Three‑dimensional Modeling and Simulation of Muscle Tissue Puncture Process

Needle biopsy is an essential part of modern clinical medicine.The puncture accuracy and sampling success rate of puncture surgery can be effectively improved through virtual surgery.There are few three-dimensional puncture(3D)models,which have little significance for surgical guidance under complicated conditions and restrict the development of virtual surgery.In this paper,a 3D simulation of the muscle tissue puncture process is studied.Firstly,the mechanical properties of muscle tissue are measured.The Mooney-Rivlin(M-R)model is selected by considering the fitting accuracy and calculation speed.Subsequently,an accurate 3D dynamic puncture model is established.The failure criterion is used to define the breaking characteristics of the muscle,and the bilinear cohesion model defines the breaking process.Experiments with different puncture speeds are carried out through the built in vitro puncture platform.The experimental results are compared with the simulation results.The experimental and simulated reaction force curves are highly consistent,which verifies the accuracy of the model.Finally,the model under different parameters is studied.The simulation results of varying puncture depths and puncture speeds are analyzed.The 3D puncture model can provide more accurate model support for virtual surgery and help improve the success rate of puncture surgery.

A Virtual Puncture Surgery System Based on Multi-Layer Soft Tissue and Force Mesh

Puncture is a common operation in surgery,which involves all kinds of tissue materials with different geometry and mechanical properties.As a new cross-disciplinary research area,Virtual Surgery(VS)makes simulation of soft tissue in puncture operation possible in virtual environment.In this paper,we introduce a VS-based puncture system composed by three-layer soft tissue,simulated with spherical harmonic function(SHF),which is covered with a force mesh,constructed by mass spring model(MSM).The two models are combined together with a parameter of SHF named surface radius,which provides MSM with real-time deformation data needed in force calculation.Meanwhile,force calculation,divided into the surface spring force and the puncture damping force,makes the force presentation better accord to the corresponding tissue characteristics.Moreover,a deformation resumption algorithm is leveraged to simulate the resumption phenomenon of the broken tissue surface.In evaluation experiment,several residents are invited to grades our model along with other four mainstream soft tissue models in terms of 7 different indicators.After the evaluation,the scores are analyzed by a comprehensive weighted grading method.Experiment results show that the proposed model has better performance during puncture operation than other models,and can well simulate surface resumption phenomenon when tissue surface is broken.

A Soft Tissue Acupuncture Model Based on Mass-Spring Force Ne

In the simulation of acupuncture manipulation,it is necessary to accurately capture the information of acupuncture points and particles around them.Therefore,a soft tissue modeling method that can accurately track model particles is needed.In this paper,a soft tissue acupuncture model based on the mass-spring force net is designed.MSM is used as the auxiliary model and the SHF model is combined.SHF is used to establish a three-layer soft tissue model of skin,fat,and muscle,and a layer of the MSM based force network is covered on the surface of soft tissue to realize the complementary advantages and disadvantages of spherical harmonic function and MSM.In addition,a springback algorithm is designed to simulate the springback phenomenon of soft tissue skin during acupuncture.The evaluation results show that the soft tissue acupuncture modeling method based on mass-spring force net can effectively simulate the springback phenomenon of soft tissue surface during acupuncture surgery,and has good comprehensive performance in the application of virtual acupuncture surgery simulation.