Support:Documents:Examples:K-Means and Fuzzy C-Means analysis

From COMKAT wiki
Revision as of 21:08, 4 August 2015 by Hsin Tommy Huang (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

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


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

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


K Fuzzy Means 13.png