[Insight-users] Helo with bspline/mutual information/gradient descent
Luis Ibanez
luis.ibanez at kitware.com
Sun Aug 9 11:50:22 EDT 2009
Hi J.X.J
You could do something like the following:
class CommandIterationUpdate : public itk::Command
{
public:
typedef CommandIterationUpdate Self;
typedef itk::Command Superclass;
typedef itk::SmartPointer<Self> Pointer;
itkNewMacro( Self );
protected:
CommandIterationUpdate() {};
public:
typedef itk::LevenbergMarquardtOptimizer OptimizerType
typedef const OptimizerType * OptimizerPointer;
void Open( const char * filename )
{
m_Output.open( filename );
}
void Close()
{
m_Output.close();
}
void Execute(itk::Object *caller, const itk::EventObject & event)
{
Execute( (const itk::Object *)caller, event);
}
void Execute(const itk::Object * object, const itk::EventObject & event)
{
OptimizerPointer optimizer =
dynamic_cast< OptimizerPointer >( object );
if( ! itk::IterationEvent().CheckEvent( &event ) )
{
return;
}
m_Output << optimizer->GetCurrentIteration() << " ";
m_Output << optimizer->GetCachedValue() << " ";
m_Output << optimizer->GetCurrentPosition() << std::endl;
}
private:
std::ofstream m_Output;
};
Then you connect it to the optimizer as:
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
observer->Open( "myOutputFile.txt");
registration->StartRegistration();
observer->Close();
Note that the actual methods to call will have to match the API
of the optimizer that you are using.
About the compilation error... please post the source code
of your test. You seem to be mixing two incompatible types.
Regards,
Luis
------------------------------------------------------
On Sun, Aug 9, 2009 at 5:17 AM, J.X.J. <wat.a.phony at gmail.com> wrote:
>
> Hi Luis,
>
> How can I store the metric value of each iteration into a file or
> variable/array within the observer? I've tried using ofstream to output the
> metric into a text file but it only stores the final metric value
> (optimizer->GetMetric()) after the registration->update() is finished. I've
> tried introducing ofstream into the observer but I cannot use the following
> command inside the observer (if that makes sense).
>
> std::ofstream infile;
> infile.open(argv[4]);
> infile<<optimizer->GetMetric();
> infile.close;
>
> As for the Levenberg Marquardt Optimizer this is the whole error message
> when compiling.
>
> 1>BSpline_ITK_DICOMM.cxx
> 1>.\BSpline_ITK_DICOMM.cxx(242) : error C2664:
> 'itk::ImageRegistrationMethod<TFixedImage,TMovingImage>::SetOptimizer' :
> cannot convert parameter 1 from 'itk::LevenbergMarquardtOptimizer::Pointer'
> to 'itk::ImageRegistrationMethod<TFixedImage,TMovingImage>::OptimizerType
> *'
> 1> with
> 1> [
> 1> TFixedImage=InternalImageType,
> 1> TMovingImage=InternalImageType
> 1> ]
> 1> No user-defined-conversion operator available that can perform
> this conversion, or the operator cannot be called
> 1>.\BSpline_ITK_DICOMM.cxx(366) : error C2039: 'GetCurrentIteration' : is
> not a member of 'itk::LevenbergMarquardtOptimizer'
> 1> D:\University -
>
> Engineering\Project\InsightToolkit-3.12.0\Code\Numerics\itkLevenbergMarquardtOptimizer.h(31)
> : see declaration of 'itk::LevenbergMarquardtOptimizer'
> 1>.\BSpline_ITK_DICOMM.cxx(367) : error C2440: 'initializing' : cannot
> convert from 'itk::MultipleValuedNonLinearOptimizer::MeasureType' to
> 'double'
> 1> No user-defined-conversion operator available that can perform
> this conversion, or the operator cannot be called
>
> J.X.J.
>
>
> Luis Ibanez wrote:
> >
> > Hi J.X.J.
> >
> > If the Metric is oscillating, this may be a symptom that your optimizer
> > is taking jumps that are too large.
> >
> > I usually plot the metric values by using GNUPlot, but you could do the
> > same with the spreadsheet of OpenOffice, or even with Excel.
> >
> > ---
> >
> > About the compilation error, please post also the sentence that
> > follows the one that you posted. The next sentence to that one
> > tells what the problem is.
> >
> >
> > Thanks
> >
> >
> > Luis
> >
> >
> > ----------------------
> > On Sat, Aug 8, 2009 at 7:45 PM, J.X.J. <wat.a.phony at gmail.com> wrote:
> >
> >>
> >> Hi Luis,
> >>
> >> thanks for your reply. I have added an observe to the code, the metric
> >> value
> >> output seems to oscillate rather than a general increase for decrease in
> >> value. How do you plot the metric values? Is there a way to output the
> >> metric value of each iteration into a text or similar file and I could
> >> use
> >> MATLAB to plot it, or is there a way to do that directly from ITK?
> >>
> >> Also I've noticed that using Viola and Wells MI is REALLY slow when
> >> coupled
> >> with BSpline Deformable Transform. I've tried using Mattes MI which is
> >> much
> >> much faster in comparison in the order of 5-10 fold, why is that the
> >> case?
> >>
> >> And finally (I'm sorry for all the questions, programming in C is not my
> >> forte), I tried using Levenberg Marquardt Optimizer but I get this error
> >> but
> >> I compile the code: error C2664:
> >> 'itk::ImageRegistrationMethod<TFixedImage,TMovingImage>::SetOptimizer' :
> >> cannot convert parameter 1 from
> >> 'itk::LevenbergMarquardtOptimizer::Pointer'
> >> to
> 'itk::ImageRegistrationMethod<TFixedImage,TMovingImage>::OptimizerType
> >> *'
> >>
> >> Any help is appreciated
> >> J.X.J.
> >>
> >>
> >> Luis Ibanez wrote:
> >> >
> >> > Hi J.X.J.
> >> >
> >> > The first thing that you want to do is to instantiate a
> >> Command/Observer
> >> > and to print out the values of the Metric at every iteration of the
> >> > optimizer.
> >> >
> >> > Plot this values and/or send the output to the mailing list.
> >> >
> >> > From the progression of the metric values it will be possible to
> >> determine
> >> > if parameters of the optimizer need to be adjusted, or whether you may
> >> > have to review other components of your registration structure.
> >> >
> >> > You will find examples on how to use Command Observers in almost
> >> > all the files in the directory:
> >> >
> >> > Insight/Examples/Registration
> >> >
> >> >
> >> > Regards,
> >> >
> >> >
> >> > Luis
> >> >
> >> >
> >> > --------------------------------------------------------------------
> >> > On Sat, Aug 1, 2009 at 6:49 AM, J.X.J. <wat.a.phony at gmail.com> wrote:
> >> >
> >> >>
> >> >> Hi everyone,
> >> >>
> >> >> I'm current using itk::BSplineDeformableTransform,
> >> >> itk::MutualInformationImageToImageMetric and
> >> >> itk::GradientDescentOptimizer
> >> >> to register 2D MRI images. My problem is that when running 2 phantom
> >> >> images
> >> >> the output image is almost exactly the same as the original moving
> >> image
> >> >> (nothing like the fixed image).
> >> >>
> >> >> I have normalized and smoothed the 2 input images using
> >> >> itk::NormalizeImageFilter and itk::DiscreteGaussianImageFilter with
> >> >> SetVariance(2.0). For mutual information the standard deviation is
> >> 0.4.
> >> >> Optimizer learning rate is 10.0, 200 iteration and with maximum on.
> >> This
> >> >> set
> >> >> up is kind of a mixture of a number of deformableregistration
> examples
> >> on
> >> >> default (as in I copied and pasted all parameter settings etc
> >> directly).
> >> >>
> >> >> Does anyone know what the problem could be? The code runs all 200
> >> >> iterations
> >> >> is thats an indication, also the metric value of each iteration is
> >> around
> >> >> 0.2 - 0.4 if that's any help.
> >> >>
> >> >> J.X.J.
> >> >> --
> >> >> View this message in context:
> >> >>
> >>
> http://www.nabble.com/Helo-with-bspline-mutual-information-gradient-descent-tp24768056p24768056.html
> >> >> Sent from the ITK - Users mailing list archive at Nabble.com.
> >> >>
> >> >> _____________________________________
> >> >> Powered by www.kitware.com
> >> >>
> >> >> Visit other Kitware open-source projects at
> >> >> http://www.kitware.com/opensource/opensource.html
> >> >>
> >> >> Please keep messages on-topic and check the ITK FAQ at:
> >> >> http://www.itk.org/Wiki/ITK_FAQ
> >> >>
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> >> >>
> >> >
> >> > _____________________________________
> >> > Powered by www.kitware.com
> >> >
> >> > Visit other Kitware open-source projects at
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> >> >
> >> > Please keep messages on-topic and check the ITK FAQ at:
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> >> >
> >> >
> >>
> >> --
> >> View this message in context:
> >>
> http://www.nabble.com/Helo-with-bspline-mutual-information-gradient-descent-tp24768056p24883109.html
> >> Sent from the ITK - Users mailing list archive at Nabble.com.
> >>
> >> _____________________________________
> >> Powered by www.kitware.com
> >>
> >> Visit other Kitware open-source projects at
> >> http://www.kitware.com/opensource/opensource.html
> >>
> >> Please keep messages on-topic and check the ITK FAQ at:
> >> http://www.itk.org/Wiki/ITK_FAQ
> >>
> >> Follow this link to subscribe/unsubscribe:
> >> http://www.itk.org/mailman/listinfo/insight-users
> >>
> >
> > _____________________________________
> > Powered by www.kitware.com
> >
> > Visit other Kitware open-source projects at
> > http://www.kitware.com/opensource/opensource.html
> >
> > Please keep messages on-topic and check the ITK FAQ at:
> > http://www.itk.org/Wiki/ITK_FAQ
> >
> > Follow this link to subscribe/unsubscribe:
> > http://www.itk.org/mailman/listinfo/insight-users
> >
> >
>
> --
> View this message in context:
> http://www.nabble.com/Helo-with-bspline-mutual-information-gradient-descent-tp24768056p24885406.html
> Sent from the ITK - Users mailing list archive at Nabble.com.
>
> _____________________________________
> Powered by www.kitware.com
>
> Visit other Kitware open-source projects at
> http://www.kitware.com/opensource/opensource.html
>
> Please keep messages on-topic and check the ITK FAQ at:
> http://www.itk.org/Wiki/ITK_FAQ
>
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