overflow the whole image
> > > while prop. scaling =3D 0.96 will grow just to half the circle
> > >
> > > OR
> > >
> > > keeping propagation scaling =3D 0.97
> > > curvature scaling =3D 3.0 will overflow the image
> > > curvature scaling =3D 3.2 will fall short on reaching the edges
> > >
> > >
> > >
> > > My guess is that it may be possible to find a
> > > continuous function F():
> > >
> > > curvatureScaling =3D 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
(=3D=3D
> > > > 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 =3D curve;
> > > > curvature_term *=3D 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_
> > > >>>>>
> > > >>>>>
> > > >>>>>
> > > >>>>
> > > >>>>
> > > >>>>
> > > >>>>_______________________________________________
> > > >>>>Insight-users mailing list
> > > >>>>Insight-users at itk . org
> > > >>>>http://www . itk . org/mailman/listinfo/insight-users
> > > >>>>
> > > >>>
> > > >>>_______________________________________________
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> > > >>>
> > > >>
> > > >>
> > > >>
> > > >>
> > > >
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