Automatic Centerline Extraction for Virtual Colonoscopy
description
Transcript of Automatic Centerline Extraction for Virtual Colonoscopy
Automatic Centerline Extractionfor 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
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Outline
IntroductionRequirementsBrief Review of Existing Algorithms
for VCDescription of New AlgorithmResults Conclusion
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Introduction
Virtual endoscopy is an integration of medical imaging computer graphics
Advantages: noninvasive cost-effective highly accurate
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Requirements(1/2)
1.Connectivity: centerline is a sequence of directly connected v
oxels. 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
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Requirements(2/2)
4. Detectability : branch area
5. Automation: fully automatic procedure
6. Efficiency: seconds on PC platform
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Outline
IntroductionRequirementsBrief Review of Existing Algorithms
for VCDescription of New AlgorithmResults Conclusion
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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
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Topological Thinning
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Outline
IntroductionRequirementsBrief Review of Existing Algorithms
for VCDescription of New AlgorithmResults Conclusion
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DFB / DFS
DFS: distance from a user-specified source point to e
ach voxelDFB: ( DFB-cost = 1/DFB )
distance from each inside voxel to the nearest object boundary
SDFS
DFB A
B
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Description of New Algorithm1.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
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Description of New Algorithm
2. Extraction of Colon Centerline and Branches does not specify the end point of the colon cent
erline Find inside voxel with the maximum DFS-value
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Modified Dijkstra Algorithm
SourceCurrent
B
DFS(C)
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圖解
start
current
B1B2
B26
有相鄰 26個點
找 DFB COST最小的點也就是 DFB最大的點
B3
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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 neigh
bors and find those voxel Bi Pathlink pointing to C
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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).
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Results
Machine PC platform
CPU :Intel Pentium 700-MHz processor Memory: 655 MB
Data: 44 human colon datasets.
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Results
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Conclusion
Extend their centerline algorithm to study more complicated human organs with tree structures as airways and blood vessels.