Real-time simulation of surgical cutting in biological tissues using a semi-implicit time integration scheme (original) (raw)
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Real-Time Nonlinear Finite Element Analysis for Surgical Simulation Using Graphics Processing Units
Lecture Notes in Computer Science
Clinical employment of biomechanical modelling techniques in areas of medical image analysis and surgical simulation is often hindered by conflicting requirements for high fidelity in the modelling approach and high solution speeds. We report the development of techniques for high-speed nonlinear finite element (FE) analysis for surgical simulation. We employ a previously developed nonlinear total Lagrangian explicit FE formulation which offers significant computational advantages for soft tissue simulation. However, the key contribution of the work is the presentation of a fast graphics processing unit (GPU) solution scheme for the FE equations. To the best of our knowledge this represents the first GPU implementation of a nonlinear FE solver. We show that the present explicit FE scheme is well-suited to solution via highly parallel graphics hardware, and that even a midrange GPU allows significant solution speed gains (up to 16.4×) compared with equivalent CPU implementations. For the models tested the scheme allows realtime solution of models with up to 16000 tetrahedral elements. The use of GPUs for such purposes offers a cost-effective high-performance alternative to expensive multi-CPU machines, and may have important applications in medical image analysis and surgical simulation.
New finite element algorithm for surgical simulation
2006
We propose an efficient numerical algorithm for computing deformations of "very" soft tissues (such as the brain, liver, kidney etc.), with applications to real time surgical simulation. The algorithm is based on the finite element method using the Total Lagrangian formulation, where stresses and strains are measured with respect to the original configuration. This choice allows for pre-computing of most spatial derivatives before the commencement of the time-stepping procedure. We used explicit time integration that eliminated the need for iterative equation solving during the time stepping procedure. The algorithm is capable of handling both geometric and material non-linearities. Stability analysis of the algorithm suggests that due to much lower stiffness of very soft tissues than that of typical engineering materials, integration time steps a few order of magnitude larger than what is typically used in engineering simulations are possible. A numerical example confirms the accuracy and efficiency of the proposed Total Lagrangian Explicit Dynamics (TLED) algorithm.
Efficient linear elastic models of soft tissues for real-time surgery simulation
Studies in health technology and informatics, 1999
In this paper, we describe the basic components of a surgery simulator prototype developed at INRIA. We present two physical models which are well suited for surgery simulation. These models are based on linear elasticity theory and finite elements modeling. The former model can deforme large tetrahedral meshes in real-time but does not allow any topological changes. On the contrary, the latter biomechanical model can simulate the cutting and tearing of soft tissue but must have a limited number of vertices to run in real-time. We propose a method for combining these two approaches into a hybrid model which may allow real time deformations and cuttings of large enough anatomical structures.
Medical image analysis, 2009
Real time computation of soft tissue deformation is important for the use of augmented reality devices and for providing haptic feedback during operation or surgeon training. This requires algorithms that are fast, accurate and can handle material nonlinearities and large deformations. A set of such algorithms is presented in this paper, starting with the finite element formulation and the integration scheme used and addressing common problems such as hourglass control and locking. The computation examples presented prove that by using these algorithms, real time computations become possible without sacrificing the accuracy of the results. For a brain model having more than 7,000 degrees of freedom, we computed the reaction forces due to indentation with frequency of around 1,000 Hz using a standard dual core PC. Similarly, we conducted simulation of brain shift using a model with more than 50,000 degrees of freedom in less than one minute. The speed benefits of our models result fr...
High-Speed Nonlinear Finite Element Analysis for Surgical Simulation Using Graphics Processing Units
IEEE Transactions on Medical Imaging, 2000
The use of biomechanical modelling, especially in conjunction with finite element analysis, has become common in many areas of medical image analysis and surgical simulation. Clinical employment of such techniques is hindered by conflicting requirements for high fidelity in the modelling approach, and fast solution speeds. We report the development of techniques for high-speed nonlinear finite element analysis for surgical simulation. We use a fully nonlinear total Lagrangian explicit finite element formulation which offers significant computational advantages for soft tissue simulation. However, the key contribution of the work is the presentation of a fast graphics processing unit (GPU) solution scheme for the finite element equations. To the best of our knowledge, this represents the first GPU implementation of a nonlinear finite element solver. We show that the present explicit finite element scheme is well suited to solution via highly parallel graphics hardware, and that even a midrange GPU allows significant solution speed gains (up to 16 8 ) compared with equivalent CPU implementations. For the models tested the scheme allows real-time solution of models with up to 16 000 tetrahedral elements. The use of GPUs for such purposes offers a cost-effective high-performance alternative to expensive multi-CPU machines, and may have important applications in medical image analysis and surgical simulation.
Computer Methods in Applied Mechanics and Engineering, 2019
We present the corotational cut Finite Element Method (FEM) for real-time surgical simulation. The only requirement of the proposed method is a background mesh, which is not necessarily conforming to the boundaries/interfaces of the simulated object. The details of the surface, which can be directly obtained from binary images, are taken into account by a multilevel embedding algorithm which is applied to elements of the background mesh that are cut by the surface. Dirichlet boundary conditions can be implicitly imposed on the surface using Lagrange multipliers, whereas traction or Neumann boundary conditions, which is/are applied on parts of the surface, can be distributed to the background nodes using shape functions. The implementation is verified by convergences studies, of the geometry and of numerical solutions, which exhibit optimal rates. To verify the reliability of the method, it is applied to various needle insertion simulations (e.g. for biopsy or brachytherapy) into brain and liver models. The numerical results show that, while retaining the
Total Lagrangian explicit dynamics finite element algorithm for computing soft tissue deformation
Communications in Numerical Methods in Engineering, 2007
We propose an efficient numerical algorithm for computing deformations of 'very' soft tissues (such as the brain, liver, kidney etc.), with applications to real-time surgical simulation. The algorithm is based on the finite element method using the total Lagrangian formulation, where stresses and strains are measured with respect to the original configuration. This choice allows for pre-computing of most spatial derivatives before the commencement of the time-stepping procedure.
The determination of biological material behaviors and numerical tools for medical application have been largely ongoing in the last hundred years and numerous models were developed at different scales and for different physics. We present here some late development of numerical models regarding direct medical applications for the use by clinicians, surgeons and repair surgery. These models are mostly concerned with multi-scale and multi-physics approaches with real time applications and priority is given to direct clinical transfer for everyday use. More specifically, examples are presented for bone remodeling, maxillo-facial surgery, and soft-tissue behavior for augmented reality surgery.
GPU-based real-time soft tissue deformation with cutting and haptic feedback
Progress in Biophysics and Molecular Biology, 2010
This article describes a series of contributions in the field of real-time simulation of soft tissue biomechanics. These contributions address various requirements for interactive simulation of complex surgical procedures. In particular, this article presents results in the areas of soft tissue deformation, contact modelling, simulation of cutting, and haptic rendering, which are all relevant to a variety of medical interventions. The contributions described in this article share a common underlying model of deformation and rely on GPU implementations to significantly improve computation times. This consistency in the modelling technique and computational approach ensures coherent results as well as efficient, robust and flexible solutions.
Computationally efficient techniques for real time surgical simulation with force feedback
In this paper, we present computationally efficient algorithms for the real time simulation of minimally invasive surgical (MIS) procedures. To develop a surgical simulator for training medical personnel, due to high computational speed required for realistic simulation in real time, there is a fundamental trade-off between realism and processing speed of the simulator. Our research focuses on how we can optimally utilize computing resources in the presence of constraints related to real time performance. We first present a novel approach to rapid collision detection so as to maximize the available time for computing collision response. We then present a real time tissue model that computes visual rendering of deformations and haptic rendering of interaction forces by using a newly developed meshless numerical scheme. By integrating these techniques with a force-feedback device and a visual display connected to PC, we simulate a specific procedure (palpation) with update rate of 1KHz for force and 30Hz frame rate for graphics.