ITK
6.0.0
Insight Toolkit
Examples/RegistrationITKv4/ImageRegistration12.cxx
/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 : BeginLatex
//
// This example illustrates the use of \code{SpatialObject}s as masks for
// selecting the pixels that should contribute to the computation of Image
// Metrics. This example is almost identical to ImageRegistration6 with the
// exception that the \code{SpatialObject} masks are created and passed to the
// image metric.
//
//
// Software Guide : EndLatex
#include "
itkImageRegistrationMethodv4.h
"
#include "
itkMeanSquaresImageToImageMetricv4.h
"
#include "
itkRegularStepGradientDescentOptimizerv4.h
"
#include "
itkEuler2DTransform.h
"
#include "
itkCenteredTransformInitializer.h
"
#include "
itkImageFileReader.h
"
#include "
itkImageFileWriter.h
"
#include "
itkResampleImageFilter.h
"
#include "
itkCastImageFilter.h
"
#include "
itkSquaredDifferenceImageFilter.h
"
// Software Guide : BeginLatex
//
// The most important header in this example is the one corresponding to the
// \doxygen{ImageMaskSpatialObject} class.
//
// \index{itk::ImageMaskSpatialObject!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "
itkImageMaskSpatialObject.h
"
// Software Guide : EndCodeSnippet
//
// 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
:
using
Self
= CommandIterationUpdate;
using
Superclass
=
itk::Command
;
using
Pointer
=
itk::SmartPointer<Self>
;
itkNewMacro(
Self
);
protected
:
CommandIterationUpdate() =
default
;
public
:
using
OptimizerType =
itk::RegularStepGradientDescentOptimizerv4<double>
;
using
OptimizerPointer =
const
OptimizerType *;
void
Execute
(
itk::Object
* caller,
const
itk::EventObject
& event)
override
{
Execute
((
const
itk::Object
*)caller, event);
}
void
Execute
(
const
itk::Object
*
object
,
const
itk::EventObject
& event)
override
{
auto
optimizer = static_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(
int
argc,
char
* argv[])
{
if
(argc < 5)
{
std::cerr <<
"Missing Parameters "
<< std::endl;
std::cerr <<
"Usage: "
<< argv[0];
std::cerr <<
" fixedImageFile movingImageFile fixedImageMaskFile"
;
std::cerr <<
" outputImagefile [differenceOutputfile] "
;
std::cerr <<
" [differenceBeforeRegistration] "
<< std::endl;
return
EXIT_FAILURE;
}
constexpr
unsigned
int
Dimension
= 2;
using
PixelType = float;
using
FixedImageType =
itk::Image<PixelType, Dimension>
;
using
MovingImageType =
itk::Image<PixelType, Dimension>
;
using
TransformType =
itk::Euler2DTransform<double>
;
using
OptimizerType =
itk::RegularStepGradientDescentOptimizerv4<double>
;
using
MetricType =
itk::MeanSquaresImageToImageMetricv4<FixedImageType, MovingImageType>
;
using
RegistrationType = itk::
ImageRegistrationMethodv4<FixedImageType, MovingImageType, TransformType>;
auto
metric =
MetricType::New
();
auto
optimizer =
OptimizerType::New
();
auto
registration =
RegistrationType::New
();
registration->SetMetric(metric);
registration->SetOptimizer(optimizer);
auto
transform =
TransformType::New
();
registration->SetInitialTransform(transform);
registration->InPlaceOn();
using
FixedImageReaderType =
itk::ImageFileReader<FixedImageType>
;
using
MovingImageReaderType =
itk::ImageFileReader<MovingImageType>
;
auto
fixedImageReader =
FixedImageReaderType::New
();
auto
movingImageReader =
MovingImageReaderType::New
();
fixedImageReader->SetFileName(argv[1]);
movingImageReader->SetFileName(argv[2]);
registration->SetFixedImage(fixedImageReader->GetOutput());
registration->SetMovingImage(movingImageReader->GetOutput());
fixedImageReader->Update();
using
TransformInitializerType =
itk::CenteredTransformInitializer
<TransformType,
FixedImageType,
MovingImageType>;
auto
initializer =
TransformInitializerType::New
();
initializer->SetTransform(transform);
initializer->SetFixedImage(fixedImageReader->GetOutput());
initializer->SetMovingImage(movingImageReader->GetOutput());
initializer->MomentsOn();
initializer->InitializeTransform();
transform->SetAngle(0.0);
using
OptimizerScalesType = OptimizerType::ScalesType;
OptimizerScalesType optimizerScales(transform->GetNumberOfParameters());
const
double
translationScale = 1.0 / 1000.0;
optimizerScales[0] = 1.0;
optimizerScales[1] = translationScale;
optimizerScales[2] = translationScale;
optimizer->SetScales(optimizerScales);
optimizer->SetLearningRate(0.1);
optimizer->SetMinimumStepLength(0.001);
optimizer->SetNumberOfIterations(200);
// Create the Command observer and register it with the optimizer.
//
auto
observer =
CommandIterationUpdate::New
();
optimizer->AddObserver(itk::IterationEvent(), observer);
// Software Guide : BeginLatex
//
// Here we instantiate the type of the \doxygen{ImageMaskSpatialObject}
// using the same dimension of the images to be registered.
//
// \index{itk::ImageMaskSpatialObject!Instantiation}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using
MaskType =
itk::ImageMaskSpatialObject<Dimension>
;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Then we use the type for creating the spatial object mask that will
// restrict the registration to a reduced region of the image.
//
// \index{itk::ImageMaskSpatialObject!New}
// \index{itk::ImageMaskSpatialObject!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
auto
spatialObjectMask =
MaskType::New
();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The mask in this case is read from a binary file using the
// \code{ImageFileReader} instantiated for an \code{unsigned char} pixel
// type.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using
ImageMaskType =
itk::Image<unsigned char, Dimension>
;
using
MaskReaderType =
itk::ImageFileReader<ImageMaskType>
;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The reader is constructed and a filename is passed to it.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
auto
maskReader =
MaskReaderType::New
();
maskReader->SetFileName(argv[3]);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// As usual, the reader is triggered by invoking its \code{Update()}
// method. Since this may eventually throw an exception, the call must be
// placed in a \code{try/catch} block. Note that a full fledged application
// will place this \code{try/catch} block at a much higher level, probably
// under the control of the GUI.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
try
{
maskReader->Update();
}
catch
(
const
itk::ExceptionObject
& err)
{
std::cerr <<
"ExceptionObject caught !"
<< std::endl;
std::cerr << err << std::endl;
return
EXIT_FAILURE;
}
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The output of the mask reader is connected as input to the
// \code{ImageMaskSpatialObject}.
//
// \index{itk::ImageMaskSpatialObject!SetImage()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
spatialObjectMask->SetImage(maskReader->GetOutput());
spatialObjectMask->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Finally, the spatial object mask is passed to the image metric.
//
// \index{itk::ImageToImageMetricv4!SetFixedImageMask()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
metric->SetFixedImageMask(spatialObjectMask);
// Software Guide : EndCodeSnippet
// One level registration process without shrinking and smoothing.
//
constexpr
unsigned
int
numberOfLevels = 1;
RegistrationType::ShrinkFactorsArrayType shrinkFactorsPerLevel;
shrinkFactorsPerLevel.SetSize(1);
shrinkFactorsPerLevel[0] = 1;
RegistrationType::SmoothingSigmasArrayType smoothingSigmasPerLevel;
smoothingSigmasPerLevel.SetSize(1);
smoothingSigmasPerLevel[0] = 0;
registration->SetNumberOfLevels(numberOfLevels);
registration->SetSmoothingSigmasPerLevel(smoothingSigmasPerLevel);
registration->SetShrinkFactorsPerLevel(shrinkFactorsPerLevel);
try
{
registration->Update();
std::cout <<
"Optimizer stop condition = "
<< registration->GetOptimizer()->GetStopConditionDescription()
<< std::endl;
}
catch
(
const
itk::ExceptionObject
& err)
{
std::cerr <<
"ExceptionObject caught !"
<< std::endl;
std::cerr << err << std::endl;
return
EXIT_FAILURE;
}
OptimizerType::ParametersType finalParameters = transform->GetParameters();
const
double
finalAngle = finalParameters[0];
const
double
finalTranslationX = finalParameters[1];
const
double
finalTranslationY = finalParameters[2];
const
double
rotationCenterX =
registration->GetOutput()->Get()->GetFixedParameters()[0];
const
double
rotationCenterY =
registration->GetOutput()->Get()->GetFixedParameters()[1];
const
unsigned
int
numberOfIterations = optimizer->GetCurrentIteration();
const
double
bestValue = optimizer->GetValue();
// Print out results
//
const
double
finalAngleInDegrees = finalAngle * 45.0 / std::atan(1.0);
std::cout <<
"Result = "
<< std::endl;
std::cout <<
" Angle (radians) "
<< finalAngle << std::endl;
std::cout <<
" Angle (degrees) "
<< finalAngleInDegrees << std::endl;
std::cout <<
" Translation X = "
<< finalTranslationX << std::endl;
std::cout <<
" Translation Y = "
<< finalTranslationY << std::endl;
std::cout <<
" Fixed Center X = "
<< rotationCenterX << std::endl;
std::cout <<
" Fixed Center Y = "
<< rotationCenterY << 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 provided in
// \code{Examples/Data}, for example:
//
// \begin{itemize}
// \item \code{BrainProtonDensitySliceBorder20.png}
// \item \code{BrainProtonDensitySliceR10X13Y17.png}
// \end{itemize}
//
// The second image is the result of intentionally rotating the first
// image by $10$ degrees and shifting it $13mm$ in $X$ and $17mm$ in
// $Y$. Both images have unit-spacing and are shown in Figure
// \ref{fig:FixedMovingImageRegistration5}.
//
// The registration converges after $20$ iterations and produces the
// following results:
//
// \begin{verbatim}
//
// Angle (radians) 0.174712
// Angle (degrees) 10.0103
// Translation X = 12.4521
// Translation Y = 16.0765
//
// \end{verbatim}
//
// These values are a very close match to the true misalignments
// introduced in the moving image.
//
// Now we resample the moving image using the transform resulting from the
// registration process.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const
TransformType::MatrixType matrix = transform->GetMatrix();
const
TransformType::OffsetType offset = transform->GetOffset();
std::cout <<
"Matrix = "
<< std::endl << matrix << std::endl;
std::cout <<
"Offset = "
<< std::endl << offset << std::endl;
// Software Guide : EndCodeSnippet
using
ResampleFilterType =
itk::ResampleImageFilter<MovingImageType, FixedImageType>
;
auto
finalTransform =
TransformType::New
();
finalTransform->SetParameters(finalParameters);
finalTransform->SetFixedParameters(transform->GetFixedParameters());
auto
resample =
ResampleFilterType::New
();
resample->SetTransform(finalTransform);
resample->SetInput(movingImageReader->GetOutput());
const
FixedImageType::Pointer
fixedImage = fixedImageReader->GetOutput();
resample->SetSize(fixedImage->GetLargestPossibleRegion().GetSize());
resample->SetOutputOrigin(fixedImage->GetOrigin());
resample->SetOutputSpacing(fixedImage->GetSpacing());
resample->SetOutputDirection(fixedImage->GetDirection());
resample->SetDefaultPixelValue(100);
using
OutputPixelType =
unsigned
char;
using
OutputImageType =
itk::Image<OutputPixelType, Dimension>
;
using
CastFilterType =
itk::CastImageFilter<FixedImageType, OutputImageType>
;
using
WriterType =
itk::ImageFileWriter<OutputImageType>
;
auto
writer =
WriterType::New
();
auto
caster =
CastFilterType::New
();
writer->SetFileName(argv[4]);
caster->SetInput(resample->GetOutput());
writer->SetInput(caster->GetOutput());
writer->Update();
using
DifferenceFilterType =
itk::SquaredDifferenceImageFilter
<FixedImageType,
FixedImageType,
OutputImageType>;
auto
difference =
DifferenceFilterType::New
();
auto
writer2 =
WriterType::New
();
writer2->SetInput(difference->GetOutput());
// Compute the difference image between the
// fixed and resampled moving image.
if
(argc >= 6)
{
difference->SetInput1(fixedImageReader->GetOutput());
difference->SetInput2(resample->GetOutput());
writer2->SetFileName(argv[5]);
writer2->Update();
}
// Compute the difference image between the
// fixed and moving image before registration.
if
(argc >= 7)
{
writer2->SetFileName(argv[6]);
difference->SetInput1(fixedImageReader->GetOutput());
difference->SetInput2(movingImageReader->GetOutput());
writer2->Update();
}
return
EXIT_SUCCESS;
}
Pointer
SmartPointer< Self > Pointer
Definition:
itkAddImageFilter.h:93
itk::CastImageFilter
Casts input pixels to output pixel type.
Definition:
itkCastImageFilter.h:100
itk::SquaredDifferenceImageFilter
Implements pixel-wise the computation of squared difference.
Definition:
itkSquaredDifferenceImageFilter.h:82
itkEuler2DTransform.h
itkRegularStepGradientDescentOptimizerv4.h
itkCenteredTransformInitializer.h
itkImageFileReader.h
itk::SmartPointer< Self >
itkCastImageFilter.h
itkImageRegistrationMethodv4.h
itkMeanSquaresImageToImageMetricv4.h
itk::ImageFileReader
Data source that reads image data from a single file.
Definition:
itkImageFileReader.h:75
itk::RegularStepGradientDescentOptimizerv4
Regular Step Gradient descent optimizer.
Definition:
itkRegularStepGradientDescentOptimizerv4.h:47
itk::Command
Superclass for callback/observer methods.
Definition:
itkCommand.h:45
itk::ImageFileWriter
Writes image data to a single file.
Definition:
itkImageFileWriter.h:90
itk::Command
class ITK_FORWARD_EXPORT Command
Definition:
itkObject.h:42
itk::Command::Execute
virtual void Execute(Object *caller, const EventObject &event)=0
itk::Euler2DTransform
Euler2DTransform of a vector space (e.g. space coordinates)
Definition:
itkEuler2DTransform.h:41
itkImageFileWriter.h
itk::ExceptionObject
Standard exception handling object.
Definition:
itkExceptionObject.h:50
itkSquaredDifferenceImageFilter.h
itk::ImageMaskSpatialObject
Implementation of an image mask as spatial object.
Definition:
itkImageMaskSpatialObject.h:47
itkImageMaskSpatialObject.h
itk::MeanSquaresImageToImageMetricv4
Class implementing a mean squares metric.
Definition:
itkMeanSquaresImageToImageMetricv4.h:46
itk::ResampleImageFilter
Resample an image via a coordinate transform.
Definition:
itkResampleImageFilter.h:90
itk::Object
Base class for most ITK classes.
Definition:
itkObject.h:61
itk::Image
Templated n-dimensional image class.
Definition:
itkImage.h:88
itk::EventObject
Abstraction of the Events used to communicating among filters and with GUIs.
Definition:
itkEventObject.h:58
New
static Pointer New()
AddImageFilter
Definition:
itkAddImageFilter.h:81
itkResampleImageFilter.h
itk::GTest::TypedefsAndConstructors::Dimension2::Dimension
constexpr unsigned int Dimension
Definition:
itkGTestTypedefsAndConstructors.h:44
itkCommand.h
Superclass
BinaryGeneratorImageFilter< TInputImage1, TInputImage2, TOutputImage > Superclass
Definition:
itkAddImageFilter.h:90
itk::CenteredTransformInitializer
CenteredTransformInitializer is a helper class intended to initialize the center of rotation and the ...
Definition:
itkCenteredTransformInitializer.h:61
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