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/*=========================================================================
*
* Copyright UMC Utrecht and contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#include "itkAdvancedBSplineDeformableTransform.h" // original elastix
#include "itkRecursiveBSplineTransform.h" // recursive version
// Report timings
#include "itkTimeProbe.h"
#include "itkTimeProbesCollectorBase.h"
#include <fstream>
#include <iomanip>
//-------------------------------------------------------------------------------------
int
main( int argc, char * argv[] )
{
/** Some basic type definitions.
* NOTE: don't change the dimension or the spline order, since the
* hard-coded ground truth depends on this.
*/
const unsigned int Dimension = 3;
const unsigned int SplineOrder = 3;
typedef double CoordinateRepresentationType;
/** The number of calls to Evaluate(). Distinguish between
* Debug and Release mode.
*/
#ifndef NDEBUG
unsigned int N = static_cast< unsigned int >( 1e3 );
#else
unsigned int N = static_cast< unsigned int >( 1e5 );
#endif
std::cerr << "N = " << N << std::endl;
/** Check. */
if( argc != 2 )
{
std::cerr << "ERROR: You should specify a text file with the B-spline "
<< "transformation parameters." << std::endl;
return 1;
}
/** Typedefs. */
typedef itk::AdvancedBSplineDeformableTransform<
CoordinateRepresentationType, Dimension, SplineOrder > TransformType;
typedef itk::RecursiveBSplineTransform<
CoordinateRepresentationType, Dimension, SplineOrder > RecursiveTransformType;
typedef TransformType::NumberOfParametersType NumberOfParametersType;
typedef TransformType::InputPointType InputPointType;
typedef TransformType::ParametersType ParametersType;
typedef TransformType::NonZeroJacobianIndicesType NonZeroJacobianIndicesType;
typedef TransformType::DerivativeType DerivativeType;
typedef TransformType::JacobianType JacobianType;
typedef TransformType::MovingImageGradientType MovingImageGradientType;
typedef itk::Image< CoordinateRepresentationType,
Dimension > InputImageType;
typedef InputImageType::RegionType RegionType;
typedef InputImageType::SizeType SizeType;
typedef InputImageType::IndexType IndexType;
typedef InputImageType::SpacingType SpacingType;
typedef InputImageType::PointType OriginType;
typedef InputImageType::DirectionType DirectionType;
/** Create the transform. */
TransformType::Pointer transform = TransformType::New();
RecursiveTransformType::Pointer recursiveTransform = RecursiveTransformType::New();
/** Setup the B-spline transform:
* (GridSize 44 43 35)
* (GridIndex 0 0 0)
* (GridSpacing 10.7832773148 11.2116431394 11.8648235177)
* (GridOrigin -237.6759555555 -239.9488431747 -344.2315805162)
*/
SizeType gridSize;
gridSize[ 0 ] = 44; gridSize[ 1 ] = 43; gridSize[ 2 ] = 35;
IndexType gridIndex;
gridIndex.Fill( 0 );
RegionType gridRegion;
gridRegion.SetSize( gridSize );
gridRegion.SetIndex( gridIndex );
SpacingType gridSpacing;
gridSpacing[ 0 ] = 10.7832773148;
gridSpacing[ 1 ] = 11.2116431394;
gridSpacing[ 2 ] = 11.8648235177;
OriginType gridOrigin;
gridOrigin[ 0 ] = -237.6759555555;
gridOrigin[ 1 ] = -239.9488431747;
gridOrigin[ 2 ] = -344.2315805162;
DirectionType gridDirection;
gridDirection.SetIdentity();
transform->SetGridOrigin( gridOrigin );
transform->SetGridSpacing( gridSpacing );
transform->SetGridRegion( gridRegion );
transform->SetGridDirection( gridDirection );
recursiveTransform->SetGridOrigin( gridOrigin );
recursiveTransform->SetGridSpacing( gridSpacing );
recursiveTransform->SetGridRegion( gridRegion );
recursiveTransform->SetGridDirection( gridDirection );
/** Now read the parameters as defined in the file par.txt. */
ParametersType parameters( transform->GetNumberOfParameters() );
std::ifstream input( argv[ 1 ] );
if( input.is_open() )
{
for( unsigned int i = 0; i < parameters.GetSize(); ++i )
{
input >> parameters[ i ];
}
}
else
{
std::cerr << "ERROR: could not open the text file containing the "
<< "parameter values." << std::endl;
return 1;
}
transform->SetParameters( parameters );
recursiveTransform->SetParameters( parameters );
/** Declare variables. */
InputPointType inputPoint; inputPoint.Fill( 4.1 );
MovingImageGradientType movingImageGradient;
movingImageGradient[ 0 ] = 29.43; movingImageGradient[ 1 ] = 18.21; movingImageGradient[ 2 ] = 1.7;
const NumberOfParametersType nnzji = transform->GetNumberOfNonZeroJacobianIndices();
JacobianType jacobian( Dimension, nnzji );
DerivativeType imageJacobian_old( nnzji );
DerivativeType imageJacobian_new( nnzji );
DerivativeType imageJacobian_recursive( nnzji );
NonZeroJacobianIndicesType nzji( nnzji );
itk::TimeProbesCollectorBase timeCollector;
double sum = 0.0;
/** Time the plain old way. */
timeCollector.Start( "JacobianGradient plain old" );
for( unsigned int i = 0; i < N; ++i )
{
/** Get the TransformJacobian dT/dmu. */
transform->GetJacobian( inputPoint, jacobian, nzji );
/** Compute the inner products (dM/dx)^T (dT/dmu). */
const unsigned int numberOfParametersPerDimension = nnzji / Dimension;
unsigned int counter = 0;
for( unsigned int dim = 0; dim < Dimension; ++dim )
{
const double imDeriv = movingImageGradient[ dim ];
for( unsigned int mu = 0; mu < numberOfParametersPerDimension; ++mu )
{
imageJacobian_old( counter ) = jacobian( dim, counter ) * imDeriv;
++counter;
}
}
sum += imageJacobian_old( 0 ); // just to avoid compiler to optimize away
}
timeCollector.Stop( "JacobianGradient plain old" );
/** Time the plain new way. */
timeCollector.Start( "JacobianGradient plain new" );
for( unsigned int i = 0; i < N; ++i )
{
/** Compute the inner product of the transform Jacobian dT/dmu and the moving image gradient dM/dx. */
transform->EvaluateJacobianWithImageGradientProduct(
inputPoint, movingImageGradient,
imageJacobian_new, nzji );
sum += imageJacobian_new( 0 ); // just to avoid compiler to optimize away
}
timeCollector.Stop( "JacobianGradient plain new" );
/** Time the recursive old way. */
timeCollector.Start( "JacobianGradient recursive old" );
for( unsigned int i = 0; i < N; ++i )
{
/** Compute the inner product of the transform Jacobian dT/dmu and the moving image gradient dM/dx. */
recursiveTransform->GetJacobian( inputPoint, jacobian, nzji );
/** Compute the inner products (dM/dx)^T (dT/dmu). */
const unsigned int numberOfParametersPerDimension = nnzji / Dimension;
unsigned int counter = 0;
for( unsigned int dim = 0; dim < Dimension; ++dim )
{
const double imDeriv = movingImageGradient[ dim ];
for( unsigned int mu = 0; mu < numberOfParametersPerDimension; ++mu )
{
imageJacobian_old( counter ) = jacobian( dim, counter ) * imDeriv;
++counter;
}
}
sum += imageJacobian_old( 0 ); // just to avoid compiler to optimize away
}
timeCollector.Stop( "JacobianGradient recursive old" );
/** Time the recursive new way. */
timeCollector.Start( "JacobianGradient recursive new" );
for( unsigned int i = 0; i < N; ++i )
{
/** Compute the inner product of the transform Jacobian dT/dmu and the moving image gradient dM/dx. */
recursiveTransform->EvaluateJacobianWithImageGradientProduct(
inputPoint, movingImageGradient,
imageJacobian_new, nzji );
sum += imageJacobian_new( 0 ); // just to avoid compiler to optimize away
}
timeCollector.Stop( "JacobianGradient recursive new" );
/** Report timings. */
timeCollector.Report();
// Avoid compiler optimizations, so use sum
std::cerr << sum << std::endl; // works but ugly on screen
/**
*
* Test accuracy
*
*/
transform->EvaluateJacobianWithImageGradientProduct(
inputPoint, movingImageGradient,
imageJacobian_old, nzji );
recursiveTransform->EvaluateJacobianWithImageGradientProduct(
inputPoint, movingImageGradient,
imageJacobian_new, nzji );
double diffNorm = ( imageJacobian_old - imageJacobian_new ).magnitude();
std::cerr << "Recursive B-spline MSD with previous: " << diffNorm << std::endl;
if( diffNorm > 1e-5 )
{
std::cerr << "ERROR: Recursive B-spline EvaluateJacobianWithImageGradientProduct() returning incorrect result." << std::endl;
return EXIT_FAILURE;
}
/** Return a value. */
return EXIT_SUCCESS;
} // end main
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