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Proceedings Paper

Stochastical segmentation method for vascular images and its convergence and parallelization
Author(s): Maurits J. Malfait; Dirk Roose; Dirk Vandermeulen
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Paper Abstract

A stochastical algorithm to improve the visual appearance of blood-vessel images is presented. Each pixel value in the output image represents the probability that the pixel belongs to a blood-vessel. The algorithm incorporates a Metropolis sampler that approximates a posterior distribution. We first describe this algorithm and present some results. In the second part, we focus on methods to assess the sampler convergence. For a first method some versions of the sampler algorithm are executed in parallel. We propose a convergence measure based on the deviations between the parallel versions. We compare this measure with one based on the analysis of the underlying Markov chains, by applying the measures to Ising model simulations. We also examine whether the parallel samplers can be used to accelerate the algorithm.

Paper Details

Date Published: 23 June 1993
PDF: 12 pages
Proc. SPIE 2035, Mathematical Methods in Medical Imaging II, (23 June 1993); doi: 10.1117/12.146593
Show Author Affiliations
Maurits J. Malfait, Katholieke Univ. Leuven (Belgium)
Dirk Roose, Katholieke Univ. Leuven (Belgium)
Dirk Vandermeulen, Katholieke Univ. Leuven (Belgium)


Published in SPIE Proceedings Vol. 2035:
Mathematical Methods in Medical Imaging II
Joseph N. Wilson; David C. Wilson, Editor(s)

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