A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage

Emmanuel Faure 1, 2, 3, 4 Thierry Savy 3, 4, 1 Barbara Rizzi 1, 3, 4 Camilo Melani 1, 5, 4 Olga Stašová 6, 7 Dimitri Fabrèges 1, 3, 5, 4 Róbert Špir 6, 7 Mark Hammons 3, 1, 4 Róbert Čúnderlík 6, 7 Gaëlle Recher 1, 3, 4 Benoit Lombardot 1, 2, 3 Louise Duloquin 1, 3, 4 Ingrid Colin 3 Jozef Kollár 6, 7 Sophie Desnoulez 3 Pierre Affaticati 8 Benoit Maury 3 Adeline Boyreau 3 Jean-Yves Nief 9 Pascal Calvat 9 Philippe Vernier 8, 3 Monique Frain 5, 3 Georges Lutfalla 10 Yannick Kergosien 1, 3, 5, 11, 4 Pierre Suret 12 Mariana Remešíková 6, 7 René Doursat 5, 3, 4, 1, 2 Alessandro Sarti 13, 14 Karol Mikula 7, 6 Nadine Peyriéras 5, 3, 1 Paul Bourgine 2, 3, 5, 1
Abstract : The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3Dþtime image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology.
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Emmanuel Faure, Thierry Savy, Barbara Rizzi, Camilo Melani, Olga Stašová, et al.. A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage. Nature Communications, Nature Publishing Group, 2016, 7, pp.8674. ⟨10.1038/ncomms9674⟩. ⟨hal-02086959⟩

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