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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. In 2017 IEEE International Conference on Computer Vision: ICCV 2017: proceedings: 22-29 October 2017, Venice, Italy (pp. 4705-4714). Piscataway, N.J.: IEEE.

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Genre: Konferenzbeitrag

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https://publications.mpi-cbg.de/Rempfler_2017_7097.pdf (beliebiger Volltext)
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Rempfler, Markus, Autor
Lange, Jan-Hendrik, Autor
Jug, Florian1, Autor           
Blasse, Corinna1, Autor           
Myers, Eugene W1, Autor           
Menze, Bjoern H., Autor
Andres, Bjoern, Autor
Affiliations:
1Max Planck Institute for Molecular Cell Biology and Genetics, ou_2340692              

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 Zusammenfassung: 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. [21] have proposed a mathematical abstraction of this task, the moral lineage tracing problem (MLTP), whose feasible solutions define both a segmentation of every image and a lineage forest of cells. Their branch-and-cut algorithm, however, is prone to many cuts and slow convergence for large instances. To address this problem, we make three contributions: (i) we devise the first efficient primal feasible local search algorithms for the MLTP, (ii) we improve the branch-and-cut algorithm by separating tighter cutting planes and by incorporating our primal algorithms, (iii) we show in experiments that our algorithms find accurate solutions on the problem instances of Jug et al. and scale to larger instances, leveraging moral lineage tracing to practical significance.

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 Datum: 2017-10-29
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1109/ICCV.2017.503
Anderer: cbg-7097
 Art des Abschluß: -

Veranstaltung

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Titel: 2017 IEEE International Conference on Computer Vision : ICCV 2017
Veranstaltungsort: Venice, Italy
Start-/Enddatum: 2017-10-22 - 2017-10-29

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Titel: 2017 IEEE International Conference on Computer Vision : ICCV 2017 : proceedings : 22-29 October 2017, Venice, Italy
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Piscataway, N.J. : IEEE
Seiten: - Band / Heft: 2017 IEEE International Conference on Computer Vision : ICCV 2017 : proceedings : 22-29 October 2017, Venice, Italy Artikelnummer: - Start- / Endseite: 4705 - 4714 Identifikator: ISBN: 978-15386-1032-9