[Rtk-users] 回复: scatterglarecorrection

[dongping.wang at simmhealthcare.com]

Hi all

 

I have a 3d raw data which has a size of 512*512*1012.

When I use the following code:

 

inputImage=ROIRegionFilter.GetOutput()

SGFilterType=rtk.ScatterGlareCorrectionImageFilter[ImageType,ImageType,itk.F]

SGFilter=SGFilterType.New()

SGFilter.SetInput(ROIRegionFilter.GetOutput())

SGFilter.SetCoefficients([0.0787,10.6244])

SGFilter.SetTruncationCorrection(0.5)

 

And Extract a full size:

I got one error said:

 

RuntimeError: C:\P\IPP\ITK-source\ITK\Modules\Filtering\FFT\include\itkVnlRealToHalfHermitianForwardFFTImageFilter.hxx:58:

ITK ERROR: VnlRealToHalfHermitianForwardFFTImageFilter(000002AD61E8C4E0): Cannot compute FFT of image with size [1024, 1024, 1012]. VnlRealToHalfHermitianForwardFFTImageFilter operates only on images whose size in each dimension has a prime factorization consisting of only 2s, 3s, or 5s.

 

When I extract the slices upto 512 or 2,  then the python hung up.

 

If I just extracted one of the slices, it is ok.

 

So my question is:

ScatterGlareCorrectionImageFilter is only working with a slice (for example 512X512X1)？

If I wanted to use this filter, I have to walk through the raw data slice by slice? Thanks!

 

Regards

 

Wang Dongping

 

 

发件人: dongping.wang at simmhealthcare.com <dongping.wang at simmhealthcare.com> 
发送时间: 2022年7月19日 11:29
收件人: 'rtk-users at openrtk.org' <rtk-users at openrtk.org>
主题: scatterglarecorrection 

 

Hi all

 

I am trying to use ScatterGlareCorrectionImageFilter to do some scattering correction. From the test, we can see we just need to set the coef, then call the update().

 


ImageType::Pointer testImage = createInputImage(coef);

	
  SFilter->SetInput(testImage);

	
  TRY_AND_EXIT_ON_ITK_EXCEPTION(SFilter->Update())

 


The question is if we need to call the UpdateFFTProjectionsConvolutionKernel() to build the filter before we call update()?


If we wanted to correct one 3D raw project data, how we do the correction slice by slice?  Any example for it?


 


 


Regards


Wang Dongping


 

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