Connective Tissues Simulation on GPU

International audienceRecent work in the field of medical simulation have led to real advances in the mechanical simulation of organs. However, it is important to notice that, despite the major role they may have in the interaction between organs, the connective tissues are often left out of these simulations. In this paper, we propose a model which can rely on either a mesh based or a meshless methods. To provide a realistic simulation of these tissues, our work is based on the weak form of continuum mechanics equations for hyperelastic soft materials. Furthermore, the stability of deformable objects simulation is ensured by an implicit temporal integration scheme. Our method allows to model these tissues without prior assumption on the dimension of their of their geometry (curve, surface or volume), and enables mechanical coupling between organs. To obtain an interactive frame rate, we develop a parallel version suitable for to GPU computation. Finally we demonstrate the proper convergence of our finite element scheme

Meshless Mechanics and Point-Based Visualization Methods for Surgical Simulations

Computer-based modeling and simulation practices have become an integral part of the medical education field. For surgical simulation applications, realistic constitutive modeling of soft tissue is considered to be one of the most challenging aspects of the problem, because biomechanical soft-tissue models need to reflect the correct elastic response, have to be efficient in order to run at interactive simulation rates, and be able to support operations such as cuts and sutures. Mesh-based solutions, where the connections between the individual degrees of freedom (DoF) are defined explicitly, have been the traditional choice to approach these problems. However, when the problem under investigation contains a discontinuity that disrupts the connectivity between the DoFs, the underlying mesh structure has to be reconfigured in order to handle the newly introduced discontinuity correctly. This reconfiguration for mesh-based techniques is typically called dynamic remeshing, and most of the time it causes the performance bottleneck in the simulation. In this dissertation, the efficiency of point-based meshless methods is investigated for both constitutive modeling of elastic soft tissues and visualization of simulation objects, where arbitrary discontinuities/cuts are applied to the objects in the context of surgical simulation. The point-based deformable object modeling problem is examined in three functional aspects: modeling continuous elastic deformations with, handling discontinuities in, and visualizing a point-based object. Algorithmic and implementation details of the presented techniques are discussed in the dissertation. The presented point-based techniques are implemented as separate components and integrated into the open-source software framework SOFA. The presented meshless continuum mechanics model of elastic tissue were verified by comparing it to the Hertzian non-adhesive frictionless contact theory. Virtual experiments were setup with a point-based deformable block and a rigid indenter, and force-displacement curves obtained from the virtual experiments were compared to the theoretical solutions. The meshless mechanics model of soft tissue and the integrated novel discontinuity treatment technique discussed in this dissertation allows handling cuts of arbitrary shape. The implemented enrichment technique not only modifies the internal mechanics of the soft tissue model, but also updates the point-based visual representation in an efficient way preventing the use of costly dynamic remeshing operations

Trajectory planning with task constraints in densely filled environments

In this paper the problem of computing a rigid object trajectory in an environment populated with deformable objects is addressed. The problem arises in Minimally Invasive Robotic Surgery (MIRS) from the needs of reaching a point of interest inside the anatomy with rigid laparoscopic instruments. We address the case of abdominal surgery. The abdomen is a densely populated soft environment and it is not possible to apply classical techniques for obstacle avoidance because a collision free solution is, most of the time, not feasible. In order to have a convergent algorithm with, at least, one possible solution we have to relax the constraints and allow collision under a specific contact threshold to avoid tissue damaging. In this work a new approach for trajectory planning under these peculiar conditions is implemented. The method computes offline the path which is then tested in a surgical simulator as part of a pre-operative surgical plan

Research on real-time physics-based deformation for haptic-enabled medical simulation

This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room

An interactive meshless cutting model for nonlinear viscoelastic soft tissue in surgical simulators

In this paper, we present a novel interactive cutting simulation model for soft tissue based on the meshless framework. Unlike most existing methods that consider the cutting process of soft tissue in an over simplified manner, the presented model is able to simulate the complete cutting process that includes three stages: deformation before cutting open (DBCO), cutting open (CO), and deformation after cutting open (DACO). To characterize the complicated physical and mechanical properties of soft tissue, both nonlinearity and viscoelasticity were incorporated into the equations governing the motion of soft tissue. A line contact model was used for simulating the cutting process after analyzing the two major types of surgical instruments, i.e., scalpel and electrostick. The cutting speed and angle were taken into account in order to improve haptic rendering. Biomechanical tests and simulation experiments verified the validity of the introduced model. Specifically, the displacement vs. cutting force curves can be divided into three segments corresponding to the three stages of the cutting process. The results were also applied in a liver cutting simulating system and satisfactory visual effect and haptic feedback were achieved

Real-time measurement corrected prediction of soft tissue response for medical simulations

Medical simulators, such as in palpation and disease diagnosis, require an efficient model of the biological soft tissue deformation. Hence, a computationally fast and accurate algorithm is required to support and enhance user interactions in near real-time simulations. The visual accuracy of such simulators is dependent on the user¿s reaction time. Static visual images that update at a rate of 25 Hz are perceived as real-time moving images. Hence, visualizing software requires fast algorithms to compute the deformation of soft tissue to facilitate a meaningful simulation. Furthermore, soft tissue behaviour should be modelled accurately while compatible with real-time computation. This work proposes a fast solver for the linearized finite element method (FEM) and validates the proposed algorithm with experimental results. The novelty of the method lies in the utilization of real-time force/displacement measurements that are embedded in the solution via the Kalman filter. A novel computational algorithm that utilizes the strength of the FEM in terms of accuracy and employs direct measurements from the manipulated tissue to overcome the slow computational process of the FEM is proposed in the first part of the thesis. As the behaviour of the mechanically loaded tissue can be regarded as linearly responding at each time step, a constant acceleration temporal discretization method, i.e., the Newmark-ß is employed. In real-time applications, the accuracy of the target variable highly depends on the accuracy of the inputs while differentiating noise from the signal is hardly ever possible. To address this problem, a Kalman filter-based method is developed. The proposed algorithm not only filters the noise from the measurements but also adapts the filter gain to the estimates of the target variable, i.e., the resulting tissue deformation. For a simulated tension test of a cubic model, the proposed algorithm achieves the update frequency of 63.3 Hz. This rate is a significant improvement in computational speed compared to the 5.8 Hz update rate by the classic FEM. Besides, this novel combination of the KF and the FEM makes it possible to expand the displacement estimates in the spatial domain when the measurements are only partially available at certain points. The performance of the above method is validated experimentally through a comparison with indentation tests on artificial human tissue-like material and with the FEM result under identical simulation conditions. The test is repeated on several samples, and the displacement variation from the FEM outcome is considered as the model error. Simulation results show that the proposed method achieves the deformation update frequency of 145.7 Hz compared to the 2.7 Hz from the reference FEM. The proposed method shows the same predictive ability, only 0.47% difference from FEM on average. Experimental validation of the proposed KF-FEM confirms that by consideration of both the measurement noise and the model error, the proposed method is capable of achieving high-frequency response without sacrificing the accuracy. Further to this, the experiments confirmed the linearized model response is reliable within the applied displacement range and therefore proving that KF can be employed. The developed KF-FEM was modified in the next study to address the problem resulting from inaccurate external loads measurements by the force sensors. In the modified version, both the external force, i.e., driving variable, and the displacement, i.e., driven variable, are taken as system states. It is considered that the uncertainty of the model input influences the accuracy of the system estimates. The modified model is calibrated to differentiate the system noise from the input noise. Numerical simulations were conducted on a liver shape geometrical model, and the simulation results demonstrate that more than 90% of the measurement noise is removed. The computational speed is also increased, delivering up to 89 Hz update rate. While the uncertainty of the external load is replicated in the displacements in an FEM solution, the developed algorithm can differentiate the measurement noise, including the displacement and external forces, from the system error, i.e., the FE model error. In the last study, the proposed model was developed to reflect the nonlinear behaviour of the manipulated tissue. The Central Difference time discretization method was used to model large deformations. A novel feature is that the Equation of motion is formulated within the element level rather than in the global spatial domain. This approach helped to improve the computational speed. Indentation with strains of slightly over 10% was simulated to assess the performance of the proposed model. The developed algorithm achieved the 33.85 Hz update frequency on a standard-issue PC and confirmed its suitability for real-time applications. Also, the proposed model achieved estimates with a maximum 5.75% mean absolute error (MAE) concerning the measurements while the classic FEM showed 6.20% MAE under identical simulation condition. Results confirm that deformation estimates for noisy boundary loads of the FEM can be improved with the help of direct measurements and yet be realistic in terms of real-time visual update. This study proposed a novel computational algorithm that achieved update frequencies of higher than 25 Hz to be perceived as real-time in human eyes. The developed KF-FEM model has also shown the potential of improving the FEM accuracy with the help of direct measurements. The proposed algorithm used partially available measurements and expanded its estimates in the spatial domain. The method was experimentally validated, and the model input uncertainty, as well as the nonlinear behaviour of the soft tissue, were assessed and verified

Virtual reality surgery simulation: A survey on patient specific solution

For surgeons, the precise anatomy structure and its dynamics are important in the surgery interaction, which is critical for generating the immersive experience in VR based surgical training applications. Presently, a normal therapeutic scheme might not be able to be straightforwardly applied to a specific patient, because the diagnostic results are based on averages, which result in a rough solution. Patient Specific Modeling (PSM), using patient-specific medical image data (e.g. CT, MRI, or Ultrasound), could deliver a computational anatomical model. It provides the potential for surgeons to practice the operation procedures for a particular patient, which will improve the accuracy of diagnosis and treatment, thus enhance the prophetic ability of VR simulation framework and raise the patient care. This paper presents a general review based on existing literature of patient specific surgical simulation on data acquisition, medical image segmentation, computational mesh generation, and soft tissue real time simulation

Point Primitives Based Virtual Surgery System

In order to achieve a high degree of visual realism in surgery simulation, we present a virtual surgery system framework, which is based on point primitives for the virtual surgery scene rendering and the biomechanical calculation of the soft tissue. To embody the superiority of this framework, two virtual surgery systems based on point primitives we developed are exhibited in this paper. Six critical functional modules were selected as representative of basic and advanced virtual surgery skill. These modules were: 1) point-based texture mapping; 2) deformation simulation; 3) cutting simulation; 4) tearing simulation; 5) dynamic texture mapping; and 6) 3-D display. These modules were elaborated by including working principle, execution process, and the performance of the algorithm. The experimental results have shown that point primitives-based virtual surgery systems obtained higher performance in terms of computational efficiency and rendering effect than traditional meshes-based virtual surgery system