A Bayesian Approach to inferring vascular tree structure from 2D imagery(5)

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

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Fig.3.(a)2Dretinalangiogramsize404404pixels.(b)Reconstructionofdatafrommodelparametersestimates

forblocksizesof64and(c)

16.

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Fig.4.Estimatesfromthetree-basedsampler,at(a)200,(b)1000and(c)50000iterations,showinghowuseismadeofthelocalmultiresolutionfeatureestimates,inacoarse- neapproachtotheMCMCalgorithm.After50000iterations,fewchangesoccur.

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