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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkScalarImageToTextureFeaturesFilter_hxx
#define itkScalarImageToTextureFeaturesFilter_hxx
#include "itkScalarImageToTextureFeaturesFilter.h"
#include "itkNeighborhood.h"
#include "itkMath.h"
namespace itk
{
namespace Statistics
{
template< typename TImage, typename THistogramFrequencyContainer >
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::ScalarImageToTextureFeaturesFilter()
{
this->SetNumberOfRequiredInputs(1);
this->SetNumberOfRequiredOutputs(1);
for ( int i = 0; i < 2; ++i )
{
this->ProcessObject::SetNthOutput( i, this->MakeOutput(i) );
}
this->m_GLCMGenerator = CooccurrenceMatrixFilterType::New();
this->m_GLCMCalculator = TextureFeaturesFilterType::New();
this->m_GLCMCalculator->SetInput( this->m_GLCMGenerator->GetOutput() );
this->m_FeatureMeans = FeatureValueVector::New();
this->m_FeatureStandardDeviations = FeatureValueVector::New();
// Set the requested features to the default value:
// {Energy, Entropy, InverseDifferenceMoment, Inertia, ClusterShade,
// ClusterProminence}
FeatureNameVectorPointer requestedFeatures = FeatureNameVector::New();
// can't directly set m_RequestedFeatures since it is const!
requestedFeatures->push_back(TextureFeaturesFilterType::Energy);
requestedFeatures->push_back(TextureFeaturesFilterType::Entropy);
requestedFeatures->push_back(TextureFeaturesFilterType::InverseDifferenceMoment);
requestedFeatures->push_back(TextureFeaturesFilterType::Inertia);
requestedFeatures->push_back(TextureFeaturesFilterType::ClusterShade);
requestedFeatures->push_back(TextureFeaturesFilterType::ClusterProminence);
this->SetRequestedFeatures(requestedFeatures);
// Set the offset directions to their defaults: half of all the possible
// directions 1 pixel away. (The other half is included by symmetry.)
// We use a neighborhood iterator to calculate the appropriate offsets.
typedef Neighborhood< typename ImageType::PixelType, ImageType::ImageDimension > NeighborhoodType;
NeighborhoodType hood;
hood.SetRadius(1);
// select all "previous" neighbors that are face+edge+vertex
// connected to the current pixel. do not include the center pixel.
unsigned int centerIndex = hood.GetCenterNeighborhoodIndex();
OffsetType offset;
OffsetVectorPointer offsets = OffsetVector::New();
for ( unsigned int d = 0; d < centerIndex; d++ )
{
offset = hood.GetOffset(d);
offsets->push_back(offset);
}
this->SetOffsets(offsets);
m_FastCalculations = false;
}
template< typename TImage, typename THistogramFrequencyContainer >
typename
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::DataObjectPointer
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >
::MakeOutput( DataObjectPointerArraySizeType itkNotUsed(idx) )
{
return FeatureValueVectorDataObjectType::New().GetPointer();
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::GenerateData(void)
{
if ( m_FastCalculations )
{
this->FastCompute();
}
else
{
this->FullCompute();
}
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::FullCompute(void)
{
size_t numOffsets = m_Offsets->size();
size_t numFeatures = m_RequestedFeatures->size();
double **features;
features = new double *[numOffsets];
for ( size_t i = 0; i < numOffsets; i++ )
{
features[i] = new double[numFeatures];
}
// For each offset, calculate each feature
typename OffsetVector::ConstIterator offsetIt;
size_t offsetNum, featureNum;
typedef typename TextureFeaturesFilterType::TextureFeatureName InternalTextureFeatureName;
for ( offsetIt = m_Offsets->Begin(), offsetNum = 0;
offsetIt != m_Offsets->End(); offsetIt++, offsetNum++ )
{
this->m_GLCMGenerator->SetOffset( offsetIt.Value() );
this->m_GLCMCalculator->Update();
typename FeatureNameVector::ConstIterator fnameIt;
for ( fnameIt = m_RequestedFeatures->Begin(), featureNum = 0;
fnameIt != m_RequestedFeatures->End(); fnameIt++, featureNum++ )
{
features[offsetNum][featureNum] = this->m_GLCMCalculator->GetFeature( (InternalTextureFeatureName)fnameIt.Value() );
}
}
// Now get the mean and deviaton of each feature across the offsets.
m_FeatureMeans->clear();
m_FeatureStandardDeviations->clear();
double *tempFeatureMeans = new double[numFeatures];
double *tempFeatureDevs = new double[numFeatures];
/*Compute incremental mean and SD, a la Knuth, "The Art of Computer
Programming, Volume 2: Seminumerical Algorithms", section 4.2.2.
Compute mean and standard deviation using the recurrence relation:
M(1) = x(1), M(k) = M(k-1) + (x(k) - M(k-1) ) / k
S(1) = 0, S(k) = S(k-1) + (x(k) - M(k-1)) * (x(k) - M(k))
for 2 <= k <= n, then
sigma = std::sqrt(S(n) / n) (or divide by n-1 for sample SD instead of
population SD).
*/
// Set up the initial conditions (k = 1)
for ( featureNum = 0; featureNum < numFeatures; featureNum++ )
{
tempFeatureMeans[featureNum] = features[0][featureNum];
tempFeatureDevs[featureNum] = 0;
}
// Run through the recurrence (k = 2 ... N)
for ( offsetNum = 1; offsetNum < numOffsets; offsetNum++ )
{
size_t k = offsetNum + 1;
for ( featureNum = 0; featureNum < numFeatures; featureNum++ )
{
double M_k_minus_1 = tempFeatureMeans[featureNum];
double S_k_minus_1 = tempFeatureDevs[featureNum];
double x_k = features[offsetNum][featureNum];
double M_k = M_k_minus_1 + ( x_k - M_k_minus_1 ) / k;
double S_k = S_k_minus_1 + ( x_k - M_k_minus_1 ) * ( x_k - M_k );
tempFeatureMeans[featureNum] = M_k;
tempFeatureDevs[featureNum] = S_k;
}
}
for ( featureNum = 0; featureNum < numFeatures; featureNum++ )
{
tempFeatureDevs[featureNum] = std::sqrt(tempFeatureDevs[featureNum] / numOffsets);
m_FeatureMeans->push_back(tempFeatureMeans[featureNum]);
m_FeatureStandardDeviations->push_back(tempFeatureDevs[featureNum]);
}
FeatureValueVectorDataObjectType *meanOutputObject =
itkDynamicCastInDebugMode< FeatureValueVectorDataObjectType * >( this->ProcessObject::GetOutput(0) );
meanOutputObject->Set(m_FeatureMeans);
FeatureValueVectorDataObjectType *standardDeviationOutputObject =
itkDynamicCastInDebugMode< FeatureValueVectorDataObjectType * >( this->ProcessObject::GetOutput(1) );
standardDeviationOutputObject->Set(m_FeatureStandardDeviations);
delete[] tempFeatureMeans;
delete[] tempFeatureDevs;
for ( size_t i = 0; i < numOffsets; i++ )
{
delete[] features[i];
}
delete[] features;
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::FastCompute(void)
{
// Compute the feature for the first offset
typename OffsetVector::ConstIterator offsetIt = m_Offsets->Begin();
this->m_GLCMGenerator->SetOffset( offsetIt.Value() );
this->m_GLCMCalculator->Update();
typedef typename TextureFeaturesFilterType::TextureFeatureName InternalTextureFeatureName;
m_FeatureMeans->clear();
m_FeatureStandardDeviations->clear();
typename FeatureNameVector::ConstIterator fnameIt;
for ( fnameIt = m_RequestedFeatures->Begin();
fnameIt != m_RequestedFeatures->End(); fnameIt++ )
{
m_FeatureMeans->push_back( this->m_GLCMCalculator->GetFeature( (InternalTextureFeatureName)fnameIt.Value() ) );
m_FeatureStandardDeviations->push_back(0.0);
}
FeatureValueVectorDataObjectType *meanOutputObject =
itkDynamicCastInDebugMode< FeatureValueVectorDataObjectType * >( this->ProcessObject::GetOutput(0) );
meanOutputObject->Set(m_FeatureMeans);
FeatureValueVectorDataObjectType *standardDeviationOutputObject =
itkDynamicCastInDebugMode< FeatureValueVectorDataObjectType * >( this->ProcessObject::GetOutput(1) );
standardDeviationOutputObject->Set(m_FeatureStandardDeviations);
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::SetInput(const ImageType *image)
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput( 0,
const_cast< ImageType * >( image ) );
m_GLCMGenerator->SetInput(image);
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::SetNumberOfBinsPerAxis(
unsigned int numberOfBins)
{
itkDebugMacro("setting NumberOfBinsPerAxis to " << numberOfBins);
m_GLCMGenerator->SetNumberOfBinsPerAxis(numberOfBins);
this->Modified();
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::SetPixelValueMinMax(PixelType min,
PixelType max)
{
itkDebugMacro("setting Min to " << min << "and Max to " << max);
m_GLCMGenerator->SetPixelValueMinMax(min, max);
this->Modified();
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::SetMaskImage(const ImageType *image)
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput( 1,
const_cast< ImageType * >( image ) );
m_GLCMGenerator->SetMaskImage(image);
}
template< typename TImage, typename THistogramFrequencyContainer >
const TImage *
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >
::GetInput() const
{
return itkDynamicCastInDebugMode< const ImageType * >( this->GetPrimaryInput() );
}
template< typename TImage, typename THistogramFrequencyContainer >
const typename
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::FeatureValueVectorDataObjectType *
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::GetFeatureMeansOutput() const
{
return itkDynamicCastInDebugMode< const FeatureValueVectorDataObjectType * >( this->ProcessObject::GetOutput(0) );
}
template< typename TImage, typename THistogramFrequencyContainer >
const typename
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::FeatureValueVectorDataObjectType *
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >
::GetFeatureStandardDeviationsOutput() const
{
return itkDynamicCastInDebugMode< const FeatureValueVectorDataObjectType * >( this->ProcessObject::GetOutput(1) );
}
template< typename TImage, typename THistogramFrequencyContainer >
const TImage *
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >
::GetMaskImage() const
{
return static_cast< const ImageType * >( this->ProcessObject::GetInput(1) );
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::SetInsidePixelValue(
PixelType insidePixelValue)
{
itkDebugMacro("setting InsidePixelValue to " << insidePixelValue);
m_GLCMGenerator->SetInsidePixelValue(insidePixelValue);
this->Modified();
}
template< typename TImage, typename THistogramFrequencyContainer >
void
ScalarImageToTextureFeaturesFilter< TImage, THistogramFrequencyContainer >::PrintSelf(std::ostream & os,
Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "RequestedFeatures: " << this->GetRequestedFeatures() << std::endl;
os << indent << "FeatureStandardDeviations: " << this->GetFeatureStandardDeviations() << std::endl;
os << indent << "FastCalculations: " << this->GetFastCalculations() << std::endl;
os << indent << "Offsets: " << this->GetOffsets() << std::endl;
os << indent << "FeatureMeans: " << this->GetFeatureMeans() << std::endl;
}
} // end of namespace Statistics
} // end of namespace itk
#endif
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