Real-Time Nonlinear FEM with Neural Network for Simulating Soft Organ Model Deformation
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
An electromechanical based deformable model for soft tissue simulation
Artificial Intelligence in Medicine
Presence: Teleoperators and Virtual Environments
Soft tissue deformation with reaction-diffusion process for surgery simulation
Journal of Visual Languages and Computing
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This paper presents a new methodology to simulate soft object deformation by drawing an analogy between a cellular neural network (CNN) and elastic deformation. The potential energy stored in an elastic body as a result of a deformation caused by an external force is propagated among mass points by a nonlinear CNN. The novelty of the methodology is that: 1) CNN techniques are established to describe the potential energy distribution of the deformation for extrapolating internal forces and 2) nonlinear materials are modeled with nonlinear CNNs rather than geometric nonlinearity. Integration with a haptic device has been achieved for deformable object simulation with force feedback. The proposed methodology not only predicts the typical behaviors of living tissues, but it also accommodates isotropic, anisotropic, and inhomogeneous materials, as well as local and large-range deformation