Serpentes

Les serpents, de nom scientifique Serpentes, forment un sous-ordre de squamates carnivores au corps très allongé et dépourvus de membres apparents. Il s'agit plus précisément de vertébrés amniotes caractérisés par un tégument recouvert d'écailles, imbriquées les unes sur les autres et protégées par une couche cornée épaisse, et par une thermorégulation assurée par trois mécanismes, l'ectothermie, la poïkilothermie et le bradymétabolisme. Ils sont aussi appelés plus rarement Ophidiens (du grec ). Les serpents ont comme caractéristiques spécifiques d'avoir une langue bifide, des yeux sans paupière, un crâne articulé et des mâchoires mobiles qui facilitent l'ingestion de proies. Ils partagent la disparition des pattes avec deux autres groupes de vertébrés tétrapodes : les amphisbènes, qui sont d'autres squamates, et les gymnophiones, qui appartiennent au groupe des lissamphibiens. Au cours de leur longue évolution qui remonte au Crétacé, les serpents ont perfectionné plusieurs modes d

Introduction to discrete modelling : Modelling slithering locomotion

Meriton Beqiraj

The study of animal locomotion is vast since animals have various shapes and modes of locomotion. It finds multiple applications especially in robotics. In this report, the focus will be put on snake locomotion. However snakes still have various techniques for moving their bodies such as unilateral contraction/extension of their belly, accordion-like, side-winding or lateral undulation of the body. This report will focus on the last gait mentioned. Studies have already shown how snakes move around push points and applications to wheeled-snake robots have been made. However in some cases snakes may have to move their body over flat surfaces without any rocks or branches to push on. From that observation, the need for a new model considering frictional anisotropy is raised. A mathematical model for slithering locomotion based on frictional anisotropy with all the assumptions implied will firstly be addressed. Then some elements of the work will be kept and focus particularly on the friction force will be put in order to get a better understanding of its need and origin through two models. To conclude, the anisotropy will be seen in the context of biotribology.

2018

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Anaïs Laure Marie-Thérèse Badoual

Ongoing advances in imaging techniques create new demands regarding the analysis of images in medicine and biology. Image segmentation is a key step of many image analysis pipelines and its proper execution is a particularly challenging task. This thesis is dedicated to the development of segmentation algorithms for biomedical structures in 2D and 3D images. In this work, we aim to improve upon classical parametric active contours/surfaces, whose limitations we address. This thesis is organized in three parts. First, we introduce two representation models. They adapt their resolution to the level of detail of the object to be segmented. We then focus on the formulation of cost functions, called energies, that guide the curve/surface toward the boundary of the target in the image. Among others, we present novel energies based on ridge and texture information. Finally, with these two ingredients in hand, we design new semi-automated active contours/surfaces, also called snakes, for various applications. Our methods are generic enough to be used with a broad variety of data. In particular, we illustrate their performance in segmenting real biomedical images. In addition to those three parts, we provide mathematical tools for signal processing that we designed to efficiently process periodic functions. To find the optimal curve/surface that best fits a given target, we adopt throughout the thesis a subdivide and conquer strategy. First, we look at several smoothed versions of the original image and, for each, adapt the resolution of the snake curve/surface to the level of detail of the target (i.e., subdivide). Then, we segment the object of interest at each resolution recursively, from the coarsest to the finest image (i.e., conquer). This robust subdivide and conquer strategy exploits the multiresolution property of our curve/surface representations, as well as characteristics of smoothed images (few details and low noise). Finally, we give a special attention to the conversion of our algorithms into usable software that respect the open-source, user-friendly and reproducibility criteria.

EPFL2019

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Anaïs Laure Marie-Thérèse Badoual

EPFL2019

Introduction to discrete modelling : Modelling slithering locomotion

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Active contours for lipreading - combining snakes with templates

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Introduction to discrete modelling : Modelling slithering locomotion

Active contours for lipreading - combining snakes with templates