Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.
In this paper we propose a Particle Filter-based approach for the segmentation of coronary arteries. To this end, successive planes of the vessel are modeled as unknown states of a sequential process. Such states consist of the orientation, position, shape model and appearance (in statistical terms) of the vessel that are recovered in an incremental fashion, using a sequential Bayesian filter (Particle Filter). In order to account for bifurcations and branchings, we consider a Monte Carlo sampling rule that propagates in parallel multiple hypotheses. Promising results on the segmentation of coronary arteries demonstrate the potential of the proposed approach.
Florin
Charles
C
Imaging & Visualization Department, Siemens Corporate Research, Princeton, NJ, USA.
Paragios
Nikos
N
Williams
Jim
J