Deformable boundary detection of stents in angiographic images.
In this paper, a procedure is described for deformable boundary detection of medical tools, called stents, in angiographic images. A stent is a surgical stainless steel coil that is placed in the artery in order to improve blood circulation in regions where a stenosis has appeared. Assuming initially a set of three-dimensional (3-D) models of stents and using perspective projection of various deformations of the 3-D model of the stent, a large set of synthetic two-dimensional (2-D) images of stents is constructed. These synthetic images are then used as a training set for deriving a multivariate Gaussian density estimate based on eigenspace decomposition and formulating a maximum-likelihood estimation framework in order to reach an initial rough estimate for automatic object recognition. The silhouette of the detected stent is then refined by using a 2-D active contour (snake) algorithm integrated with a novel iterative initialization technique, which takes into consideration the geometry of the stent. The algorithm is experimentally evaluated using real angiographic images containing stents.
Kompatsiaris
I
I
Electrical and Computer Engineering Department, Aristotle University of Thessaloniki, Greece.
Tzovaras
D
D
Koutkias
V
V
Strintzis
M G
MG
D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001672:Biocompatible Materials; D001807:Blood Vessel Prosthesis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D019047:Phantoms, Imaging; D018583:Pliability; D013193:Stainless Steel; D015607:Stents
D001672:Biocompatible Materials; D013193:Stainless Steel