/*=========================================================================
*
*  Copyright Insight Software Consortium
*
*  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.
*
*=========================================================================*/

//  Software Guide : BeginCommandLineArgs
//    INPUTS: brainweb1e1a10f20.mha
//    INPUTS: brainweb1e1a10f20Rot10Tx15.mha
//    OUTPUTS: ImageRegistration8Output.mhd
//    OUTPUTS: ImageRegistration8DifferenceBefore.mhd
//    OUTPUTS: ImageRegistration8DifferenceAfter.mhd
//    OUTPUTS: {ImageRegistration8Output.png}
//    OUTPUTS: {ImageRegistration8DifferenceBefore.png}
//    OUTPUTS: {ImageRegistration8DifferenceAfter.png}
//    OUTPUTS: {ImageRegistration8RegisteredSlice.png}
//  Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// This example illustrates the use of the \doxygen{VersorRigid3DTransform}
// class for performing registration of two $3D$ 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 is done in $3D$. The class \doxygen{CenteredTransformInitializer} is
// used to initialize the center and translation of the transform.  The case of
// rigid registration of 3D images is probably one of the most commonly found
// cases of image registration.
//
//
// \index{itk::Versor\-Rigid3D\-Transform}
// \index{itk::Centered\-Transform\-Initializer!In 3D}
//
//
// Software Guide : EndLatex
#include "itkImageRegistrationMethod.h"
#include "itkMeanSquaresImageToImageMetric.h"

//  Software Guide : BeginLatex
//
//  The following are the most relevant headers of this example.
//
//  \index{itk::Versor\-Rigid3D\-Transform!header}
//  \index{itk::Centered\-Transform\-Initializer!header}
//
//  Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkVersorRigid3DTransform.h"
#include "itkCenteredTransformInitializer.h"
// Software Guide : EndCodeSnippet
//  Software Guide : BeginLatex
//
//  The parameter space of the \code{VersorRigid3DTransform} is not a vector
//  space, due to the fact that addition is not a closed operation in the space
//  of versor components. This precludes the use of standard gradient descent
//  algorithms for optimizing the parameter space of this transform. A special
//  optimizer should be used in this registration configuration. The optimizer
//  designed for this transform is the
//  \doxygen{VersorRigid3DTransformOptimizer}. This optimizer uses Versor
//  composition for updating the first three components of the parameters
//  array, and Vector addition for updating the last three components of the
//  parameters array~\cite{Hamilton1866,Joly1905}.
//
//  \index{itk::Versor\-Rigid3D\-Transform\-Optimizer!header}
//
//  Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkVersorRigid3DTransformOptimizer.h"
// Software Guide : EndCodeSnippet
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkSubtractImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkExtractImageFilter.h"




#include "itkNrrdImageIO.h"
#include "itkGDCMImageIO.h"
#include "itkGDCMSeriesFileNames.h"
#include "itkImageSeriesReader.h"
#include "itkImageSeriesWriter.h"


//  The following section of code implements a Command observer
//  that will monitor the evolution of the registration process.
//
#include "itkCommand.h"
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::VersorRigid3DTransformOptimizer OptimizerType;
	typedef   const OptimizerType *              OptimizerPointer;
	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;
		}
		std::cout << optimizer->GetCurrentIteration() << "   ";
		std::cout << optimizer->GetValue() << "   ";
		std::cout << optimizer->GetCurrentPosition() << std::endl;
	}
};

int main()
{
	char* argv[6] = {"chu.exe",
		//"../../data/3DT1",
		//"../../data/Atlas/t1w_atlas_256.nrrd",
		"../../data/3DT1",
		"../../data/Atlas/t1w_atlas_256.nrrd",
		"../../outputRegist3D/transformed.png",
		"../../outputRegist3D/substract1.png",
		"../../outputRegist3D/substract2.png"	} ;

	const unsigned int                          Dimension = 3;
	typedef  float                              PixelType;
	typedef itk::Image< signed short, Dimension >  FixedImageType;
	typedef itk::Image< PixelType, Dimension >  MovingImageType;

	//  Software Guide : BeginLatex
	//
	//  The Transform class is instantiated using the code below. The only
	//  template parameter to this class is the representation type of the
	//  space coordinates.
	//
	//  \index{itk::Versor\-Rigid3D\-Transform!Instantiation}
	//
	//  Software Guide : EndLatex
	// Software Guide : BeginCodeSnippet
	typedef itk::VersorRigid3DTransform< double > TransformType;
	// Software Guide : EndCodeSnippet
	typedef itk::VersorRigid3DTransformOptimizer                                  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::Versor\-Rigid3D\-Transform!New()}
	//  \index{itk::Versor\-Rigid3D\-Transform!Pointer}
	//  \index{itk::Registration\-Method!SetTransform()}
	//
	//  Software Guide : EndLatex
	// Software Guide : BeginCodeSnippet
	TransformType::Pointer  transform = TransformType::New();
	registration->SetTransform( transform );
	// Software Guide : EndCodeSnippet
	typedef itk::ImageSeriesReader< 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] );*/


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

	// lecture première image (DICOM)
	std::cout << "Le fichier " << argv[1] << " est une serie de DICOM " << std::endl;

	typedef itk::GDCMImageIO ImageIOType; // une image DICOM
	typedef itk::GDCMSeriesFileNames InputNamesGeneratorType;

	// lecture d'un DICOM
	ImageIOType::Pointer gdcmIO = ImageIOType::New();

	// on crée le générateur de noms de fichier
	InputNamesGeneratorType::Pointer namesGenerator = InputNamesGeneratorType::New();
	// on indique au générateur de nom le dossier d'entrée
	namesGenerator->SetInputDirectory( argv[1] );
	// on récupère à présent la liste des fichiers à lire
	const FixedImageReaderType::FileNamesContainer & filenames =
		namesGenerator->GetInputFileNames();

	// on lui indique que ce sont des DICOM
	fixedImageReader->SetImageIO( gdcmIO );
	// on lui fournit la liste des fichiers à charger
	fixedImageReader->SetFileNames( filenames );
	try
	{// on lance le processus de lecture
		fixedImageReader->Update();
	}
	catch (itk::ExceptionObject &excp)
	{
		std::cerr << "Exception thrown while reading the series" << std::endl;
		std::cerr << excp << std::endl;
	}
		std::cout << "The input series in directory " << argv[1]
	<< " has " << fixedImageReader->GetFileNames().size() << " files "
		<< " of size " << fixedImageReader->GetOutput()->GetBufferedRegion().GetSize()
		<< std::endl;

	/////////////////////////////////////////////////////////////////////////////////////
	// test : on écrit les DICOM (pour vérifier leur lecture)
	/////////////////////////////////////////////////////////////////////////////////////

	// on renseigne le dossier de sortie
	const char * outputDirectory = "../../output";
	typedef itk::Image< signed short, 2 >	testOutputImageType;
	typedef itk::ImageSeriesWriter< FixedImageType, testOutputImageType >	SeriesWriterType;
	// on crée l'enregistreur de série
	SeriesWriterType::Pointer seriesWriter = SeriesWriterType::New();
	// on récupère les fichier enregistrés en mémoire et on les passe à l'enregistreur
	itk::ImageSource<itk::Image<signed short, 3U>>::OutputImageType * readerOutput = fixedImageReader->GetOutput() ;
	seriesWriter->SetInput(readerOutput);

	// on indique à l'enregistreur que ce sont des DICOM qu'il doit enregistrer
	seriesWriter->SetImageIO( gdcmIO );

	// on génère les nouveaux noms de fichiers en utilisant le dossier de sortie
	namesGenerator->SetOutputDirectory(outputDirectory) ;

	// on donne la liste des nouveaux fichiers à l'enregistreur
	seriesWriter->SetFileNames( namesGenerator->GetOutputFileNames() );

	// on récupère les métadonnées qui on été récupérées dans le lecteur et on
	// les passe à l'enregistreur
	seriesWriter->SetMetaDataDictionaryArray(
		fixedImageReader->GetMetaDataDictionaryArray()) ;



	try
	{// on procède à l'enregistrement des nouveaux fichiers
		seriesWriter->Update();
	}
	catch( itk::ExceptionObject & excp )
	{
		std::cerr << "Exception thrown while writing the series " << std::endl;
		std::cerr << excp << std::endl;
		return EXIT_FAILURE;
	}



	std::cout << "The output series in directory " << argv[2]
	<< " has " << seriesWriter->GetFileNames().size() << " files "
		<< " of size "
		<< fixedImageReader->GetOutput()->GetBufferedRegion().GetSize()
		<< std::endl;

	/////////////////////////////////////////////////////////////////////////////////////
	// fin test
	/////////////////////////////////////////////////////////////////////////////////////


	// lecture deuxieme image (nrrd)
	typedef itk::NrrdImageIO nrrdType; // une image nrrd

	std::cout << "Le fichier  " <<  argv[2]  << " est un nrrd" << std::endl;

	// lecture d'un nrrd
	nrrdType::Pointer nrrdIO = nrrdType::New();
	// on lui indique que ce sont des nrrd
	movingImageReader->SetImageIO( nrrdIO );
	// on lui fournit la liste des fichiers à charger
	movingImageReader->SetFileName(  argv[2]  );
	try
	{// on lance le processus de lecture
		movingImageReader->Update();
	}
	catch (itk::ExceptionObject &excp)
	{
		std::cerr << "Exception thrown while reading the series" << std::endl;
		std::cerr << excp << std::endl;
	}







	fixedImageReader->Update();
	registration->SetFixedImageRegion(
		fixedImageReader->GetOutput()->GetBufferedRegion() );

	//  Software Guide : BeginLatex
	//
	//  The input images are taken from readers. It is not necessary here to
	//  explicitly call \code{Update()} on the readers since the
	//  \doxygen{CenteredTransformInitializer} will do it as part of its
	//  computations. The following code instantiates the type of the
	//  initializer. This class is templated over the fixed and moving image type
	//  as well as the transform type. An initializer is then constructed by
	//  calling the \code{New()} method and assigning the result to a smart
	//  pointer.
	//
	// \index{itk::Centered\-Transform\-Initializer!Instantiation}
	// \index{itk::Centered\-Transform\-Initializer!New()}
	// \index{itk::Centered\-Transform\-Initializer!SmartPointer}
	//
	//  Software Guide : EndLatex
	// Software Guide : BeginCodeSnippet
	typedef itk::CenteredTransformInitializer< TransformType,
		FixedImageType,
		MovingImageType
	>  TransformInitializerType;
	TransformInitializerType::Pointer initializer =
		TransformInitializerType::New();
	// Software Guide : EndCodeSnippet

	//  Software Guide : BeginLatex
	//
	//  The initializer is now connected to the transform and to the fixed and
	//  moving images.
	//
	//  Software Guide : EndLatex

	// Software Guide : BeginCodeSnippet
	initializer->SetTransform(   transform );
	initializer->SetFixedImage(  fixedImageReader->GetOutput() );
	initializer->SetMovingImage( movingImageReader->GetOutput() );
	// Software Guide : EndCodeSnippet
	//  Software Guide : BeginLatex
	//
	//  The use of the geometrical centers is selected by calling
	//  \code{GeometryOn()} while the use of center of mass is selected by
	//  calling \code{MomentsOn()}.  Below we select the center of mass mode.
	//
	//  \index{Centered\-Transform\-Initializer!MomentsOn()}
	//  \index{Centered\-Transform\-Initializer!GeometryOn()}
	//
	//  Software Guide : EndLatex
	// Software Guide : BeginCodeSnippet
	initializer->MomentsOn();
	// Software Guide : EndCodeSnippet

	//  Software Guide : BeginLatex
	//
	//  Finally, the computation of the center and translation is triggered by
	//  the \code{InitializeTransform()} method. The resulting values will be
	//  passed directly to the transform.
	//
	//  Software Guide : EndLatex

	// Software Guide : BeginCodeSnippet
	initializer->InitializeTransform();
	// Software Guide : EndCodeSnippet

	//  Software Guide : BeginLatex
	//
	//  The rotation part of the transform is initialized using a
	//  \doxygen{Versor} which is simply a unit quaternion.  The
	//  \code{VersorType} can be obtained from the transform traits. The versor
	//  itself defines the type of the vector used to indicate the rotation axis.
	//  This trait can be extracted as \code{VectorType}. The following lines
	//  create a versor object and initialize its parameters by passing a
	//  rotation axis and an angle.
	//
	//  Software Guide : EndLatex
	// Software Guide : BeginCodeSnippet
	typedef TransformType::VersorType  VersorType;
	typedef VersorType::VectorType     VectorType;
	VersorType     rotation;
	VectorType     axis;
	axis[0] = 0.0;
	axis[1] = 0.0;
	axis[2] = 1.0;
	const double angle = 0;
	rotation.Set(  axis, angle  );
	transform->SetRotation( rotation );
	// 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
	typedef OptimizerType::ScalesType       OptimizerScalesType;
	OptimizerScalesType optimizerScales( transform->GetNumberOfParameters() );
	const double translationScale = 1.0 / 1000.0;
	optimizerScales[0] = 1.0;
	optimizerScales[1] = 1.0;
	optimizerScales[2] = 1.0;
	optimizerScales[3] = translationScale;
	optimizerScales[4] = translationScale;
	optimizerScales[5] = translationScale;
	optimizer->SetScales( optimizerScales );
	optimizer->SetMaximumStepLength( 0.2000  );
	optimizer->SetMinimumStepLength( 0.0001 );
	optimizer->SetNumberOfIterations( 200 );

	// Create the Command observer and register it with the optimizer.
	//
	CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
	optimizer->AddObserver( itk::IterationEvent(), observer );

	try
	{
		registration->Update();
		std::cout << "Optimizer stop condition: "
			<< registration->GetOptimizer()->GetStopConditionDescription()
			<< std::endl;
	}
	catch( itk::ExceptionObject & err )
	{
		std::cerr << "ExceptionObject caught !" << std::endl;
		std::cerr << err << std::endl;
		return EXIT_FAILURE;
	}
	OptimizerType::ParametersType finalParameters =
		registration->GetLastTransformParameters();

	const double versorX              = finalParameters[0];
	const double versorY              = finalParameters[1];
	const double versorZ              = finalParameters[2];
	const double finalTranslationX    = finalParameters[3];
	const double finalTranslationY    = finalParameters[4];
	const double finalTranslationZ    = finalParameters[5];
	const unsigned int numberOfIterations = optimizer->GetCurrentIteration();
	const double bestValue = optimizer->GetValue();

	// Print out results
	//
	std::cout << std::endl << std::endl;
	std::cout << "Result = " << std::endl;
	std::cout << " versor X      = " << versorX  << std::endl;
	std::cout << " versor Y      = " << versorY  << std::endl;
	std::cout << " versor Z      = " << versorZ  << std::endl;
	std::cout << " Translation X = " << finalTranslationX  << std::endl;
	std::cout << " Translation Y = " << finalTranslationY  << std::endl;
	std::cout << " Translation Z = " << finalTranslationZ  << std::endl;
	std::cout << " Iterations    = " << numberOfIterations << std::endl;
	std::cout << " Metric value  = " << bestValue          << std::endl;

	//  Software Guide : BeginLatex
	//
	//  Let's execute this example over some of the images available in the ftp
	//  site
	//
	//  \url{ftp://public.kitware.com/pub/itk/Data/BrainWeb}
	//
	//  Note that the images in the ftp site are compressed in \code{.tgz} files.
	//  You should download these files an uncompress them in your local system.
	//  After decompressing and extracting the files you could take a pair of
	//  volumes, for example the pair:
	//
	//  \begin{itemize}
	//  \item \code{brainweb1e1a10f20.mha}
	//  \item \code{brainweb1e1a10f20Rot10Tx15.mha}
	//  \end{itemize}
	//
	//  The second image is the result of intentionally rotating the first image
	//  by $10$ degrees around the origin and shifting it $15mm$ in $X$.  The
	//  registration takes $24$ iterations and produces:
	//
	//  \begin{center}
	//  \begin{verbatim}
	//  [-6.03744e-05, 5.91487e-06, -0.0871932, 2.64659, -17.4637, -0.00232496]
	//  \end{verbatim}
	//  \end{center}
	//
	//  That are interpreted as
	//
	//  \begin{itemize}
	//  \item Versor        = $(-6.03744e-05, 5.91487e-06, -0.0871932)$
	//  \item Translation   = $(2.64659,  -17.4637,  -0.00232496)$ millimeters
	//  \end{itemize}
	//
	//  This Versor is equivalent to a rotation of $9.98$ degrees around the $Z$
	//  axis.
	//
	//  Note that the reported translation is not the translation of $(15.0,0.0,0.0)$
	//  that we may be naively expecting. The reason is that the
	//  \code{VersorRigid3DTransform} is applying the rotation around the center
	//  found by the \code{CenteredTransformInitializer} and then adding the
	//  translation vector shown above.
	//
	//  It is more illustrative in this case to take a look at the actual
	//  rotation matrix and offset resulting form the $6$ parameters.
	//
	//  Software Guide : EndLatex
	// Software Guide : BeginCodeSnippet
	transform->SetParameters( finalParameters );
	TransformType::MatrixType matrix = transform->GetMatrix();
	TransformType::OffsetType offset = transform->GetOffset();
	std::cout << "Matrix = " << std::endl << matrix << std::endl;
	std::cout << "Offset = " << std::endl << offset << std::endl;
	// Software Guide : EndCodeSnippet

	//  Software Guide : BeginLatex
	//
	//  The output of this print statements is
	//
	//  \begin{center}
	//  \begin{verbatim}
	//  Matrix =
	//      0.984795 0.173722 2.23132e-05
	//      -0.173722 0.984795 0.000119257
	//      -1.25621e-06 -0.00012132 1
	//
	//  Offset =
	//      [-15.0105, -0.00672343, 0.0110854]
	//  \end{verbatim}
	//  \end{center}
	//
	//  From the rotation matrix it is possible to deduce that the rotation is
	//  happening in the X,Y plane and that the angle is on the order of
	//  $\arcsin{(0.173722)}$ which is very close to 10 degrees, as we expected.
	//
	//  Software Guide : EndLatex

	//  Software Guide : BeginLatex
	//
	// \begin{figure}
	// \center
	// \includegraphics[width=0.44\textwidth]{BrainProtonDensitySliceBorder20.eps}
	// \includegraphics[width=0.44\textwidth]{BrainProtonDensitySliceR10X13Y17.eps}
	// \itkcaption[CenteredTransformInitializer input images]{Fixed and moving image
	// provided as input to the registration method using
	// CenteredTransformInitializer.}
	// \label{fig:FixedMovingImageRegistration8}
	// \end{figure}
	//
	//
	// \begin{figure}
	// \center
	// \includegraphics[width=0.32\textwidth]{ImageRegistration8Output.eps}
	// \includegraphics[width=0.32\textwidth]{ImageRegistration8DifferenceBefore.eps}
	// \includegraphics[width=0.32\textwidth]{ImageRegistration8DifferenceAfter.eps}
	// \itkcaption[CenteredTransformInitializer output images]{Resampled moving
	// image (left). Differences between fixed and moving images, before (center)
	// and after (right) registration with the
	// CenteredTransformInitializer.}
	// \label{fig:ImageRegistration8Outputs}
	// \end{figure}
	//
	// Figure \ref{fig:ImageRegistration8Outputs} shows the output of the
	// registration. The center image in this figure shows the differences
	// between the fixed image and the resampled moving image before the
	// registration. The image on the right side presents the difference between
	// the fixed image and the resampled moving image after the registration has
	// been performed. Note that these images are individual slices extracted
	// from the actual volumes. For details, look at the source code of this
	// example, where the ExtractImageFilter is used to extract a slice from the
	// the center of each one of the volumes. One of the main purposes of this
	// example is to illustrate that the toolkit can perform registration on
	// images of any dimension. The only limitations are, as usual, the amount of
	// memory available for the images and the amount of computation time that it
	// will take to complete the optimization process.
	//
	// \begin{figure}
	// \center
	// \includegraphics[height=0.32\textwidth]{ImageRegistration8TraceMetric.eps}
	// \includegraphics[height=0.32\textwidth]{ImageRegistration8TraceAngle.eps}
	// \includegraphics[height=0.32\textwidth]{ImageRegistration8TraceTranslations.eps}
	// \itkcaption[CenteredTransformInitializer output plots]{Plots of the metric,
	// rotation angle, center of rotation and translations during the
	// registration using CenteredTransformInitializer.}
	// \label{fig:ImageRegistration8Plots}
	// \end{figure}
	//
	//  Figure \ref{fig:ImageRegistration8Plots} shows the plots of the main
	//  output parameters of the registration process. The metric values at every
	//  iteration. The Z component of the versor is plotted as an indication of
	//  how the rotation progress. The X,Y translation components of the
	//  registration are plotted at every iteration too.
	//
	//  Shell and Gnuplot scripts for generating the diagrams in
	//  Figure~\ref{fig:ImageRegistration8Plots} are available in the directory
	//
	//  \code{InsightDocuments/SoftwareGuide/Art}
	//
	//  You are strongly encouraged to run the example code, since only in this
	//  way you can gain a first hand experience with the behavior of the
	//  registration process. Once again, this is a simple reflection of the
	//  philosophy that we put forward in this book:
	//
	//  \emph{If you can not replicate it, then it does not exist!}.
	//
	//  We have seen enough published papers with pretty pictures, presenting
	//  results that in practice are impossible to replicate. That is vanity, not
	//  science.
	//
	//  Software Guide : EndLatex

	typedef itk::ResampleImageFilter<
		MovingImageType,
		FixedImageType >    ResampleFilterType;
	TransformType::Pointer finalTransform = TransformType::New();
	finalTransform->SetCenter( transform->GetCenter() );
	finalTransform->SetParameters( finalParameters );
	finalTransform->SetFixedParameters( transform->GetFixedParameters() );
	ResampleFilterType::Pointer resampler = ResampleFilterType::New();
	resampler->SetTransform( finalTransform );
	resampler->SetInput( movingImageReader->GetOutput() );
	FixedImageType::Pointer fixedImage = fixedImageReader->GetOutput();
	resampler->SetSize(    fixedImage->GetLargestPossibleRegion().GetSize() );
	resampler->SetOutputOrigin(  fixedImage->GetOrigin() );
	resampler->SetOutputSpacing( fixedImage->GetSpacing() );
	resampler->SetOutputDirection( fixedImage->GetDirection() );
	resampler->SetDefaultPixelValue( 100 );

	typedef  unsigned char                                          OutputPixelType;
	typedef itk::Image< OutputPixelType, Dimension >                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( resampler->GetOutput() );
	writer->SetInput( caster->GetOutput()   );
	writer->Update();

	typedef itk::SubtractImageFilter<
		FixedImageType,
		FixedImageType,
		FixedImageType > DifferenceFilterType;
	DifferenceFilterType::Pointer difference = DifferenceFilterType::New();

	typedef itk::RescaleIntensityImageFilter<
		FixedImageType,
		OutputImageType >   RescalerType;
	RescalerType::Pointer intensityRescaler = RescalerType::New();
	intensityRescaler->SetInput( difference->GetOutput() );
	intensityRescaler->SetOutputMinimum(   0 );
	intensityRescaler->SetOutputMaximum( 255 );
	difference->SetInput1( fixedImageReader->GetOutput() );
	difference->SetInput2( resampler->GetOutput() );
	resampler->SetDefaultPixelValue( 1 );
	WriterType::Pointer writer2 = WriterType::New();
	writer2->SetInput( intensityRescaler->GetOutput() );

	// Compute the difference image between the
	// fixed and resampled moving image.
	if( /*argc > 5*/1 )
	{
		writer2->SetFileName( argv[5] );
		writer2->Update();
	}

	typedef itk::IdentityTransform< double, Dimension > IdentityTransformType;
	IdentityTransformType::Pointer identity = IdentityTransformType::New();
	// Compute the difference image between the
	// fixed and moving image before registration.
	if( /*argc > 4*/1 )
	{
		resampler->SetTransform( identity );
		writer2->SetFileName( argv[4] );
		writer2->Update();
	}
	//
	//  Here we extract slices from the input volume, and the difference volumes
	//  produced before and after the registration.  These slices are presented as
	//  figures in the Software Guide.
	//
	//
	typedef itk::Image< OutputPixelType, 2 > OutputSliceType;
	typedef itk::ExtractImageFilter<
		OutputImageType,
		OutputSliceType > ExtractFilterType;
	ExtractFilterType::Pointer extractor = ExtractFilterType::New();
	extractor->SetDirectionCollapseToSubmatrix();
	extractor->InPlaceOn();

	FixedImageType::RegionType inputRegion =
		fixedImage->GetLargestPossibleRegion();
	FixedImageType::SizeType  size  = inputRegion.GetSize();
	FixedImageType::IndexType start = inputRegion.GetIndex();
	// Select one slice as output
	size[2]  =  0;
	start[2] = 90;
	FixedImageType::RegionType desiredRegion;
	desiredRegion.SetSize(  size  );
	desiredRegion.SetIndex( start );
	extractor->SetExtractionRegion( desiredRegion );
	typedef itk::ImageFileWriter< OutputSliceType > SliceWriterType;
	SliceWriterType::Pointer sliceWriter = SliceWriterType::New();
	sliceWriter->SetInput( extractor->GetOutput() );
	if( /*argc > 6*/1 )
	{
		extractor->SetInput( caster->GetOutput() );
		resampler->SetTransform( identity );
		sliceWriter->SetFileName( argv[6] );
		sliceWriter->Update();
	}
	if( /*argc > 7*/1 )
	{
		extractor->SetInput( intensityRescaler->GetOutput() );
		resampler->SetTransform( identity );
		sliceWriter->SetFileName( argv[7] );
		sliceWriter->Update();
	}
	if( /*argc > 8*/1 )
	{
		resampler->SetTransform( finalTransform );
		sliceWriter->SetFileName( argv[8] );
		sliceWriter->Update();
	}
	if( /*argc > 9*/1 )
	{
		extractor->SetInput( caster->GetOutput() );
		resampler->SetTransform( finalTransform );
		sliceWriter->SetFileName( argv[9] );
		sliceWriter->Update();
	}
	return EXIT_SUCCESS;
}