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23 June 1993 Stochastical segmentation method for vascular images and its convergence and parallelization
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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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maurits J. Malfait, Dirk Roose, and Dirk Vandermeulen "Stochastical segmentation method for vascular images and its convergence and parallelization", Proc. SPIE 2035, Mathematical Methods in Medical Imaging II, (23 June 1993);


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