ITK  4.8.0 Insight Segmentation and Registration Toolkit
Examples/Filtering/BinaryMinMaxCurvatureFlowImageFilter.cxx
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// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {BinaryMinMaxCurvatureFlowImageFilterOutput.png}
// ARGUMENTS: 10 0.125 1 128
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// The \doxygen{BinaryMinMaxCurvatureFlowImageFilter} applies a variant of the
// CurvatureFlow algorithm. Which means that the speed of propagation is
// proportional to the curvature $\kappa$ of iso-contours. This filter adds
// however, the restriction that negative curvatures are only accepted in
// regions of the image having low intensities. The user should provide an
// intensity threshold over which negative curvatures are not considered for
// the propagation.
//
// In practice the algorithm do the following for each pixel. First, the
// curvature $\kappa$ is computed on the current pixel. If the computed
// curvature is null this is returned as value. Otherwise, an average of
// neighbor pixel intensities is computed and it is compared against a
// user-provided threshold. If this average is less than the threshold then
// the algorithm returns $\min(\kappa,0)$. If the average intensity is greater
// or equal than user-provided threshold, then the returned value is
// $\max(\kappa,0)$.
//
//
// I_t = F |\nabla I|
//
//
// where $F$ is defined as
//
//
// \mbox{Average} < \mbox{Threshold} \\ \max(\kappa,0) & \mbox{Average} \ge
// \mbox{Threshold} \end{array} \right.
//
//
// \index{itk::Binary\-MinMax\-Curvature\-Flow\-Image\-Filter}
//
// Software Guide : EndLatex
#include "itkImage.h"
// Software Guide : BeginLatex
//
// The first step required for using this filter is to include its header file
//
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 7 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile ";
std::cerr << "numberOfIterations timeStep stencilRadius threshold" << std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Types should be chosen for the pixels of the input and output images and
// with them the image types are instantiated.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef float InputPixelType;
typedef float OutputPixelType;
typedef itk::Image< InputPixelType, 2 > InputImageType;
typedef itk::Image< OutputPixelType, 2 > OutputImageType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The BinaryMinMaxCurvatureFlowFilter type is now instantiated using both the
// input image and the output image types. The filter is then created using
// the \code{New()} method.
//
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!instantiation}
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!New()}
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
InputImageType, OutputImageType > FilterType;
FilterType::Pointer filter = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input image can be obtained from the output of another filter. Here,
// an image reader is used as source.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
const unsigned int numberOfIterations = atoi( argv[3] );
const double timeStep = atof( argv[4] );
const double threshold = atof( argv[6] );
// Software Guide : BeginLatex
//
// The \doxygen{BinaryMinMaxCurvatureFlowImageFilter} requires the same
// parameters of the MinMaxCurvatureFlowImageFilter plus the value of the
// threshold against which the neighborhood average will be compared. The
// threshold is passed using the \code{SetThreshold()} method. Then the
// filter can be executed by invoking \code{Update()}.
//
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!Update()}
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!SetTimeStep()}
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!SetNumberOfIterations()}
// \index{itk::BinaryMinMaxCurvatureFlowImageFilter!SetThreshold()}
// \index{SetTimeStep()!itk::BinaryMinMaxCurvatureFlowImageFilter}
// \index{SetThreshold()!itk::BinaryMinMaxCurvatureFlowImageFilter}
// \index{SetNumberOfIterations()!itk::BinaryMinMaxCurvatureFlowImageFilter}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetTimeStep( timeStep );
filter->SetNumberOfIterations( numberOfIterations );
filter->SetThreshold( threshold );
filter->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Typical values for the time step are $0.125$ in $2D$ images and $0.0625$ in
// $3D$ images. The number of iterations can be usually around $10$, more
// iterations will result in further smoothing and will increase linearly
// the computing time. The radius of the stencil can be typically $1$. The
// value of the threshold should be selected according to the gray levels of
// the object of interest and the gray level of its background.
//
// Software Guide : EndLatex
typedef unsigned char WritePixelType;
typedef itk::Image< WritePixelType, 2 > WriteImageType;
OutputImageType, WriteImageType > RescaleFilterType;
RescaleFilterType::Pointer rescaler = RescaleFilterType::New();
rescaler->SetOutputMinimum( 0 );
rescaler->SetOutputMaximum( 255 );
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[2] );
rescaler->SetInput( filter->GetOutput() );
writer->SetInput( rescaler->GetOutput() );
writer->Update();
// Software Guide : BeginLatex
//
// \begin{figure}
// \center
// \includegraphics[width=0.44\textwidth]{BrainProtonDensitySlice}
// \includegraphics[width=0.44\textwidth]{BinaryMinMaxCurvatureFlowImageFilterOutput}
// \itkcaption[BinaryMinMaxCurvatureFlowImageFilter output]{Effect of the
// BinaryMinMaxCurvatureFlowImageFilter on a slice from a MRI proton density
// image of the brain.}
// \label{fig:BinaryMinMaxCurvatureFlowImageFilterInputOutput}
// \end{figure}
//
// Figure \ref{fig:BinaryMinMaxCurvatureFlowImageFilterInputOutput} illustrates
// the effect of this filter on a MRI proton density image of the brain. In
// this example the filter was run with a time step of $0.125$, $10$ iterations,
// a stencil radius of $1$ and a threshold of $128$.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}