A 3D discrete model of the diaphragm and human trunk

In this paper, a 3D discrete model is presented to model the movements of the trunk during breathing. In this model, objects are represented by physical particles on their contours. A simple notion of force generated by a linear actuator allows the model to create forces on each particle by way of a geometrical attractor. Tissue elasticity and contractility are modeled by local shape memory and muscular fibers attractors. A specific dynamic MRI study was used to build a simple trunk model comprised of by three compartments: lungs, diaphragm and abdomen. This model was registered on the real geometry. Simulation results were compared qualitatively as well as quantitatively to the experimental data, in terms of volume and geometry. A good correlation was obtained between the model and the real data. Thanks to this model, pathology such as hemidiaphragm paralysis can also be simulated.Comment: published in: "Lung Modelling", France (2006

3D-2D ultrasound feature-based registration for navigated prostate biopsy: A feasibility study

International audienceThe aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity-based function. The results are encouraging and show acceptable errors with simulated transforms applied on ultrasound volumes from real patients

Shell finite element model for interactive fetal head deformation during childbirth

International audienceIn this paper, we design a flat shell finite element model in order to simulate the fetal head deformation during childbirth. This new method also guarantees the incompressibility of the fetal head enclosed volume

In vivo measurement of human brain elasticity using a light aspiration device

The brain deformation that occurs during neurosurgery is a serious issue impacting the patient "safety" as well as the invasiveness of the brain surgery. Model-driven compensation is a realistic and efficient solution to solve this problem. However, a vital issue is the lack of reliable and easily obtainable patient-specific mechanical characteristics of the brain which, according to clinicians' experience, can vary considerably. We designed an aspiration device that is able to meet the very rigorous sterilization and handling process imposed during surgery, and especially neurosurgery. The device, which has no electronic component, is simple, light and can be considered as an ancillary instrument. The deformation of the aspirated tissue is imaged via a mirror using an external camera. This paper describes the experimental setup as well as its use during a specific neurosurgery. The experimental data was used to calibrate a continuous model. We show that we were able to extract an in vivo constitutive law of the brain elasticity: thus for the first time, measurements are carried out per-operatively on the patient, just before the resection of the brain parenchyma. This paper discloses the results of a difficult experiment and provide for the first time in-vivo data on human brain elasticity. The results point out the softness as well as the highly non-linear behavior of the brain tissue.Comment: Medical Image Analysis (2009) accept\'

Initial validation of a virtual-reality learning environment for prostate biopsies: realism matters!

: Introduction-objectives: A virtual-reality learning environment dedicated to prostate biopsies was designed to overcome the limitations of current classical teaching methods. The aim of this study was to validate reliability, face, content and construct of the simulator. Materials and methods: The simulator is composed of a) a laptop computer, b) a haptic device with a stylus that mimics the ultrasound probe, c) a clinical case database including three dimensional (3D) ultrasound volumes and patient data and d) a learning environment with a set of progressive exercises including a randomized 12-core biopsy procedure. Both visual (3D biopsy mapping) and numerical (score) feedback are given to the user. The simulator evaluation was conducted in an academic urology department on 7 experts and 14 novices who each performed a virtual biopsy procedure and completed a face and content validity questionnaire. Results: The overall realism of the biopsy procedure was rated at a median of 9/10 by non-experts (7.1-9.8). Experts rated the usefulness of the simulator for the initial training of urologists at 8.2/10 (7.9-8.3), but reported the range of motion and force feedback as significantly less realistic than novices (p=0.01 and 0.03 respectively). Pearson's r correlation coefficient between correctly placed biopsies on the right and left side of the prostate for each user was 0.79 (p<0.001). The 7 experts had a median score of 64% (59-73), and the 14 novices a median score of 52% (43-67), without reaching statistical significance (p=0,19). Conclusion: The newly designed virtual reality learning environment proved its versatility and its reliability, face and content were validated. Demonstrating the construct validity will require improvements to the realism and scoring system used

Hand-Eye Calibration of a Robot -UltraSound Probe System without any 3D Localizers

International audience3D UltraSound (US) probes are used in clinical applications for their ease of use and ability to obtain intra-operative volumes. In surgical navigation applications a calibration step is needed to localize the probe in a general coordinate system. This paper presents a new hand-eye calibration method using directly the kinematic model of a robot and US volume registration data that does not require any 3D localizers. First results show a targeting error of 2.34 mm on an experimental setup using manual segmentation of five beads in ten US volumes

Environnement générique pour la validation de simulations médicales

Dans le cadre des simulations pour l'entrainement, le planning, ou l'aide per-opératoire aux gestes médicaux-chirurgicaux, de nombreux modèles ont été développés pour décrire le comportement mécanique des tissus mous. La vérification, la validation et l'évaluation sont des étapes cruciales en vue de l'acceptation clinique des résultats de simulation. Ces tâches, souvent basées sur des comparaisons avec des données expérimentales ou d'autres simulations, sont rendues difficiles par le nombre de techniques de modélisation existantes, le nombre d'hypothèses à considérer et la difficulté de réaliser des expériences réelles utilisables. Nous proposons un environnement de comparaison basé sur une analyse du processus de modélisation et une description générique des éléments constitutifs d'une simulation (e.g. géométrie, chargements, critère de stabilité) ainsi que des résultats (expérimentaux ou provenant d'une simulation). La description générique des simulations permet d'effectuer des comparaisons avec diverses techniques de modélisation (e.g. masse-ressorts, éléments finis) implémentées sur diverses plateformes de simulation. Les comparaisons peuvent être faites avec des expériences réelles, d'autres résultats de simulation ou d'anciennes versions du modèle grâce à la description commune des résultats, et s'appuient sur un ensemble de métriques pour quantifier la précision et la vitesse de calcul. La description des résultats permet également de faciliter l'échange d'expériences de validation. La pertinence de la méthode est montrée sur différentes expériences de validation et de comparaison de modèles. L'environnement et ensuite utilisé pour étudier l'influence des hypothèses de modélisations et des paramètres d'un modèle d'aspiration de tissu utilisé par un dispositif de caractérisation des lois de comportement. Cette étude permet de donner des pistes pour l'amélioration des prédictions du dispositif.Numerous models have been developed to describe the mechanical behavior of soft tissues for medical simulation. Verification, validation and evaluation are crucial steps towards the acceptance of simulation results by clinicians. These tasks, often based on comparisons between simulation results and experimental data or other simulations, are difficult because of the wide range of available modeling techniques, the number of possible assumptions, and the difficulty to perform validation experiments. A comparison framework is proposed based on the analysis of the modelisation process and on a generic description of both constitutive elements of a simulation (e.g. geometry, loads, stability criterion) and results (from simulations or experiments). Generic description allows comparisons between different modeling techniques implemented in various simulation platforms. Comparisons can be performed against real experiments, other simulation results or previous versions of a model thanks to the generic description of results and use a set of metrics to quantify both accuracy and computational efficiency. This description also facilitates validation experiments sharing. The usability of the method is shown on several validation and comparison experiments. The framework is then used to investigate the influence of modeling assumptions and parameters in a biomechanical finite element model of an in-vivo tissue aspiration device. This study gives clues towards the improvement of the predictions of the characterization device.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Algebraic and analytic reconstruction methods for dynamic tomography.

In this work, we discuss algebraic and analytic approaches for dynamic tomography. We present a framework of dynamic tomography for both algebraic and analytic approaches. We finally present numerical experiments

Comparison of LASTIC (Light Aspiration device for in vivo Soft TIssue Characterization) with classic Tensile Tests.

International audienceLASTIC is a device estimating in vivo soft tissue elasticity. It uses negative pressure to deform the tissue surface and captures several deformation stages to trace the behavioral curve. Using Finite Element inverse analysis and a Neo Hookean constitutive law, the tissue's Young modulus is evaluated. This paper compares LASTIC capabilities with standard tensile tests on four samples with elastic properties ranging from 10 kPa to 100 kPa. Although LASTIC overestimates Young modulus by an average of 24 %, it allows a first estimation of the elastic modulus of different materials

Using CamiTK for rapid prototyping of interactive Computer Assisted Medical Intervention applications

Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc