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List: insight-users
Subject: Re: [Insight-users] CannyLevelSet Speed Image - dimension returned
From: conn sullivan <sullivanconn () yahoo ! com>
Date: 2005-03-29 16:10:07
Message-ID: 20050329161007.73455.qmail () web31408 ! mail ! mud ! yahoo ! com
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Hello Luis,
I appreciate your reply. I use BrainT1Slice.png as input image (smoothed with \
curvature Anisotropic diffusion) and ventricle output of threshold level set is used \
as initial model. I get nice refined image of ventricles, but the speed image (.mhd) \
is returned with 0 size.
Attached is the output of reader1 & 2--->getoutput()->print, as you have suggested
Thanks,
conn
Luis Ibanez <luis.ibanez@kitware.com> wrote:
Hi Conn,
Please try the following first:
1) before calling Update() in the writer, invoke
reader1->Update();
reader2->Update();
reader1->GetOutput()->Print( std::cout );
reader2->GetOutput()->Print( std::cout );
2) then run the program again, and post to the list
the result that you get in the standard output.
That should help to determine whether the input
images are being provided correctly to the
canny level set filtetr.
Please let us know what you find.
Thanks
Luis
-------------------------
conn sullivan wrote:
> Hello All,
>
> I am new to ITK and currently trying to check with Level set
> segmentation methods.
> I have written following code to refine the segmentation of Threshold
> Level Set. I have used different types of images for this as input.
> The problem is: speed image returned is of 0 bytes, basically
> GetRegionIO() receives 0 as dimension of the input image.
> Does anyone have idea why this is happening?
>
> Ex. -->
> Input Files used -->
> Input FileName --> c:\\BrainT1Slice_thresholdLevelSet.png
> Feature Image --> c:\\BrainT1Slice.png
> Output FileName --> c:\\BrainT1Slice_output.png
>
> Command Line paramters are used as -->
> c:\\BrainT1Slice.png 0.02 20 c:\\BrainT1Slice_thresholdLevelSet.png 10
> 128 10 -1 1 -1 -1 -1 -1 -1 -1 0.3 30 c:\\BrainT1Slice_op.png
>
> int main( int argc, char *argv[] )
> {
> FILE *fp = fopen("c:\\check.txt", "w+");
> if(NULL != fp ){
> fprintf(fp,"argv[1] Input File Name --> %s \n", argv[1]);
> fprintf(fp,"argv[2] RMS Error --> %s \n", argv[2]);
> fprintf(fp,"argv[3] Maximum Number Of Iterations--> %s \n", argv[3]);
> fprintf(fp,"argv[4] Input File #2 --> %s \n", argv[4]);
> fprintf(fp,"argv[5] Variance --> %s \n", argv[5]);
> fprintf(fp,"argv[6] Iso-Surface Value --> %s \n", argv[6]);
> fprintf(fp,"argv[7] Lower Threshold --> %s \n", argv[7]);
> fprintf(fp,"argv[8] Upper Threshold --> %s \n", argv[8]);
> fprintf(fp,"argv[9] AdvectionScaling--> %s \n", argv[9]);
> fprintf(fp,"argv[10] SeedX --> %s \n", argv[10]);
> fprintf(fp,"argv[11] SeedY --> %s \n", argv[11]);
> fprintf(fp,"argv[12] X-Radius/InitialDistance--> %s \n", argv[12]);
> fprintf(fp,"argv[13] Y-Radius --> %s \n", argv[13]);
> fprintf(fp,"argv[14] SeedX2 --> %s \n", argv[14]);
> fprintf(fp,"argv[15] SeedY2 --> %s \n", argv[15]);
> fprintf(fp,"argv[16] Propagation Scaling --> %s \n", argv[16]);
> fprintf(fp,"argv[17] Curvature Scaling --> %s \n", argv[17]);
> fprintf(fp,"argv[18] Output File Name --> %s \n", argv[18]);
> }
> fclose(fp);
> typedef float InternalPixelType;
> const unsigned int Dimension = 2;
> typedef unsigned char OutputPixelType;
> typedef itk::Image< InternalPixelType, Dimension > InternalImageType;
> typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
> typedef itk::BinaryThresholdImageFilter< InternalImageType,
> OutputImageType > ThresholdingFilterType;
> typedef itk::ImageFileReader< InternalImageType > ReaderType;
> typedef itk::ImageFileWriter< OutputImageType > WriterType;
> typedef float InternalPixelType;
> typedef unsigned char OutputPixelType;
> typedef itk::BinaryThresholdImageFilter> OutputImageType> ThresholdingFilterType;
> ThresholdingFilterType::Pointer thresholder =
> ThresholdingFilterType::New();
>
> float propgationScale = 0.0, curvatureScale = 0.0;
> typedef itk::ImageFileReader< InternalImageType > ReaderType;
> typedef itk::ImageFileWriter< OutputImageType > WriterType;
> ReaderType::Pointer reader1 = ReaderType::New();
> ReaderType::Pointer reader2 = ReaderType::New();
> WriterType::Pointer writer = WriterType::New();
> reader1->SetFileName( argv[1] ); // Feature image (smoothed image)
> reader2->SetFileName( argv[4] ); // already segmented initial model
> writer->SetFileName( argv[18] ); // output file name
> thresholder->SetUpperThreshold( 10.0 );
> thresholder->SetLowerThreshold( 0.0 );
> thresholder->SetOutsideValue( 0 );
> thresholder->SetInsideValue( 255 );
>
> typedef itk::CannySegmentationLevelSetImageFilter< InternalImageType,
> InternalImageType >
> CannySegmentationLevelSetImageFilterType;
> CannySegmentationLevelSetImageFilterType::Pointer cannySegmentation =
> CannySegmentationLevelSetImageFilterType::New();
>
> cannySegmentation->SetAdvectionScaling( ::atof(argv[9]) );
> cannySegmentation->SetCurvatureScaling( ::atof(argv[17]) );
> cannySegmentation->SetPropagationScaling( 0.0 );
> // For cases in which some surface expansion is to be allowed, a
> non-zero value may be set for the
> // propagation term. The propagation term is simply D. Here,we set it
> to 0.0
> // The maximum number of iterations is specified from the command
> line. It may not be desirable in some
> // applications to run the filter to convergence. Only a few
> iterations may be required.
>
> cannySegmentation->SetMaximumRMSError( ::atof(argv[2]) );
> cannySegmentation->SetNumberOfIterations( ::atoi(argv[3]) );
> cannySegmentation->SetThreshold( ::atof(argv[7]) );
> cannySegmentation->SetVariance( ::atof(argv[5]) );
> cannySegmentation->SetIsoSurfaceValue( ::atof(argv[6]) );
> cannySegmentation->SetInput( reader2->GetOutput() );
> cannySegmentation->SetFeatureImage( reader1->GetOutput() );
> thresholder->SetInput( cannySegmentation->GetOutput() );
> writer->SetInput( thresholder->GetOutput() );
> // Examining the propagation (speed) and advection images can help the
> process of tuning parameters.
> // These images are available using \code{Set/Get} methods from the
> filter after it has been updated.
>
> try {
> writer->Update();
> }
> catch( itk::ExceptionObject & excep ) {
> std::cerr << "Exception caught !" << std::endl;
> std::cerr << excep << std::endl;
> }
> // Print useful information
> std::cout << std::endl;
> std::cout << "Max. no. iterations: " <<
> cannySegmentation->GetNumberOfIterations() << std::endl;
> std::cout << "Max. RMS error: " <<
> cannySegmentation->GetMaximumRMSError() << std::endl;
> std::cout << std::endl;
> std::cout << "No. elpased iterations: " <<
> cannySegmentation->GetElapsedIterations() << std::endl;
> std::cout << "RMS change: " << cannySegmentation->GetRMSChange() <<
> std::endl;
> // Write out the speed (propagation) image for parameter tuning purposes.
> //itk::ImageFileWriter< OutputImageType >::Pointer speedWriter =
> itk::ImageFileWriter::New();
> itk::ImageFileWriter< InternalImageType >::Pointer speedWriter =
> itk::ImageFileWriter::New();
>
> speedWriter->SetFileName( "Canny_speedImage.mhd" );
> speedWriter->SetInput( cannySegmentation->GetSpeedImage());
>
> // Since output of LaplacianLevelSet is Float type, we need to rescale
> it to "unsigned char" (for png).
> /*typedef itk::RescaleIntensityImageFilter< InternalImageType,
> OutputImageType > RescaleFilterType;
> RescaleFilterType::Pointer rescaler = RescaleFilterType::New();
>
> // Set Rescaler Parameters
> rescaler->SetOutputMinimum( 0 );
> rescaler->SetOutputMaximum( 255 );
>
> speedWriter->SetFileName( "Canny_speedImage.mhd" );
> rescaler->SetInput( cannySegmentation->GetSpeedImage());
> speedWriter->SetInput( rescaler->GetOutput() ); */
>
> try { speedWriter->Update(); }
> catch( itk::ExceptionObject & excep ){
> std::cerr << "Exception caught !" << std::endl;
> std::cerr << excep << std::endl;
> }
> return 0;
> } // end of main
>
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[Attachment #5 (text/html)]
<DIV>
<DIV>Hello Luis,</DIV>
<DIV> </DIV>
<DIV>I appreciate your reply. I use BrainT1Slice.png as input image (smoothed \
with curvature Anisotropic diffusion) and ventricle output of threshold level set is \
used as initial model. I get nice refined image of ventricles, but the speed \
image (.mhd) is returned with 0 size. </DIV> <DIV> </DIV>
<DIV>Attached is the output of reader1 & 2--->getoutput()->print, as you \
have suggested </DIV> <DIV>Thanks,</DIV>
<DIV>conn</DIV>
<DIV><BR><B><I>Luis Ibanez <luis.ibanez@kitware.com></I></B> wrote: </DIV>
<BLOCKQUOTE class=replbq style="PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: \
#1010ff 2px solid"><BR>Hi Conn,<BR><BR><BR><BR>Please try the following \
first:<BR><BR><BR>1) before calling Update() in the writer, \
invoke<BR><BR>reader1->Update();<BR>reader2->Update();<BR><BR><BR>reader1->GetOutput()->Print( \
std::cout );<BR>reader2->GetOutput()->Print( std::cout );<BR><BR><BR>2) then \
run the program again, and post to the list<BR>the result that you get in the \
standard output.<BR><BR>That should help to determine whether the input<BR>images are \
being provided correctly to the<BR>canny level set filtetr.<BR><BR><BR><BR>Please let \
us know what you find.<BR><BR><BR>Thanks<BR><BR><BR><BR>Luis<BR><BR><BR><BR>-------------------------<BR>conn \
sullivan wrote:<BR><BR>> Hello All,<BR>> <BR>> I am new to ITK and currently \
trying to check with Level set <BR>> segmentation methods.<BR>> I have written \
following code to refine the segmentation of Threshold <BR>> Level Set. I have \
used different types of images for this as input. <BR>> The problem is: speed \
image returned is of 0 bytes, basically <BR>> GetRegionIO() receives 0 as \
dimension of the input image.<BR>> Does anyone have idea why this is \
happening?<BR>> <BR>> Ex. --><BR>> Input Files used --><BR>> Input \
FileName --> c:\\BrainT1Slice_thresholdLevelSet.png<BR>> Feature Image --> \
c:\\BrainT1Slice.png<BR>> Output FileName --> \
c:\\BrainT1Slice_output.png<BR>> <BR>> Command Line paramters are used as \
--><BR>> c:\\BrainT1Slice.png 0.02 20 c:\\BrainT1Slice_thresholdLevelSet.png 10 \
<BR>> 128 10 -1 1 -1 -1 -1 -1 -1 -1 0.3 30 c:\\BrainT1Slice_op.png<BR>> \
<BR>> int main( int argc, char *argv[] )<BR>> {<BR>> FILE *fp = \
fopen("c:\\check.txt", "w+");<BR>> if(NULL != fp ){<BR>> fprintf(fp,"argv[1] \
Input File Name --> %s \n", argv[1]);<BR>> fprintf(fp,"argv[2] RMS Error --> \
%s \n", argv[2]);<BR>> fprintf(fp,"argv[3] Maximum Number Of Iterations--> %s \
\n", argv[3]);<BR>> fprintf(fp,"argv[4] Input File #2 --> %s \n", \
argv[4]);<BR>> fprintf(fp,"argv[5] Variance --> %s \n", argv[5]);<BR>> \
fprintf(fp,"argv[6] Iso-Surface Value --> %s \n", argv[6]);<BR>> \
fprintf(fp,"argv[7] Lower Threshold --> %s \n", argv[7]);<BR>> \
fprintf(fp,"argv[8] Upper Threshold --> %s \n", argv[8]);<BR>> \
fprintf(fp,"argv[9] AdvectionScaling--> %s \n", argv[9]);<BR>> \
fprintf(fp,"argv[10] SeedX --> %s \n", argv[10]);<BR>> fprintf(fp,"argv[11] \
SeedY --> %s \n", argv[11]);<BR>> fprintf(fp,"argv[12] \
X-Radius/InitialDistance--> %s \n", argv[12]);<BR>> fprintf(fp,"argv[13] \
Y-Radius --> %s \n", argv[13]);<BR>> fprintf(fp,"argv[14] SeedX2 --> %s \n", \
argv[14]);<BR>> fprintf(fp,"argv[15] SeedY2 --> %s \n", argv[15]);<BR>> \
fprintf(fp,"argv[16] Propagation Scaling --> %s \n", argv[16]);<BR>> \
fprintf(fp,"argv[17] Curvature Scaling --> %s \n", argv[17]);<BR>> \
fprintf(fp,"argv[18] Output File Name --> %s \n", argv[18]); <BR>> }<BR>> \
fclose(fp); <BR>> typedef float InternalPixelType; <BR>> const unsigned int \
Dimension = 2;<BR>> typedef unsigned char OutputPixelType;<BR>> typedef \
itk::Image< InternalPixelType, Dimension > InternalImageType;<BR>> typedef \
itk::Image< OutputPixelType, Dimension > OutputImageType;<BR>> typedef \
itk::BinaryThresholdImageFilter< InternalImageType, <BR>> OutputImageType > \
ThresholdingFilterType;<BR>> typedef itk::ImageFileReader< InternalImageType \
> ReaderType;<BR>> typedef itk::ImageFileWriter< OutputImageType > \
WriterType; <BR>> typedef float InternalPixelType;<BR>> typedef unsigned char \
OutputPixelType;<BR>> typedef itk::BinaryThresholdImageFilter<INTERNALIMAGETYPE, \
<br>> OutputImageType> ThresholdingFilterType;<BR>> \
ThresholdingFilterType::Pointer thresholder = <BR>> \
ThresholdingFilterType::New();<BR>> <BR>> float propgationScale = 0.0, \
curvatureScale = 0.0;<BR>> typedef itk::ImageFileReader< InternalImageType > \
ReaderType;<BR>> typedef itk::ImageFileWriter< OutputImageType > \
WriterType;<BR>> ReaderType::Pointer reader1 = ReaderType::New();<BR>> \
ReaderType::Pointer reader2 = ReaderType::New();<BR>> WriterType::Pointer writer = \
WriterType::New();<BR>> reader1->SetFileName( argv[1] ); // Feature image \
(smoothed image)<BR>> reader2->SetFileName( argv[4] ); // already segmented \
initial model<BR>> writer->SetFileName( argv[18] ); // output file name \
<BR>> thresholder->SetUpperThreshold( 10.0 );<BR>> \
thresholder->SetLowerThreshold( 0.0 );<BR>> thresholder->SetOutsideValue( 0 \
);<BR>> thresholder->SetInsideValue( 255 ); <BR>> <BR>> typedef \
itk::CannySegmentationLevelSetImageFilter< InternalImageType,<BR>> \
InternalImageType > <BR>> CannySegmentationLevelSetImageFilterType;<BR>> \
CannySegmentationLevelSetImageFilterType::Pointer cannySegmentation =<BR>> \
CannySegmentationLevelSetImageFilterType::New(); <BR>> <BR>> \
cannySegmentation->SetAdvectionScaling( ::atof(argv[9]) );<BR>> \
cannySegmentation->SetCurvatureScaling( ::atof(argv[17]) );<BR>> \
cannySegmentation->SetPropagationScaling( 0.0 );<BR>> // For cases in which \
some surface expansion is to be allowed, a <BR>> non-zero value may be set for \
the<BR>> // propagation term. The propagation term is simply D. Here,we set it \
<BR>> to 0.0 <BR>> // The maximum number of iterations is specified from the \
command <BR>> line. It may not be desirable in some<BR>> // applications to run \
the filter to convergence. Only a few <BR>> iterations may be required.<BR>> \
<BR>> cannySegmentation->SetMaximumRMSError( ::atof(argv[2]) );<BR>> \
cannySegmentation->SetNumberOfIterations( ::atoi(argv[3]) ); <BR>> \
cannySegmentation->SetThreshold( ::atof(argv[7]) );<BR>> \
cannySegmentation->SetVariance( ::atof(argv[5]) ); <BR>> \
cannySegmentation->SetIsoSurfaceValue( ::atof(argv[6]) ); <BR>> \
cannySegmentation->SetInput( reader2->GetOutput() );<BR>> \
cannySegmentation->SetFeatureImage( reader1->GetOutput() );<BR>> \
thresholder->SetInput( cannySegmentation->GetOutput() ); <BR>> \
writer->SetInput( thresholder->GetOutput() );<BR>> // Examining the \
propagation (speed) and advection images can help the <BR>> process of tuning \
parameters. <BR>> // These images are available using \code{Set/Get} methods from \
the <BR>> filter after it has been updated.<BR>> <BR>> try {<BR>> \
writer->Update();<BR>> }<BR>> catch( itk::ExceptionObject & excep ) \
{<BR>> std::cerr << "Exception caught !" << std::endl;<BR>> \
std::cerr << excep << std::endl;<BR>> }<BR>> // Print useful \
information<BR>> std::cout << std::endl;<BR>> std::cout << "Max. \
no. iterations: " << <BR>> cannySegmentation->GetNumberOfIterations() \
<< std::endl;<BR>> std::cout << "Max. RMS error: " << <BR>> \
cannySegmentation->GetMaximumRMSError() << std::endl;<BR>> std::cout \
<< std::endl;<BR>> std::cout << "No. elpased iterations: " << \
<BR>> cannySegmentation->GetElapsedIterations() << std::endl;<BR>> \
std::cout << "RMS change: " << cannySegmentation->GetRMSChange() \
<< <BR>> std::endl; <BR>> // Write out the speed (propagation) image for \
parameter tuning purposes.<BR>> //itk::ImageFileWriter< OutputImageType \
>::Pointer speedWriter = <BR>> itk::ImageFileWriter<OUTPUTIMAGETYPE>::New(); \
<BR>> itk::ImageFileWriter< InternalImageType >::Pointer speedWriter = \
<BR>> itk::ImageFileWriter<INTERNALIMAGETYPE>::New(); <BR>> <BR>> \
speedWriter->SetFileName( "Canny_speedImage.mhd" ); <BR>> \
speedWriter->SetInput( cannySegmentation->GetSpeedImage());<BR>> <BR>> // \
Since output of LaplacianLevelSet is Float type, we need to rescale <BR>> it to \
"unsigned char" (for png).<BR>> /*typedef itk::RescaleIntensityImageFilter< \
InternalImageType, <BR>> OutputImageType > RescaleFilterType; <BR>> \
RescaleFilterType::Pointer rescaler = RescaleFilterType::New(); <BR>> <BR>> // \
Set Rescaler Parameters<BR>> rescaler->SetOutputMinimum( 0 );<BR>> \
rescaler->SetOutputMaximum( 255 ); <BR>> <BR>> speedWriter->SetFileName( \
"Canny_speedImage.mhd" ); <BR>> rescaler->SetInput( \
cannySegmentation->GetSpeedImage()); <BR>> speedWriter->SetInput( \
rescaler->GetOutput() ); */<BR>> <BR>> try { speedWriter->Update(); \
}<BR>> catch( itk::ExceptionObject & excep ){<BR>> std::cerr << \
"Exception caught !" << std::endl;<BR>> std::cerr << excep << \
std::endl;<BR>> } <BR>> return 0;<BR>> } // end of main<BR>> <BR>> \
------------------------------------------------------------------------<BR>> Do \
you Yahoo!?<BR>> Yahoo! Small Business - Try our new resources site! <BR>> \
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us.rd.yahoo.com><BR>> <BR>> <BR>> <BR>> \
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<BR>> _______________________________________________<BR>> Insight-users \
mailing list<BR>> Insight-users@itk.org<BR>> \
http://www.itk.org/mailman/listinfo/insight-users<BR><BR><BR><BR></BLOCKQUOTE></DIV><p>
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--0-662805275-1112112607=:69552--
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\par Observers:}{\insrsid10101212 }{\insrsid10101212 none
\par Source: (01396B78)
\par Source output index: 0
\par Release Data: Off
\par Data Released: False
\par Global Release Data: Off
\par PipelineMTime: 39
\par UpdateMTime: 202
\par LargestPossibleRegion:
\par Dimension: 2
\par Index: [0, 0]
\par Size: [181, 217]
\par BufferedRegion:
\par Dimension: 2
\par Index: [0, 0]
\par Size: [181, 217]
\par RequestedRegion:
\par Dimension: 2
\par Index: [0, 0]
\par Size: [181, 217]
\par Spacing: [1, 1]
\par Origin: [0, 0]
\par PixelContainer:
\par ImportImageContainer (01396C30)
\par RTTI typeinfo: class itk::ImportImageContainer<unsigned long,float>
\par Reference Count: 1
\par Modified Time: 199
\par Debug: Off
\par Observers:
\par none
\par Pointer: 01396C60
\par Container manages memory: true
\par Size: 39277
\par Capacity: 39277
\par
\par Max. no. iterations: 20
\par Max. RMS error: 0.02
\par
\par No. elpased iterations: 20
\par RMS change: 0.0773829
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par
\par }{\insrsid12659036\charrsid10101212
\par }}
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