[Insight-users] segmentation evaluation metrics help

[abatzis at ceid.upatras.gr]

Dear Luis/All,

i want to compare two binary images(foreground->255, background->0) by use
of the appropriate metrics such as itkContourMeanDistanceImageFilter,
itkHausdorffDistanceImageFilter and itkKappaStatisticImageToImageMetric.
Unfortunately havent found the way to do so since now. Below i state some
code so as to speak in a more practical basis. If anyone has successfully
deployed these metrics, let he gives me a hint.(i just fixed the input
fragment of the code below and copied the other from the corresponding
metrics tests in itk though i dont really understand it).
Thanks in advance
Jim

#include "itkImage.h"
#include "itkImageFileReader.h"

#include "itkKappaStatisticImageToImageMetric.h"
#include "itkNearestNeighborInterpolateImageFunction.h"
#include "itkTranslationTransform.h"

#include "itkContourMeanDistanceImageFilter.h"
#include "itkContourDIrectedMeanDistanceImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkFilterWatcher.h"
#include "itkDirectedHausdorffDistanceImageFilter.h"
#include "itkHausdorffDistanceImageFilter.h"







int main( int argc, char *argv[] )	{


	if( argc < 2 )    {
			std::cerr << "Missing Parameters " << std::endl;
	    	std::cerr << "Usage: " << argv[0];
	    	std::cerr << " inputImage1  inputImage2";
	    	return 1;

    }

  typedef unsigned char PixelType;
  //typedef float Pixel2Type;
  const int ImageDimension = 3 ;

  typedef itk::Image<PixelType,ImageDimension> ImageType;
  //typedef itk::Image<Pixel2Type,ImageDimension> ImageManualType;

  typedef itk::ImageFileReader<ImageType> ReaderType;
//  typedef itk::ImageFileReader<Image2Type> ReaderType2;

  ReaderType::Pointer reader1 = ReaderType::New();
  ReaderType::Pointer reader2 = ReaderType::New();

  ImageType::Pointer image1 = ImageType::New();
  ImageType::Pointer image2 = ImageType::New();

  reader1->SetFileName(argv[1]);
  reader2->SetFileName(argv[2]);

  try		{
		reader1->Update();
		reader2->Update();
	}

	catch( itk::ExceptionObject & excep )    {
	    std::cerr << "Exception caught !" << std::endl;
	    std::cerr << excep << std::endl;
    }

  ImageType::SizeType size1, size2;
  size1 = reader1->GetOutput()->GetBufferedRegion().GetSize();
  size2 = reader2->GetOutput()->GetBufferedRegion().GetSize();


  image1->SetRegions( size1 );
  image2->SetRegions( size2 );

  image1->Allocate();
  image2->Allocate();

  image1->FillBuffer( itk::NumericTraits<PixelType>::Zero );
  image2->FillBuffer( itk::NumericTraits<PixelType>::Zero );

  typedef ImageType::RegionType RegionType;
  RegionType region1;
  RegionType region2;

  typedef ImageType::IndexType IndexType;
  IndexType index1;
  IndexType index2;
  index1 = reader1->GetOutput()->GetBufferedRegion().GetIndex();
  index2 = reader2->GetOutput()->GetBufferedRegion().GetIndex();
  //size.Fill( 20 );
  //index.Fill( 10 );
  region1.SetSize( size1 );
  region1.SetIndex( index1 );

  region2.SetSize( size2 );
  region2.SetIndex( index2 );

  itk::ImageRegionIterator<ImageType> it1( image1, region1 );
  PixelType count = itk::NumericTraits<PixelType>::Zero;
  while ( !it1.IsAtEnd() )
    {
    it1.Set( ++count );
    ++it1;
    }

  itk::ImageRegionIterator<ImageType> it2( image2, region2 );
  while ( !it2.IsAtEnd() )
    {
    it2.Set( 7.2 );
    ++it2;
    }
typedef itk::ContourDirectedMeanDistanceImageFilter<ImageType,ImageType>
FilterType1;   //ContourDirectedMeanDistance(im1,im2)
  FilterType1::Pointer filter1 = FilterType1::New();
  FilterWatcher watcher1(filter1, "filter");

  filter1->SetInput1( image1 );
  filter1->SetInput2( image2 );
  filter1->Update();
  filter1->Print( std::cout );

   FilterType1::RealType distance1 =
filter1->GetContourDirectedMeanDistance();
   std::cout << " Computed distance1: " << distance1 << std::endl;



  typedef itk::ContourDirectedMeanDistanceImageFilter<ImageType,ImageType>
 FilterType2;  //ContourDirectedMeanDistance(im2,im1)
  FilterType2::Pointer filter2 = FilterType2::New();
  FilterWatcher watcher2(filter2, "filter");
  filter2->SetInput1( image2 );
  filter2->SetInput2( image1 );
  filter2->Update();

  FilterType2::RealType distance2 =
filter2->GetContourDirectedMeanDistance();
  std::cout << " Computed distance2: " << distance2 << std::endl;

return EXIT_SUCCESS;

}