Modèles déformables pour la segmentation et la modélisation d'images médicales 3D et 4D

Dans cette these, nous nous interessons a l'utilisation des modeles deformables surfaciques pour la segmentation d'images 3D et 4D. Dans un premier temps, nous nous sommes attaches a contraindre l'espace des deformations admissibles du modele afin de rendre le processus de deformation plus fiable. Nous avons utilise le formalisme des maillages simplexes pour exprimer des contraintes regularisantes de la surface. Nous avons developpe un processus evolutif de deformation combinant une transformation globale ayant peu de degres de liberte et un champ de deformations locales. Il permet de controler le nombre de degres de liberte offerts au modele surfacique de maniere simple et efficace. Nous avons egalement cherche a enrichir la connaissance a priori des donnees apportee par le modele. Nous utilisons des contraintes de forme pour faciliter la segmentation des structures a reconstruire, notamment dans les zones ou les donnees de l'image sont bruitees ou lacunaires. Nous nous sommes egalement interesses a la convergence formelle du processus de deformation. Nous avons developpe un algorithme de changement de topologie des modeles discrets que nous avons compare a l'approche par ensembles de niveaux. Dans un deuxieme temps, nous nous sommes interesses a la definition du terme d'attache aux donnees pour differents types d'images 3D. Nous avons envisage plusieurs geometries rencontrees dans les images medicales. Nous avons etudie l'apport d'une information sur les regions ou sur la distribution des niveaux de gris de l'image pour la deformation ou le recalage multimodal d'un modele. Finalement, nous nous sommes interesses a la segmentation de sequences temporelles d'images cardiaques 2D ou 3D. La prise en compte de l'information temporelle permet d'introduire de nouvelles contraintes de deformations. Nous avons mis nos methodes en pratique avec la segmentation d'images ou des sequences d'images cardiaques provenant de differentes modalites d'acquisition.

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