[Insight-users] combining output from segmentation with label map attributes using Gaetan Lehmann's paper: "Label object representation and manipulation with ITK"
John Drozd
john.drozd at gmail.com
Tue Dec 8 17:30:42 EST 2009
Hi again,
I reverted to using an antiquated "RelabelComponentImageFilter.h" header to
get the volume of the ventricles, *but is there a way to get the physical
size using a non-antiquated currently used header?*
I used:
//ADDED PER WEB PAGE
//
http://old.nabble.com/Labeling-an-image-and-displaying-results-with-distinguished-levels-of-gray-colors-td26623991.html
typedef itk::ConnectedComponentImageFilter <OutputImageType,
OutputImageType> LabelType2;
typedef itk::RelabelComponentImageFilter <OutputImageType,
OutputImageType> RelabelType;
LabelType2::Pointer labeler = LabelType2::New();
RelabelType::Pointer relabeler = RelabelType::New();
labeler->SetInput(caster->GetOutput());
labeler->Update();
relabeler->SetInput(labeler->GetOutput());
relabeler->Update();
for (unsigned int i=0; i<relabeler->GetNumberOfObjects(); i++)
{
std::cout<<"Number of pixel for object "<<i<<":
"<<relabeler->GetSizeOfObjectsInPixels()[i]<<std::endl;
std::cout<<"Physical size for object "<<i<<":
"<<relabeler->GetSizeOfObjectsInPhysicalUnits()[i]<<std::endl;
}
//END OF ADDED CODE
This gave me a ventricle size of
Number of pixel for object 0: 22129
Physical size for object 0: 23901
When I created a label map using the gui in 3DSlicer, I got a similar size
but not exactly the same size:
Number of pixel for object 0: 22130
Physical size for object 0: 23901.284681
Below is the updated code:
/*
to run type:
./ConnectedThresholdImageFilter correctedsubject5.dcm outsubject5.dcm 103
142 95 17100 17300
*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#ifdef __BORLANDC__
#define ITK_LEAN_AND_MEAN
#endif
#include "itkConnectedThresholdImageFilter.h"
#include "itkImage.h"
#include "itkCastImageFilter.h"
#include "itkCurvatureFlowImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkGDCMImageIO.h"
#include "itkVersion.h"
#include "itkOrientedImage.h"
#include "itkMinimumMaximumImageFilter.h"
#include "itkGDCMImageIO.h"
#include "itkGDCMSeriesFileNames.h"
#include "itkNumericSeriesFileNames.h"
#include "itkImageSeriesReader.h"
#include "itkImageSeriesWriter.h"
#include "itkResampleImageFilter.h"
#include "itkShiftScaleImageFilter.h"
#include "itkIdentityTransform.h"
#include "itkLinearInterpolateImageFunction.h"
#include <itksys/SystemTools.hxx>
#include "gdcm/src/gdcmFile.h"
#include "gdcm/src/gdcmUtil.h"
#include <string>
//added per attribute_values.cxx
#include "itkImageFileReader.h"
#include "itkShapeLabelObject.h"
//#include "itkStatisticsLabelObject.h"
#include "itkLabelMap.h"
#include "itkBinaryImageToShapeLabelMapFilter.h"
//#include "itkBinaryImageToStatisticsLabelMapFilter.h"
//ADDED PER WEB PAGE
//
http://old.nabble.com/Labeling-an-image-and-displaying-results-with-distinguished-levels-of-gray-colors-td26623991.html
#include "itkConnectedComponentImageFilter.h"
#include "itkRelabelComponentImageFilter.h"
//END OF ADDED CODE
//end of added code
int main( int argc, char *argv[])
{
if( argc < 7 )
{
std::cerr << "Missing Parameters " << std::endl;
std::cerr << "Usage: " << argv[0];
std::cerr << " inputImage outputImage seedX seedY seedZ lowerThreshold
upperThreshold" << std::endl;
return 1;
}
typedef float InternalPixelType;
const unsigned int Dimension = 3;
typedef itk::Image< InternalPixelType, Dimension > InternalImageType;
typedef signed short OutputPixelType;
typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
typedef itk::Image< float, Dimension > OutputImageType2;
typedef itk::CastImageFilter< InternalImageType, OutputImageType >
CastingFilterType;
CastingFilterType::Pointer caster = CastingFilterType::New();
const unsigned int ImageDimension = 3;
typedef signed short PixelType;
typedef itk::Image< PixelType, ImageDimension > FixedImageType;
typedef itk::Image< float, ImageDimension > FloatImageType;
typedef itk::ImageFileReader< FixedImageType > ReaderType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
typedef itk::ImageFileWriter< FloatImageType > WriterType2;
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
WriterType2::Pointer writer2 = WriterType2::New();
typedef itk::GDCMImageIO ImageIOTypefixed;
ImageIOTypefixed::Pointer gdcmImageIOfixed = ImageIOTypefixed::New();
reader->SetImageIO( gdcmImageIOfixed );
typedef itk::GDCMImageIO ImageIOTypefixed2;
ImageIOTypefixed2::Pointer gdcmImageIOfixed2 = ImageIOTypefixed2::New();
reader->SetFileName( argv[1] );
reader->Update();
typedef itk::CurvatureFlowImageFilter< InternalImageType,
InternalImageType >
CurvatureFlowImageFilterType;
CurvatureFlowImageFilterType::Pointer smoothing =
CurvatureFlowImageFilterType::New();
typedef itk::ConnectedThresholdImageFilter< InternalImageType,
InternalImageType > ConnectedFilterType;
ConnectedFilterType::Pointer connectedThreshold =
ConnectedFilterType::New();
typedef signed short InputAPixelType;
typedef float OutputBPixelType;
typedef itk::Image< InputAPixelType, 3 > InputAImageType;
typedef itk::Image< OutputBPixelType, 3 > OutputBImageType;
typedef itk::CastImageFilter< InputAImageType, OutputBImageType >
CastFilterType;
CastFilterType::Pointer castFilter = CastFilterType::New();
castFilter->SetInput( reader->GetOutput() );
connectedThreshold->SetInput( castFilter->GetOutput() );
caster->SetInput( connectedThreshold->GetOutput() );
smoothing->SetNumberOfIterations( 20 ); //was 5
smoothing->SetTimeStep( 0.125 );
const InternalPixelType lowerThreshold = atof( argv[6] );
const InternalPixelType upperThreshold = atof( argv[7] );
connectedThreshold->SetLower( lowerThreshold );
connectedThreshold->SetUpper( upperThreshold );
connectedThreshold->SetReplaceValue( 255 );
InternalImageType::IndexType index;
index[0] = atoi( argv[3] );
index[1] = atoi( argv[4] );
//added
index[2] = atoi( argv[5] );
std::cout << index << std::endl;
// Software Guide : BeginCodeSnippet
connectedThreshold->SetSeed( index );
//obtain a 5 x 5 bounding region of seeds
int ii, jj, kk;
ii = index[0];
jj = index[1];
kk = index[2];
for (int i = ii; i < ii + 5; i++)
for (int j = jj; j < jj + 5; j++)
for (int k = kk; k < kk + 5; k++)
{
index[0] = i;
index[1] = j;
index[2] = k;
connectedThreshold->AddSeed( index );
}
for (int i = ii; i > ii - 5; i--)
for (int j = jj; j > jj - 5; j--)
for (int k = kk; k > kk - 5; k--)
{
index[0] = i;
index[1] = j;
index[2] = k;
connectedThreshold->AddSeed( index );
}
connectedThreshold->Print(std::cout,17100);
typedef itk::MetaDataDictionary DictionaryType;
DictionaryType inputdict = reader->GetMetaDataDictionary();
writer->SetMetaDataDictionary( inputdict );
writer->SetFileName( argv[2] );
//added per attribute_values.cxx
// define the object type. Here the ShapeLabelObject type
// is chosen in order to read some attribute related to the shape
// of the objects (by opposition to the content of the object, with
// the StatisticsLabelObejct).
typedef unsigned long LabelType;
typedef itk::ShapeLabelObject< LabelType, 3 > LabelObjectType;
typedef itk::LabelMap< LabelObjectType > LabelMapType;
// convert the image in a collection of objects
typedef itk::BinaryImageToLabelMapFilter< OutputImageType, LabelMapType >
ConverterType;
ConverterType::Pointer converter = ConverterType::New();
//ADDED after email
connectedThreshold->Update();
//END OF ADDED code
//ADDED PER WEB PAGE
//
http://old.nabble.com/Labeling-an-image-and-displaying-results-with-distinguished-levels-of-gray-colors-td26623991.html
typedef itk::ConnectedComponentImageFilter <OutputImageType,
OutputImageType> LabelType2;
typedef itk::RelabelComponentImageFilter <OutputImageType,
OutputImageType> RelabelType;
LabelType2::Pointer labeler = LabelType2::New();
RelabelType::Pointer relabeler = RelabelType::New();
labeler->SetInput(caster->GetOutput());
labeler->Update();
relabeler->SetInput(labeler->GetOutput());
relabeler->Update();
for (unsigned int i=0; i<relabeler->GetNumberOfObjects(); i++)
{
std::cout<<"Number of pixel for object "<<i<<":
"<<relabeler->GetSizeOfObjectsInPixels()[i]<<std::endl;
std::cout<<"Physical size for object "<<i<<":
"<<relabeler->GetSizeOfObjectsInPhysicalUnits()[i]<<std::endl;
}
//END OF ADDED CODE
//converter->SetInput( connectedThreshold->GetOutput() );
converter->SetInput( relabeler->GetOutput() );
//converter->SetForegroundValue( atoi(argv[2]) );
//converter->SetForegroundValue( 255 );
// valuate the attributes with the dedicated filter: ShapeLabelMapFilter
typedef itk::ShapeLabelMapFilter< LabelMapType > ShapeFilterType;
ShapeFilterType::Pointer shape = ShapeFilterType::New();
shape->SetInput( converter->GetOutput() );
shape->Update();
// then we can read the attribute values we're interested in. The
BinaryImageToShapeLabelMapFilter
// produce consecutive labels, so we can use a for loop and
GetLabelObject() method to retrieve
// the label objects. If the labels are not consecutive, the
GetNthLabelObject() method must be
// use instead of GetLabelObject(), or an iterator on the label object
container of the label map.
LabelMapType::Pointer labelMap = shape->GetOutput();
std::cout << "Number of label objects = " <<
labelMap->GetNumberOfLabelObjects() << std::endl;
for( unsigned int label=1; label<=labelMap->GetNumberOfLabelObjects();
label++ )
{
// we don't need a SmartPointer of the label object here, because the
reference is kept in
// in the label map.
const LabelObjectType * labelObject = labelMap->GetLabelObject( label );
std::cout << label << "\t" << labelObject->GetPhysicalSize() << "\t" <<
labelObject->GetCentroid() << std::endl;
}
writer->SetInput( caster->GetOutput() );
try
{
writer->Update();
}
catch( itk::ExceptionObject & excep )
{
std::cerr << "Exception caught !" << std::endl;
std::cerr << excep << std::endl;
}
std::cout << "output from reader->GetOutput()->GetDirection()" <<
std::endl;
std::cout << reader->GetOutput()->GetDirection() << std::endl;
std::cout << "output from castFilter->GetOutput()->GetDirection()" <<
std::endl;
std::cout << castFilter->GetOutput()->GetDirection() << std::endl;
std::cout << "output from connectedThreshold->GetOutput()->GetDirection()"
<< std::endl;
std::cout << connectedThreshold->GetOutput()->GetDirection() << std::endl;
std::cout << "output from caster->GetOutput()->GetDirection()" <<
std::endl;
std::cout << caster->GetOutput()->GetDirection() << std::endl;
return 0;
}
and output:
[jdrozd at trumpetConnectedThresholdImageFilter_and_BinaryImageToStatisticsLabelMapFilter]$
make
Scanning dependencies of target
ConnectedThresholdImageFilter
[100%] Building CXX object
CMakeFiles/ConnectedThresholdImageFilter.dir/ConnectedThresholdImageFilter.o
In file included from
/usr/lib/gcc/x86_64-redhat-linux/4.3.2/../../../../include/c++/4.3.2/ext/hash_map:64,
from
/trumpet/downloads/3DSlicerDec22009/Slicer3-lib/Insight/Code/Common/itk_hash_map.h:69,
from
/trumpet/downloads/3DSlicerDec22009/Slicer3-lib/Insight/Code/BasicFilters/itkRelabelComponentImageFilter.txx:25,
from
/trumpet/downloads/3DSlicerDec22009/Slicer3-lib/Insight/Code/BasicFilters/itkRelabelComponentImageFilter.h:298,
from
/trumpet/downloads/ConnectedThresholdImageFilter_and_BinaryImageToStatisticsLabelMapFilter_Plugin/ConnectedThresholdImageFilter_and_BinaryImageToStatisticsLabelMapFilter/ConnectedThresholdImageFilter.cxx:65:
/usr/lib/gcc/x86_64-redhat-linux/4.3.2/../../../../include/c++/4.3.2/backward/backward_warning.h:33:2:
warning: #warning This file includes at least one deprecated or antiquated
header which may be removed without further notice at a future date. Please
use a non-deprecated interface with equivalent functionality instead. For a
listing of replacement headers and interfaces, consult the file
backward_warning.h. To disable this warning use -Wno-deprecated.
Linking CXX executable
ConnectedThresholdImageFilter
[100%] Built target
ConnectedThresholdImageFilter
[jdrozd at trumpetConnectedThresholdImageFilter_and_BinaryImageToStatisticsLabelMapFilter]$
./ConnectedThresholdImageFilter correctedsubject5.dcm outsubject5.dcm 103
142 95 17100
17300
[103, 142,
95]
��H��H�}�H�U�H��9(ConnectedThresholdImageFilter
(0xe37580)
RTTI typeinfo:
itk::ConnectedThresholdImageFilter<itk::Image<float, 3u>, itk::Image<float,
3u> >
Reference Count:
1
Modified Time:
376
Debug:
Off
Observers:
none
Number Of Required Inputs:
1
Number Of Required Outputs:
1
Number Of Threads:
8
ReleaseDataFlag:
Off
ReleaseDataBeforeUpdateFlag:
Off
Input 0:
(0xe49e50)
Input 1:
(0xe399b0)
Input 2:
(0xe37980)
Output 0:
(0xe376a0)
AbortGenerateData:
Off
Progress:
0
Multithreader:
RTTI typeinfo:
itk::MultiThreader
Reference Count:
1
Modified Time:
82
Debug:
Off
Observers:
none
Thread Count: 8
Global Maximum Number Of Threads:
128
Global Default Number Of Threads: 8
Upper: 3.40282e+38
Lower: -3.40282e+38
ReplaceValue: 255
Connectivity: 0
Number of pixel for object 0: 22129
Physical size for object 0: 23901
Number of pixel for object 1: 1
Physical size for object 1: 1.08004
Number of label objects = 0
output from reader->GetOutput()->GetDirection()
0 0 1
0 1 0
-1 0 0
output from castFilter->GetOutput()->GetDirection()
0 0 1
0 1 0
-1 0 0
output from connectedThreshold->GetOutput()->GetDirection()
0 0 1
0 1 0
-1 0 0
output from caster->GetOutput()->GetDirection()
0 0 1
0 1 0
-1 0 0
[jdrozd at trumpetConnectedThresholdImageFilter_and_BinaryImageToStatisticsLabelMapFilter]$
On Tue, Dec 8, 2009 at 2:38 PM, John Drozd <john.drozd at gmail.com> wrote:
> Hello,
>
> I have segmented the ventricles from an image using a connected threshold
> image filter.
> I then tried to convert my outputted segmentation to a label map filter and
> then to get the label's attributes.
>
> I am using parts of the example code attribute_values.cxx that is described
> in section 9.4 of
> Gaetan Lehmann's paper: "Label object representation and manipulation with
> ITK"
>
> My problem is that my code is telling me that the number of labels is 0.
> How do I apply a label to my segmented ventricles?
>
> Below is my code:
>
> /*
> to run type:
> ./ConnectedThresholdImageFilter correctedsubject5.dcm outsubject5.dcm 103
> 142 95 17100 17300
> */
>
> #if defined(_MSC_VER)
> #pragma warning ( disable : 4786 )
> #endif
>
> #ifdef __BORLANDC__
> #define ITK_LEAN_AND_MEAN
> #endif
>
>
> #include "itkConnectedThresholdImageFilter.h"
>
> #include "itkImage.h"
> #include "itkCastImageFilter.h"
>
> #include "itkCurvatureFlowImageFilter.h"
>
> #include "itkImageFileReader.h"
> #include "itkImageFileWriter.h"
>
> #include "itkGDCMImageIO.h"
>
> #include "itkVersion.h"
>
> #include "itkOrientedImage.h"
> #include "itkMinimumMaximumImageFilter.h"
>
> #include "itkGDCMImageIO.h"
> #include "itkGDCMSeriesFileNames.h"
> #include "itkNumericSeriesFileNames.h"
>
> #include "itkImageSeriesReader.h"
> #include "itkImageSeriesWriter.h"
>
> #include "itkResampleImageFilter.h"
> #include "itkShiftScaleImageFilter.h"
>
> #include "itkIdentityTransform.h"
> #include "itkLinearInterpolateImageFunction.h"
>
> #include <itksys/SystemTools.hxx>
>
> #include "gdcm/src/gdcmFile.h"
> #include "gdcm/src/gdcmUtil.h"
>
> #include <string>
>
> //added per attribute_values.cxx
> #include "itkImageFileReader.h"
>
> #include "itkShapeLabelObject.h"
> //#include "itkStatisticsLabelObject.h"
>
> #include "itkLabelMap.h"
>
> #include "itkBinaryImageToShapeLabelMapFilter.h"
> //#include "itkBinaryImageToStatisticsLabelMapFilter.h"
>
> //end of added code
>
> int main( int argc, char *argv[])
> {
> if( argc < 7 )
> {
> std::cerr << "Missing Parameters " << std::endl;
> std::cerr << "Usage: " << argv[0];
> std::cerr << " inputImage outputImage seedX seedY seedZ lowerThreshold
> upperThreshold" << std::endl;
>
> return 1;
> }
>
> typedef float InternalPixelType;
>
> const unsigned int Dimension = 3;
>
> typedef itk::Image< InternalPixelType, Dimension > InternalImageType;
>
> typedef signed short OutputPixelType;
>
> typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
> typedef itk::Image< float, Dimension > OutputImageType2;
> typedef itk::CastImageFilter< InternalImageType, OutputImageType >
> CastingFilterType;
> CastingFilterType::Pointer caster = CastingFilterType::New();
>
> const unsigned int ImageDimension = 3;
> typedef signed short PixelType;
>
> typedef itk::Image< PixelType, ImageDimension > FixedImageType;
> typedef itk::Image< float, ImageDimension > FloatImageType;
>
> typedef itk::ImageFileReader< FixedImageType > ReaderType;
> typedef itk::ImageFileWriter< OutputImageType > WriterType;
> typedef itk::ImageFileWriter< FloatImageType > WriterType2;
>
> ReaderType::Pointer reader = ReaderType::New();
> WriterType::Pointer writer = WriterType::New();
> WriterType2::Pointer writer2 = WriterType2::New();
>
> typedef itk::GDCMImageIO ImageIOTypefixed;
> ImageIOTypefixed::Pointer gdcmImageIOfixed = ImageIOTypefixed::New();
> reader->SetImageIO( gdcmImageIOfixed );
>
> typedef itk::GDCMImageIO ImageIOTypefixed2;
> ImageIOTypefixed2::Pointer gdcmImageIOfixed2 = ImageIOTypefixed2::New();
>
> reader->SetFileName( argv[1] );
>
> reader->Update();
>
> typedef itk::CurvatureFlowImageFilter< InternalImageType,
> InternalImageType >
> CurvatureFlowImageFilterType;
>
> CurvatureFlowImageFilterType::Pointer smoothing =
> CurvatureFlowImageFilterType::New();
>
> typedef itk::ConnectedThresholdImageFilter< InternalImageType,
> InternalImageType >
> ConnectedFilterType;
>
> ConnectedFilterType::Pointer connectedThreshold =
> ConnectedFilterType::New();
>
> typedef signed short InputAPixelType;
> typedef float OutputBPixelType;
>
> typedef itk::Image< InputAPixelType, 3 > InputAImageType;
> typedef itk::Image< OutputBPixelType, 3 > OutputBImageType;
>
> typedef itk::CastImageFilter< InputAImageType, OutputBImageType >
> CastFilterType;
>
> CastFilterType::Pointer castFilter = CastFilterType::New();
>
>
> castFilter->SetInput( reader->GetOutput() );
>
>
> connectedThreshold->SetInput( castFilter->GetOutput() );
>
> caster->SetInput( connectedThreshold->GetOutput() );
>
>
> smoothing->SetNumberOfIterations( 20 ); //was 5
> smoothing->SetTimeStep( 0.125 );
>
> const InternalPixelType lowerThreshold = atof( argv[6] );
> const InternalPixelType upperThreshold = atof( argv[7] );
>
> connectedThreshold->SetLower( lowerThreshold );
> connectedThreshold->SetUpper( upperThreshold );
>
> connectedThreshold->SetReplaceValue( 255 );
>
> InternalImageType::IndexType index;
>
> index[0] = atoi( argv[3] );
> index[1] = atoi( argv[4] );
>
> //added
> index[2] = atoi( argv[5] );
>
> std::cout << index << std::endl;
>
> // Software Guide : BeginCodeSnippet
> connectedThreshold->SetSeed( index );
>
> //obtain a 5 x 5 bounding region of seeds
> int ii, jj, kk;
>
> ii = index[0];
> jj = index[1];
> kk = index[2];
>
> for (int i = ii; i < ii + 5; i++)
> for (int j = jj; j < jj + 5; j++)
> for (int k = kk; k < kk + 5; k++)
> {
>
> index[0] = i;
> index[1] = j;
> index[2] = k;
> connectedThreshold->AddSeed( index );
> }
>
> for (int i = ii; i > ii - 5; i--)
> for (int j = jj; j > jj - 5; j--)
> for (int k = kk; k > kk - 5; k--)
> {
>
> index[0] = i;
> index[1] = j;
> index[2] = k;
> connectedThreshold->AddSeed( index );
> }
>
> connectedThreshold->Print(std::cout,17100);
>
> typedef itk::MetaDataDictionary DictionaryType;
>
> DictionaryType inputdict = reader->GetMetaDataDictionary();
>
> writer->SetMetaDataDictionary( inputdict );
>
> writer->SetFileName( argv[2] );
>
> //added per attribute_values.cxx
>
> // define the object type. Here the ShapeLabelObject type
> // is chosen in order to read some attribute related to the shape
> // of the objects (by opposition to the content of the object, with
> // the StatisticsLabelObejct).
> typedef unsigned long LabelType;
>
> typedef itk::ShapeLabelObject< LabelType, 3 > LabelObjectType;
>
> typedef itk::LabelMap< LabelObjectType > LabelMapType;
>
> // convert the image in a collection of objects
> typedef itk::BinaryImageToLabelMapFilter< InternalImageType, LabelMapType
> > ConverterType;
>
> ConverterType::Pointer converter = ConverterType::New();
>
> converter->SetInput( connectedThreshold->GetOutput() );
>
> //converter->SetForegroundValue( atoi(argv[2]) );
> //converter->SetForegroundValue( 255 );
>
> // valuate the attributes with the dedicated filter: ShapeLabelMapFilter
>
> typedef itk::ShapeLabelMapFilter< LabelMapType > ShapeFilterType;
> ShapeFilterType::Pointer shape = ShapeFilterType::New();
> shape->SetInput( converter->GetOutput() );
>
> shape->Update();
>
>
> // then we can read the attribute values we're interested in. The
> BinaryImageToShapeLabelMapFilter
> // produce consecutive labels, so we can use a for loop and
> GetLabelObject() method to retrieve
> // the label objects. If the labels are not consecutive, the
> GetNthLabelObject() method must be
> // use instead of GetLabelObject(), or an iterator on the label object
> container of the label map.
> LabelMapType::Pointer labelMap = shape->GetOutput();
>
> std::cout << "Number of label objects = " <<
> labelMap->GetNumberOfLabelObjects() << std::endl;
>
>
> for( unsigned int label=1; label<=labelMap->GetNumberOfLabelObjects();
> label++ )
> {
> // we don't need a SmartPointer of the label object here, because the
> reference is kept in
> // in the label map.
> const LabelObjectType * labelObject = labelMap->GetLabelObject( label
> );
> std::cout << label << "\t" << labelObject->GetPhysicalSize() << "\t" <<
> labelObject->GetCentroid() << std::endl;
> }
>
> writer->SetInput( caster->GetOutput() );
>
> try
> {
> writer->Update();
> }
> catch( itk::ExceptionObject & excep )
> {
> std::cerr << "Exception caught !" << std::endl;
> std::cerr << excep << std::endl;
> }
>
> std::cout << "output from reader->GetOutput()->GetDirection()" <<
> std::endl;
> std::cout << reader->GetOutput()->GetDirection() << std::endl;
>
> std::cout << "output from castFilter->GetOutput()->GetDirection()" <<
> std::endl;
> std::cout << castFilter->GetOutput()->GetDirection() << std::endl;
>
> std::cout << "output from
> connectedThreshold->GetOutput()->GetDirection()" << std::endl;
> std::cout << connectedThreshold->GetOutput()->GetDirection() <<
> std::endl;
>
> std::cout << "output from caster->GetOutput()->GetDirection()" <<
> std::endl;
> std::cout << caster->GetOutput()->GetDirection() << std::endl;
>
> return 0;
> }
>
>
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