Flux driven automatic centerline extraction.
We present a fast, robust and automatic method for computing centerline paths through tubular structures for application to virtual endoscopy. The key idea is to utilize a skeletonization algorithm which exploits properties of the average outward flux of the gradient vector field of a Euclidean distance function from the boundary of the structure. The algorithm is modified to yield a collection of 3D curves, each of which is locally centered. The approach requires no user interaction, is virtually parameter free and has low computational complexity. We validate the method quantitatively on a number of synthetic data sets with known centerlines and qualitatively on colon and vessel data segmented from CT and CRA images.
Bouix
Sylvain
S
Department of Psychiatry, Boston VA Healthcare System, Harvard Medical School, Boston, USA. sylvain@bwh.harvard.edu
Siddiqi
Kaleem
K
Tannenbaum
Allen
A
D000465:Algorithms; D001185:Artificial Intelligence; D023881:Colonography, Computed Tomographic / Q000379:methods; D004724:Endoscopy / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014584:User-Computer Interface