Multiple optimization meshless soft tissue deformation simulation method

Abstract

The invention discloses a multiple optimization meshless soft tissue deformation simulation method, which comprises the following steps: (1) the vertex information of a soft tissue CT (computerized tomography) image is acquired, so that point cloud data are obtained; (2) a unified streamline method based on octree encoding is adopted to simplify the point cloud data; (3) a moving least square method is adopted to construct a meshless shape function according to the simplified point cloud data; (4) a Kelvin viscoelastic model is adopted to construct a non-linear viscoelastic model; (5) according to the non-linear viscoelastic model and the meshless shape function, an EFG method is adopted to construct a meshless equation of the non-linear viscoelastic model; (6) on the basis of a high-resolution approximation algorithm, at each time slice, the meshless equation of the non-linear viscoelastic model is adopted to calculate the new position of each point, and thereby soft tissue deformation simulation is fulfilled. According to the invention, the cost is low, and the simulation effect is good.

Description

technical field [0001] The invention relates to a soft tissue simulation method, in particular to a multi-optimized meshless soft tissue deformation simulation method. Background technique [0002] With the continuous advancement of science and technology, virtual surgery simulation systems have been developed unprecedentedly. These systems are of great significance to the training of surgical interns in hospitals. On the one hand, they can quickly improve the surgical skills of interns and reduce training costs. On the one hand, it can improve the success rate of surgery, and it is also responsible for patient safety. In the medical field, the real soft tissue will show complex biomechanical properties during the deformation process, which brings great difficulties to soft tissue modeling. [0003] Therefore, in recent years, the simulation of soft tissue deformation has become the focus of virtual object simulation research. At present, many deformation models have been ...

AI Technical Summary

Problems solved by technology

At present, many deformation models have been proposed, and the common ones are: (1) The spring-mass model is often used for surgical simulation due to its simple structure and fast calculation, but it is difficult to set appropriate parameter values, and the model is unstable; (2) The finite element model has high precision but high computational complexity; (3) the meshless model does not need to maintain the topological information between data points, avoiding the inherent complex topology in the mesh model (such as: ill-conditioned mesh, mesh reconstruction etc.), have strong adaptability, but the existing models combined with meshless models still have many shortcomings, such as: linear viscoelastic meshless model, although the linear elastic model can reduce calculation problems, but also Many tissue biomechanical properties are lost. Although some other models related to meshless can simulate soft tissue more realistically, they do not optimize and store the data points of the object well, and the calculation cost is high.

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