Matthieu Chabanas

Simulation of dynamic orofacial movements using a constitutive law varying with muscle activation

This paper presents a biomechanical model of the face to simulate orofacial movements in speech and non-verbal communication. A 3D finite element model, based on medical images of a subject, is presented. A hyperelastic Mooney–Rivlin constitutive law accounts for the non-linear behaviour of facial tissue. Muscle fibres are represented by piece-wise uniaxial tensile element that generate force. The stress stiffening effect, an increase in the stiffness of the muscles when activated, is modelled by varying the constitutive law of the tissue with the level of activation of the muscle. A large number of facial movements occurring during speech and facial mimics are simulated. Results show that our modelling approach provides a realistic account of facial mimics. The differences between dynamic vs. quasi-static simulations are also discussed, proving that dynamic trajectories better fit experimental data.

A 3D Finite Element Model of the Face for Simulation in Plastic and Maxillo-Facial Surgery

This paper introduces a new Finite Element biomechanical model of the human face, which has been developed to be integrated into a simulator for plastic and maxillo-facial surgery. The idea is to be able to predict, from an aesthetic and functional point of view, the deformations of a patient face, resulting from repositioning of the maxillary and mandibular bone structures. This work will complete the simulator for bone-repositioning diagnosis that has been developed by the laboratory. After a description of our research project context, each step of the modeling is precisely described: the continuous and elastic structure of the skin tissues, the orthotropic muscular fibers and their insertions points, and the functional model of force generation. First results of face deformations due to muscles activations are presented. They are qualitatively compared to the functional studies provided by the literature on face muscles roles and actions.

Biomechanical models to simulate consequences of maxillofacial surgery

This paper presents the biomechanical finite element models that have been developed in the framework of the computer-assisted maxillofacial surgery. After a brief overview of the continuous elastic modelling method, two models are introduced and their use for computer-assisted applications discussed. The first model deals with orthognathic surgery and aims at predicting the facial consequences of maxillary and mandibular osteotomies. For this, a generic three-dimensional model of the face is automatically adapted to the morphology of the patient by the mean of elastic registration. Qualitative simulations of the consequences of an osteotomy of the mandible can thus be provided. The second model addresses the Sleep Apnoea Syndrome. Its aim is to develop a complete modelling of the interaction between airflow and upper airways walls during breathing. Dynamical simulations of the interaction during a respiratory cycle are computed and compared with observed phenomena.

Efficient 3d finite element modeling of a muscle-activated tongue

We describe our investigation of a fast 3D finite element method (FEM) for biomedical simulation of a muscle-activated human tongue. Our method uses a linear stiffness-warping scheme to achieve simulation speeds which are within a factor 10 of real-time rates at the expense of a small loss in accuracy. Muscle activations are produced by an arrangement of forces acting along selected edges of the FEM geometry. The models dynamics are integrated using an implicit Euler formulation, which can be solved using either the conjugate gradient method or a direct sparse solver. To assess the utility of this model, we compare its accuracy against slower, but less approximate, simulations of a reference tongue model prepared using the FEM simulation package ANSYS

Resection-induced brain-shift compensation using vessel-based methods

Most brain-shift compensation methods address the problem of updating preoperative images to reflect brain deformations following the craniotomy and dura opening. However, fewer enable to take into account the resection-induced deformations occuring all along the tumor removal procedure. This paper evaluates the use of two existing methods to tackle that problem. Both techniques rely on blood vessels segmented then skeletonized from preoperative MR Angiography and navigated Doppler Ultrasound images acquired during resection. While the first one proposes to register the vascular trees using a rigid modified ICP algorithm, the second method relies on a non-rigid constrained-based biomechanical approach. Quantitative results are provided, based on distances between paired landmarks set on blood vessels then anatomical structures delineated on medical images. A qualitative evaluation of the compensation is also presented using initial and updated images. An analysis on three cases of surface tumor shows both methods, especially the biomechanical one, can compensate up to 63% of the brain-shift, with an error in the range of 2 mm. However, these results are not reproduced on a more complex case of deep tumor. While more patients must be included, these preliminary results show that vesselbased methods are well suited to compensate for resection-induced brain-shift, but better outcomes in complex cases still require to improve the methods to take the resection into account.