Name
Title | ||
|---|---|---|
Extraction of 3d vascular tree skeletons based on the analysis of connected components evolution |
Abstract | ||
|---|---|---|
The article is dealing with the automated extraction of branching structures in 3D medical images. A generic object-oriented programming framework is proposed, in which most existing iterative algorithms for centerline extraction in tubular objects can be efficiently implemented, and the bifurcations can be handled. New algorithms can thus easily be derived. We describe a simple algorithm for fast extraction of the 3D structure of the vascular tree, which has been implemented within this framework. The algorithm recursively tracks the branches and detects the bifurcations by analyzing the binary connected components on the surface of a sphere that moves along the vessels. It assumes that the vessels can locally be separated from the background by an appropriate adaptive threshold. The originality of the algorithm resides in the analysis of the evolution of the connected components during the sphere growth that allows it to cope with local abrupt changes of the vessel diameter and shape. It was successfully tested in 16 magnetic resonance angiography images. Its accuracy was assessed by comparing the resulting axes with those extracted by a reference algorithm. The distance between them was less than one voxel except in bifurcations, where the maximum distance was 3.8 voxels. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11556121_74 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
connected components evolution,centerline extraction,algorithm resides,existing iterative algorithm,algorithm recursively,binary connected component,fast extraction,automated extraction,new algorithm,reference algorithm,vascular tree,simple algorithm,bifurcation,generic programming,branching,object oriented programming,nuclear magnetic resonance imaging,image analysis,image processing,skeleton,circulatory system,iterative algorithm,iterative method,ramification,sphere,pattern analysis,adaptive thresholding,object oriented,connected component,voxel | Voxel,Pattern recognition,Iterative method,Computer science,Image processing,Algorithm,Artificial intelligence,Connected component,SIMPLE algorithm,Software framework,Recursion,Binary number | Conference |
Volume | ISSN | ISBN |
3691 | 0302-9743 | 3-540-28969-0 |
Citations | PageRank | References |
5 | 0.50 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan F. Carrillo | 1 | 23 | 1.43 |
| Maciej Orkisz | 2 | 315 | 24.14 |
| Marcela Hernández Hoyos | 3 | 228 | 15.91 |