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Figure 1

  Figure 1. Capturing global hanging togetherness.
 

Figure 2

  Figure 2. Fuzzy k-connectedness K.
 

Figure 3

  Figure 3. The equivalence class Oq  Ì  C.
 
Figure 4A Figure 4B
  Figure 4.
(a) Voronoi diagram
(b) Delaunay triangulation
 

Figure 5

  Figure 5. Hybrid Method I  (segmentation of temporalis muscle): Initialization of fuzzy connectedness algorithm.
 

Figure 6

  Figure 6. Hybrid Method I  (segmentation of temporalis muscle): Choosing the strength of connectedness, q Î [0,1] and generating of a fuzzy connected component.
 

Figure 7

  Figure 7. Hybrid Method I  (segmentation of temporalis muscle): Selection of three strong channels in average and variation, and initialization of the Voronoi Diagram based algorithm.
 

Figure 8

  Figure 8. Hybrid Method I  (segmentation of temporalis muscles): An iteration of the Voronoi Diagram based algorithm.
 

Figure 9

  Figure 9. Hybrid Method I  (segmentation of temporalis muscles):  Final iteration of the Voronoi Diagram based algorithm.
 

Figure 10a Figure 10b Figure 10c Figure 10d Figure 10e Figure 10f Figure 10g Figure 10h

  Figure 10. Hybrid Method I  (segmentation of temporalis muscles): 
(a)  Color VH male cryosection slice
(b) a fuzzy connected component
(c)-(g) iterations of the Voronoi diagram-based algorithm
(h) an outline of the boundary
 

Figure 11a Figure 11b Figure 11c Figure 11d Figure 11e Figure 11f Figure 11g Figure 11h

  Figure 11. Hybrid Method I  (segmentation of brain gray matter):
(a)  Color VH male cryosection slice
(b) a fuzzy connected componentm
(c)-(g) iterations of the Voronoi diagram-based algorithm
(h) an outline of the boundary
 

Figure 12a Figure 12b Figure 12c Figure 12d Figure 12e Figure 12f Figure 12g Figure 12h

  Figure 12. Hybrid Method I  (segmentation of fat tissue):
(a)  Color VH male cryosection slice
(b) a fuzzy connected
(c)-(h) iterations of the Voronoi diagram-based algorithm.
 

Figure 13a Figure 13b Figure 13c Figure 13d Figure 13e Figure 13f Figure 13g Figure 13h

  Figure 13. Hybrid Method I  (segmentation of (MRI) fat tissue):
(a)  MRI patient slice
(b) fuzzy connected component
(c)-(g) iterations of the Voronoi diagram-based algorithm
(h) an outline the boundary.
 

Figure 14

  Figure 14. Hybrid Method II (segmentation of temporalis muscle):
(a)  VH slice
(b) Gibbs prior estimation
(c) deformable model result.
 

Figure 15

  Figure 15. Hybrid Method II (segmentation of eyeball(small scale)):
(a) VH slice
(b) Gibbs prior estimation
(c) deformable model result.
 

Figure 16a Figure 16b Figure 16c Figure 16d Figure 16e

  Figure 16. Hybrid Method II (segmentation of eyeball (large scale) ):
(a)  VH slice
(b) Gibbs prior estimation in first iteration
(c) deformable model fit in first iteration
(d) Gibbs prior estimation in second iteration
(e) deformable model result.
 
 
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Last updated: 2 July 2001