Ошибка при запуске Affine Transformation в примере кода. & Quot;

Я скачал AffineTranformation из Wiki Example и изменил его, чтобы связать два файла DICOM. Я строю это успешно. Но когда я запускаю это. У него есть мессенджер ошибки:

terminate called after throwing an instance of 'itk::ExceptionObject'
what():  /usr/local/include/ITK-4.4/itkImageFileWriter.hxx:123:
itk::ERROR: ImageFileWriter(0x9808fd8): No filename was specified
Aborted (core dumped)

Это мой код для редактирования. Пожалуйста, помогите мне отредактировать это. Я использую новейшую версию ITK 4.3.1 для Linux

  #include "itkCastImageFilter.h"``
#include "itkEllipseSpatialObject.h"#include "itkImage.h"#include "itkImageRegistrationMethod.h"#include "itkLinearInterpolateImageFunction.h"#include "itkImageFileReader.h"#include "itkImageFileWriter.h"#include "itkMeanSquaresImageToImageMetric.h"#include "itkRegularStepGradientDescentOptimizer.h"#include "itkResampleImageFilter.h"#include "itkRescaleIntensityImageFilter.h"#include "itkSpatialObjectToImageFilter.h"#include "itkAffineTransform.h"#include "itkGDCMImageIO.h"// Software Guide : EndCodeSnippet
#include <list>
#include <fstream>
const    unsigned int    Dimension = 2;
typedef  unsigned char           PixelType;

typedef itk::Image< PixelType, Dimension >  ImageType;

static void CreateEllipseImage(ImageType::Pointer image);
static void CreateSphereImage(ImageType::Pointer image);

int main(int, char *[] )
{
//  The transform that will map the fixed image into the moving image.
typedef itk::AffineTransform< double, Dimension > TransformType;

//  An optimizer is required to explore the parameter space of the transform
//  in search of optimal values of the metric.
typedef itk::RegularStepGradientDescentOptimizer       OptimizerType;

//  The metric will compare how well the two images match each other. Metric
//  types are usually parameterized by the image types as it can be seen in
//  the following type declaration.
typedef itk::MeanSquaresImageToImageMetric<
ImageType,
ImageType >    MetricType;

//  Finally, the type of the interpolator is declared. The interpolator will
//  evaluate the intensities of the moving image at non-grid positions.
typedef itk:: LinearInterpolateImageFunction<
ImageType,
double          >    InterpolatorType;
//  The registration method type is instantiated using the types of the
//  fixed and moving images. This class is responsible for interconnecting
//  all the components that we have described so far.
typedef itk::ImageRegistrationMethod<
ImageType,
ImageType >    RegistrationType;
// Create components
MetricType::Pointer         metric        = MetricType::New();
TransformType::Pointer      transform     = TransformType::New();
OptimizerType::Pointer      optimizer     = OptimizerType::New();
InterpolatorType::Pointer   interpolator  = InterpolatorType::New();
RegistrationType::Pointer   registration  = RegistrationType::New();

// Each component is now connected to the instance of the registration method.
registration->SetMetric(        metric        );
registration->SetOptimizer(     optimizer     );
registration->SetTransform(     transform     );
registration->SetInterpolator(  interpolator  );

// Write the two synthetic inputs

typedef itk::Image< PixelType, Dimension >  FixedImageType;
typedef itk::Image< PixelType, Dimension >  MovingImageType;
// Software Guide : EndCodeSnippet

// Set up the file readers
typedef itk::ImageFileReader< FixedImageType  > FixedImageReaderType;
typedef itk::ImageFileReader< MovingImageType > MovingImageReaderType;

FixedImageReaderType::Pointer fixedImageReader   = FixedImageReaderType::New();
MovingImageReaderType::Pointer movingImageReader = MovingImageReaderType::New();

fixedImageReader->SetFileName("fix.dcm" );
movingImageReader->SetFileName( "mov.dcm" );

typedef itk::ImageFileWriter< ImageType >  WriterType;

WriterType::Pointer      fixedWriter =  WriterType::New();
//ixedWriter->SetFileName("fixed.png");
fixedWriter->SetInput( fixedImageReader->GetOutput());
fixedWriter->Update();

WriterType::Pointer      movingWriter =  WriterType::New();
// movingWriter->SetFileName("moving.png");
movingWriter->SetInput( movingImageReader->GetOutput());
movingWriter->Update();

// Set the registration inputs
registration->SetFixedImage(fixedImageReader->GetOutput());
registration->SetMovingImage(movingImageReader->GetOutput());

registration->SetFixedImageRegion(
fixedImageReader->GetOutput()->GetLargestPossibleRegion() );

//  Initialize the transform
typedef RegistrationType::ParametersType ParametersType;
ParametersType initialParameters( transform->GetNumberOfParameters() );

// rotation matrix
initialParameters[0] = 1.0;  // R(0,0)
initialParameters[1] = 0.0;  // R(0,1)
initialParameters[2] = 0.0;  // R(1,0)
initialParameters[3] = 1.0;  // R(1,1)

// translation vector
initialParameters[4] = 0.0;
initialParameters[5] = 0.0;
registration->SetInitialTransformParameters( initialParameters );

optimizer->SetMaximumStepLength( .1 ); // If this is set too high, you will get a
//"itk::ERROR: MeanSquaresImageToImageMetric(0xa27ce70): Too many samples map outside moving image buffer: 1818 / 10000" error

optimizer->SetMinimumStepLength( 0.01 );

// Set a stopping criterion
optimizer->SetNumberOfIterations( 200 );

// Connect an observer
//CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
//optimizer->AddObserver( itk::IterationEvent(), observer );

try
{
registration->Update();
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
//  The result of the registration process is an array of parameters that
//  defines the spatial transformation in an unique way. This final result is
//  obtained using the \code{GetLastTransformParameters()} method.

ParametersType finalParameters = registration->GetLastTransformParameters();
std::cout << "Final parameters: " << finalParameters << std::endl;

//  The value of the image metric corresponding to the last set of parameters
//  can be obtained with the \code{GetValue()} method of the optimizer.

const double bestValue = optimizer->GetValue();

// Print out results
//
std::cout << "Result = " << std::endl;
std::cout << " Metric value  = " << bestValue          << std::endl;

//  It is common, as the last step of a registration task, to use the
//  resulting transform to map the moving image into the fixed image space.
//  This is easily done with the \doxygen{ResampleImageFilter}.

typedef itk::ResampleImageFilter<
ImageType,
ImageType >    ResampleFilterType;

ResampleFilterType::Pointer resampler = ResampleFilterType::New();
resampler->SetInput( movingImageReader->GetOutput());

//  The Transform that is produced as output of the Registration method is
//  also passed as input to the resampling filter. Note the use of the
//  methods \code{GetOutput()} and \code{Get()}. This combination is needed
//  here because the registration method acts as a filter whose output is a
//  transform decorated in the form of a \doxygen{DataObject}. For details in
//  this construction you may want to read the documentation of the
//  \doxygen{DataObjectDecorator}.

resampler->SetTransform( registration->GetOutput()->Get() );

//  As described in Section \ref{sec:ResampleImageFilter}, the
//  ResampleImageFilter requires additional parameters to be specified, in
//  particular, the spacing, origin and size of the output image. The default
//  pixel value is also set to a distinct gray level in order to highlight
//  the regions that are mapped outside of the moving image.

resampler->SetSize( fixedImageReader->GetOutput()->GetLargestPossibleRegion().GetSize() );
resampler->SetOutputOrigin(  fixedImageReader->GetOutput()->GetOrigin() );
resampler->SetOutputSpacing( fixedImageReader->GetOutput()->GetSpacing() );
resampler->SetOutputDirection( fixedImageReader->GetOutput()->GetDirection() );
resampler->SetDefaultPixelValue( 100 );

//  The output of the filter is passed to a writer that will store the
//  image in a file. An \doxygen{CastImageFilter} is used to convert the
//  pixel type of the resampled image to the final type used by the
//  writer. The cast and writer filters are instantiated below.

typedef unsigned char OutputPixelType;
typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
typedef itk::CastImageFilter<
ImageType,
ImageType > CastFilterType;

WriterType::Pointer      writer =  WriterType::New();
CastFilterType::Pointer  caster =  CastFilterType::New();
writer->SetFileName("output.png");
caster->SetInput( resampler->GetOutput() );
writer->SetInput( caster->GetOutput()   );
writer->Update();
return EXIT_SUCCESS;
}