Main Article Content
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.
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.