Error using Registration - Mutual Information + AffineTransform

Discussion:

sharath v

2009-06-23 23:44:41 UTC

Hi,

I am trying to run example ImageRegistration2 with Affine Transform. This example uses originally used Mutual Information based registration with Translation.

I extended by using AffineTransform, and used the CenteredTransformInitializer for initialization ( according to example ImageRegistration9, which uses Affine with MeanSquares optimizer)

But, I do run into errors.

For the CenteredTransformInitializer, I use the following piece of code

typedef itk::CenteredTransformInitializer< TransformType, FixedImageType, MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer = TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() ); //*******
initializer->MomentsOn();

initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters() );

The program runs into completion, but gives WRONG values for scale and rotation parameters. The translation parameters obtained are correct.

If I change the starred lines (above in the code) to the take the output of the fixedSmoother and movingSmoother respectively ( which I think is correct, as they are output of the smoothing function in example2) , I get an exception

***** Description: itk::ERROR: MutualInformationImageToImageMetric(012D3058): All the sampled point mapped to outside of the moving image

I have tried the same with Mattes Mutual Information example, to get the same exception.

I have also used the appropriate scale setting code as in example 9.

Thanks in advance for the help,

Sharath Venkatesha

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sharath v

2009-06-23 23:52:07 UTC

Permalink

Hi,

I am trying to run example ImageRegistration2 with Affine Transform. This example uses originally used Mutual Information based registration with Translation.

I extended by using AffineTransform, and used the CenteredTransformInitializer for initialization ( according to example ImageRegistration9, which uses Affine with MeanSquares optimizer)

But, I do run into errors. I am using the BrainProtonDensity images for testing.

For the CenteredTransformInitializer, I use the following piece of code

typedef itk::CenteredTransformInitializer< TransformType, FixedImageType, MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer = TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() ); //*******
initializer->MomentsOn();

initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters() );

The program runs into completion, but gives WRONG values for scale and rotation parameters. The translation parameters obtained are correct.

If I change the starred lines (above in the code) to the take the output of the fixedSmoother and movingSmoother respectively ( which I think is correct, as they are output of the smoothing function in example2) , I get an exception

***** Description: itk::ERROR: MutualInformationImageToImageMetric(012D3058): All the sampled point mapped to outside of the moving image

I have tried the same with Mattes Mutual Information example, to get the same exception.

I have also used the appropriate scale setting code as in example 9.

Thanks in advance for the help,

Sharath Venkatesha

_____________________________________
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Visit other Kitware open-source projects at
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Luis Ibanez

2009-06-24 04:21:42 UTC

Permalink

Hi Sharath,

If you are interested in Affine registration you should probably
start with ImageRegistration9.cxx instead of modifying
ImageRegisration2.cxx.

In particular, you are probably missing to set up the
ParameterScaling array, which is critical for normalizing the
dynamic range of the different Transform parameters.

This was not critical for the case of the Translation Transform,
but it becomes very important in Rigid and Affine transforms.

Please study the ImageRegistration9.cxx example and
let us know if you have any questions.

Thanks

Luis

----------------------------------------------------

Post by sharath v
Hi,
I am trying to run example ImageRegistration2 with Affine Transform. This
example uses originally used Mutual Information based registration with
Translation.
I extended by using AffineTransform, and used the
CenteredTransformInitializer for initialization ( according to example
ImageRegistration9, which uses Affine with MeanSquares optimizer)
But, I do run into errors.
For the CenteredTransformInitializer, I use the following piece of code
typedef itk::CenteredTransformInitializer< TransformType, FixedImageType,
MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer =
TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() ); //*******
initializer->MomentsOn();
initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters() );
The program runs into completion, but gives WRONG values for scale and
rotation parameters. The translation parameters obtained are correct.
If I change the starred lines (above in the code) to the take the output of
the fixedSmoother and movingSmoother respectively ( which I think is
correct, as they are output of the smoothing function in example2) , I get
an exception
MutualInformationImageToImageMetric(012D3058): All the sampled point mapped
to outside of the moving image
I have tried the same with Mattes Mutual Information example, to get the same exception.
I have also used the appropriate scale setting code as in example 9.
Thanks in advance for the help,
Sharath Venkatesha
_____________________________________
Powered by www.kitware.com
Visit other Kitware open-source projects at
http://www.kitware.com/opensource/opensource.html
http://www.itk.org/Wiki/ITK_FAQ
http://www.itk.org/mailman/listinfo/insight-users

sharath v

2009-06-24 16:18:16 UTC

Permalink

Hi Luis,

Thanks for the reply.

I have already done the task that you have mentioned. I studied the example ImageRegistration9.cxx, and it worked for me with RTS images (from BrianProtonDensity set).

Below are the set of things I added to ImageRegistration9.cxx for Mutual Information + Affine

- changed the metric from MeanSquare to Mutual Information, and set the required parameters
- changed RegularStepGradientDescentOptimizer to GradientDescentOptimizer (as said in example 2)
- enabled optimizer->MaximizeOn()
- started with a low value of learning rate (5.0) as it gave an exception when 15.0 was used.
- used NormalizeImageFilter and DiscreteGaussianImageFilter on both the images as in example 2
- used CenteredTransformInitializer as explained in the manual

- And as you have mentioned I have used the Parameter scaling i.e optimizer->SetScales( optimizerScales ) with translation scale value = 0.001

** I got an exception when I tried to give the output of fixedSmoother and movingSmoother (from Example 2) to the initializer code below.

initializer->SetFixedImage( fixedImageReader->GetOutput() );
initializer->SetMovingImage( movingImageReader->GetOutput() );

Hence I retained it to the outputs from fixedImageReader and movingImageReader, as in the code snippet above. *****PLEASE LET ME KNOW IF THIS IS CORRECT ?

If I removed the Normalizing and Smoothing filters, I got an exception that the standard deviation of the metric is very low. It works when sigma = 1.5, but the output is wrong . Hence I retained these filters, with sigma = 0.4.

I followed your reply at a thread at nabble.com to download the imageregistration.exe and tried to overlay the output of the initializer (moving image warped with the initializer params) and this step is correct for BrainProtonDensitySliceShifted13x17y.png .

My current code fails for both BrainProtonDensitySliceShifted13x17y.png image and BrainProtonDensitySliceR10X13Y17.png image. It gives correct values for translation, but fails for rotation angle, and in both cases, gives high value for scaling ( Sx = ~4 and Sy= ~2) which are completely wrong.

I also tried working with MultiResImageRegistration2.cxx code which uses Matte + Affine. The output parameters obtained were WRONG when I tried with BrainProtonDensitySliceR10X13Y17.png image, instead of the example mentioned in the code.

I also tried with other optimizers such as Amoeba and OnePlusOne optimizers, with Viola MI + Affine. For Amoeba, the code gives correct result for translation for BrainProtonDensitySliceShifted13x17y.png only if the Parameter scaling is DISABLED. In other cases, the affine angle obtained starts with -83 degrees (where the expected value is R = 10 ) i.e in few cases code runs to completion, but the answer is wrong OR exception occurs, that sampled point mapped to outside of the moving image.

I am totally confused with the results . I have planned to use Mutual Information registration from ITK for non-medical images.

Can you please give me pointers, where I might be going wrong?

Thanks for the help,

Sharath Venkatesha

________________________________
From: Luis Ibanez <luis.ibanez-***@public.gmane.org>
To: sharath v <sharath20284-/***@public.gmane.org>
Cc: insight-users-***@public.gmane.org
Sent: Tuesday, June 23, 2009 9:21:42 PM
Subject: Re: [Insight-users] Error using Registration - Mutual Information + AffineTransform

Hi Sharath,

If you are interested in Affine registration you should probably
start with ImageRegistration9.cxx instead of modifying
ImageRegisration2.cxx.

In particular, you are probably missing to set up the
ParameterScaling array, which is critical for normalizing the
dynamic range of the different Transform parameters.

This was not critical for the case of the Translation Transform,
but it becomes very important in Rigid and Affine transforms.

Please study the ImageRegistration9.cxx example and
let us know if you have any questions.

Thanks

Luis

----------------------------------------------------

Post by sharath v

Post by sharath v
Hi,
I am trying to run example ImageRegistration2 with Affine Transform. This example uses originally used Mutual Information based registration with Translation.
I extended by using AffineTransform, and used the CenteredTransformInitializer for initialization ( according to example ImageRegistration9, which uses Affine with MeanSquares optimizer)
But, I do run into errors.
For the CenteredTransformInitializer, I use the following piece of code
typedef itk::CenteredTransformInitializer< TransformType, FixedImageType, MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer = TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() ); //*******
initializer->MomentsOn();
initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters() );
The program runs into completion, but gives WRONG values for scale and rotation parameters. The translation parameters obtained are correct.
If I change the starred lines (above in the code) to the take the output of the fixedSmoother and movingSmoother respectively ( which I think is correct, as they are output of the smoothing function in example2) , I get an exception
***** Description: itk::ERROR: MutualInformationImageToImageMetric(012D3058): All the sampled point mapped to outside of the moving image
I have tried the same with Mattes Mutual Information example, to get the same exception.
I have also used the appropriate scale setting code as in example 9.
Thanks in advance for the help,
Sharath Venkatesha
_____________________________________
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Visit other Kitware open-source projects at

http://www.kitware.com/opensource/opensource.html

Post by sharath v
Please keep messages on-topic and check the ITK FAQ at: http://www.itk.org/Wiki/ITK_FAQ

http://www.itk.org/mailman/listinfo/insight-users

Bill Lorensen

2009-06-24 16:39:40 UTC

Permalink

I think your learning rate is way too high for Viola-Wells MI. Try
something like .001.

Post by sharath v
Hi Luis,
Thanks for the reply.
I have already done the task that you have mentioned. I studied the example
ImageRegistration9.cxx, and it worked for me with RTS images (from
BrianProtonDensity set).
Below are the set of things I added to ImageRegistration9.cxx for Mutual
Information + Affine
- changed the metric from MeanSquare to Mutual Information, and set the
required parameters
- changed RegularStepGradientDescentOptimizer to GradientDescentOptimizer
(as said in example 2)
- enabled optimizer->MaximizeOn()
- started with a low value of learning rate (5.0) as it gave an exception
when 15.0 was used.
- used NormalizeImageFilter and DiscreteGaussianImageFilter on both the
images as in example 2
- used CenteredTransformInitializer as explained in the manual
- And as you have mentioned I have used the Parameter scaling i.e
optimizer->SetScales( optimizerScales ) with translation scale value = 0.001
** I got an exception when I tried to give the output of fixedSmoother and
movingSmoother (from Example 2) to the initializer code below.
initializer->SetFixedImage( fixedImageReader->GetOutput() );
initializer->SetMovingImage( movingImageReader->GetOutput() );
Hence I retained it to the outputs from fixedImageReader and
movingImageReader, as in the code snippet above. *****PLEASE LET ME KNOW IF
THIS IS CORRECT ?
If I removed the Normalizing and Smoothing filters, I got an exception that
the standard deviation of the metric is very low. It works when sigma = 1.5,
but the output is wrong . Hence I retained these filters, with sigma = 0.4.
I followed your reply at a thread at nabble.com to download the
imageregistration.exe and tried to overlay the output of the initializer
(moving image warped with the initializer params) and this step is correct
for BrainProtonDensitySliceShifted13x17y.png .
My current code fails for both BrainProtonDensitySliceShifted13x17y.png
image and BrainProtonDensitySliceR10X13Y17.png image. It gives correct
values for translation, but fails for rotation angle, and in both cases,
gives high value for scaling ( Sx = ~4 and Sy= ~2) which are completely
wrong.
I also tried working with MultiResImageRegistration2.cxx code which uses
Matte + Affine. The output parameters obtained were WRONG when I tried with
BrainProtonDensitySliceR10X13Y17.png image, instead of the example mentioned
in the code.
I also tried with other optimizers such as Amoeba and OnePlusOne optimizers,
with Viola MI + Affine. For Amoeba, the code gives correct result for
translation for BrainProtonDensitySliceShifted13x17y.png only if the
Parameter scaling is DISABLED. In other cases, the affine angle obtained
starts with -83 degrees (where the expected value is R = 10 ) i.e in few
cases code runs to completion, but the answer is wrong OR exception occurs,
that sampled point mapped to outside of the moving image.
I am totally confused with the results . I have planned to use Mutual
Information registration from ITK for non-medical images.
Can you please give me pointers, where I might be going wrong?
Thanks for the help,
Sharath Venkatesha
________________________________
Sent: Tuesday, June 23, 2009 9:21:42 PM
Subject: Re: [Insight-users] Error using Registration - Mutual Information +
AffineTransform
Hi Sharath,
If you are interested in Affine registration you should probably
start with ImageRegistration9.cxx instead of modifying
ImageRegisration2.cxx.
In particular, you are probably missing to set up the
ParameterScaling array, which is critical for normalizing the
dynamic range of the different Transform parameters.
This was not critical for the case of the Translation Transform,
but it becomes very important in Rigid and Affine transforms.
Please study the ImageRegistration9.cxx example and
let us know if you have any questions.
Thanks
Luis
----------------------------------------------------

Post by sharath v
Hi,
I am trying to run example ImageRegistration2 with Affine Transform. This
example uses originally used Mutual Information based registration with
Translation.
I extended by using AffineTransform, and used the
CenteredTransformInitializer for initialization ( according to example
ImageRegistration9, which uses Affine with MeanSquares optimizer)
But, I do run into errors.
For the CenteredTransformInitializer, I use the following piece of code
typedef itk::CenteredTransformInitializer< TransformType, FixedImageType,
MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer =
TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() );
//*******
initializer->MomentsOn();
initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters()
);
The program runs into completion, but gives WRONG values for scale and
rotation parameters. The translation parameters obtained are correct.
If I change the starred lines (above in the code) to the take the output
of the fixedSmoother and movingSmoother respectively ( which I think is
correct, as they are output of the smoothing function in example2) , I get
an exception
MutualInformationImageToImageMetric(012D3058): All the sampled point mapped
to outside of the moving image
I have tried the same with Mattes Mutual Information example, to get the same exception.
I have also used the appropriate scale setting code as in example 9.
Thanks in advance for the help,
Sharath Venkatesha
_____________________________________
Powered by www.kitware.com
Visit other Kitware open-source projects at
http://www.kitware.com/opensource/opensource.html
http://www.itk.org/Wiki/ITK_FAQ
http://www.itk.org/mailman/listinfo/insight-users

_____________________________________
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http://www.itk.org/mailman/listinfo/insight-users

_____________________________________
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sharath v

2009-06-25 00:06:10 UTC

Permalink

Hi,

Thanks for the help. Changing the learning parameter worked...

For Viola MI + Affine and with learning rate of 0.01 and 100 iterations, I get good results on BrainProtonDensitySliceR10X13Y17 image. Whereas on the BrainProtonDensitySliceR10X13Y17S12 image, it requires atleast 200 iterations to give correct results.

I want to use an optimizer which has a stopping value (i.e not fixed number of iterations) like Amoeba/Evolutionary/GradientDescentStep

I tried using the Amoeba optimizer with the following

OptimizerType::ParametersType simplexDelta( transform->GetNumberOfParameters() );
simplexDelta.Fill( 5.0 );
optimizer->AutomaticInitialSimplexOff();
optimizer->SetInitialSimplexDelta( simplexDelta );
optimizer->SetParametersConvergenceTolerance( 0.01 ); // quarter pixel
optimizer->SetFunctionConvergenceTolerance(0.001); // 0.1%
optimizer->SetMaximumNumberOfIterations( 200 );

but I get an exception that sampled point mapped to outside of the moving image, after 6-7 iterations. Similar issue happens for OnePlusOne optimizer with

typedef itk::Statistics::NormalVariateGenerator GeneratorType;
GeneratorType::Pointer generator = GeneratorType::New();
generator->Initialize(12345);
optimizer->SetNormalVariateGenerator( generator );
optimizer->Initialize( 10 );
optimizer->SetEpsilon( 1.0 );
optimizer->SetMaximumIteration( 4000 );

Can you please let me know what values need to be used?

And is there a way to make the registration process partially independent of these parameters?

Thanks,
Sharath

----- Original Message ----
From: Bill Lorensen <bill.lorensen-***@public.gmane.org>
To: sharath v <sharath20284-/***@public.gmane.org>
Cc: insight-users-***@public.gmane.org
Sent: Wednesday, June 24, 2009 9:39:40 AM
Subject: Re: [Insight-users] Error using Registration - Mutual Information + AffineTransform

I think your learning rate is way too high for Viola-Wells MI. Try
something like .001.

Post by sharath v
Hi,
I am trying to run example ImageRegistration2 with Affine Transform. This
example uses originally used Mutual Information based registration with
Translation.
I extended by using AffineTransform, and used the
CenteredTransformInitializer for initialization ( according to example
ImageRegistration9, which uses Affine with MeanSquares optimizer)
But, I do run into errors.
For the CenteredTransformInitializer, I use the following piece of code
typedef itk::CenteredTransformInitializer< TransformType, FixedImageType,
MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer =
TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() ); //*******
initializer->MomentsOn();
initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters() );
The program runs into completion, but gives WRONG values for scale and
rotation parameters. The translation parameters obtained are correct.
If I change the starred lines (above in the code) to the take the output
of the fixedSmoother and movingSmoother respectively ( which I think is
correct, as they are output of the smoothing function in example2) , I get
an exception
MutualInformationImageToImageMetric(012D3058): All the sampled point mapped
to outside of the moving image
I have tried the same with Mattes Mutual Information example, to get the same exception.
I have also used the appropriate scale setting code as in example 9.
Thanks in advance for the help,
Sharath Venkatesha
_____________________________________
Powered by www.kitware.com
Visit other Kitware open-source projects at
http://www.kitware.com/opensource/opensource.html
http://www.itk.org/Wiki/ITK_FAQ
http://www.itk.org/mailman/listinfo/insight-users

Luis Ibanez

2009-06-30 19:33:57 UTC

Permalink

Hi Sharath,

0) Whenever you get the exception saying that too many points
mapped outside of the moving image, it means that the
current Transform is such that when mapping the moving image
into the Fixed image coordinate system the overlap between
the two image is so small that it is unlikely that the
registration will recover in further iterations.

This is typically due to:

A) Poor initilization of the Transform

B) Poor selection of Scaling parameters
(the array that normalizes the dynamic
range of the different Transform parameters,
e.g. radians versus millimeters)

C) Optimizers that are set to perform jumps
that are too large, and bring the Transform
out of the range of the image.

1) You want to check this potential suspects in order.

That is.

First, verify that the initial transform
is reasonably placing the Moving image on top of the
Fixed image. You can do this by using the Resample
image filter, passing the moving image as input,
using the initial transform as Transform, and using
the Fixed image as reference. Then compare the
fixed image to the resampled moving image.

If the initial image looks ok,
then you want to check the values of the ParameterScaling.
It should be such that when you look at the Transform
parameters at ever iteration (using an Observer), the
values should change from iteration to iteration, according
to the expected dynamic range.

For example, transform parameters that correspond to rotations
should change by increments smaller than 0.01 (since they are
measured in Radians). While transform parameters that correspond
to translations should change at increments of 1 ~ 10

Finally, you should identify the parameter of the optimzer
that is responsible for selecting the size of jumps that
are performed in the parameteric space. (e.g. as you have
done for the learning rate in the GradientDescent optimizer).

You want to reduce the size of that jump, until you get the
Transform to have small increments at every iteration.

2) These parameters must be set up for every "family" of
registration problems. That is, the parameters that may be
good for registering a T1 to T2 MRI brain images, may not be
appropriate for registering a confocal microscopy image to
another.

However, once you fine tune the paramters for a pair of
T1-T2 images, it is likely that the same set of parameters
will work for another pair of the same type.

There is a need for a "smart layer" above the registration
framework, that could take away from the user the burden
of finding proper parameter settings....

any ideas are welcome :-)

3) Visual monitoring of the registraiton process
will help to make the fine-tunning process less
frustrating.

You may want to give it a try at the VTK helper
classes:

InsightApplications/Auxiliary/vtk/
vtkRegistrationMonitor.h
vtkRegistrationMonitor.cxx

they will display renderings from iso-surfaces
at every iteration of the registration process.

This is usually very informative...

Regards,

Luis

--------------

Post by sharath v
Hi,
Thanks for the help. Changing the learning parameter worked...
For Viola MI + Affine and with learning rate of 0.01 and 100 iterations, I get good results on BrainProtonDensitySliceR10X13Y17 image. Whereas on the BrainProtonDensitySliceR10X13Y17S12 image, it requires atleast 200 iterations to give correct results.
I want to use an optimizer which has a stopping value (i.e not fixed number of iterations) like Amoeba/Evolutionary/GradientDescentStep
I tried using the Amoeba optimizer with the following
OptimizerType::ParametersType simplexDelta( transform->GetNumberOfParameters() );
simplexDelta.Fill( 5.0 );
optimizer->AutomaticInitialSimplexOff();
optimizer->SetInitialSimplexDelta( simplexDelta );
optimizer->SetParametersConvergenceTolerance( 0.01 ); // quarter pixel
optimizer->SetFunctionConvergenceTolerance(0.001); // 0.1%
optimizer->SetMaximumNumberOfIterations( 200 );
but I get an exception that sampled point mapped to outside of the moving image, after 6-7 iterations. Similar issue happens for OnePlusOne optimizer with
typedef itk::Statistics::NormalVariateGenerator GeneratorType;
GeneratorType::Pointer generator = GeneratorType::New();
generator->Initialize(12345);
optimizer->SetNormalVariateGenerator( generator );
optimizer->Initialize( 10 );
optimizer->SetEpsilon( 1.0 );
optimizer->SetMaximumIteration( 4000 );
Can you please let me know what values need to be used?
And is there a way to make the registration process partially independent of these parameters?
Thanks,
Sharath
----- Original Message ----
Sent: Wednesday, June 24, 2009 9:39:40 AM
Subject: Re: [Insight-users] Error using Registration - Mutual Information + AffineTransform
I think your learning rate is way too high for Viola-Wells MI. Try
something like .001.

Post by sharath v
Hi,
I am trying to run example ImageRegistration2 with Affine Transform. This
example uses originally used Mutual Information based registration with
Translation.
I extended by using AffineTransform, and used the
CenteredTransformInitializer for initialization ( according to example
ImageRegistration9, which uses Affine with MeanSquares optimizer)
But, I do run into errors.
For the CenteredTransformInitializer, I use the following piece of code
typedef itk::CenteredTransformInitializer< TransformType, FixedImageType,
MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer =
TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() ); //*******
initializer->SetMovingImage( movingImageReader->GetOutput() ); //*******
initializer->MomentsOn();
initializer->InitializeTransform();
registration->SetInitialTransformParameters(transform->GetParameters() );
The program runs into completion, but gives WRONG values for scale and
rotation parameters. The translation parameters obtained are correct.
If I change the starred lines (above in the code) to the take the output
of the fixedSmoother and movingSmoother respectively ( which I think is
correct, as they are output of the smoothing function in example2) , I get
an exception
MutualInformationImageToImageMetric(012D3058): All the sampled point mapped
to outside of the moving image
I have tried the same with Mattes Mutual Information example, to get the same exception.
I have also used the appropriate scale setting code as in example 9.
Thanks in advance for the help,
Sharath Venkatesha
_____________________________________
Powered by www.kitware.com
Visit other Kitware open-source projects at
http://www.kitware.com/opensource/opensource.html
http://www.itk.org/Wiki/ITK_FAQ
http://www.itk.org/mailman/listinfo/insight-users

_____________________________________
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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
http://www.itk.org/mailman/listinfo/insight-users