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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkHessianSmoothed3DToVesselnessMeasureImageFilter.txx,v $
Language: C++
Date: $Date: 2007/06/12 20:59:44 $
Version: $Revision: 1.12 $
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.
=========================================================================*/
#ifndef __itkHessianSmoothed3DToVesselnessMeasureImageFilter_txx
#define __itkHessianSmoothed3DToVesselnessMeasureImageFilter_txx
#include "itkHessianSmoothed3DToVesselnessMeasureImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
#include "vnl/vnl_math.h"
#define EPSILON 1e-03
namespace itk
{
/**
* Constructor
*/
template < typename TPixel >
HessianSmoothed3DToVesselnessMeasureImageFilter< TPixel >
::HessianSmoothed3DToVesselnessMeasureImageFilter()
{
m_Alpha = 0.5;
m_Beta = 0.5;
m_Gamma = 5.0;
m_C = 1e-5;
m_SymmetricEigenValueFilter = EigenAnalysisFilterType::New();
m_SymmetricEigenValueFilter->SetDimension( ImageDimension );
m_SymmetricEigenValueFilter->OrderEigenValuesBy(
EigenAnalysisFilterType::FunctorType::OrderByValue );
// By default, *do not* scale the vesselness measure by the largest
// eigen value
m_ScaleVesselnessMeasure = false;
}
template < typename TPixel >
void
HessianSmoothed3DToVesselnessMeasureImageFilter< TPixel >
::GenerateData()
{
itkDebugMacro(
<< "HessianSmoothed3DToVesselnessMeasureImageFilter generating data ");
m_SymmetricEigenValueFilter->SetInput( this->GetInput() );
typename OutputImageType::Pointer output = this->GetOutput();
typedef typename EigenAnalysisFilterType::OutputImageType
EigenValueImageType;
m_SymmetricEigenValueFilter->Update();
const typename EigenValueImageType::ConstPointer eigenImage =
m_SymmetricEigenValueFilter->GetOutput();
// walk the region of eigen values and get the vesselness measure
EigenValueArrayType eigenValue;
ImageRegionConstIterator<EigenValueImageType> it;
it = ImageRegionConstIterator<EigenValueImageType>(
eigenImage, eigenImage->GetRequestedRegion());
ImageRegionIterator<OutputImageType> oit;
this->AllocateOutputs();
oit = ImageRegionIterator<OutputImageType>(output,
output->GetRequestedRegion());
oit.GoToBegin();
it.GoToBegin();
while (!it.IsAtEnd())
{
// Get the eigen value
eigenValue = it.Get();
// Find the smallest eigenvalue
double smallest = vnl_math_abs( eigenValue[0] );
double Lambda1 = eigenValue[0];
for ( unsigned int i=1; i <=2; i++ )
{
if ( vnl_math_abs( eigenValue[i] ) < smallest )
{
Lambda1 = eigenValue[i];
smallest = vnl_math_abs( eigenValue[i] );
}
}
// Find the largest eigenvalue
double largest = vnl_math_abs( eigenValue[0] );
double Lambda3 = eigenValue[0];
for ( unsigned int i=1; i <=2; i++ )
{
if ( vnl_math_abs( eigenValue[i] > largest ) )
{
Lambda3 = eigenValue[i];
largest = vnl_math_abs( eigenValue[i] );
}
}
// find Lambda2 so that |Lambda1| < |Lambda2| < |Lambda3|
double Lambda2 = eigenValue[0];
for ( unsigned int i=0; i <=2; i++ )
{
if ( eigenValue[i] != Lambda1 && eigenValue[i] != Lambda3 )
{
Lambda2 = eigenValue[i];
break;
}
}
if ( Lambda2 >= 0.0 || Lambda3 >= 0.0 ||
vnl_math_abs( Lambda2) < EPSILON ||
vnl_math_abs( Lambda3 ) < EPSILON )
{
oit.Set( NumericTraits< OutputPixelType >::Zero );
}
else
{
double Lambda1Abs = vnl_math_abs( Lambda1 );
double Lambda2Abs = vnl_math_abs( Lambda2 );
double Lambda3Abs = vnl_math_abs( Lambda3 );
double Lambda1Sqr = vnl_math_sqr( Lambda1 );
double Lambda2Sqr = vnl_math_sqr( Lambda2 );
double Lambda3Sqr = vnl_math_sqr( Lambda3 );
double AlphaSqr = vnl_math_sqr( m_Alpha );
double BetaSqr = vnl_math_sqr( m_Beta );
double GammaSqr = vnl_math_sqr( m_Gamma );
double A = Lambda2Abs / Lambda3Abs;
double B = Lambda1Abs / vcl_sqrt ( vnl_math_abs( Lambda2 * Lambda3 ));
double S = vcl_sqrt( Lambda1Sqr + Lambda2Sqr + Lambda3Sqr );
double vesMeasure_1 =
( 1 - vcl_exp(-1.0*(( vnl_math_sqr(A) ) / ( 2.0 * ( AlphaSqr)))));
double vesMeasure_2 =
vcl_exp ( -1.0 * ((vnl_math_sqr( B )) / ( 2.0 * (BetaSqr))));
double vesMeasure_3 =
( 1 - vcl_exp( -1.0 * (( vnl_math_sqr( S )) / ( 2.0 * ( GammaSqr)))));
double vesMeasure_4 =
vcl_exp ( -1.0 * ( 2.0 * vnl_math_sqr( m_C )) /
( Lambda2Abs * (Lambda3Sqr)));
double vesselnessMeasure =
vesMeasure_1 * vesMeasure_2 * vesMeasure_3 * vesMeasure_4;
if( m_ScaleVesselnessMeasure )
{
oit.Set( static_cast< OutputPixelType >(
Lambda3Abs*vesselnessMeasure ) );
}
else
{
oit.Set( static_cast< OutputPixelType >( vesselnessMeasure ) );
}
}
++it;
++oit;
}
}
template < typename TPixel >
void
HessianSmoothed3DToVesselnessMeasureImageFilter< TPixel >
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Alpha: " << m_Alpha << std::endl;
os << indent << "Beta: " << m_Beta << std::endl;
os << indent << "Gamma: " << m_Gamma << std::endl;
os << indent << "C: " << m_C << std::endl;
}
} // end namespace itk
#endif
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