Skeletonization of volumetric angiograms for display.
The display of three-dimensional angiograms can benefit from the knowledge of quantitative shape features such as tangent and curvature of the centerline of vessels. These can be obtained from a curve-like skeleton representation. If connectivity and topology are preserved, and if geometrical constraints such as smoothness and centeredness are satisfied, it is possible to estimate length, orientation, curvature, and torsion. It is also required that no part of the original object be left unrepresented. An efficient method for the identification of such shape components is developed. First, a suitable representation is obtained using a voxel coding approach to yield connected and labeled unit-thick paths. The desired features are estimated from a smoothed version of the skeleton produced by a moving average filter. The computational cost is linear, of the order of N(object), the total number of object voxels contained in the binary volumetric data. The method is also shown to be robust to boundary noise. Examples are discussed.
Department of Electrical and Computer Engineering and Center for Interlligent Machine, McGill University, 3480 University Street, Montreal, Que Canada H3A 2A7. yidingr@cim.mcgill.ca
Dingrong
D
Yi
Vincent
V
Hayward
D000465:Algorithms; D000792:Angiography / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted