Embryo Cell Membranes Reconstruction by Tensor Voting

Gaël Michelin 1, * Léo Guignard 2, 3 Ulla-Maj Fiuza 2 Grégoire Malandain 1
* Corresponding author
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
3 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales, INRA - Institut National de la Recherche Agronomique, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Image-based studies of developing organs or embryos produce a huge quantity of data. To handle such high-throughput experimental protocols, automated computer-assisted methods are highly desirable. This article aims at designing an efficient cell segmentation method from microscopic images. The proposed approach is twofold: first, cell membranes are enhanced or extracted by the means of structure-based filters, and then perceptual grouping (i.e. tensor voting) allows to correct for segmentation gaps. To decrease the computational cost of this last step, we propose different methodologies to reduce the number of voters. Assessment on real data allows us to deduce the most efficient approach.
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Submitted on : Monday, December 9, 2013 - 9:13:22 AM
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Gaël Michelin, Léo Guignard, Ulla-Maj Fiuza, Grégoire Malandain. Embryo Cell Membranes Reconstruction by Tensor Voting. ISBI - International Symposium on Biomedical Imaging, Apr 2014, Beijing, China. ⟨10.1109/ISBI.2014.6868105 ⟩. ⟨hal-00915000v2⟩



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