Cells segmentation from 3-D confocal images of early zebrafish embryogenesis

Authors:
Cecilia Zanella;Matteo Campana;Barbara Rizzi;Camilo Melani;Gonzalo Sanguinetti;Paul Bourgine;Karol Mikula;Nadine Peyriéras;Alessandro Sarti
Affiliations:
DEIS, Bologna University, Bologna, Italy;DEIS, Bologna University, Bologna, Italy;DEIS, Bologna University, Bologna, Italy;Facultad de Ciencias Exactas y Naturales, Buenos Aires University, Buenos Aires, Argentina and DEIS, Bologna University, Bologna, Italy;Instituto de Ingeniería Eléctrica, Universidad de la República, Montevideo, Uruguay and DEIS, Bologna University, Bologna, Italy;Centre de Recherche en Epistémologie Appliquée, CNRS, École Polytechnique, Paris, France;Department of Mathematics, Slovak University of Technology, Bratislava, Slovak Republic;CNRS-DEPSN, Institut de Neurobiologie Alfred Fessard, Gif sur Yvette, France;DEIS, Bologna University, Bologna, Italy
Venue:
IEEE Transactions on Image Processing
Year:
2010

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Abstract

We designed a strategy for extracting the shapes of cell membranes and nuclei from time lapse confocal images taken throughout early zebrafish embryogenesis using a partial-differential-equation-based segmentation. This segmentation step is a prerequisite for an accurate quantitative analysis of cell morphodynamics during embryogenesis and it is the basis for an integrated understanding of biological processes. The segmentation of embryonic cells requires live zebrafish embryos fluorescently labeled to highlight sub-cellular structures and designing specific algorithms by adapting classical methods to image features. Our strategy includes the following steps: the signal-to-noise ratio is first improved by an edge-preserving filtering, then the cell shape is reconstructed applying a fully automated algorithm based on a generalized version of the Subjective Surfaces technique. Finally we present a procedure for the algorithm validation either from the accuracy and the robustness perspective.