Parallel algorithms for segmentation of cellular structures in 2D+Time and 3D morphogenesis data

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Karol Mikula Michal Smíšek Róbert Špir

Abstract

In this paper we present a robust method to segment 3D and 2D+time biological data. Our method uses distance function and the Generalized Subjective Surfaces (GSUBSURF) level-set segmentation algorithm. We focus on memory-ecient implementation of distance function computation, a novel way of nite volume method discretization of GSUBSURF PDE and the optimized parallelization of our code via the MPI library, enabling us to take the advantage of high-performance computing servers. Several experiments, including optimized parallelization test, validation of parallel GSUBSURF implementation and visual check of method performance on real data, are presented as well. 

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How to Cite
MIKULA, Karol; SMÍŠEK, Michal; ŠPIR, Róbert. Parallel algorithms for segmentation of cellular structures in 2D+Time and 3D morphogenesis data. Proceedings of the Conference Algoritmy, [S.l.], p. 416-426, nov. 2015. Available at: <http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/algoritmy/article/view/352>. Date accessed: 20 oct. 2017.
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