1. A method of segmenting tubular structures in digital images, comprising the steps of: providing a digitized image comprising a plurality of intensities corresponding to a domain of points on a 3-dimensional grid; selecting a point within a tubular object in said digitized image, wherein said tubular object is to be segmented; defining an initial state of said selected point of said tubular object as comprising an object center position, an object orientation, and an object cross section model modeled by an ellipse; initializing measurement weights, a conditional probability distribution and a prior probability distribution of a feature space of said initial state, wherein said initial conditional probability of said object cross section is proportional to exp(−R/R 0 ), where R is a ribbon measure defined by { ⁢ R = - ∞ , ⁢ μ int ≤ μ ext , ⁢ R = μ int - μ ext μ int + μ ext , ⁢ otherwise , wherein R 0 is an application specific normalization constant, μ int is the mean intensity value for points in the ellipse, and μ ext is the mean intensity value for points in a ribbon around the ellipse, wherein the ribbon and the ellipse have the same area; sampling said feature space from said prior probability distribution; estimating a posterior probability distribution by summing sample measurements weighted by said measurement weights, and segmenting a cross section of said tubular object from said posterior probability distribution.