[Insight-users] Problem with 2D Registration (local minima)

Thu Oct 22 11:56:45 EDT 2009

Hi Bill,

The optimum value for the metric that I spect is about 2000, and I normally get a metric of 4000.

I will try just now to set:

optimizer->SetMaximumStepLength( 0.1 );

and I´ll let you know the results in a while.

Thanks!

Manuel.

> Date: Thu, 22 Oct 2009 11:52:23 -0400
> Subject: Re: [Insight-users] Problem with 2D Registration (local minima)
> From: bill.lorensen at gmail.com
> To: manueldavid.tabas at hotmail.es
> CC: insight-users at itk.org
> 
> The optimizer is stopping after reaching the maximum number of
> iterations. This is normally not the best way to terminate an
> optimization.
> 
> What do you expect for the optimum value of the parameters?
> 
> Perhaps you need a larger maximum step length? Or perhaps, as Luis
> suggested, the starting point is too far from the optimum for this
> optimizer.
> 
> Bill
> 
> 
> On Thu, Oct 22, 2009 at 10:09 AM, Manuel David Tabas Calle
> <manueldavid.tabas at hotmail.es> wrote:
> >
> > Hi Luis,
> >
> > Thank you for answering me.
> >
> > 1) As you said, my images are from Microscopy and the spacing is about 2.85
> > micrometres/pixel. The images are in a raw format and I used the following
> > .mhd file for reading it:
> >
> >
> >     NDims = 2
> >     DimSize = 2000 2000
> >     ElementType = MET_UCHAR
> >     ElementSpacing = 1.0 1.0
> >     Offset = 0.0 0.0
> >     ElementByteOrderMSB = False
> >     ElementDataFile = fixed.raw
> >
> > I also tried to as ElementSpacing 2.83 and 0.00283 (just in case...) but the
> > results weren´t good either.
> >
> > 2) I also try to put a relaxation factor of 0.9 as you said and I couldn´t
> > see any improvement.
> >
> > 3)  I´m attaching three .txt files with some results obtained.
> > The results1.txt file shows the output of the program as you can find it on
> > ITK/Examples/Registration/.
> > The results2.txt file shows the output of the program with a predifined
> > center in the position 1000x1000. The results3.txt file shows the output of
> > the program with a predifined center in the position 1000x1000, a predefined
> > angle of 0.9 radians and a predefined traslation of -340 in the X axis and
> > 800 in the Y axis (that are the values for an optimal registration).
> >
> >
> > I hope you can help me to fix my problem with that information... an be free
> > to ask anything else :P.
> >
> > Thank you really much.
> >
> > Manuel.
> >
> >
> >> Date: Wed, 21 Oct 2009 17:29:08 -0400
> >> Subject: Re: [Insight-users] Problem with 2D Registration (local minima)
> >> From: luis.ibanez at kitware.com
> >> To: manueldavid.tabas at hotmail.es
> >> CC: insight-users at itk.org
> >>
> >> Hi Manuel,
> >>
> >> Thanks for the detailed description of your problem.
> >>
> >> A couple of questions:
> >>
> >>
> >> 1) What is the pixel spacing of your image ?
> >>
> >> The typical proportion of :
> >>
> >> > const double translationScale = 1.0 / 1000.0;
> >>
> >> is set up for images whose physical extent in
> >> the units used by the spacing is in the range
> >> of hundreds.
> >>
> >> For example, a typical CT scan will have 512x512
> >> pixels with a spacing close to 1mm / pixel.
> >>
> >> Your images are probably from Microscopy or
> >> from a Satellite, so I'm wondering about the units
> >> that you use (microns or kilometers) and the
> >> exact numeric values of the spacing.
> >>
> >>
> >> 2) Could you post to the list the output of the
> >> command observer that tracks the values of
> >> the metric and the transform at every iteration ?
> >>
> >>
> >> Something that happens often when using the
> >> RegularStepGradientDescentOptimizer is that,
> >> if the registration process have a couple of
> >> bounces of direction in the parametric space,
> >> the step length may be reduced too fast, and
> >> not give the optimizer the oportunity to walk
> >> far enough to get to the solution.
> >>
> >>
> >> You may want to try using the method:
> >>
> >> optimizer->SetRelaxationFactor( 0.9 );
> >>
> >>
> >> This method defines the factor by which the
> >> step length is reduced at every time that the
> >> parametric space step changes direction.
> >> This may prevent the premature shrinkage
> >> of the step length (assuming that this is the
> >> real problem).
> >>
> >>
> >> Anothe typical issue: It may simply be that you
> >> need a better initialization for your images.
> >>
> >>
> >> Note that the Transform initializer in the example:
> >>
> >> ImageRegistration6.cxx
> >>
> >> is using the methods MomentsOn().
> >>
> >> This may or may not be the right method to use,
> >> depending on the content of your images.
> >>
> >> For example: If the two images have different
> >> modalities, or if the main features of one image
> >> may not overlap to the one in the other image.
> >>
> >> If you could post a screenshot of both images
> >> we could avoid all this speculation... :-)
> >>
> >> Or...
> >> If you can share your images in a public web
> >> site, that will be even better.
> >>
> >>
> >>
> >> Thanks
> >>
> >>
> >> Luis
> >>
> >>
> >> ----------------------------------------------------------------
> >> On Wed, Oct 21, 2009 at 11:56 AM, Manuel David Tabas Calle
> >> <manueldavid.tabas at hotmail.es> wrote:
> >> > Hello ITK,
> >> >
> >> > I´m working with ITK to do registration of 2D images and I think I reach
> >> > a
> >> > local minima that makes a poor registration.
> >> >
> >> > I´m using 2D images 2000x2000 pixels in what the moving image needs a
> >> > rotation and a translation. So I reproduced the ImageRegistration6.cxx
> >> > to do
> >> > that. But the result I got is not good enough so I think that the
> >> > MeanSquares metric reaches a local minima. The value of the metric is
> >> > about
> >> > 4000 (aprox.), and I run a test using as input parameters the optimal
> >> > ones
> >> > (that is, the result I think i should obtain) and the metric returns a
> >> > value
> >> > of 2500 (aprox.).
> >> >
> >> > The framework I use is:
> >> >
> >> >    itkImageRegistrationMethod
> >> >    itkMeanSquaresImageToImageMetric
> >> >    itkLinearInterpolateImageFunction
> >> >    itkRegularStepGradientDescentOptimizer
> >> >    itkCenteredRigid2DTransform
> >> >
> >> > And the parameters of my registration are:
> >> >
> >> > const double translationScale = 1.0 / 1000.0;
> >> > optimizerScales[0] = 1.0;
> >> > optimizerScales[1] = translationScale;
> >> > optimizerScales[2] = translationScale;
> >> > optimizerScales[3] = translationScale;
> >> > optimizerScales[4] = translationScale;
> >> >
> >> > optimizer->SetMaximumStepLength( 0.1 );
> >> > optimizer->SetMinimumStepLength( 0.001 );
> >> > optimizer->SetNumberOfIterations( 200 );
> >> >
> >> >
> >> > The scales are well defined and I tried to vary the parameters of the
> >> > optimizer but the results were similar, so I don´t know what to do next.
> >> > Any
> >> > idea??
> >> >
> >> > Thank you in advance, I hope you can have more ideas to try.
> >> >
> >> >
> >> >
> >> > Manuel.
> >> >
> >> >
> >> >
> >> >
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> >> >
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