A Bayesian approach to inferring vascular tree structure from 2D imagery

We describe a method for inferring tree-like vascular structures from 2D imagery. A Markov Chain Monte Carlo (MCMC) algorithm is employed to produce approximate samples from the posterior distribution given local feature estimates, derived from likelihood maximisation for a Gaussian intensity profile. A multiresolution scheme, in which coarse scale estimates are used to initialise the algorithm for finer scales, has been implemented and used to model retinal images. Results are presented to show the effectiveness of the method.

• Type: Conference
• Year: 2002
• Where: ICIP
• Authors: Abhir Bhalerao, Elke Thönnes, Roland Wilson, Wilfrid Kendall
• Keywords: Coarse Scale Estimates, ICIP 2002, Image Processing, Local Feature Estimates, Tree-like Vascular Structures