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iMathFunctions.hxx
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/*=========================================================================
Program: Advanced Normalization Tools
Copyright (c) ConsortiumOfANTS. All rights reserved.
See accompanying COPYING.txt or
https://github.com/stnava/ANTs/blob/master/ANTSCopyright.txt 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.
=========================================================================*/
#include "iMathFunctions.h"
#include "ReadWriteData.h"
#include "antsUtilities.h"
#include "itkAdaptiveHistogramEqualizationImageFilter.h"
#include "itkBinaryBallStructuringElement.h"
#include "itkBinaryErodeImageFilter.h"
#include "itkBinaryDilateImageFilter.h"
#include "itkBinaryMorphologicalClosingImageFilter.h"
#include "itkBinaryMorphologicalOpeningImageFilter.h"
#include "itkBinaryThresholdImageFilter.h"
#include "itkCannyEdgeDetectionImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkConnectedComponentImageFilter.h"
#include "itkDanielssonDistanceMapImageFilter.h"
#include "itkFlatStructuringElement.h"
#include "itkGradientAnisotropicDiffusionImageFilter.h"
#include "itkGradientMagnitudeRecursiveGaussianImageFilter.h"
#include "itkGrayscaleDilateImageFilter.h"
#include "itkGrayscaleErodeImageFilter.h"
#include "itkGrayscaleMorphologicalClosingImageFilter.h"
#include "itkGrayscaleMorphologicalOpeningImageFilter.h"
#include "itkIdentityTransform.h"
#include "itkIntensityWindowingImageFilter.h"
#include "itkLabelStatisticsImageFilter.h"
#include "itkLaplacianRecursiveGaussianImageFilter.h"
#include "itkLaplacianSharpeningImageFilter.h"
#include "itkMultiScaleLaplacianBlobDetectorImageFilter.h"
#include "itkNearestNeighborInterpolateImageFunction.h"
#include "itkRelabelComponentImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkSignedMaurerDistanceMapImageFilter.h"
#include "itkImageFileWriter.h"
namespace ants
{
/*
template <class ImageType>
typename ImageType::Pointer
BlobCorrespondence( typename ImageType::Pointer image, unsigned int nBlobs,
typename ImageType::Pointer itkNotUsed(image2),
double itkNotUsed(corrThresh), double itkNotUsed(radius), double itkNotUsed(distanceThresh) )
{
typedef float RealType;
// sensitive parameters are set here - begin
//RealType gradsig = 1.0; // sigma for gradient filter
unsigned int stepsperoctave = 10; // number of steps between doubling of scale
RealType minscale = std::pow( 1.0, 1.0 );
RealType maxscale = std::pow( 2.0, 10.0 );
//RealType uniqfeat_thresh = 0.01;
//RealType smallval = 1.e-2; // assumes images are normalizes in [ 0, 1 ]
//bool dosinkhorn = false;
//RealType maxradiusdiffallowed = 0.25; // IMPORTANT feature size difference
//RealType kneighborhoodval = 3; // IMPORTANT - defines how many nhood nodes to use in k-hood definition
//unsigned int radval = 20; // IMPORTANT radius for correlation
//RealType dthresh = 0.02; // IMPORTANT distance preservation threshold
// sensitive parameters are set here - end
}
*/
unsigned int morph_shape_flag( const char * shape )
{
std::string shapeStr( shape );
std::transform(shapeStr.begin(), shapeStr.end(), shapeStr.begin(), ::tolower);
unsigned int flag = 1;
if ( !shapeStr.compare("ball") )
{
flag = 1;
}
else if ( !shapeStr.compare("box") )
{
flag = 2;
}
if ( !shapeStr.compare("cross") )
{
flag = 3;
}
if ( !shapeStr.compare("annulus") )
{
flag = 4;
}
if ( !shapeStr.compare("polygon") )
{
flag = 5;
}
return flag;
}
template <class ImageType>
typename ImageType::Pointer
iMathBlobDetector( typename ImageType::Pointer image, unsigned int nBlobs )
{
typedef float RealType;
unsigned int stepsperoctave = 10; // number of steps between doubling of scale
RealType minscale = std::pow( 1.0, 1.0 );
RealType maxscale = std::pow( 2.0, 10.0 );
typedef itk::MultiScaleLaplacianBlobDetectorImageFilter<ImageType> BlobFilterType;
typename BlobFilterType::Pointer blobFilter = BlobFilterType::New();
blobFilter->SetStartT( minscale );
blobFilter->SetEndT( maxscale );
blobFilter->SetStepsPerOctave( stepsperoctave );
blobFilter->SetNumberOfBlobs( nBlobs );
blobFilter->SetInput( image );
blobFilter->Update();
typedef typename BlobFilterType::BlobRadiusImageType BlobRadiusImageType;
typename BlobRadiusImageType::Pointer labimg = blobFilter->GetBlobRadiusImage();
return( labimg );
}
template <class ImageType>
typename ImageType::Pointer
iMathCanny( typename ImageType::Pointer image,
double sigma,
double lowerThreshold,
double upperThreshold )
{
typedef typename ImageType::PixelType PixelType;
typedef itk::CannyEdgeDetectionImageFilter< ImageType, ImageType > FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetVariance( sigma );
filter->SetUpperThreshold( (PixelType) upperThreshold );
filter->SetLowerThreshold( (PixelType) lowerThreshold );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathDistanceMap( typename ImageType::Pointer image, bool useSpacing )
{
typedef itk::DanielssonDistanceMapImageFilter<ImageType, ImageType> FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->InputIsBinaryOff();
filter->SetUseImageSpacing(useSpacing);
filter->SetInput(image);
filter->Update();
return filter->GetOutput();
}
// algorithm :
// 1. get distance map of object
// 2. threshold
// 3. label connected components
// 4. label surface
// 5. if everywhere on surface is next to object then it's a hole
// 6. make sure it's not the background
template <class ImageType>
typename ImageType::Pointer
iMathFillHoles( typename ImageType::Pointer image, double holeParam )
{
if ( (holeParam < 0) || (holeParam > 2) )
{
//itk::itkExceptionMacro("FillHoles: holeParam value must lie in [0,2]");
}
typedef typename ImageType::Pointer ImagePointerType;
typedef itk::Image<int, ImageType::ImageDimension> MaskType;
typedef typename ImageType::PixelType PixelType;
typedef typename MaskType::PixelType LabelType;
const PixelType imageMax = itk::NumericTraits<PixelType>::max();
const LabelType labelMax = itk::NumericTraits<LabelType>::max();
const PixelType objectMin = 0.5;
const PixelType distanceMin = 0.001;
typedef itk::CastImageFilter<MaskType,ImageType> MaskToImage;
typedef itk::BinaryThresholdImageFilter<ImageType,MaskType> ThresholdFilterType;
typedef itk::BinaryThresholdImageFilter<MaskType,MaskType> ThresholdMaskFilterType;
typename ThresholdFilterType::Pointer threshold = ThresholdFilterType::New();
threshold->SetInput( image );
threshold->SetInsideValue(1);
threshold->SetOutsideValue(0);
threshold->SetLowerThreshold(objectMin);
threshold->SetUpperThreshold(imageMax);
typedef itk::DanielssonDistanceMapImageFilter<MaskType, ImageType> FilterType;
typename FilterType::Pointer distance = FilterType::New();
distance->InputIsBinaryOff();
distance->SetUseImageSpacing(false);
distance->SetInput(threshold->GetOutput());
typename ThresholdFilterType::Pointer dThreshold = ThresholdFilterType::New();
dThreshold->SetInput( distance->GetOutput() );
dThreshold->SetInsideValue(1);
dThreshold->SetOutsideValue(0);
dThreshold->SetLowerThreshold(distanceMin);
dThreshold->SetUpperThreshold(imageMax);
dThreshold->Update();
typedef itk::ConnectedComponentImageFilter<MaskType,MaskType> ConnectedFilterType;
typename ConnectedFilterType::Pointer connected = ConnectedFilterType::New();
connected->SetInput( dThreshold->GetOutput() );
connected->SetFullyConnected( false );
typedef itk::RelabelComponentImageFilter<MaskType, MaskType> RelabelFilterType;
typename RelabelFilterType::Pointer relabel = RelabelFilterType::New();
relabel->SetInput( connected->GetOutput() );
relabel->SetMinimumObjectSize( 0 );
relabel->Update();
if( holeParam == 2 )
{
typename ThresholdMaskFilterType::Pointer oThreshold = ThresholdMaskFilterType::New();
oThreshold->SetInput( relabel->GetOutput() );
oThreshold->SetInsideValue(1);
oThreshold->SetOutsideValue(0);
oThreshold->SetLowerThreshold(2);
oThreshold->SetUpperThreshold(labelMax);
typedef itk::AddImageFilter<MaskType,MaskType> AddFilterType;
typename AddFilterType::Pointer add = AddFilterType::New();
add->SetInput1( threshold->GetOutput() );
add->SetInput2( oThreshold->GetOutput() );
typename MaskToImage::Pointer maskToImage = MaskToImage::New();
maskToImage->SetInput( add->GetOutput() );
maskToImage->Update();
return maskToImage->GetOutput();
}
// FIXME - add filter for below -- avoid iterators in these functions
typename MaskToImage::Pointer caster = MaskToImage::New();
caster->SetInput( threshold->GetOutput() );
caster->Update();
ImagePointerType imageout = caster->GetOutput();
typedef itk::NeighborhoodIterator<MaskType> iteratorType;
typename iteratorType::RadiusType rad;
for( unsigned int j = 0; j < ImageType::ImageDimension; j++ )
{
rad[j] = 1;
}
iteratorType GHood(rad, relabel->GetOutput(), relabel->GetOutput()->GetLargestPossibleRegion() );
float maximum = relabel->GetNumberOfObjects();
// now we have the exact number of objects labeled independently
for( int lab = 2; lab <= maximum; lab++ )
{
float erat = 2;
if( holeParam <= 1 )
{
GHood.GoToBegin();
unsigned long objectedge = 0;
unsigned long backgroundedge = 0;
unsigned long totaledge = 0;
unsigned long volume = 0;
while( !GHood.IsAtEnd() )
{
typename ImageType::PixelType p = GHood.GetCenterPixel();
typename ImageType::IndexType ind2;
if( p == lab )
{
volume++;
for( unsigned int i = 0; i < GHood.Size(); i++ )
{
ind2 = GHood.GetIndex(i);
float val2 = threshold->GetOutput()->GetPixel(ind2);
if( (val2 == 1) && GHood.GetPixel(i) != lab )
{
objectedge++;
totaledge++;
}
else if( (val2 == 1) && GHood.GetPixel(i) != lab )
{
backgroundedge++;
totaledge++;
}
}
}
++GHood;
}
erat = (float)objectedge / (float)totaledge;
}
if( erat > holeParam ) // fill the hole
{
// std::cout << " Filling " << lab << " of " << maximum << std::endl;
typedef itk::ImageRegionIteratorWithIndex<MaskType> RelabelIterator;
RelabelIterator vfIter( relabel->GetOutput(),
relabel->GetOutput()->GetLargestPossibleRegion() );
for( vfIter.GoToBegin(); !vfIter.IsAtEnd(); ++vfIter )
{
if( vfIter.Get() == lab )
{
imageout->SetPixel(vfIter.GetIndex(), 1);
}
}
}
}
return imageout;
}
template <class ImageType>
typename ImageType::Pointer
iMathGC(typename ImageType::Pointer image, unsigned long radius)
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename ImageType::PixelType PixelType;
typedef itk::BinaryBallStructuringElement<PixelType, ImageDimension>
StructuringElementType;
typedef itk::GrayscaleMorphologicalClosingImageFilter< ImageType, ImageType, StructuringElementType > FilterType;
StructuringElementType structuringElement;
structuringElement.SetRadius(radius);
structuringElement.CreateStructuringElement();
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( structuringElement );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathGD(typename ImageType::Pointer image, unsigned long radius)
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename ImageType::PixelType PixelType;
typedef itk::BinaryBallStructuringElement<PixelType, ImageDimension>
StructuringElementType;
typedef itk::GrayscaleDilateImageFilter< ImageType, ImageType, StructuringElementType > FilterType;
StructuringElementType structuringElement;
structuringElement.SetRadius(radius);
structuringElement.CreateStructuringElement();
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( structuringElement );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathGE( typename ImageType::Pointer image, unsigned long radius)
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename ImageType::PixelType PixelType;
typedef itk::BinaryBallStructuringElement<PixelType, ImageDimension>
StructuringElementType;
typedef itk::GrayscaleErodeImageFilter< ImageType, ImageType, StructuringElementType > FilterType;
StructuringElementType structuringElement;
structuringElement.SetRadius(radius);
structuringElement.CreateStructuringElement();
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( structuringElement );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathGO( typename ImageType::Pointer image, unsigned long radius)
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename ImageType::PixelType PixelType;
typedef itk::BinaryBallStructuringElement<PixelType, ImageDimension>
StructuringElementType;
typedef itk::GrayscaleMorphologicalOpeningImageFilter< ImageType, ImageType, StructuringElementType > FilterType;
StructuringElementType structuringElement;
structuringElement.SetRadius(radius);
structuringElement.CreateStructuringElement();
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( structuringElement );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathGetLargestComponent( typename ImageType::Pointer image,
unsigned long smallest )
{
const unsigned int ImageDimension = ImageType::ImageDimension;
if ( image->GetNumberOfComponentsPerPixel() != 1 )
{
// NOPE
}
typedef itk::ImageRegionIteratorWithIndex<ImageType> Iterator;
// compute the voxel volume
typename ImageType::SpacingType spacing = image->GetSpacing();
float volumeelement = 1.0;
for( unsigned int i = 0; i < spacing.Size(); i++ )
{
volumeelement *= spacing[i];
}
typedef itk::Image<unsigned long, ImageDimension> LabelImageType;
typedef itk::BinaryThresholdImageFilter<ImageType, LabelImageType> ThresholdFilterType;
typedef itk::ConnectedComponentImageFilter<LabelImageType, LabelImageType> FilterType;
typedef itk::RelabelComponentImageFilter<LabelImageType, ImageType> RelabelType;
typename ThresholdFilterType::Pointer threshold = ThresholdFilterType::New();
typename FilterType::Pointer filter = FilterType::New();
typename RelabelType::Pointer relabel = RelabelType::New();
threshold->SetInput(image);
threshold->SetInsideValue(1);
threshold->SetOutsideValue(0);
threshold->SetLowerThreshold(0.25); //FIXME - why these values?
threshold->SetUpperThreshold(1.e9);
threshold->Update();
filter->SetInput(threshold->GetOutput() );
filter->SetFullyConnected( 0 );
filter->Update();
relabel->SetInput( filter->GetOutput() );
relabel->SetMinimumObjectSize( smallest );
// relabel->SetUseHistograms(true);
try
{
relabel->Update();
}
catch( itk::ExceptionObject & excep )
{
// std::cout << "Relabel: exception caught !" << std::endl;
// std::cout << excep << std::endl;
}
// WriteImage<ImageType>(relabel->GetOutput(),outname.c_str());
// return 0;
typename ImageType::Pointer Clusters = MakeNewImage<ImageType>(relabel->GetOutput(), 0);
// typename ImageType::Pointer Clusters=relabel->GetOutput();
typedef itk::ImageRegionIteratorWithIndex<ImageType> Iterator;
Iterator vfIter( relabel->GetOutput(), relabel->GetOutput()->GetLargestPossibleRegion() );
float maximum = relabel->GetNumberOfObjects();
float maxtstat = 0;
std::vector<unsigned int> histogram( (int)maximum + 1);
std::vector<float> clustersum( (int)maximum + 1);
for( int i = 0; i <= maximum; i++ )
{
histogram[i] = 0;
clustersum[i] = 0;
}
for( vfIter.GoToBegin(); !vfIter.IsAtEnd(); ++vfIter )
{
if( vfIter.Get() > 0 )
{
float vox = image->GetPixel(vfIter.GetIndex() );
histogram[(unsigned int)vfIter.Get()] = histogram[(unsigned int)vfIter.Get()] + 1;
clustersum[(unsigned int)vfIter.Get()] += vox;
if( vox > maxtstat )
{
maxtstat = vox;
}
}
}
for( vfIter.GoToBegin(); !vfIter.IsAtEnd(); ++vfIter )
{
if( vfIter.Get() > 0 )
{
Clusters->SetPixel( vfIter.GetIndex(), histogram[(unsigned int)vfIter.Get()] );
// if ( Clusters->GetPixel( vfIter.GetIndex() ) > maximgval )
// maximgval=Clusters->GetPixel( vfIter.GetIndex());
}
else
{
Clusters->SetPixel(vfIter.GetIndex(), 0);
}
}
float maximgval = 0;
for( vfIter.GoToBegin(); !vfIter.IsAtEnd(); ++vfIter )
{
if( Clusters->GetPixel( vfIter.GetIndex() ) > maximgval )
{
maximgval = Clusters->GetPixel( vfIter.GetIndex() );
}
}
for( vfIter.GoToBegin(); !vfIter.IsAtEnd(); ++vfIter )
{
if( Clusters->GetPixel( vfIter.GetIndex() ) >= maximgval )
{
image->SetPixel( vfIter.GetIndex(), 1);
}
else
{
image->SetPixel( vfIter.GetIndex(), 0);
}
}
return image;
}
template <class ImageType>
typename ImageType::Pointer
iMathGrad(typename ImageType::Pointer image, double sigma, bool normalize )
{
typedef itk::GradientMagnitudeRecursiveGaussianImageFilter<ImageType,ImageType> FilterType;
typename FilterType::Pointer grad = FilterType::New();
grad->SetInput( image );
grad->SetSigma( sigma );
grad->Update();
typename ImageType::Pointer output = grad->GetOutput();
if ( normalize )
{
typedef itk::RescaleIntensityImageFilter<ImageType, ImageType> RescaleFilterType;
typename RescaleFilterType::Pointer rescaler = RescaleFilterType::New();
rescaler->SetOutputMinimum( 0 );
rescaler->SetOutputMaximum( 1 );
rescaler->SetInput( grad->GetOutput() );
rescaler->Update();
output = rescaler->GetOutput();
}
return output;
}
template <class ImageType>
typename ImageType::Pointer
iMathHistogramEqualization( typename ImageType::Pointer image, double alpha, double beta, unsigned int r )
{
if ( image->GetNumberOfComponentsPerPixel() != 1 )
{
// NOPE
}
typedef itk::AdaptiveHistogramEqualizationImageFilter< ImageType > AdaptiveHistogramEqualizationImageFilterType;
typename AdaptiveHistogramEqualizationImageFilterType::Pointer adaptiveHistogramEqualizationImageFilter = AdaptiveHistogramEqualizationImageFilterType::New();
adaptiveHistogramEqualizationImageFilter->SetInput( image );
typename AdaptiveHistogramEqualizationImageFilterType::RadiusType radius;
radius.Fill( r );
adaptiveHistogramEqualizationImageFilter->SetRadius(radius);
adaptiveHistogramEqualizationImageFilter->SetAlpha(alpha);
adaptiveHistogramEqualizationImageFilter->SetBeta(beta);
adaptiveHistogramEqualizationImageFilter->Update( );
return adaptiveHistogramEqualizationImageFilter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathLaplacian(typename ImageType::Pointer image, double sigma, bool normalize )
{
typedef itk::LaplacianRecursiveGaussianImageFilter<ImageType,ImageType> FilterType;
typename FilterType::Pointer laplacian = FilterType::New();
laplacian->SetInput( image );
laplacian->SetSigma( sigma );
laplacian->Update();
typename ImageType::Pointer output = laplacian->GetOutput();
if ( normalize )
{
typedef itk::RescaleIntensityImageFilter<ImageType, ImageType> RescaleFilterType;
typename RescaleFilterType::Pointer rescaler = RescaleFilterType::New();
rescaler->SetOutputMinimum( 0 );
rescaler->SetOutputMaximum( 1 );
rescaler->SetInput( laplacian->GetOutput() );
rescaler->Update();
output = rescaler->GetOutput();
}
return output;
}
template <class ImageType>
typename ImageType::Pointer
iMathMaurerDistance(typename ImageType::Pointer image,
typename ImageType::PixelType foreground )
{
typedef itk::BinaryThresholdImageFilter<ImageType, ImageType> ThresholderType;
typename ThresholderType::Pointer thresholder = ThresholderType::New();
thresholder->SetInput( image);
thresholder->SetLowerThreshold( foreground );
thresholder->SetUpperThreshold( foreground );
thresholder->SetInsideValue( 1 );
thresholder->SetOutsideValue( 0 );
typedef itk::SignedMaurerDistanceMapImageFilter<ImageType, ImageType> FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( thresholder->GetOutput() );
filter->SetSquaredDistance( false );
filter->SetUseImageSpacing( true );
filter->SetInsideIsPositive( false );
filter->Update();
return filter->GetOutput();
}
//
// shape (1=ball, 2=box, 3=cross, 4=annulus, 5=polygon)
template <unsigned int ImageDimension>
typename itk::FlatStructuringElement<ImageDimension>
iMathGetFlatStructuringElement( unsigned int shape, unsigned long radius,
bool radiusIsParametric, unsigned int lines,
unsigned int thickness, bool includeCenter )
{
typedef typename itk::FlatStructuringElement<ImageDimension> ElementType;
ElementType element;
typename ElementType::RadiusType elRadius;
elRadius.Fill( radius );
switch( shape )
{
case 1:
element = ElementType::Ball(elRadius,radiusIsParametric);
break;
case 2:
element = ElementType::Box(elRadius);
break;
case 3:
element = ElementType::Cross(elRadius);
break;
case 4:
element = ElementType::Annulus(elRadius,thickness,includeCenter,radiusIsParametric);
break;
case 5:
element = ElementType::Polygon(elRadius, lines);
break;
default:
break;
}
return element;
}
template <class ImageType>
typename ImageType::Pointer
iMathMC(typename ImageType::Pointer image, unsigned long radius,
typename ImageType::PixelType closeValue, unsigned int shape,
bool radiusIsParametric, unsigned int lines,
unsigned int thickness, bool includeCenter )
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename itk::FlatStructuringElement<ImageType::ImageDimension> ElementType;
ElementType element = iMathGetFlatStructuringElement<ImageDimension>(shape,radius,radiusIsParametric,
lines,thickness,includeCenter);
typedef itk::BinaryMorphologicalClosingImageFilter< ImageType, ImageType, ElementType > FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( element );
filter->SetForegroundValue( closeValue );
//filter->SetBackgroundValue(0);
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathMD(typename ImageType::Pointer image, unsigned long radius,
typename ImageType::PixelType dilateValue, unsigned int shape,
bool radiusIsParametric, unsigned int lines,
unsigned int thickness, bool includeCenter )
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename itk::FlatStructuringElement<ImageType::ImageDimension> ElementType;
ElementType element = iMathGetFlatStructuringElement<ImageDimension>(shape,radius,radiusIsParametric,
lines,thickness,includeCenter);
typedef itk::BinaryDilateImageFilter< ImageType, ImageType, ElementType > FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( element );
filter->SetDilateValue( dilateValue );
filter->SetBackgroundValue(0);
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathME(typename ImageType::Pointer image, unsigned long radius,
typename ImageType::PixelType erodeValue, unsigned int shape,
bool radiusIsParametric, unsigned int lines,
unsigned int thickness, bool includeCenter )
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename itk::FlatStructuringElement<ImageType::ImageDimension> ElementType;
ElementType element = iMathGetFlatStructuringElement<ImageDimension>(shape,radius,radiusIsParametric,
lines,thickness,includeCenter);
typedef itk::BinaryErodeImageFilter< ImageType, ImageType, ElementType > FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( element );
filter->SetErodeValue( erodeValue );
filter->SetBackgroundValue(0);
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathMO(typename ImageType::Pointer image, unsigned long radius,
typename ImageType::PixelType openValue, unsigned int shape,
bool radiusIsParametric, unsigned int lines,
unsigned int thickness, bool includeCenter )
{
const unsigned int ImageDimension = ImageType::ImageDimension;
typedef typename itk::FlatStructuringElement<ImageType::ImageDimension> ElementType;
ElementType element = iMathGetFlatStructuringElement<ImageDimension>(shape,radius,radiusIsParametric,
lines,thickness,includeCenter);
typedef itk::BinaryMorphologicalOpeningImageFilter< ImageType, ImageType, ElementType > FilterType;
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetKernel( element );
filter->SetForegroundValue( openValue );
filter->SetBackgroundValue( 0 );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathNormalize( typename ImageType::Pointer image )
{
if ( image->GetNumberOfComponentsPerPixel() != 1 )
{
// NOPE
}
typedef typename ImageType::PixelType PixelType;
typedef itk::RescaleIntensityImageFilter<ImageType,ImageType> NormFilterType;
typename NormFilterType::Pointer normFilter = NormFilterType::New();
normFilter->SetInput( image );
normFilter->SetOutputMinimum( itk::NumericTraits<PixelType>::ZeroValue() );
normFilter->SetOutputMaximum( itk::NumericTraits<PixelType>::OneValue() );
normFilter->Update();
return normFilter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathPad( typename ImageType::Pointer image1, int padvalue )
{
typedef itk::ImageRegionIteratorWithIndex<ImageType> Iterator;
typename ImageType::SizeType size = image1->GetLargestPossibleRegion().GetSize();
typename ImageType::PointType origin2 = image1->GetOrigin();
typename ImageType::SizeType newsize = image1->GetLargestPossibleRegion().GetSize();
typename ImageType::RegionType newregion;
// determine new image size
for( unsigned int i = 0; i < ImageType::ImageDimension; i++ )
{
float dimsz = (float)size[i];
newsize[i] = (unsigned int)(dimsz + padvalue * 2);
}
newregion.SetSize(newsize);
newregion.SetIndex(image1->GetLargestPossibleRegion().GetIndex() );
typename ImageType::Pointer padimage =
AllocImage<ImageType>(newregion,
image1->GetSpacing(),
origin2,
image1->GetDirection(), 0);
typename ImageType::IndexType index;
typename ImageType::IndexType index2;
if( padvalue > 0 )
{
index.Fill(0);
index2.Fill( (unsigned int)fabs( static_cast<float>( padvalue ) ) );
}
else
{
index2.Fill(0);
index.Fill( (unsigned int)fabs( static_cast<float>( padvalue ) ) );
}
typename ImageType::PointType point1, pointpad;
image1->TransformIndexToPhysicalPoint(index, point1);
padimage->TransformIndexToPhysicalPoint(index2, pointpad);
for( unsigned int i = 0; i < ImageType::ImageDimension; i++ )
{
origin2[i] += (point1[i] - pointpad[i]);
}
padimage->SetOrigin(origin2);
Iterator iter( image1, image1->GetLargestPossibleRegion() );
for( iter.GoToBegin(); !iter.IsAtEnd(); ++iter )
{
typename ImageType::IndexType oindex = iter.GetIndex();
typename ImageType::IndexType padindex = iter.GetIndex();
bool isinside = true;
for( unsigned int i = 0; i < ImageType::ImageDimension; i++ )
{
float shifted = ( (float)oindex[i] + padvalue);
if( shifted < 0 || shifted > newsize[i] - 1 )
{
isinside = false;
}
// if (shifted < 0) shifted=0;
// padindex[i]=
}
if( isinside )
{
for( unsigned int i = 0; i < ImageType::ImageDimension; i++ )
{
float shifted = ( (float)oindex[i] + padvalue);
padindex[i] = (unsigned int)shifted;
}
padimage->SetPixel(padindex, iter.Get() );
}
}
return padimage;
}
template <class ImageType>
typename ImageType::Pointer
iMathPeronaMalik( typename ImageType::Pointer image, unsigned long nIterations,
double conductance )
{
if ( image->GetNumberOfComponentsPerPixel() != 1 )
{
// NOPE
}
typedef itk::GradientAnisotropicDiffusionImageFilter< ImageType, ImageType >
FilterType;
typedef typename FilterType::TimeStepType TimeStepType;
// Select time step size.
TimeStepType spacingsize = 0;
for( unsigned int d = 0; d < ImageType::ImageDimension; d++ )
{
TimeStepType sp = image->GetSpacing()[d];
spacingsize += sp * sp;
}
spacingsize = sqrt( spacingsize );
// FIXME - cite reason for this step
double dimPlusOne = ImageType::ImageDimension + 1;
TimeStepType mytimestep = spacingsize / std::pow( 2.0 , dimPlusOne );
TimeStepType reftimestep = 0.4 / std::pow( 2.0 , dimPlusOne );
if ( mytimestep > reftimestep )
{
mytimestep = reftimestep;
}
typename FilterType::Pointer filter = FilterType::New();
filter->SetInput( image );
filter->SetConductanceParameter( conductance ); // might need to change this
filter->SetNumberOfIterations( nIterations );
filter->SetTimeStep( mytimestep );
filter->Update();
return filter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathSharpen( typename ImageType::Pointer image )
{
if ( image->GetNumberOfComponentsPerPixel() != 1 )
{
// NOPE
}
typedef itk::LaplacianSharpeningImageFilter<ImageType, ImageType> FilterType;
typename FilterType::Pointer sharpenFilter = FilterType::New();
sharpenFilter->SetInput( image );
sharpenFilter->Update();
return sharpenFilter->GetOutput();
}
template <class ImageType>
typename ImageType::Pointer
iMathTruncateIntensity( typename ImageType::Pointer image, double lowerQ, double upperQ, int nBins,
typename itk::Image<unsigned int, ImageType::ImageDimension>::Pointer mask )
{
typedef typename ImageType::PixelType PixelType;
typedef unsigned int LabelType;
typedef itk::Image<LabelType, ImageType::ImageDimension> MaskType;
if( mask.IsNull() )
{
typedef itk::BinaryThresholdImageFilter<ImageType, MaskType> ThresholdFilterType;
typename ThresholdFilterType::Pointer thresh = ThresholdFilterType::New();
thresh->SetInput( image );
thresh->SetLowerThreshold( 1e-6 );
thresh->SetUpperThreshold( itk::NumericTraits<PixelType>::max() );
thresh->SetInsideValue(1);
thresh->SetOutsideValue(0);
thresh->Update();
mask = thresh->GetOutput();
}
typedef itk::LabelStatisticsImageFilter<ImageType, MaskType> HistogramFilterType;
typename HistogramFilterType::Pointer stats = HistogramFilterType::New();
stats->SetInput( image );
stats->SetLabelInput( mask );
stats->Update();
PixelType minValue = stats->GetMinimum( 1 );
PixelType maxValue = stats->GetMaximum( 1 );
// Hack increment by delta
if (minValue == 0)
{
minValue = (PixelType) (minValue + 1e-6);
}
if (minValue == 0)
{
minValue++;
}
stats->SetUseHistograms( true );
stats->SetHistogramParameters( nBins, minValue, maxValue );
stats->Update();
typedef typename HistogramFilterType::HistogramPointer HistogramPointer;