[Insight-users] is it limitation in itkMRFImageFilter class?

[Baoyun Li]

Dear Luis and All:

I am woring on EM and MRF for image segmentation. I made the EM clustering working, and then using the segmenation result to perfrom MRF for refinment.

I followed the styles in ITK example ScalarImageMarkovRandomField1.cxx  .

If I use the DistancCentroid as membershim function of the classifier, I can get the segmetation improved after MRF filter.

Since I using EM GaussianMixture model to intial segmentation, I think using itkGaussianDensityFunction as membership function of classifier may give better result.

When I changed the membership function, the result is totally wrong, then I checked the code for itkMRFImageFilter.cxx, I figure out why.

//////////////////////////////////////////////////////////////////////////////////

00625   const std::vector<double> & pixelMembershipValue = 
00626     m_ClassifierPtr->GetPixelMembershipValue( *inputPixelVec );

00648   //Add the prior probability to the pixel probability
00649   for( index = 0; index < m_NumberOfClasses; index++ )
00650     {
00651     m_MahalanobisDistance[index] = m_NeighborInfluence[index] - 
00652       pixelMembershipValue[index] ;
00653     }

////////////////////////////////////////////////////////////////////////////////

In line 651, when calculating the MahaanoistDistance,  m_MahalanobisDistance[index] = m_NeighborInfluence[index] -  pixelMembershipValue[index] ;
assuming my weight are all zeros, then class with maximum pdf will give the lowest Distance. As a result, the segmentation is fully wrong.

My question is why the filter was designed in the way, is MRFImageFilter not designed to apply GassianDensityFuncion as membershipfunction.

Can I still use GaussianDensityFunction in this case? Would if work if I  change the sign of code 651 to +?

Please give me some guide.

Baoyun



      
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