Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics

Medical & Biological Engineering & Computing
Jinao ZhangChengfan Gu

Abstract

Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelle...Continue Reading

References

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Citations

Jul 26, 2019·Computer Assisted Surgery·Jinao ZhangChengfan Gu
May 28, 2021·Annals of Medicine and Surgery·Gerd ReisNareg Minaskan

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Software Mentioned

OpenMP
OpenHaptic
Geomagic
NiftySim
PHANToM
OpenGL graphics
CNN

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