[Insight-users] White Output after Rigid Registration

[Andy Eow]

Hi Luis,

I'm using 3D Slicer to visualize the volume. The actual values in the volume 
are all the same ... hence I don't think the problem is with visualizing. 
I'm guessing there's something I'm not setting right in the registration 
process. Pls advise. Thanks!

Cheers,
Andy

----- Original Message ----- 
From: "Luis Ibanez" <luis.ibanez at kitware.com>
To: "Andy Eow" <vtkitk at hotmail.com>
Cc: <insight-users at itk.org>
Sent: Wednesday, September 29, 2004 11:54 AM
Subject: Re: [Insight-users] White Output after Rigid Registration


> Hi Andy,
>
> What are you  using for visualizing your resampled moving image ?
>
> When you say that the output is "white", did you verified the
> actual values in the output image ?
>
> Please let us know.
>
>
>    Thanks
>
>
>      Luis
>
>
> -----------------
> Andy Eow wrote:
>
>> Hi,
>>  I'm trying to perform a straightforward rigid registration in 3D using 
>> sample code from the MultiResMIRegistration application. The transform 
>> parameters after registration are as follows for my MRI (T1 & T2) 
>> dataset: [0.61162, 0.0627385, 0.0105601, 0.78859, 1.63678, -0.662944, 
>> 0.223458]. However, I suspect my post registration resampling is not 
>> working because the resulting volume from that is completely white. 
>> Attached is the exact code that I'm running. Any advice is appreciated. 
>> Thanks!!!
>>  VolumeType::Pointer MakeSymmetrical( VolumeType::Pointer fixedVol, 
>> VolumeType::Pointer movingVol ) {
>>   typedef itk::ChangeInformationImageFilter< VolumeType > CentererType;
>>   typedef itk::NormalizeImageFilter< VolumeType, VolumeType > 
>> NormalizerType;
>>   typedef itk::QuaternionRigidTransform< double > TransformType;
>>   typedef itk::QuaternionRigidTransformGradientDescentOptimizer 
>> OptimizerType;
>>   typedef itk::MutualInformationImageToImageMetric< VolumeType, 
>> VolumeType > MetricType;
>>   typedef itk::LinearInterpolateImageFunction< VolumeType, double > 
>> InterpolatorType;
>>   typedef itk::RecursiveMultiResolutionPyramidImageFilter< VolumeType, 
>> VolumeType > FixedImagePyramidType;
>>   typedef itk::RecursiveMultiResolutionPyramidImageFilter< VolumeType, 
>> VolumeType > MovingImagePyramidType;
>>   typedef itk::MultiResolutionImageRegistrationMethod< VolumeType, 
>> VolumeType > RegistrationType;
>>   typedef itk::FixedArray< unsigned int, 3 > ShrinkFactorsArray;
>>   typedef itk::Array< unsigned int > UnsignedIntArray;
>>   typedef itk::Array< double > DoubleArray;
>>   typedef itk::AffineTransform< double, 3 > AffineTransformType;
>>   typedef AffineTransformType::ScalarType CoordRepType;
>>   typedef itk::LinearInterpolateImageFunction< VolumeType, CoordRepType > 
>> ResampleInterpolatorType;
>>   typedef itk::ResampleImageFilter< VolumeType, VolumeType > 
>> ResamplerType;
>>  // Parameters
>>   unsigned short noOfLevels = 1;
>>   double translationScale = 1.0;
>>   double movingVolStdDev = 0.4;
>>   double fixedVolStdDev = 0.4;
>>   unsigned short noOfSpatialSamples = 50;
>>   DoubleArray learningRates = DoubleArray( noOfLevels );
>>   learningRates.Fill( 1e-4 );
>>   UnsignedIntArray noOfIterations = UnsignedIntArray( noOfLevels );
>>   noOfIterations.Fill( 2500 );
>>   ShrinkFactorsArray fixedVolShrinkFactors;
>>   fixedVolShrinkFactors.Fill( 1 );
>>   ShrinkFactorsArray movingVolShrinkFactors;
>>   movingVolShrinkFactors.Fill( 1 );
>>  // Fixed Volume
>>   CentererType::Pointer centerer =  CentererType::New();
>>   centerer->CenterImageOn();
>>   centerer->SetInput( fixedVol );
>>  NormalizerType::Pointer normalizer = NormalizerType::New(); 
>> normalizer->SetInput( centerer->GetOutput() );
>>   ITK_TRY_MACRO( normalizer->Update() );
>>   VolumeType::Pointer tFixedVol = normalizer->GetOutput();
>>  // Moving Volume
>>   CentererType::Pointer centerer2 =  CentererType::New();
>>   centerer2->CenterImageOn();
>>   centerer2->SetInput( movingVol );
>>  NormalizerType::Pointer normalizer2 = NormalizerType::New(); 
>> normalizer2->SetInput( centerer2->GetOutput() );
>>   ITK_TRY_MACRO( normalizer2->Update() );
>>   VolumeType::Pointer tMovingVol = normalizer2->GetOutput();
>>  // Setup the registrator
>>   TransformType::Pointer transform = TransformType::New();
>>   RegistrationType::ParametersType transformInitialParameters = 
>> RegistrationType::ParametersType( transform->GetNumberOfParameters() );
>>   transformInitialParameters.Fill( 0.0 );
>>   transformInitialParameters[3] = 1.0;
>>  OptimizerType::Pointer optimizer = OptimizerType::New();
>>   OptimizerType::ScalesType scales( transform->GetNumberOfParameters() );
>>   scales.Fill( 1.0 );
>>   for ( int i = 4; i < 7; i++ )
>>     scales[i] = translationScale;
>>   optimizer->SetScales( scales );
>>   optimizer->MaximizeOn();
>>  MetricType::Pointer metric = MetricType::New();
>>   metric->SetMovingImageStandardDeviation( movingVolStdDev );
>>   metric->SetFixedImageStandardDeviation( fixedVolStdDev );
>>   metric->SetNumberOfSpatialSamples( noOfSpatialSamples );
>>  FixedImagePyramidType::Pointer fixedImagePyramid = 
>> FixedImagePyramidType::New();
>>   fixedImagePyramid->SetNumberOfLevels( noOfLevels );
>>   fixedImagePyramid->SetStartingShrinkFactors( 
>> fixedVolShrinkFactors.GetDataPointer() );
>>  MovingImagePyramidType::Pointer movingImagePyramid = 
>> MovingImagePyramidType::New(); movingImagePyramid->SetNumberOfLevels( 
>> noOfLevels );
>>   movingImagePyramid->SetStartingShrinkFactors( 
>> movingVolShrinkFactors.GetDataPointer() );
>>  InterpolatorType::Pointer interpolator = InterpolatorType::New();
>>  RegistrationType::Pointer registration  = RegistrationType::New();
>>   registration->SetTransform( transform );
>>   registration->SetOptimizer( optimizer );
>>   registration->SetMetric( metric );
>>   registration->SetInterpolator( interpolator );
>>   registration->SetFixedImagePyramid( fixedImagePyramid );
>>   registration->SetMovingImagePyramid( movingImagePyramid );
>>   registration->SetFixedImage( tFixedVol );
>>   registration->SetMovingImage( tMovingVol );
>>   registration->SetNumberOfLevels( noOfLevels );
>>   registration->SetInitialTransformParameters( 
>> transformInitialParameters );
>>   registration->SetFixedImageRegion( tFixedVol->GetBufferedRegion() );
>>   ITK_TRY_MACRO( registration->StartRegistration() );
>>   MESSAGE( "Transform Parameters (post-reg): " << 
>> transform->GetParameters() );
>>   MESSAGE( "Rotation (post-reg): " << transform->GetRotation() );
>>   MESSAGE( "Translation (post-reg): " << transform->GetTranslation() );
>>  // Setup the resampler
>>   AffineTransformType::Pointer resamTransform = 
>> AffineTransformType::New();
>>   resamTransform->SetIdentity();
>>   resamTransform->SetParameters( transform->GetParameters() );
>>   resamTransform->SetMatrix( transform->GetRotationMatrix() );
>>   resamTransform->SetOffset( transform->GetOffset() );
>>  ResampleInterpolatorType::Pointer resamInterpolator = 
>> ResampleInterpolatorType::New();
>>  ResamplerType::Pointer resampler = ResamplerType::New();
>>   resampler->SetInput( tMovingVol );
>>   resampler->SetTransform( resamTransform );
>>   resampler->SetInterpolator( resamInterpolator );
>>   resampler->SetSize( tFixedVol->GetLargestPossibleRegion().GetSize() );
>>   resampler->SetOutputOrigin( tFixedVol->GetOrigin() );
>>   resampler->SetOutputSpacing( tFixedVol->GetSpacing() );
>>   resampler->SetDefaultPixelValue( 0 );
>>   ITK_TRY_MACRO( resampler->Update() );
>>  return resampler->GetOutput();
>> }
>>  Cheers,
>> Andy
>>
>>
>> ------------------------------------------------------------------------
>>
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