1. Automatic Centerline Extraction for Virtual Colonoscopy 作者 : Ming Wan, Zhengrong Liang*, Qi Ke, Lichan Hong, Ingmar Bitter, and Arie Kaufman 出處 :  IEEE Transaction on Medical Imaging, Dec. 2002, pp. 1450 - 1460 學生 : 林上智 指導老師 : 張顧耀

2. 2 Outline Introduction Requirements Brief Review of Existing Algorithms for VC Description of New Algorithm Results Conclusion

3. 3 Introduction Virtual endoscopy is an integration of  medical imaging  computer graphics Advantages:  noninvasive  cost-effective  highly accurate

4. 4 Requirements(1/2) 1.Connectivity:  centerline is a sequence of directly connected voxels. 6-, 18-, 26- connected 2. Centricity:  centerline should stay away from the colon wall 3. Singularity:  centerline should be a single path of one-voxel width

5. 5 Requirements(2/2) 4. Detectability :  branch area 5. Automation:  fully automatic procedure 6. Efficiency:  seconds on PC platform

6. 6 Outline Introduction Requirements Brief Review of Existing Algorithms for VC Description of New Algorithm Results Conclusion

7. 7 Brief Review of Existing Algorithms for VC Manual Extraction:  manually mark the center of each colon region on each image Topological Thinning:  peels off a volumetric object layer by layer

8. 8 Topological Thinning

9. 9 Outline Introduction Requirements Brief Review of Existing Algorithms for VC Description of New Algorithm Results Conclusion

10. 10 DFB / DFS DFS:  distance from a user-specified source point to each voxel DFB: ( DFB-cost = 1/DFB )  distance from each inside voxel to the nearest object boundary S DFS DFB A B

11. 11 Description of New Algorithm 1.Construction of a MST tree:  minimum-cost spanning tree  First: converts the CT volume with DFB-distances to a 3D directed weighted graph.  Second: builds up a MST tree from the weighted graph Dijkstra’s shortest path technique. DFB-cost

12. 12 Description of New Algorithm 2. Extraction of Colon Centerline and Branches  does not specify the end point of the colon centerline Find inside voxel with the maximum DFS-value

13. 13 Modified Dijkstra Algorithm Source Current B DFS(C)

14. 14 圖解 start current B1 B2 B26 有相鄰 26 個點 找 DFB COST 最小的點 也就是 DFB 最大的點 B3

15. 15 Branch detection algorithm(1/2) Step1:  Scan the centerline by tracking back from end point(E) to start point(S) Step2:  For each centerline voxel C, check its 24 neighbors and find those voxel Bi Pathlink pointing to C

16. 16 Branch detection algorithm(2/2) Setp3:  for each voxel Bi Record voxel C to be the closet centerline voxel Find the voxel with largest DFS-distance,Ti. Length of branch DFS(Ti) – DFS(C).

17. 17 Results Machine  PC platform CPU :Intel Pentium 700-MHz processor Memory: 655 MB Data:  44 human colon datasets.

18. 18 Results

19. 19 Conclusion Extend their centerline algorithm to study more complicated human organs with tree structures as airways and blood vessels.