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  Efficient Algorithms for Moral Lineage Tracing

Rempfler, M., Lange, J.-H., Jug, F., Blasse, C., Myers, E. W., Menze, B. H., et al. (2017). Efficient Algorithms for Moral Lineage Tracing. Retrieved from http://arxiv.org/abs/1702.04111.

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arXiv:1702.04111.pdf (Preprint), 839KB
 
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 Creators:
Rempfler, Markus1, Author
Lange, Jan-Hendrik2, Author           
Jug, Florian1, Author
Blasse, Corinna1, Author
Myers, Eugene W.1, Author
Menze, Bjoern H.1, Author
Andres, Bjoern2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society, ou_1116547              

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Free keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV
 Abstract: Lineage tracing, the joint segmentation and tracking of living cells as they move and divide in a sequence of light microscopy images, is a challenging task. Jug et al. have proposed a mathematical abstraction of this task, the moral lineage tracing problem (MLTP) whose feasible solutions define a segmentation of every image and a lineage forest of cells. Their branch-and-cut algorithm, however, is prone to many cuts and slow convergences for large instances. To address this problem, we make three contributions: Firstly, we improve the branch-and-cut algorithm by separating tighter cutting planes. Secondly, we define two primal feasible local search algorithms for the MLTP. Thirdly, we show in experiments that our algorithms decrease the runtime on the problem instances of Jug et al. considerably and find solutions on larger instances in reasonable time.

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 Dates: 2017-02-142017
 Publication Status: Published online
 Pages: 9 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 1702.04111
URI: http://arxiv.org/abs/1702.04111
BibTex Citekey: rempfler-2017-arxiv
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