在示例代码中运行仿射转换时出错。

我从Wiki Example下载了affinetransformation，并将其修改为仿射两个DICOM文件。我成功地建造了它。但是当我运行它时。它有一个错误消息:

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)

  #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;
}