Bionic meniscus 3D printing method and system

Abstract

The invention relates to a bionic meniscus 3D printing method and system, and the method comprises the steps: reading a meniscus STL model, carrying out the data preprocessing of the data of the model, and carrying out the construction to obtain a concave envelope contour; performing offset processing and four-curve segmentation to generate an elliptic equation fiber field; establishing a bidirectional mapping relation between a parameter space of an elliptic equation fiber field and a meniscus physical space based on an RBF mapping theory; based on a meniscus fiber density gradient change theory, performing simulation in a parameter space of the elliptic equation fiber field to obtain a bionic gradient fiber field; according to the meniscus STL model, the bidirectional mapping relation and the bionic gradient fiber field, fiber path coordinates of a meniscus physical space are obtained, and a 3D printing path is generated; and printing according to the 3D printing path to obtain the bionic meniscus. Precise simulation of a natural meniscus complex fiber structure is achieved through mathematical modeling, and the technical problems that in the prior art, fiber field control precision is insufficient, and regional characteristics are difficult to achieve are solved.

Description

Technical Field

[0001] This invention belongs to the field of biomedical 3D printing technology, and in particular relates to a biomimetic meniscus 3D printing method and system. Background Technology

[0002] The meniscus is an important fibrocartilaginous structure within the knee joint, playing vital physiological functions such as shock absorption, joint stability, load distribution, and joint lubrication. The natural meniscus possesses a highly complex three-dimensional fibrous network structure, with distinct regional differences in fiber arrangement: the lateral zone (red zone) is richly vascularized with relatively sparse fibers and higher porosity; the medial zone (white zone) has sparser blood vessels, denser fibers, and lower porosity. This unique fibrous field distribution endows the meniscus with excellent biomechanical properties.

[0003] Meniscus injury is a common knee joint disease that seriously affects patients' quality of life. Traditional meniscus repair methods mainly include suturing and partial resection, which are difficult to fully restore the original function of the meniscus. In recent years, tissue engineering technology has provided new ideas for meniscus repair, among which 3D printing technology has attracted much attention due to its ability to precisely control the microstructure of the scaffold.

[0004] Existing methods for 3D printing menisci face the following technical challenges:

[0005] Bionic fiber structure is difficult to mimic: The fiber arrangement of the natural meniscus has a complex three-dimensional spatial orientation. Existing methods mainly use simple layered or grid-like structures, which cannot achieve true bionic design of the meniscus.

[0006] Regional gradient characteristics are difficult to control: The inner and outer regions of the natural meniscus have different fiber density and porosity characteristics. Existing methods are difficult to achieve continuous gradient changes in the fiber field and cannot truly simulate the structural characteristics of the red and white regions of the natural meniscus.

[0007] Inadequate optimization of printing path: Existing 3D printing methods are mainly based on layer-by-layer slicing, which cannot take into account the continuity and orientation of fibers, resulting in significant differences in mechanical properties between the printed meniscus structure and the natural meniscus.

[0008] High mathematical modeling complexity: Due to the lack of effective mathematical theoretical support, existing methods are unable to establish a complete mathematical mapping relationship from medical images to printed data, which affects the universality and reliability of the methods.

[0009] Therefore, there is an urgent need to develop a 3D printing method for menisci that can precisely control the fiber field structure and achieve true biomimicry, so as to promote the development of meniscus tissue engineering technology. Summary of the Invention

[0010] To address the aforementioned technical problems, this invention provides a biomimetic meniscus 3D printing method and system.

[0011] The technical solution adopted in this invention is:

[0012] Firstly, a biomimetic meniscus 3D printing method is provided, including:

[0013] Read the STL model of the meniscus, preprocess the data of the STL model of the meniscus, and construct the concave hull contour;

[0014] After biasing and segmenting the concave hull profile using four curves, an elliptical equation fiber field is generated.

[0015] A two-way mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus is established based on RBF mapping theory.

[0016] Based on the theory of meniscus fiber density gradient change, a biomimetic gradient fiber field is obtained by simulating the parameter space of the elliptic equation fiber field.

[0017] Based on the STL model of the meniscus, the bidirectional mapping relationship, and the biomimetic gradient fiber field, the fiber path coordinates of the physical space of the meniscus are obtained, and the 3D printing path is generated.

[0018] A biomimetic meniscus was printed based on the 3D printing path.

[0019] Furthermore, the STL model of the meniscus is read, and the data of the STL model of the meniscus is preprocessed to construct the concave hull contour, including:

[0020] Using a standardized STL file reading algorithm, the meniscus STL model was obtained. The meniscus STL model is composed of... It consists of triangular mesh patches, each containing vertices , ;

[0021] Perform data preprocessing on all vertices to remove duplicates and isolated vertices, resulting in a vertex set. ;

[0022] Vertex set Projecting all vertices onto the XY plane yields the initial two-dimensional point set. ;

[0023] Use the unique function to remove the initial 2D point set after projection. By identifying the repeated points in the set, a unique two-dimensional point set is obtained. ;

[0024] Construct a unique two-dimensional point set using the Alpha Shape algorithm The original concave contour points are obtained by Gaussian smoothing, resulting in smooth contour points, which form the concave contour.

[0025] Furthermore, after biasing and quadrature segmentation of the concave hull profile, an elliptical equation fiber field is generated, including:

[0026] Calculate the outer normal vector for each contour point on the concave hull contour, and move it along the direction of the outer normal vector by a preset offset distance to obtain the offset contour.

[0027] Based on the known crescent shape characteristics of the meniscus, the offset profile is divided into four boundary curves. The overlapping points of each boundary curve are removed and interpolated to obtain four smooth boundary curves.

[0028] Using four smooth boundary curves as constraints, an elliptical equation fiber field is generated by an elliptical partial differential equation mesh generation technique.

[0029] Furthermore, using four smooth boundary curves as constraints, an elliptical equation fiber field is generated using an elliptical partial differential equation mesh generation technique, including:

[0030] An elliptic partial differential equation system for the fiber field is constructed using an elliptic partial differential equation mesh generation technique. The expression for the elliptic partial differential equation system is as follows:

[0031] ;

[0032] ;

[0033] in, , , , , , , , Let x be the abscissa of the parameter space of the elliptic equation fiber field. Let be the ordinate of the parameter space of the elliptic equation fiber field. The x-axis represents the physical space of the meniscus. The vertical coordinate represents the physical space of the meniscus.

[0034] Four smooth boundary curves are mapped to four boundaries in the parameter space of the elliptic equation fiber field, and these four boundaries are used as constraints for the elliptic partial differential equation system.

[0035] The initial values ​​of the internal grid points of the elliptic partial differential equation system are provided by the cross-finite interpolation technique, and the initial grid points that satisfy the constraints are obtained.

[0036] The elliptic partial differential equation system was solved by the successive over-relaxation iterative method to obtain the elliptic fiber field.

[0037] Furthermore, based on RBF mapping theory, a two-way mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus, including:

[0038] A positive mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus based on RBF mapping theory. positive mapping relationship The expression is:

[0039] ;

[0040] ;

[0041] in, For Gaussian RBF, , For shape parameters, , The average distance between RBF center points is given by the RBF center points, which are selected from the internal grid points. Here, i represents the i-th RBF center point. Let be the coordinates of the i-th RBF center point in the parameter space. , and The coefficients of the polynomial on the horizontal axis. The horizontal axis represents the RBF weights. , and The coefficients of the polynomial on the ordinate are... The RBF weights are on the ordinate.

[0042] Similarly, based on RBF mapping theory, an inverse mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus. .

[0043] Furthermore, based on the theory of meniscus fiber density gradient change, a biomimetic gradient fiber field is obtained by simulation in the parameter space of the elliptic equation fiber field, including:

[0044] Based on the theory of meniscus fiber density gradient change, the gradient characteristics of the fiber density of a known natural meniscus changing continuously from the outer to the inner side were obtained.

[0045] Based on the gradient characteristics, the parameters in the parameter space are adjusted by gradient to obtain the gradient adjustment parameters in the parameter space;

[0046] By using a cumulative width homogenization method to process the gradient change continuity of the gradient adjustment parameters, a biomimetic gradient fiber field is obtained.

[0047] Furthermore, based on the STL model of the meniscus, the bidirectional mapping relationship, and the biomimetic gradient fiber field, the fiber path coordinates in the physical space of the meniscus are obtained, and a 3D printing path is generated, including:

[0048] The STL model of the meniscus is sliced ​​layer by layer to obtain the two-dimensional contour of each slice.

[0049] By using the reverse mapping relationship of the bidirectional mapping relationship, the two-dimensional contour is mapped to the parameter space to obtain the parametric contour;

[0050] Generate perpendicularly intersecting parametric fiber paths in the parameter space based on the parametric profile;

[0051] By utilizing the forward mapping relationship of the bidirectional mapping relationship, the parameter fiber path is mapped to the biomimetic gradient fiber field to obtain the biomimetic gradient fiber path.

[0052] Based on the coordinates of each path point in the biomimetic gradient fiber path, the fiber path coordinates in the physical space of the meniscus are obtained.

[0053] Generate the 3D printing path based on the fiber path coordinates.

[0054] Secondly, a biomimetic meniscus 3D printing system is provided, including:

[0055] The data processing module is used to read the STL model of the meniscus, preprocess the data of the STL model of the meniscus, and construct the concave hull contour.

[0056] The elliptical equation fiber field generation module is used to generate an elliptical equation fiber field after biasing and four-curve segmentation of the concave hull profile.

[0057] The two-way mapping relationship establishment module is used to establish a two-way mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus based on RBF mapping theory.

[0058] The biomimetic gradient fiber field construction module is used to simulate and obtain the biomimetic gradient fiber field in the parameter space of the elliptic equation fiber field based on the theory of meniscus fiber density gradient change.

[0059] The 3D printing path generation module is used to obtain the fiber path coordinates of the meniscus in physical space based on the meniscus STL model, bidirectional mapping relationship and biomimetic gradient fiber field, and generate the 3D printing path.

[0060] The biomimetic meniscus printing module is used to print biomimetic meniscuses according to the 3D printing path.

[0061] The beneficial effects achieved by this invention are as follows:

[0062] The STL model of the meniscus was read, and the data of the STL model was preprocessed to construct a concave contour. After offset processing and four-curve segmentation of the concave contour, an elliptical equation fiber field was generated. Based on RBF mapping theory, a two-way mapping relationship between the parameter space of the elliptical equation fiber field and the physical space of the meniscus was established. Based on the theory of meniscus fiber density gradient change, a biomimetic gradient fiber field was obtained by simulating in the parameter space of the elliptical equation fiber field. The fiber path coordinates of the meniscus physical space were obtained according to the meniscus STL model, the two-way mapping relationship, and the biomimetic gradient fiber field, and a 3D printing path was generated. The biomimetic meniscus was printed according to the 3D printing path. Through mathematical modeling, the accurate biomimetic of the complex fiber structure of the natural meniscus was achieved, solving the technical problems of insufficient fiber field control accuracy and difficulty in realizing regional features in the existing technology. Attached Figure Description

[0063] Figure 1 This is a flowchart of the biomimetic meniscus 3D printing method of the present invention;

[0064] Figure 2 This is a result diagram of the biomimetic meniscus 3D printing system of the present invention. Detailed Implementation

[0065] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0066] like Figure 1 As shown, this embodiment of the invention provides a biomimetic meniscus 3D printing method, including:

[0067] 101. Read the STL model of the meniscus, preprocess the data of the STL model of the meniscus, and construct the concave hull contour;

[0068] Using a standardized stereolithography (STL) file reading algorithm, the meniscus STL model was obtained. The meniscus STL model is derived from... It consists of triangular mesh patches, each containing vertices , ; Indicates the first One vertex;

[0069] Data preprocessing is performed on all vertices to remove duplicates and isolated vertices, ensuring the topological integrity of the model, resulting in a vertex set. ;

[0070] Vertex set Projecting all vertices onto the XY plane yields the initial two-dimensional point set. ;

[0071] Use the unique function to remove the initial 2D point set after projection. By identifying the repeated points in the set, a unique two-dimensional point set is obtained. The number of points in a two-dimensional point set is ;

[0072] Construct a unique two-dimensional point set using the Alpha Shape algorithm The original concave contour points are obtained by Gaussian smoothing to obtain smooth contour points, thus forming the concave contour.

[0073] The Alpha Shape algorithm is a generalization of the convex hull, capable of better describing the boundary shape of a point set, and is particularly suitable for geometries with concave features. It first calculates the Delaunay triangulation of all 2D points, given the Alpha parameters... Keep the circumcircle radius smaller than The triangle is used to extract the boundaries of the triangulation and form the concave hull profile.

[0074] Alpha parameter The selection adopts an adaptive approach. ,in, The average distance between adjacent points in a two-dimensional point set;

[0075] The extracted concave contour is Gaussian smoothed to eliminate the jagged effect caused by discrete sampling. Assume the set of original concave contour points is... , The coordinates of point k on the original concave hull contour are given. The total number of points in the original concave hull contour is given by the Gaussian smoothing process.

[0076] ;

[0077] ;

[0078] in, For Gaussian kernel function, Standard deviation, , For the window radius, , j represents the offset relative to the position of the original concave hull contour point k.

[0079] 102. After biasing and segmenting the concave hull profile, an elliptical equation fiber field is generated.

[0080] To ensure that the elliptic equation fiber field can completely cover the meniscus structure, the concave contour is outwardly offset, the outward normal vector is calculated for each contour point on the concave contour, and the point is moved by a preset offset distance along the direction of the outward normal vector. This yields the offset profile;

[0081] For contour points Its outer normal vector The calculation is as follows:

[0082] ;

[0083] ;

[0084] The coordinates of the offset contour points are ; The value ranges from 0.1mm to 0.5mm, which ensures complete coverage without excessively expanding the computational domain.

[0085] Based on the known crescent shape of the meniscus, the offset profile is divided into four boundary curves: curve 1 corresponds to the anterior horn region, curve 2 corresponds to the outer boundary, curve 3 corresponds to the posterior horn region, and curve 4 corresponds to the inner boundary. Assume the total number of points on the offset profile is... The segmentation points are determined based on the known crescent shape of the meniscus. To ensure the geometric quality of the boundary curves, overlapping points are removed from each segmented boundary curve, and adjacent contour points are calculated. and Distance between points: ,like , The default value is 0.001mm, so it is removed. and If there is an overlapping point, then there is no need to remove it;

[0086] In addition, if there are discontinuities in the boundary curves, re-interpolation is required to ensure that the curves are smooth and continuous, resulting in four smooth boundary curves.

[0087] Elliptic equation fiber field generation method is based on harmonic mapping theory, and its goal is to establish a quadrilateral domain in physical space. To the unit square of the parameter space A smooth bijective mapping;

[0088] An elliptic partial differential equation system for the fiber field is constructed using an elliptic partial differential equation mesh generation technique. The expression for the elliptic partial differential equation system is as follows:

[0089] ;

[0090] ;

[0091] in, , , , , , , , Let x be the abscissa of the parameter space of the elliptic equation fiber field. Let be the ordinate of the parameter space of the elliptic equation fiber field. The x-axis represents the physical space of the meniscus. The vertical coordinate represents the physical space of the meniscus.

[0092] Four smooth boundary curves are mapped to four boundaries in the parameter space of the elliptic equation fiber field, and these four boundaries are used as constraints for the elliptic partial differential equation system.

[0093] For example, the four smooth boundary curves can be mapped to the four boundaries of the parameter space as follows:

[0094] Curve 1 → South Boundary: ,

[0095] Curve 2 → Eastern Boundary: ,

[0096] Curve 3 → North Boundary: ,

[0097] Curve 4 → Western Boundary: ,

[0098] For each boundary, arc length parameterization resampling is performed to ensure uniform distribution in the parameter space. For the h-th boundary curve... Calculate the boundary curve Cumulative arc length of all contour points:

[0099] ;

[0100] in, This represents the g-th contour point. Represents the h-th boundary curve The total number of contour points on the surface;

[0101] Normalized arc length parameter: ;

[0102] Resampling at the uniform parameter point t using spline interpolation: ;

[0103] Initial values ​​are provided for the internal grid points of the elliptic partial differential equation system using the Transfinite Interpolation (TFI) technique:

[0104] ;

[0105] right The coordinates use the same formula, and the TFI technology provides initial grid points that meet the constraints, accelerating subsequent iteration convergence;

[0106] The elliptic partial differential equations are solved using the successive over-relaxation SOR iterative method to obtain the elliptic fiber field, specifically:

[0107] For internal grid points The discretized ellipse equation is: ;

[0108] The over-relaxed SOR iteration scheme is as follows: ;in, H is the relaxation factor, and H represents the number of iterations. This is the new value calculated from the equation of the ellipse;

[0109] Iteration termination condition: ,in .

[0110] 103. Based on RBF mapping theory, establish a two-way mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus.

[0111] A positive mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus is established based on the radial basis function (RBF) mapping theory. positive mapping relationship The expression is:

[0112] ;

[0113] ;

[0114] in, For Gaussian RBF, , For shape parameters, , The average distance between RBF center points is given by the RBF center points, which are selected from the internal grid points. Here, i represents the i-th RBF center point. Let be the coordinates of the i-th RBF center point in the parameter space. , and The coefficients of the polynomial on the horizontal axis. The horizontal axis represents the RBF weights. , and The coefficients of the polynomial on the ordinate are... The RBF weights are on the ordinate.

[0115] Similarly, based on RBF mapping theory, an inverse mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus. ;

[0116] The RBF weights can be used to construct and solve a system of linear equations. The expression for the linear equations is as follows:

[0117] ;

[0118] in, It is an RBF matrix. Let R be the coordinates of the R-th data point in physical space. Let J be the coordinates of the J-th RBF center point in the parameter space. For polynomial basis matrices, These are the regularization parameters; the linear system is solved using QR decomposition or SVD methods to obtain the weight coefficients. and polynomial coefficients .

[0119] 104. Based on the theory of meniscus fiber density gradient change, a biomimetic gradient fiber field is obtained by simulation in the parameter space of elliptic equation fiber field.

[0120] Based on the theory of meniscus fiber density gradient change, the gradient characteristics of the fiber density of a known natural meniscus, which changes continuously from the outer side (called the red zone) to the inner side (called the white zone), are obtained.

[0121] Based on the gradient characteristics, the parameters in the parameter space are adjusted by gradient to obtain the gradient adjustment parameters in the parameter space;

[0122] Assume the original parameters are , The number of input arrays represents the number of points uniformly distributed along the U direction in the parameter space. The gradient adjustment parameters after gradient adjustment are:

[0123] ;

[0124] in, These are gradient control parameters, and their values ​​range from [value range missing]. The preferred value is ; A value close to 1 indicates that the inner side is dense and the outer side is sparse (simulating the red and white area). Indicates a uniform distribution; A value close to 0 indicates that the outer side is dense and the inner side is sparse;

[0125] The gradient adjustment parameters are processed to ensure continuous gradient variation by using a cumulative width homogenization method, resulting in a biomimetic gradient fiber field.

[0126] To ensure the continuity of gradient changes, a cumulative width homogenization method is required:

[0127] First, calculate the gradient magnitude of the grid (E, F). The calculation formula is:

[0128] ;

[0129] Calculate the corresponding width The calculation formula is:

[0130] ;

[0131] Calculate cumulative width The calculation formula is:

[0132] ;

[0133] The expression for uniform interpolation is:

[0134] ;

[0135] The gradient transformation expression is as follows:

[0136] ;

[0137] according to Calculate new contour points using a mapping function .

[0138] 105. Based on the STL model of the meniscus, the bidirectional mapping relationship, and the biomimetic gradient fiber field, the fiber path coordinates of the physical space of the meniscus are obtained, and the 3D printing path is generated.

[0139] The STL model of the meniscus is sliced ​​layer by layer to obtain the two-dimensional contour of each slice; the specific slicing algorithm is as follows: for slice height... Traverse all triangular faces and calculate their relationship with the plane. The intersection line of the three vertices of the triangle; The coordinates span the slice plane; the intersection points are calculated; all intersection points are collected and connected to form a closed contour.

[0140] By utilizing the reverse mapping relationship of the bidirectional mapping relationship, the two-dimensional contour is mapped to the parameter space to obtain the parametric contour; for the contour points of each slice... The corresponding parameter coordinates are calculated using the established reverse mapping relationship: ;

[0141] Generate perpendicularly intersecting parametric fiber paths in the parameter space based on the parametric profile; specifically, the path in the U-direction of the horizontal coordinate: , Path in the V direction (vertical coordinate): , The path spacing is determined based on the desired fiber density. ;

[0142] Using the forward mapping relationship of the bidirectional mapping relationship, the parametric fiber path is mapped to the biomimetic gradient fiber field to obtain the biomimetic gradient fiber path. The formula for the forward mapping relationship is: ; where the extrusion length The calculation formula is based on the path length and material parameters:

[0143] ;

[0144] Based on the coordinates of each point in the biomimetic gradient fiber path, the fiber path coordinates in the physical space of the meniscus are obtained; based on the fiber path coordinates, a 3D printing path is generated, specifically, the G-code for the 3D printer can be generated.

[0145] G1 X{x_F} Y{y_F} Z{z_slice} L{extrusion_length} RA{feed_rate};

[0146] By adjusting The parameters allow for flexible control of the porosity gradient range from 10% to 100%.

[0147] 106. A biomimetic meniscus was printed according to the 3D printing path.

[0148] A 3D printer can print a biomimetic meniscus by executing the G-code generated by the 3D printing path.

[0149] The beneficial effects achieved by the embodiments of the present invention are as follows:

[0150] The STL model of the meniscus was read, and the data of the STL model was preprocessed to construct a concave contour. After offset processing and four-curve segmentation of the concave contour, an elliptical equation fiber field was generated. Based on RBF mapping theory, a two-way mapping relationship between the parameter space of the elliptical equation fiber field and the physical space of the meniscus was established. Based on the theory of meniscus fiber density gradient change, a biomimetic gradient fiber field was obtained by simulating in the parameter space of the elliptical equation fiber field. The fiber path coordinates of the meniscus physical space were obtained according to the meniscus STL model, the two-way mapping relationship, and the biomimetic gradient fiber field, and a 3D printing path was generated. The biomimetic meniscus was printed according to the 3D printing path. Through mathematical modeling, the accurate biomimetic of the complex fiber structure of the natural meniscus was achieved, solving the technical problems of insufficient fiber field control accuracy and difficulty in realizing regional features in the existing technology.

[0151] Based on the biomimetic meniscus 3D printing method described in the above embodiments, the biomimetic meniscus 3D printing system will be described below through embodiments.

[0152] like Figure 2 As shown, this embodiment of the invention provides a biomimetic meniscus 3D printing system, comprising:

[0153] Data processing module 201 is used to read the meniscus STL model, perform data preprocessing on the data of the meniscus STL model, and construct the concave hull contour.

[0154] Elliptical Equation Fiber Field Generation Module 202 is used to generate elliptical equation fiber fields after offset processing and four-curve segmentation of the concave hull contour.

[0155] The bidirectional mapping relationship establishment module 203 is used to establish a bidirectional mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus based on the RBF mapping theory.

[0156] The biomimetic gradient fiber field construction module 204 is used to simulate the biomimetic gradient fiber field in the parameter space of the elliptic equation fiber field based on the theory of meniscus fiber density gradient change.

[0157] The 3D printing path generation module 205 is used to obtain the fiber path coordinates of the physical space of the meniscus based on the STL model of the meniscus, the bidirectional mapping relationship and the biomimetic gradient fiber field, and generate the 3D printing path.

[0158] The biomimetic meniscus printing module 206 is used to print a biomimetic meniscus according to the 3D printing path.

[0159] The beneficial effects achieved by the embodiments of the present invention are as follows:

[0160] The data processing module 201 reads the STL model of the meniscus, preprocesses the data of the STL model, and constructs the concave contour. The elliptical equation fiber field generation module 202 performs offset processing and four-curve segmentation on the concave contour to generate an elliptical equation fiber field. The bidirectional mapping relationship establishment module 203 establishes a bidirectional mapping relationship between the parameter space of the elliptical equation fiber field and the physical space of the meniscus based on RBF mapping theory. The biomimetic gradient fiber field construction module 204 simulates the biomimetic gradient fiber field in the parameter space of the elliptical equation fiber field based on the theory of meniscus fiber density gradient change. The 3D printing path generation module 205 obtains the fiber path coordinates of the meniscus physical space according to the meniscus STL model, the bidirectional mapping relationship, and the biomimetic gradient fiber field, and generates a 3D printing path. The biomimetic meniscus printing module 206 prints the biomimetic meniscus according to the 3D printing path. Through mathematical modeling, the accurate biomimetic of the complex fiber structure of the natural meniscus is realized, solving the technical problems of insufficient fiber field control accuracy and difficulty in realizing regional features in the existing technology.

[0161] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0162] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0163] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0164] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0165] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A biomimetic meniscus 3D printing method, characterized in that, include: Read the STL model of the meniscus, perform data preprocessing on the data of the STL model of the meniscus, and construct the concave hull contour; After biasing and quadrature segmenting the concave contour, an elliptical equation fiber field is generated. Based on RBF mapping theory, a two-way mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus. Based on the theory of meniscus fiber density gradient change, a biomimetic gradient fiber field is obtained by simulating the parameter space of the elliptical equation fiber field. Based on the STL model of the meniscus, the bidirectional mapping relationship, and the biomimetic gradient fiber field, the fiber path coordinates of the physical space of the meniscus are obtained, and the 3D printing path is generated. A biomimetic meniscus was printed according to the 3D printing path.

2. The biomimetic meniscus 3D printing method according to claim 1, characterized in that, The process of reading the STL model of the meniscus, preprocessing the data of the STL model of the meniscus, and constructing the concave hull contour includes: Using a standardized STL file reading algorithm, the meniscus STL model was obtained. The meniscus STL model is composed of... It consists of triangular mesh patches, each containing vertices , ; Perform data preprocessing on all vertices to remove duplicates and isolated vertices, resulting in a vertex set. ; The vertex set Projecting all vertices onto the XY plane yields the initial two-dimensional point set. ; The initial two-dimensional point set after projection is removed using the unique function. By identifying the repeated points in the set, a unique two-dimensional point set is obtained. ; The unique two-dimensional point set is constructed using the Alpha Shape algorithm. The original concave contour points are obtained by Gaussian smoothing, and smooth contour points are obtained to form the concave contour.

3. The biomimetic meniscus 3D printing method according to claim 2, characterized in that, After biasing and segmenting the concave contour, an elliptical equation fiber field is generated, including: Calculate the outer normal vector for each contour point on the concave hull contour, and move a preset offset distance along the direction of the outer normal vector to obtain the offset contour; Based on the known crescent shape characteristics of the meniscus, the offset contour is divided into four boundary curves, and the overlapping points of each boundary curve are removed and interpolated to obtain four smooth boundary curves. Using the four smooth boundary curves as constraints, an elliptical equation fiber field is generated using an elliptical partial differential equation mesh generation technique.

4. The biomimetic meniscus 3D printing method according to claim 3, characterized in that, The process of generating an elliptical fiber field using elliptical partial differential equation mesh generation technology, with the four smooth boundary curves as constraints, includes: An elliptic partial differential equation system is constructed for the elliptic fiber field using an elliptic partial differential equation mesh generation technique. The expression for the elliptic partial differential equation system is as follows: ； ； in, , , , , , , The Let x be the abscissa of the parameter space of the elliptic equation fiber field. Let be the ordinate of the parameter space of the elliptic equation fiber field, and be... The x-coordinate of the physical space of the meniscus is the... The vertical coordinate of the physical space of the meniscus; The four smooth boundary curves are mapped to the four boundaries of the parameter space of the elliptic equation fiber field, and the four boundaries are used as the constraint conditions of the elliptic partial differential equation system. The initial values ​​of the internal grid points of the elliptic partial differential equation system are provided by the finite interpolation technique to obtain the initial grid points that satisfy the constraints. The elliptic partial differential equations are solved by a successive over-relaxation iterative method to obtain the elliptic fiber field.

5. The biomimetic meniscus 3D printing method according to claim 4, characterized in that, The establishment of a two-way mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus based on RBF mapping theory includes: Based on RBF mapping theory, a positive mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus. The positive mapping relationship The expression is: ； ； in, For Gaussian RBF, the stated The For shape parameters, The The average distance between RBF center points is the average distance value between the RBF center points, which are selected from the internal grid points, where i represents the i-th RBF center point. Let i be the coordinates of the i-th RBF center point in the parameter space. The above and stated The coefficients of the polynomial on the horizontal axis are... The RBF weights are on the horizontal axis. The above and stated The coefficients of the polynomial on the ordinate are... The RBF weights are on the ordinate. Similarly, based on the RBF mapping theory, an inverse mapping relationship is established between the parameter space of the elliptic equation fiber field and the physical space of the meniscus. .

6. The biomimetic meniscus 3D printing method according to claim 5, characterized in that, The biomimetic gradient fiber field, obtained by simulating the parameter space of the elliptic equation fiber field based on the theory of meniscus fiber density gradient change, includes: Based on the theory of meniscus fiber density gradient change, the gradient characteristics of the fiber density of a known natural meniscus changing continuously from the outer to the inner side were obtained. The gradient adjustment parameters in the parameter space are obtained by performing gradient adjustment based on the gradient characteristics. The gradient adjustment parameters are processed to ensure the continuity of gradient changes by using a cumulative width homogenization method, resulting in a biomimetic gradient fiber field.

7. The biomimetic meniscus 3D printing method according to claim 6, characterized in that, The step of obtaining the fiber path coordinates of the meniscus in physical space based on the meniscus STL model, the bidirectional mapping relationship, and the biomimetic gradient fiber field, and generating the 3D printing path, includes: The STL model of the meniscus is sliced ​​layer by layer to obtain the two-dimensional contour of each slice. By using the reverse mapping relationship of the bidirectional mapping relationship, the two-dimensional contour is mapped to the parameter space to obtain the parameter contour; Based on the parameter profile, a vertically intersecting parameter fiber path is generated in the parameter space; By utilizing the forward mapping relationship of the bidirectional mapping relationship, the parameter fiber path is mapped to the biomimetic gradient fiber field to obtain the biomimetic gradient fiber path. Based on the coordinates of each path point in the biomimetic gradient fiber path, the fiber path coordinates of the physical space of the meniscus are obtained. A 3D printing path is generated based on the fiber path coordinates.

8. A biomimetic meniscus 3D printing system, characterized in that, include: The data processing module is used to read the STL model of the meniscus, perform data preprocessing on the data of the STL model of the meniscus, and construct the concave hull contour. The elliptical equation fiber field generation module is used to generate an elliptical equation fiber field after biasing and four-curve segmentation of the concave contour. The bidirectional mapping relationship establishment module is used to establish a bidirectional mapping relationship between the parameter space of the elliptic equation fiber field and the physical space of the meniscus based on the RBF mapping theory. A biomimetic gradient fiber field construction module is used to simulate the biomimetic gradient fiber field in the parameter space of the elliptical equation fiber field based on the theory of meniscus fiber density gradient change. The 3D printing path generation module is used to obtain the fiber path coordinates of the physical space of the meniscus based on the meniscus STL model, the bidirectional mapping relationship and the biomimetic gradient fiber field, and generate the 3D printing path. A biomimetic meniscus printing module is used to print a biomimetic meniscus according to the 3D printing path.

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