[Insight-users] Question about HybridSegmentationFuzzyVoronoi

[Jane Meinel]

Dear itk-users,
I tried the example of HybridSegmentationFuzzyVoronoi. It is quite good image segmentation frame.
Now I have some questions about this example:
 
*1. In the example image case BrainT1Slice.png, the parameters are: 140 125 140 25 0.2 2.0. Among them, (140, 125) is the seed position. It is obviously. However, "140 and 25 are the estimated mean and standard deviation,  respectively, of the object to be segmented.  Finally, 0.2 and 2.0  are the tolerance for the mean and standard deviation, respectively." What do those parameters mean? If I want to segment another image, how should I set those parameters by myself?
 
*2. In the BrainT1Slice.png case, the voronoi diagram classification improves the segmentation a lot after the fuzzy connectedness segmentation step. I want to know details about the voronoi diagram classification. I have read the paper "Hybrid Segmentation of Anotomical Data", which is written by Celina Imielinska, Dimitris Metaxas, Jayaram Udupa, Yinpeng Jin, Ting Chen, and published in MICCAI 2001. But it doesn't describe very clear about voronoi diagram classification. Which paper should I read in order to understand this algorithm better?
 
*3. I'm impressed deeply by the  figures of the paper mentioned about, which show the result of the iterations of VD-based algorithm. How can I draw such pictures by ITK classes? I want to know the procedure in different iterate step of Voronoi Diagram algorithm.
 
 
Any help is much appreciated! Thanks a lot!
 
 
Jane

		
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