Skip to Main content Skip to Navigation

Axonal morphology analysis : from image processing to modelling

Alejandro Ricardo Mottini d'Oliveira 1
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : The morphological analysis of axonal trees is an important problem in neuroscience. It has been shown that the morphological characteristics of thesestructures provide information on their functioning and allows the characterization of pathological states. Therefore, it is of great importance to develop methods to analyze their shape and to quantify differences between structures. In this thesis we propose a method for the comparison of axonal trees that takes into account both topological and geometrical information. Using this method, which is based on the Elastic Shape Analysis Framework, we can compute the geodesic path between two axons and the mean shape of a population of trees. In addition, we derive a classfication scheme based on this metric and compare it with state of the art approaches. Finally, we propose a 2D discrete stochastic model for the simulation of axonal biogenesis. The model is defined by a third order Markov Chain and considers two main processes: the growth process that models the elongation and shape of the neurites and the bifurcation process that models the generation of branches. The growth process depends, among other variables, on an external attraction field. Both techniques were validated on a database of real fluorescent confocal microscopy images of neurons within Drosophila fly brains. Both normal neurons and neurons in which certain genes were inactivated have been considered. Results show that the proposed comparison method obtains better results that other methods found in the literature, and that the model parameter values provide information about the growth properties of the populations.
Document type :
Complete list of metadatas

Cited literature [81 references]  Display  Hide  Download
Contributor : Abes Star :  Contact
Submitted on : Friday, March 6, 2015 - 11:46:23 PM
Last modification on : Monday, October 12, 2020 - 10:30:35 AM
Long-term archiving on: : Sunday, June 7, 2015 - 9:35:23 PM


Version validated by the jury (STAR)


  • HAL Id : tel-01074620, version 2



Alejandro Ricardo Mottini d'Oliveira. Axonal morphology analysis : from image processing to modelling. Other. Université Nice Sophia Antipolis, 2014. English. ⟨NNT : 2014NICE4066⟩. ⟨tel-01074620v2⟩



Record views


Files downloads