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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkAnisotropicDiffusionVesselEnhancementFunction.txx,v $
Language: C++
Date: $Date: 2007/06/20 16:03:23 $
Version: $Revision: 1.14 $
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 __itkAnisotropicDiffusionVesselEnhancementFunction_txx
#define __itkAnisotropicDiffusionVesselEnhancementFunction_txx
#include "itkAnisotropicDiffusionVesselEnhancementFunction.h"
#include "vnl/algo/vnl_symmetric_eigensystem.h"
namespace itk {
template< class TImageType >
AnisotropicDiffusionVesselEnhancementFunction< TImageType>
::AnisotropicDiffusionVesselEnhancementFunction()
{
RadiusType r;
for( unsigned int i=0 ; i < ImageDimension ; i++ )
{
r[i] = 1;
}
this->SetRadius(r);
// Dummy neighborhood.
NeighborhoodType it;
it.SetRadius( r );
// Find the center index of the neighborhood.
m_Center = it.Size() / 2;
// Get the stride length for each axis.
for(unsigned int i = 0; i < ImageDimension; i++)
{ m_xStride[i] = it.GetStride(i); }
}
template< class TImageType >
typename AnisotropicDiffusionVesselEnhancementFunction< TImageType >
::TimeStepType
AnisotropicDiffusionVesselEnhancementFunction<TImageType>
::ComputeGlobalTimeStep(void *GlobalData) const
{
/* returns the time step supplied by the user. We don't need
to use the global data supplied since we are returning a fixed value
*/
return this->GetTimeStep();
}
template< class TImageType >
typename AnisotropicDiffusionVesselEnhancementFunction< TImageType >::PixelType
AnisotropicDiffusionVesselEnhancementFunction< TImageType >
::ComputeUpdate(const NeighborhoodType &it, void *globalData,
const FloatOffsetType& offset)
{
double value = 0.0;
return (PixelType) (value);
}
template< class TImageType >
typename AnisotropicDiffusionVesselEnhancementFunction< TImageType >::PixelType
AnisotropicDiffusionVesselEnhancementFunction< TImageType >
::ComputeUpdate(const NeighborhoodType &it,
const DiffusionTensorNeighborhoodType >,
void *globalData,
const FloatOffsetType& offset)
{
unsigned int i, j;
// const ScalarValueType ZERO = NumericTraits<ScalarValueType>::Zero;
const ScalarValueType center_value = it.GetCenterPixel();
// Global data structure
GlobalDataStruct *gd = (GlobalDataStruct *)globalData;
// m_dx -> Intensity first derivative
// m_dxy -> Intensity second derivative
// m_DT_dxy -> Diffusion tensor first derivative
// Compute the first and 2nd derivative
gd->m_GradMagSqr = 1.0e-6;
for( i = 0; i < ImageDimension; i++)
{
const unsigned int positionA =
static_cast<unsigned int>( m_Center + m_xStride[i]);
const unsigned int positionB =
static_cast<unsigned int>( m_Center - m_xStride[i]);
gd->m_dx[i] = 0.5 * (it.GetPixel( positionA ) -
it.GetPixel( positionB ) );
gd->m_dxy[i][i] = it.GetPixel( positionA )
+ it.GetPixel( positionB ) - 2.0 * center_value;
for( j = i+1; j < ImageDimension; j++ )
{
const unsigned int positionAa = static_cast<unsigned int>(
m_Center - m_xStride[i] - m_xStride[j] );
const unsigned int positionBa = static_cast<unsigned int>(
m_Center - m_xStride[i] + m_xStride[j] );
const unsigned int positionCa = static_cast<unsigned int>(
m_Center + m_xStride[i] - m_xStride[j] );
const unsigned int positionDa = static_cast<unsigned int>(
m_Center + m_xStride[i] + m_xStride[j] );
gd->m_dxy[i][j] = gd->m_dxy[j][i] = 0.25 *( it.GetPixel( positionAa )
- it.GetPixel( positionBa )
- it.GetPixel( positionCa )
+ it.GetPixel( positionDa )
);
}
}
// Compute the diffusion tensor matrix first derivatives
TensorPixelType center_Tensor_value = gt.GetCenterPixel();
for( i = 0; i < ImageDimension; i++)
{
const unsigned int positionA =
static_cast<unsigned int>( m_Center + m_xStride[i]);
const unsigned int positionB =
static_cast<unsigned int>( m_Center - m_xStride[i]);
TensorPixelType positionA_Tensor_value = gt.GetPixel( positionA );
TensorPixelType positionB_Tensor_value = gt.GetPixel( positionB );
for( j = 0; j < ImageDimension; j++)
{
gd->m_DT_dxy[i][j] = 0.5 * ( positionA_Tensor_value(i,j) -
positionB_Tensor_value(i,j) );
}
}
ScalarValueType pdWrtDiffusion1;
pdWrtDiffusion1 = gd->m_DT_dxy[0][0] * gd->m_dx[0]
+ gd->m_DT_dxy[0][1] * gd->m_dx[1]
+ gd->m_DT_dxy[0][2] * gd->m_dx[2];
ScalarValueType pdWrtDiffusion2;
pdWrtDiffusion2 = gd->m_DT_dxy[1][0] * gd->m_dx[0]
+ gd->m_DT_dxy[1][1] * gd->m_dx[1]
+ gd->m_DT_dxy[1][2] * gd->m_dx[2];
ScalarValueType pdWrtDiffusion3;
pdWrtDiffusion3 = gd->m_DT_dxy[2][0] * gd->m_dx[0]
+ gd->m_DT_dxy[2][1] * gd->m_dx[1]
+ gd->m_DT_dxy[2][2] * gd->m_dx[2];
ScalarValueType pdWrtImageIntensity1;
pdWrtImageIntensity1 = center_Tensor_value(0,0) * gd->m_dxy[0][0] +
center_Tensor_value(0,1) * gd->m_dxy[0][1] +
center_Tensor_value(0,2) * gd->m_dxy[0][2];
ScalarValueType pdWrtImageIntensity2;
pdWrtImageIntensity2 = center_Tensor_value(1,0) * gd->m_dxy[1][0] +
center_Tensor_value(1,1) * gd->m_dxy[1][1] +
center_Tensor_value(1,2) * gd->m_dxy[1][2];
ScalarValueType pdWrtImageIntensity3;
pdWrtImageIntensity3 = center_Tensor_value(2,0) * gd->m_dxy[2][0] +
center_Tensor_value(2,1) * gd->m_dxy[2][1] +
center_Tensor_value(2,2) * gd->m_dxy[2][2];
ScalarValueType total;
total = pdWrtDiffusion1 + pdWrtDiffusion2 + pdWrtDiffusion3 +
pdWrtImageIntensity1 + pdWrtImageIntensity2 + pdWrtImageIntensity3;
return ( PixelType ) ( total );
}
template <class TImageType>
void
AnisotropicDiffusionVesselEnhancementFunction<TImageType>::
PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
}
} // end namespace itk
#endif
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