Variational time-implicit multiphase level-sets a fast convex optimization-based solution

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Abstract

We propose a new principle, the variational region competition, to simultaneously propagate multiple disjoint level-sets in a fully time-implicit manner, minimizing the total cost w.r.t. region changes. We demonstrate, that the problem of multiphase level-set evolution can be reformulated in terms of a Potts problem, for which fast optimization algorithms are available using recent developments in convex relaxation. Further, we use an efficient recently proposed duality-based continuous max-flow method [1] implemented using massively parallel computing on GPUs for high computational performance. In contrast to conventional multi-phase level-set evolution approaches, ours allows for large time steps accelerating the evolution procedure. Further, the proposed method propagates all regions simultaneously, as opposed to the one-byone phase movement of current time-implicit implementations. Promising experiment results demonstrate substantial improvements in a wide spectrum of practical applications.

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Rajchl, M., Baxter, J. S. H., Bae, E., Tai, X. C., Fenster, A., Peters, T. M., & Yuan, J. (2015). Variational time-implicit multiphase level-sets a fast convex optimization-based solution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8932, pp. 278–291). Springer Verlag. https://doi.org/10.1007/978-3-319-14612-6_21

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