Soft Tissue Deformation with Neural Dynamics for Surgery Simulation

Y. Zhong, B. Shirinzadeh, Julian Smith
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引用次数: 11

Abstract

Soft tissue deformation is of great importance to virtual-reality-based-surgery simulation. This paper presents a new neural-dynamics-based methodology for simulation of soft tissue deformation from the perspective of energy propagation. A novel neural network is established to propagate the energy generated by an external force among mass points of a soft tissue. The stability of the proposed neural network system is proved by using the Lyapunov stability theory. A potential-based method is presented to derive the internal forces from the natural energy distribution established by the neural dynamics. Integration with a haptic device has been achieved for interactive deformation simulation with force feedback. The proposed methodology not only accommodates isotropic, anisotropic and inhomogeneous materials by simple modification of the control coefficients, but it also accepts large-range deformations.
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基于神经动力学的软组织变形手术模拟
软组织变形在基于虚拟现实的手术模拟中具有重要意义。本文从能量传播的角度提出了一种新的基于神经动力学的软组织变形模拟方法。建立了一种新的神经网络,用于在软组织质量点之间传播外力产生的能量。利用李雅普诺夫稳定性理论证明了所提神经网络系统的稳定性。提出了一种基于势的内力推导方法,该方法由神经动力学建立的自然能量分布推导出内力。实现了与触觉装置的集成,实现了具有力反馈的交互变形仿真。该方法不仅可以通过简单修改控制系数来适应各向同性、各向异性和非均质材料,而且可以接受大范围的变形。
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