Difference between revisions of "Support:Documents:Examples:K-Means and Fuzzy C-Means analysis"

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=K-Means and Fuzzy C-Means=
 
=K-Means and Fuzzy C-Means=
In COMKAT R4.0a, you can analyze images by K-Means or Fuzzy C-Means.
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In COMKAT R4.0a, you can analyze images by K-Means or Fuzzy C-Means clustering.
  
  
1.Image > Clustering
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1.Select  Image > Clustering
  
 
[[Image:K_Fuzzy_Means_1.png]]
 
[[Image:K_Fuzzy_Means_1.png]]
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3.If you select Fuzzy C-means, you can choose the output Labels or Probability Maps /membership function :
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3.If you select Fuzzy C-means, you can output Labels or Probability Maps /membership functions :
  
 
[[Image:K_Fuzzy_Means_3.png]]
 
[[Image:K_Fuzzy_Means_3.png]]
  
  
4.Number of clusters
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4.Assign number of clusters
  
 
[[Image:K_Fuzzy_Means_4.png]]
 
[[Image:K_Fuzzy_Means_4.png]]
  
  
5.If your images are several MR contrast (muti-bands), you can also analyze a particular band alone by unchecking the checkbox as follows:
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5.If your images are several MR contrast (muti-bands), you can also analyze band-2 and band-3 by unchecking the checkbox as follows:
  
[[Image:K_Fuzzy_Means_5.png]]
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[[Image:K_Fuzzy_Means_12.png]]
  
  
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</pre>
 
</pre>
  
2.Colormap > GreenFire
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2.Select  Colormap > GreenFire
  
 
[[Image:K_Fuzzy_Means_6.png]]
 
[[Image:K_Fuzzy_Means_6.png]]
  
  
3.Image > Clustering
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3.Select  Image > Clustering
  
 
[[Image:K_Fuzzy_Means_7.png]]
 
[[Image:K_Fuzzy_Means_7.png]]
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5.Results
 
5.Results
  
[[Image:K_Fuzzy_Means_9.png]]
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[[Image:K_Fuzzy_Means_11.png]]

Revision as of 18:41, 3 August 2015

K-Means and Fuzzy C-Means

In COMKAT R4.0a, you can analyze images by K-Means or Fuzzy C-Means clustering.


1.Select Image > Clustering

K Fuzzy Means 1.png


2.You can select K-Means or Fuzzy C-Means here:

K Fuzzy Means 2.png


3.If you select Fuzzy C-means, you can output Labels or Probability Maps /membership functions :

K Fuzzy Means 3.png


4.Assign number of clusters

K Fuzzy Means 4.png


5.If your images are several MR contrast (muti-bands), you can also analyze band-2 and band-3 by unchecking the checkbox as follows:

K Fuzzy Means 12.png


Examples

Here we use Fuzzy C-means for an example.


1.Load phantom imge:

a= phantom(256);
b= phantom(256);
c= cat(3,a,b);           % COMKAT do not read 2-D image
comkatimagetool(c)

2.Select Colormap > GreenFire

K Fuzzy Means 6.png


3.Select Image > Clustering

K Fuzzy Means 7.png


4.Set as follows:

K Fuzzy Means 8.png

5.Results

K Fuzzy Means 11.png