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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: SpatialObjectToImageStatisticsCalculator.cxx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
// Software Guide : BeginLatex
//
// \index{itk::Spatial\-Object\-To\-Image\-Statistics\-Calculator}
// This example describes how to use the
// \doxygen{SpatialObjectToImageStatisticsCalculator} to compute statistics
// of an \doxygen{Image} only in a region defined inside a given \doxygen{SpatialObject}.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkSpatialObjectToImageStatisticsCalculator.h"
// Software Guide : EndCodeSnippet
#include "itkImage.h"
#include "itkEllipseSpatialObject.h"
#include "itkRandomImageSource.h"
int main(int, char * [] )
{
// Software Guide : BeginLatex
// We first create a test image using the \doxygen{RandomImageSource}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::Image<unsigned char,2> ImageType;
typedef itk::RandomImageSource<ImageType> RandomImageSourceType;
RandomImageSourceType::Pointer randomImageSource = RandomImageSourceType::New();
ImageType::SizeValueType size[2];
size[0] = 10;
size[1] = 10;
randomImageSource->SetSize(size);
randomImageSource->Update();
ImageType::Pointer image = randomImageSource->GetOutput();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// Next we create an \doxygen{EllipseSpatialObject} with a radius of 2.
// We also move the ellipse to the center of the image by increasing
// the offset of the IndexToObjectTransform.
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::EllipseSpatialObject<2> EllipseType;
EllipseType::Pointer ellipse = EllipseType::New();
ellipse->SetRadius(2);
EllipseType::VectorType offset;
offset.Fill(5);
ellipse->GetIndexToObjectTransform()->SetOffset(offset);
ellipse->ComputeObjectToParentTransform();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// Then we can create the \doxygen{SpatialObjectToImageStatisticsCalculator}
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
typedef itk::SpatialObjectToImageStatisticsCalculator<
ImageType, EllipseType > CalculatorType;
CalculatorType::Pointer calculator = CalculatorType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// We pass a pointer to the image to the calculator.
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
calculator->SetImage(image);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// And we also pass the SpatialObject. The statistics will be computed inside the SpatialObject
// (Internally the calculator is using the \code{IsInside()} function).
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
calculator->SetSpatialObject(ellipse);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// At the end we trigger the computation via the \code{Update()} function and we
// can retrieve the mean and the covariance matrix using \code{GetMean()} and \code{GetCovarianceMatrix()}
// respectively.
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
calculator->Update();
std::cout << "Sample mean = " << calculator->GetMean() << std::endl ;
std::cout << "Sample covariance = " << calculator->GetCovarianceMatrix();
// Software Guide : EndCodeSnippet
return EXIT_SUCCESS;
}
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