Caractérisation automatique d’organisations cellulaires dans des mosaïques d'images microscopiques de bois. Application à l'identification des files cellulaires

Abstract : This study focuses on biological numeric image processes. It aims to define and implement new automated measurements at large scale analysis. Moreover, this thesis addresses : the incidence of the proposed methodology on the results reliability measurements accuracy definition and analysis proposed approaches reproducibility limits when applied to plant biology. This work is part of cells organization study, and aims to automatically identify and analyze the cell lines in microscopic mosaic wood slice pictures. Indeed, the study of biological tendencies among the cells lines is necessary to understand the cell migration and organization. Such a study can only be realized from a huge zone of observation of wood plane. To this end, this work proposes : • a new protocol of preparation (slices of sanded wood) and of digitizing of samples, in order to acquire the entire zone of observation without bias, • a novel processing chain that permit the automated cell lines extraction in numeric mosaic images, • the definition of reliability indexes for each measurement allowing further efficient statistical analysis. The methods developed during this thesis enable to acquire and treat rapidly an important volume of information. Those data define the basis of numerous investigations, such as tree architectural analysis cell lines following and/or detection of biological perturbations. And it finally helps the analysis of the variability intra- or inter- trees, in order to better understand the tree endogenous growth.
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Submitted on : Monday, November 3, 2014 - 5:15:45 PM
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Guilhem Brunel. Caractérisation automatique d’organisations cellulaires dans des mosaïques d'images microscopiques de bois. Application à l'identification des files cellulaires. Bio-informatique [q-bio.QM]. UNIVERSITE MONTPELLIER II SCIENCES ET TECHNIQUES DU LANGUEDOC, 2014. Français. ⟨tel-01079815⟩

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