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.

• Type: Conference
• Year: 2005
• Where: MICCAI
• Authors: Charles Florin, Nikos Paragios, James Williams
• Keywords: Coronary Arteries, Medical Imaging, MICCAI 2005, Particle Filter-based Approach, Sequential Bayesian Filter