title: Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.
abstract: 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.
authors: Imaging & Visualization Department, Siemens Corporate Research, Princeton, NJ, USA.
authors: Charles
authors: C
authors: Florin
authors: Nikos
authors: N
authors: Paragios
authors: Jim
authors: J
authors: Williams