Medical simulation has facilitated the understanding of complex biological phenomenon through its inherent explanatory power. It is a critical component for planning clinical interventions and analyzing its effect on a human subject. The success of medical simulation is evidenced by the fact that over one third of all medical schools in the United States augment their teaching curricula using patient simulators. Medical simulators present combat medics and emergency providers with video-based descriptions of patient symptoms along with step-by-step instructions on clinical procedures that alleviate the patient's condition. Recent advances in clinical imaging technology have led to an effective medical visualization by coupling medical simulations with patient-specific anatomical models and their physically and physiologically realistic organ deformation. 3D physically-based deformable lung models obtained from a human subject are tools for representing regional lung structure and function analysis. Static imaging techniques such as Magnetic Resonance Imaging (MRI), Chest x-rays, and Computed Tomography (CT) are conventionally used to estimate the extent of pulmonary disease and to establish available courses for clinical intervention. The predictive accuracy and evaluative strength of the static imaging techniques may be augmented by improved computer technologies and graphical rendering techniques that can transform these static images into dynamic representations of subject specific organ deformations. By creating physically based 3D simulation and visualization, 3D deformable models obtained from subject-specific lung images will better represent lung structure and function. Variations in overall lung deformations may indicate tissue pathologies, thus 3D visualization of functioning lungs may also provide a visual tool to current diagnostic methods. The feasibility of medical visualization using static 3D lungs as an effective tool for endotracheal intubation was previously shown using Augmented Reality (AR) based techniques in one of the several research efforts at the Optical Diagnostics and Applications Laboratory (ODALAB). This research effort also shed light on the potential usage of coupling such medical visualization with dynamic 3D lungs. The purpose of this dissertation is to develop 3D deformable lung models, which are developed from subject-specific high resolution CT data and can be visualized using the AR based environment. A review of the literature illustrates that the techniques for modeling real-time 3D lung dynamics can be roughly grouped into two categories: Geometrically-based and Physically-based. Additional classifications would include considering a 3D lung model as either a volumetric or surface model, modeling the lungs as either a single-compartment or a multi-compartment, modeling either the air-blood interaction or the air-blood-tissue interaction, and considering either a normal or pathophysical behavior of lungs. Validating the simulated lung dynamics is a complex problem and has been previously approached by tracking a set of landmarks on the CT images. An area that needs to be explored is the relationship between the choice of the deformation method for the 3D lung dynamics and its visualization framework. Constraints on the choice of the deformation method and the 3D model resolution arise from the visualization framework. Such constraints of our interest are the real-time requirement and the level of interaction required with the 3D lung models. The work presented here discusses a framework that facilitates a physics-based and physiology-based deformation of a single-compartment surface lung model that maintains the frame-rate requirements of the visualization system. The framework presented here is part of several research efforts at ODALab for developing an AR based medical visualization framework. The framework consists of 3 components, (i) modeling the Pressure-Volume (PV) relation, (ii) modeling the lung deformation using a Green's function based deformation operator, and (iii) optimizing the deformation using state-of-art Graphics Processing Units (GPU). The validation of the results obtained in the first two modeling steps is also discussed for normal human subjects. Disease states such as Pneumothorax and lung tumors are modeled using the proposed deformation method. Additionally, a method to synchronize the instantiations of the deformation across a network is also discussed.

Le contexte de ma thèse rentre dans le cadre du projet IMD3D, supporté par le FUI. L'objectif de ce projet consiste à proposer une méthode automatisée permettant la décoration d'objets 3D quelconques. La solution choisie consiste à positionner un film imprimé dans le moule, ce film sera déformé par la fermeture du moule puis par injection. Ma thèse porte sur la génération de décoration. Les données dont nous disposons en entrée sont un maillage et une ou plusieurs images. Nous souhaitons d'abord obtenir le plaquage de cette image sur le maillage, de telle sorte que le rendu visuel soit équivalent à l'image initiale. Pour cela, nous avons décidé de choisir un point de vue par image et de le favoriser. Nous paramétrions alors le maillage par le biais d'une projection orthogonale ou perspective définie par ce point de vue. Nous réalisons alors la transformée inverse de déformation du maillage. L'utilisation d'une application conforme pour la déformation inverse permet de coller au mieux à la physique du problème. Nous visualisons donc le résultat à imprimer sur le film. Il reste alors à générer la texture permettant de décorer l'objet injecté par le procédé. Il suffit de parcourir bilinéairement l'intérieur des mailles et simultanément la partie de l'image correspondante, de manière à remplir les pixels de l'image. Ceci permet d'obtenir finalement la texture finale qui sera imprimée sur le film. Mais, lors des premiers essais effectués par les industriels avec une mire colorée, un effet de décoloration a été relevé. Nous avons donc pris en compte ce changement de couleur pour modifier l'image et obtenir le résultat visuel escompte, même au niveau du rendu des couleurs / This work takes part in a global industrial project called IMD3D, which is supported by FUI and aims at decorating 3D plastic objects using Insert Molding technology with an automated process. Our goal is to compute the decoration of 3D virtual objects, using data coming from polymer film characterization and mechanical simulation. My thesis deals with the generation of decoration. Firstly, we want to map the texture onto the mesh, so that the visual rendering would be equivalent to the initial picture. In order to do so, we decided to choose a viewpoint per texture and to favor it. Thus, a specific view-dependent parameterization is defined. Thus, the first goal which is to define the texture mapping with visual constraints is reached. After this step, the inverse distortion of the mesh is performed. The use of a conformal map for this inverse transform allows to respect the physics issues. Therefore we get a planar mesh representing the initial mesh of simulation whose associated textures have also been modified by this transform. The result to be printed on the film can be viewed. Finally, the texture enabling the decoration of the object injected by the process can be generated. This texture combines information from several mapped images. The inner part of the mesh and in the same time the part of the corresponding texture shall be followed in a bilinear way in order to fill the pixel of the generated picture. But during the first tests performed by industries with a colors pattern, a discoloration effect was detected. As a consequence, we thought to take into account this color change to modify the picture and to obtain the expected visual rendering