Embryo Cell Membranes Reconstruction by Tensor Voting

Gaël Michelin 1, * Léo Guignard 2, 3 Ulla-Maj Fiuza 2 Grégoire Malandain 1
* Auteur correspondant
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, SIS - Signal, Images et Systèmes
3 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, Centre de coopération internationale en recherche agronomique pour le développement [CIRAD] : UMR51
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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Communication dans un congrès
ISBI - International Symposium on Biomedical Imaging, Apr 2014, Beijing, China. IEEE, Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on 2014, <10.1109/ISBI.2014.6868105 >
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Contributeur : Gaël Michelin <>
Soumis le : lundi 9 décembre 2013 - 09:13:22
Dernière modification le : jeudi 2 février 2017 - 15:59:28

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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. IEEE, Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on 2014, <10.1109/ISBI.2014.6868105 >. <hal-00915000v2>

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