[Insight-users] Regarding analyze file format in DeformableReg4
Dalal, Dhaval
dalal at bnl.gov
Tue Sep 14 17:10:22 EDT 2004
Hi luis
thanx for your help, and sorry for bothering you so much.
I am not so technically fluent in C++ thats why i am having so many
difficulties. Plase bear with me.
-- Regarding changing the code to 3D in DeformableRegistration4.cxx
I changed
"const unsigned int Dimension = 2;"
with
"const unsigned int Dimension = 3;"
and also i added these 3 lines
Parameters[0] = 0.0; // Initial offset in mm along X
Parameters[1] = 0.0; // Initial offset in mm along Y
Parameters[2] = 0.0; // Initial offset in mm along Z
( i removed the keyword initial cause it was giving the error as undefined
)
is this correct?????
-- I read the softwareguide and am still confused,since i want to read
analyze file format,ITK has provided
the imageio class to do that. So what are the exact addidtions i have to
do in the program below (do i have to include the header files,
analyzeimageiofactory.h or analyzeimageio.h ).
also how do i instantiate the imagefilereader. Like how do i input, the
(.img and .hdr files)for the fixed image
and the (.img and .hdr files) for the moving image.
i tried to test this example using the 2 image files but it says starting
registration then it just hangs there.
Please let me know
thanx
regards
DHaval
This is my updated DeformableRegistration4.cxx
/*=========================================================================
// Software Guide : BeginLatex
//
// This example illustrates the use of the
\doxygen{BSplineDeformableTransform}
// class for performing registration of two $2D$ images. The example code is
// for the most part identical to the code presented in
// Section~\ref{sec:RigidRegistrationIn2D}. The major difference is that
this
// example we replace the Transform for a more generic one endowed with a
large
// number of degrees of freedom. Due to the large number of parameters, we
will
// also replace the simple steepest descent optimizer with the
// \doxygen{LBFGSOptimizer}.
//
//
// \index{itk::BSplineDeformableTransform}
// \index{itk::BSplineDeformableTransform!DeformableRegistration}
// \index{itk::LBFGSOptimizer}
//
//
// Software Guide : EndLatex
#include "itkImageRegistrationMethod.h"
#include "itkMeanSquaresImageToImageMetric.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkImage.h"
#include "itkTimeProbesCollectorBase.h"
// Software Guide : BeginLatex
//
// The following are the most relevant headers to this example.
//
// \index{itk::BSplineDeformableTransform!header}
// \index{itk::LBFGSOptimizer!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkBSplineDeformableTransform.h"
#include "itkLBFGSOptimizer.h"
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The parameter space of the \code{BSplineDeformableTransform} is composed
by
// the set of all the deformations associated with the nodes of the BSpline
// grid. This large number of parameters makes possible to represent a
wide
// variety of deformations, but it also has the price of requiring a
// significant amount of computation time.
//
// \index{itk::BSplineDeformableTransform!header}
//
// Software Guide : EndLatex
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkSquaredDifferenceImageFilter.h"
// NOTE: the LBFGSOptimizer does not invoke events
int main( int argc, char *argv[] )
{
if( argc < 4 )
{
std::cerr << "Missing Parameters " << std::endl;
std::cerr << "Usage: " << argv[0];
std::cerr << " fixedImageFile movingImageFile outputImagefile ";
std::cerr << " [differenceOutputfile] [differenceBeforeRegistration] ";
std::cerr << " [deformationField] ";
return 1;
}
const unsigned int ImageDimension = 3;
typedef float PixelType;
typedef itk::Image< PixelType, ImageDimension > FixedImageType;
typedef itk::Image< PixelType, ImageDimension > MovingImageType;
// Software Guide : BeginLatex
//
// We instantiate now the type of the \code{BSplineDeformableTransform}
using
// as template parameters the type for coordinates representation, the
// dimension of the space, and the order of the BSpline.
//
// \index{BSplineDeformableTransform|New}
// \index{BSplineDeformableTransform|Instantiation}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const unsigned int SpaceDimension = ImageDimension;
const unsigned int SplineOrder = 3;
typedef double CoordinateRepType;
typedef itk::BSplineDeformableTransform<
CoordinateRepType,
SpaceDimension,
SplineOrder > TransformType;
// Software Guide : EndCodeSnippet
typedef itk::LBFGSOptimizer OptimizerType;
typedef itk::MeanSquaresImageToImageMetric<
FixedImageType,
MovingImageType > MetricType;
typedef itk:: LinearInterpolateImageFunction<
MovingImageType,
double > InterpolatorType;
typedef itk::ImageRegistrationMethod<
FixedImageType,
MovingImageType > RegistrationType;
MetricType::Pointer metric = MetricType::New();
OptimizerType::Pointer optimizer = OptimizerType::New();
InterpolatorType::Pointer interpolator = InterpolatorType::New();
RegistrationType::Pointer registration = RegistrationType::New();
registration->SetMetric( metric );
registration->SetOptimizer( optimizer );
registration->SetInterpolator( interpolator );
// Software Guide : BeginLatex
//
// The transform object is constructed below and passed to the
registration
// method.
// \index{itk::RegistrationMethod!SetTransform()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
TransformType::Pointer transform = TransformType::New();
registration->SetTransform( transform );
// Software Guide : EndCodeSnippet
typedef itk::ImageFileReader< FixedImageType > FixedImageReaderType;
typedef itk::ImageFileReader< MovingImageType > MovingImageReaderType;
FixedImageReaderType::Pointer fixedImageReader =
FixedImageReaderType::New();
MovingImageReaderType::Pointer movingImageReader =
MovingImageReaderType::New();
fixedImageReader->SetFileName( argv[1] );
movingImageReader->SetFileName( argv[2] );
FixedImageType::ConstPointer fixedImage = fixedImageReader->GetOutput();
registration->SetFixedImage( fixedImage );
registration->SetMovingImage( movingImageReader->GetOutput() );
fixedImageReader->Update();
FixedImageType::RegionType fixedRegion = fixedImage->GetBufferedRegion();
registration->SetFixedImageRegion( fixedRegion );
// Software Guide : BeginLatex
//
// Here we define the parameters of the BSplineDeformableTransform grid.
We
// arbitrarily decide to use a grid with $5 \times 5$ nodes within the
image.
// The reader should note that the BSpline computation requires a
// finite support region ( 1 grid node at the lower borders and 2
// grid nodes at upper borders). Therefore in this example, we set
// the grid size to be $8 \times 8$ and place the grid origin such that
// grid node (1,1) coinicides with the first pixel in the fixed image.
//
// \index{BSplineDeformableTransform}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef TransformType::RegionType RegionType;
RegionType bsplineRegion;
RegionType::SizeType gridSizeOnImage;
RegionType::SizeType gridBorderSize;
RegionType::SizeType totalGridSize;
gridSizeOnImage.Fill( 5 );
gridBorderSize.Fill( 3 ); // Border for spline order = 3 ( 1 lower, 2
upper )
totalGridSize = gridSizeOnImage + gridBorderSize;
bsplineRegion.SetSize( totalGridSize );
typedef TransformType::SpacingType SpacingType;
SpacingType spacing = fixedImage->GetSpacing();
typedef TransformType::OriginType OriginType;
OriginType origin = fixedImage->GetOrigin();;
FixedImageType::SizeType fixedImageSize = fixedRegion.GetSize();
for(unsigned int r=0; r<ImageDimension; r++)
{
spacing[r] *= floor( static_cast<double>(fixedImageSize[r] - 1) /
static_cast<double>(gridSizeOnImage[r] - 1) );
origin[r] -= spacing[r];
}
transform->SetGridSpacing( spacing );
transform->SetGridOrigin( origin );
transform->SetGridRegion( bsplineRegion );
typedef TransformType::ParametersType ParametersType;
const unsigned int numberOfParameters =
transform->GetNumberOfParameters();
ParametersType parameters( numberOfParameters );
parameters.Fill( 0.0 );
transform->SetParameters( parameters );
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We now pass the parameters of the current transform as the initial
// parameters to be used when the registration process starts.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
registration->SetInitialTransformParameters( transform->GetParameters() );
// Software Guide : EndCodeSnippet
std::cout << "Intial Parameters = " << std::endl;
parameters[0] = 0.0; // Initial offset in mm along X
parameters[1] = 0.0; // Initial offset in mm along Y
parameters[2] = 0.0; // Initial offset in mm along Z
std::cout << transform->GetParameters() << std::endl;
// Software Guide : BeginLatex
//
// Next we set the parameters of the LBFGS Optimizer.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
optimizer->SetGradientConvergenceTolerance( 0.05 );
optimizer->SetLineSearchAccuracy( 0.9 );
optimizer->SetDefaultStepLength( 1.5 );
optimizer->TraceOn();
optimizer->SetMaximumNumberOfFunctionEvaluations( 1000 );
// Software Guide : EndCodeSnippet
// Add a time probe
itk::TimeProbesCollectorBase collector;
std::cout << std::endl << "Starting Registration" << std::endl;
try
{
collector.Start( "Registration" );
registration->StartRegistration();
collector.Stop( "Registration" );
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return -1;
}
OptimizerType::ParametersType finalParameters =
registration->GetLastTransformParameters();
std::cout << "Last Transform Parameters" << std::endl;
std::cout << finalParameters << std::endl;
// Report the time taken by the registration
collector.Report();
// Software Guide : BeginLatex
//
// Let's execute this example using the rat lung images from the previous
examples.
//
// \begin{itemize}
// \item \code{RatLungSlice1.mha}
// \item \code{RatLungSlice2.mha}
// \end{itemize}
//
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
transform->SetParameters( finalParameters );
// Software Guide : EndCodeSnippet
typedef itk::ResampleImageFilter<
MovingImageType,
FixedImageType > ResampleFilterType;
ResampleFilterType::Pointer resample = ResampleFilterType::New();
resample->SetTransform( transform );
resample->SetInput( movingImageReader->GetOutput() );
resample->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resample->SetOutputOrigin( fixedImage->GetOrigin() );
resample->SetOutputSpacing( fixedImage->GetSpacing() );
resample->SetDefaultPixelValue( 100 );
typedef unsigned char OutputPixelType;
typedef itk::Image< OutputPixelType, ImageDimension > OutputImageType;
typedef itk::CastImageFilter<
FixedImageType,
OutputImageType > CastFilterType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
CastFilterType::Pointer caster = CastFilterType::New();
writer->SetFileName( argv[3] );
caster->SetInput( resample->GetOutput() );
writer->SetInput( caster->GetOutput() );
try
{
writer->Update();
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return -1;
}
typedef itk::SquaredDifferenceImageFilter<
FixedImageType,
FixedImageType,
OutputImageType > DifferenceFilterType;
DifferenceFilterType::Pointer difference = DifferenceFilterType::New();
WriterType::Pointer writer2 = WriterType::New();
writer2->SetInput( difference->GetOutput() );
// Compute the difference image between the
// fixed and resampled moving image.
if( argc >= 5 )
{
difference->SetInput1( fixedImageReader->GetOutput() );
difference->SetInput2( resample->GetOutput() );
writer2->SetFileName( argv[4] );
try
{
writer2->Update();
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return -1;
}
}
// Compute the difference image between the
// fixed and moving image before registration.
if( argc >= 6 )
{
writer2->SetFileName( argv[5] );
difference->SetInput1( fixedImageReader->GetOutput() );
difference->SetInput2( movingImageReader->GetOutput() );
try
{
writer2->Update();
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return -1;
}
}
// Generate the explicit deformation field resulting from
// the registration.
typedef itk::Vector< float, ImageDimension > VectorType;
typedef itk::Image< VectorType, ImageDimension > DeformationFieldType;
DeformationFieldType::Pointer field = DeformationFieldType::New();
field->SetRegions( fixedRegion );
field->SetOrigin( fixedImage->GetOrigin() );
field->SetSpacing( fixedImage->GetSpacing() );
field->Allocate();
typedef itk::ImageRegionIterator< DeformationFieldType > FieldIterator;
FieldIterator fi( field, fixedRegion );
fi.GoToBegin();
TransformType::InputPointType fixedPoint;
TransformType::OutputPointType movingPoint;
DeformationFieldType::IndexType index;
VectorType displacement;
while( ! fi.IsAtEnd() )
{
index = fi.GetIndex();
field->TransformIndexToPhysicalPoint( index, fixedPoint );
movingPoint = transform->TransformPoint( fixedPoint );
displacement[0] = movingPoint[0] - fixedPoint[0];
displacement[1] = movingPoint[1] - fixedPoint[1];
fi.Set( displacement );
++fi;
}
typedef itk::ImageFileWriter< DeformationFieldType > FieldWriterType;
FieldWriterType::Pointer fieldWriter = FieldWriterType::New();
fieldWriter->SetInput( field );
if( argc >= 7 )
{
fieldWriter->SetFileName( argv[6] );
try
{
fieldWriter->Update();
}
catch( itk::ExceptionObject & excp )
{
std::cerr << "Exception thrown " << std::endl;
std::cerr << excp << std::endl;
return EXIT_FAILURE;
}
}
return 0;
}
=======================================================================
More information about the Insight-users
mailing list