Soft tissue deformation method based on metaball model driving

A model-driven, soft tissue technology, applied in the field of virtual surgery, to meet the real-time requirements of the system, good deformation effect, and smooth soft tissue surface.

Pending Publication Date: 2022-07-08

苏州迪威视景数字科技有限公司

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Problems solved by technology

[0005] The technical problem solved by the present invention is to overcome the authenticity problem of the traditional grid model and the iterative periodicity problem of the traditional physical method, provide a soft tissue deformation method driven by the metaball model, expan...

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Abstract

The invention provides a soft tissue deformation method based on metaball model driving, which comprises the following four steps: a construction stage of a metaball model topological structure: generating a Voronoi diagram according to an original grid model by using a BradshowGareth ball tree generation algorithm, further generating a metaball model, and constructing the topological structure of the metaball model through a method of setting a threshold value; in the metaball model deformation calculation stage, an extended position dynamics algorithm is combined with Laplacian coordinate constraint to simulate the deformation process of the soft tissue body model; in the skin-covering stage of the soft tissue model, distance field functions of the metaball in the body model are established respectively, a mapping relation is established between the metaball model and the epidermis grid model, and the skin-covering process is achieved; and a realistic drawing and real-time tactile rendering stage: performing realistic drawing according to the physical deformation of the soft tissue, and performing real-time tactile rendering based on a GeomagicTouch force feedback device. The method can truly simulate the deformation process of the soft tissue in the virtual operation, and has the characteristics of strong physical reality sense and good real-time performance.

Application Domain

Medical simulationSustainable transportation +2

Technology Topic

Tactile senseMesh grid +10

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Examples

Experimental program(1)

Example Embodiment

[0062] The present invention will be further described below in conjunction with other drawings and specific embodiments.

[0063] like figure 1 As shown, the present invention provides a soft tissue deformation method driven by a metaball model, and the main steps are as follows:

[0064] 1. Construction of the topological structure of the meta-sphere model and its optimization method

[0065] First use the BradshowGareth ball tree generation algorithm, based on the original triangular mesh model ( figure 2 (a) in) generate a Voronoi diagram, and according to the Voronoi diagram, generate the required meta-sphere model, such as figure 2 shown in (b). figure 2 (c) in (c) shows the comparison results of the mesh model and the metasphere model together. from figure 2 It can be seen that the generated meta-sphere model fits well with the triangular mesh model.

[0066] On the basis of the obtained meta-sphere model, the topology structure is constructed, and the following is the construction algorithm.

[0067] For metaball i, the center is c i , the point function connected to its topology is defined as:

[0068]

[0069] Among them, N is the set threshold, the value is 6, and num(i) is the number of metaballs overlapping with metaballs. The L function means that all the metaballs that overlap with the metaball i are defined as topological connections, and L' means that the N metaballs closest to i are defined as their topological connections. The topology constructed by this algorithm is as image 3 shown. in, image 3 Middle (a) is the epidermis model and the metasphere model; image 3 in (b) is in image 3 Add topological structure on the basis of (a), image 3 Middle (c) is the topology in the case of only the epidermis model.

[0070] 2. Metaball model deformation calculation

[0071] The deformation simulation of the metasphere model uses an extended position dynamics algorithm combined with Laplacian coordinate constraints.

[0072] The first is the extended position dynamics algorithm, which is a heuristic algorithm that computes deformation directly from position. When performing deformation iterations, there is no need to calculate the mutual acceleration of the units. It is only necessary to project each vertex to the appropriate position according to the position-based constraint function, and the variable from the current position to the final position can be calculated using the gradient of the constraint function. express. The method of the present invention employs the stretching constraints and volume preserving constraints in the extended position dynamics algorithm.

[0073] Figure 4 An example of a stretch constraint is given. The distance constraint function is:

[0074] C stretch (p 1 ,p 2 )=|p 1 -p 2 |-d (2)

[0075] where d is the vertex p 1 and p 2 The initial original distance between , can be obtained by the formula, end up with:

[0076]

[0077]

[0078] where w 1 with w 2 is the weight of the two vertices.

[0079] For the vertices of the 3D mesh model that are topologically connected to form a tetrahedron, use the volume-preserving constraints in the extended position dynamics algorithm, Figure 5 An example of a volume-preserving constraint is given, where (a) is the volume before deformation and (b) is the volume after deformation, and the function of the volume-preserving constraint is as follows:

[0080]

[0081] V 0 is the original volume of the tetrahedron; P 1 ,P 2 ,P 3 ,P 4 are the coordinates of the four vertices of the tetrahedron;

[0082] As a function of the volume-preserving constraint, the gradient at each point in the tetrahedron is obtained as:

[0083]

[0084]

[0085]

[0086]

[0087] The position change of each vertex is:

[0088]

[0089] During the deformation process, another 3-dimensional constraint needs to be added, and the LaplacianCoordinates Constraint is introduced here. Its algorithm is as follows.

[0090] For any metaball, let m and the center be c m , assuming that there are n adjacent metaballs in its topology, and the centers of these metaballs are set to c i , the topological center of the metaball i is c center ,which is:

[0091]

[0092] Then, the deformation simulation of the meta-sphere model is preprocessed. For the meta-sphere m, its Laplacian coordinates are defined as:

[0093]

[0094] According to the Laplacian coordinate constraints of the metasphere model, that is, L m , which is a fixed vector, and in each deformation iteration, the metaball center position is updated as:

[0095] c' m =L m +c' center (13)

[0096] where c′ m and c' center for c m and c center The new location after the update.

[0097] 3. Skinning algorithm of soft tissue model

[0098] To increase the realism in the soft tissue simulation, the skin model needs to be added, and the deformation of the skin model is determined by the skinning algorithm. The following is the skinning algorithm used in the present invention.

[0099] First, the metasphere model needs to be preprocessed. That is, for any metaball in the volume model, establish its distance field function:

[0100]

[0101] In the above formula, r is its radius, d is the distance to the center of the sphere, and c is a constant parameter whose value is determined by experiments.

[0102] Then, for any point in the epidermis model, let v be If there are n primitive spheres in the condition, then these n primitive spheres constitute a virtual topology structure, assuming that the center of this topology is p center , which is defined as:

[0103]

[0104] In this formula, c i is the center of the element ball i.

[0105] After preprocessing, the deformation simulation starts. In the iterative process of deformation simulation, the skin vertex v and its corresponding virtual topology center p are first established. center The relation of:

[0106] disp=v-pcenter (16)

[0107] Then, in each iterative calculation process, the updated position of the epidermis point v is shown in formula (12):

[0108] v'=p' center +disp (17)

[0109] where v' and p' center are v and p updated after iteration center.

[0110] 4. Experiment results of realistic rendering

[0111] According to the method of the present invention, a photorealistic rendering of soft tissue is accomplished. Visual rendering uses OpenGL API, and haptic rendering uses Geomagic Tough force feedback device and its Open Haptic API. The experimental equipment for realizing the present invention is NVIDIA GeForce GTX 460, Intel(R) Core(TM) 2Quad CPU (2.66GHz, 4cores), and 4G RAM running on Windows 764-bit system.

[0112] Image 6 The experimental results of the liver part in the present invention are shown, Image 6 (a) is the effect of the deformation of the metasphere model in the liver surgery simulation, and Image 6 (b) in (b) represents the deformation effect of the liver surface mesh model. from Image 6 It can be seen that the deformed liver surface is very smooth without any geometric distortion.

[0113] Figure 7 It is the experimental result of using other soft tissue organs except the liver in the experiment of the present invention. Among them, Figures (a) (b) (c) represent the gallbladder, small intestine and stomach, respectively. Then, the first column is the skin model and the meta-sphere model in the original state; the second column shows the skin model and topology; the third and fourth columns represent the deformation of the textured soft tissue after stretching at different positions, respectively Experimental results. from Figure 7 It can be seen that the surface of these three soft tissue organ models is very smooth without any geometric distortion after deformation.

[0114]

[0115] Table 1 Experimental data table of different soft tissue models

[0116] Table 1 is the experimental result data table of the method of the present invention. Among them, four rows represent four kinds of soft tissue organs; the first column is the number of vertices in the epidermis model of the soft tissue organ, the second column is the number of metaballs in the soft tissue organ body model, and the third column is the metaballs in the metaball model. The number of topological connection lines formed between them, the fourth column is the time to generate the meta-sphere model, and the last column is the time required for each iteration in the deformation process.

[0117] Figure 8 A comparison between the method of the present invention and the traditional physical method is given. (a) is the FEM method, (b) is the experimental result of the spring proton model, (c) is the experimental result based on the traditional position dynamics algorithm, and (d) is the experimental result of the method of the present invention. It can be seen from this that the method of the present invention and the FEM algorithm have a higher physical fidelity experimental effect than the spring proton and traditional position dynamics algorithm, but the calculation iteration cycle of the method of the present invention is much shorter than that of the FEM algorithm, and the real-time performance is much shorter. better. In addition, the existing patent CN201510746746.1, a soft tissue deformation method based on a meta-sphere model, is the applicant's previous achievement, and the position dynamics model is used, and the deformation effect is not good. The present invention now uses an extended positional dynamics model with volume-preserving constraints ( Figure 5 ), the deformation effect is more physically realistic, the calculation time is short, and the soft tissue surface is smoother after deformation.

[0118] The technical contents not described in detail in the present invention belong to the well-known technology of those skilled in the art.

[0119] Although the illustrative specific embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, As long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the inventive concept are included in the protection list.

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Soft tissue deformation method based on metaball model driving

A model-driven, soft tissue technology, applied in the field of virtual surgery, to meet the real-time requirements of the system, good deformation effect, and smooth soft tissue surface.

AI-Extracted Technical Summary

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