Fracture healing regeneration simulation system based on SNS activation

Abstract

The invention discloses a fracture healing regeneration simulation system based on SNS activation, and belongs to the technical field of biomedical engineering. In order to solve the problems of inaccurate prediction of a fracture healing process and insufficient simulation of effects of cell behaviors and nerve regulation in fracture healing, the mechanical environment and the stress-strain state of a fracture area can be more accurately simulated through three-dimensional modeling and finite element analysis, so that biomechanical changes in the fracture healing process are more accurately predicted, and the fracture healing effect is improved. By combining an SNS activation signal module, a complex neural signal conduction process in an organism after fracture is simulated, the effect of nerve regulation in fracture healing is disclosed, the prediction accuracy of the healing process is improved, behaviors of various cell types in the fracture healing process and the growth and remodeling process of callus are simulated, and the development and development of the fracture healing system are facilitated. Based on the output result of the simulation system, the influence of different treatment schemes on the fracture healing process is simulated, the scheme can be optimized before actual treatment, and the uncertainty and risk in the treatment process are reduced.

Description

Technical Field

[0001] The invention relates to the technical field of biomedical engineering, and in particular to a fracture healing regeneration simulation system based on SNS activation. Background Art

[0002] Fracture is a common trauma. The high incidence of fracture makes the study of fracture mechanism and promotion of healing particularly urgent. Once a fracture occurs, unlike other tissue damage and repair, the fracture is not connected by fibrous connective tissue, but by complete regeneration of bone tissue. However, not all fractures can be completely healed, and sometimes delayed healing or even non-healing occurs.

[0003] Fracture healing is affected by specific geometric, mechanical, and biological factors. However, the fracture healing simulation system still has the following problems in actual operation: Existing technologies often find it difficult to fully consider the complex mechanical environment and stress-strain state of the fracture area, as well as the important role of neural regulation in fracture healing. Traditional treatment plans are often based on experience or limited experimental data and are difficult to optimize for individual differences. At the same time, existing technologies often simplify processing when simulating cell behavior, ignoring cell-to-cell interactions and signal transduction, and often find it difficult to effectively simulate this process. Summary of the invention

[0004] The purpose of the present invention is to provide a fracture healing regeneration simulation system based on SNS activation to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a fracture healing regeneration simulation system based on SNS activation, comprising: Fracture region modeling module for: Acquire a two-dimensional tomographic image from a medical imaging device, and establish a three-dimensional surface geometric model of the fracture site based on three-dimensional reconstruction according to the input two-dimensional tomographic image; Fracture Area Analysis Module for: The three-dimensional model of the fracture area is divided into surface mesh and volume mesh to obtain a finite element model. According to the actual stress conditions of the fracture site, external loads and boundary conditions are set to calculate the stress and strain parameters of the fracture area. SNS activation signal module, used for: The initial SNS signal source is set in the fracture area of ​​the three-dimensional model, and the SNS conduction model is constructed to simulate the interaction between different SNS signals and the activation and conduction process of SNS in the body after fracture. Cell evolution simulation module for: Define the cell types involved in the fracture healing process, including fibroblasts, macrophages, chondroblasts, osteoblasts, osteoclasts, bone stem cells, and immune cells, and simulate cell proliferation, migration, and differentiation behaviors as well as intercellular signaling; Callus Growth Modeling Module for: Initial callus tissue is set in the fracture area. Based on the results of the cell evolution simulation module, the growth process of the callus tissue is simulated, and the remodeling process of the callus under mechanical stimulation and biological signal regulation is simulated to form new bone tissue. Blood supply simulation module for: Based on the three-dimensional model of the fracture area, the initial vascular network was constructed to simulate the flow of blood in the vascular network and analyze the effects of blood supply on cell metabolism, nutrient supply and waste discharge in the fracture area. The program termination judgment module is used to: According to the biological characteristics of fracture healing and the purpose of simulation, the termination condition is set, and whether the termination condition is met is continuously checked during the simulation process. If the termination condition is met, the simulation result is output, and the simulation result includes the fracture healing time and the callus growth; Visual interaction module for: Provides visual display of simulation results and user interaction interface.

[0006] Furthermore, the fracture area modeling module includes: Data import unit for: The two-dimensional tomographic images of the fracture site are obtained through medical imaging equipment and saved in DICOM format. The noise in the image is removed by filtering, and the image is processed by a smoothing algorithm to identify and repair the holes in the image. 3D reconstruction unit for: The two-dimensional tomography images are registered, the two-dimensional image data are divided into three-dimensional voxels, and the three-dimensional surface of the fracture site is extracted from the voxel data according to the set threshold. The extracted three-dimensional surface is optimized, and a three-dimensional surface geometric model of the fracture site is established based on three-dimensional reconstruction.

[0007] Furthermore, the process of repairing the cavity includes: Extract the number of pixels contained in the hole area; Comparing the number of pixels contained in the hole area with a preset pixel number threshold; Extracting hole regions in which the number of pixels contained in the hole regions exceeds a preset pixel number threshold as a first hole region group; Extracting hole regions in which the number of pixels contained in the hole regions does not exceed a preset pixel number threshold as a second hole region group; The first weight coefficient corresponding to each hole area of ​​the first hole area group is obtained by using the quantitative relationship between the number of pixels contained in each hole area of ​​the first hole area group and a preset pixel number threshold; wherein the first weight coefficient is obtained by the following formula: Among them, Y 01 represents the first weight coefficient; w 01 represents the position weight value corresponding to each hole region of the first hole region group; w z01 represents the corresponding weights and values ​​in all hole regions of the first hole region group; N 01 represents the number of pixels contained in each hole area of ​​the first hole area group; M represents a preset pixel number threshold; The second weight coefficient corresponding to each hole area of ​​the second hole area group is obtained by using the quantitative relationship between the number of pixels contained in each hole area of ​​the second hole area group and the preset pixel number threshold; wherein the second weight coefficient is obtained by the following formula: Among them, Y 02 represents the second weight coefficient; w 02 represents the position weight value corresponding to each hole area of ​​the second hole area group; z01 represents the corresponding weights and values ​​in all hole regions of the first hole region group; w z02 represents the corresponding weights and values ​​in all hole regions of the second hole region group; N 02 represents the number of pixels contained in each hole area of ​​the second hole area group; M represents a preset pixel number threshold; The corresponding hole area is repaired using the first weight coefficient and the second weight coefficient.

[0008] Further, using the first weight coefficient and the second weight coefficient to repair the corresponding hole area includes: Extracting valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group; Extracting a first weight coefficient corresponding to each hole area in the first hole area group; The first replacement pixel value corresponding to each pixel in the hole area is obtained by using the valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group in combination with the first weight coefficient; wherein the first replacement pixel value is obtained by the following formula: Among them, X t01represents the first replacement pixel value corresponding to each pixel point of each hole area in the first hole area group; n represents the number of valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group; Y 01 represents the first weight coefficient; X p represents the pixel average value corresponding to n valid pixels; w 01 represents the position weight value corresponding to each hole area of ​​the first hole area group; X 01i represents the pixel value corresponding to the i-th valid pixel point corresponding to the edge area of ​​each hole area in the first hole area group; X 01b represents the standard deviation of the pixel values ​​corresponding to n valid pixels corresponding to the edge area of ​​each hole area in the first hole area group; L 01i represents the straight-line distance between each pixel point in each hole area in the first hole area group and the i-th valid pixel point corresponding to the edge area of ​​each hole area; L 01b represents the standard deviation of the straight-line distance between each pixel point in each hole area in the first hole area group and n valid pixel points corresponding to the edge area of ​​each hole area; Using the first replacement pixel value corresponding to each pixel point contained in the hole area of ​​the first hole area group to replace the pixel value of the corresponding pixel point, so as to complete the hole area repair; Extracting valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; Extracting a second weight coefficient corresponding to each hole area in the second hole area group; The second replacement pixel value corresponding to each pixel in the hole area is obtained by using the valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group in combination with the second weight coefficient; wherein the second replacement pixel value is obtained by the following formula: Among them, X t02 represents the first replacement pixel value corresponding to each pixel point of each hole area in the second hole area group; m represents the number of valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; Y 02 represents the second weight coefficient; X z represents the pixel median value corresponding to m valid pixels; w 02 represents the position weight value corresponding to each hole area of ​​the second hole area group; X 02i represents the pixel value corresponding to the i-th valid pixel point corresponding to the edge area of ​​each hole area in the second hole area group; X 02brepresents the standard deviation of the pixel values ​​corresponding to the m valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; L 02i represents the straight-line distance between each pixel point in each hole area in the second hole area group and the i-th valid pixel point corresponding to the edge area of ​​each hole area; L 02b represents the standard deviation of the straight-line distance between each pixel point in each hole area in the second hole area group and m valid pixel points corresponding to the edge area of ​​each hole area; The second replacement pixel value corresponding to each pixel point contained in the hole area of ​​the second hole area group is used to replace the pixel value corresponding to the pixel point, so as to complete the hole area repair.

[0009] Furthermore, the fracture area analysis module includes: Meshing elements for: Receiving the three-dimensional surface geometric model from the fracture area modeling module, meshing the surface of the three-dimensional model to generate a two-dimensional surface mesh, and based on the two-dimensional surface mesh, performing volume meshing to generate a three-dimensional volume mesh; Finite element analysis setup unit for: According to the anatomical structure and mechanical properties of the fracture site, external loads and boundary conditions are set, wherein the external loads include body weight and muscle force, and the boundary conditions include fixed constraints and sliding constraints. Material properties are defined for the fracture area and surrounding tissues, wherein the material properties include elastic modulus and Poisson's ratio, and finite element analysis parameters are configured, wherein the finite element analysis parameters include solver type, solution accuracy, and number of iterations; Stress-strain calculation unit for: The analysis is performed based on finite element analysis to calculate the stress and strain parameters of the fracture area. After the solution is completed, the stress and strain parameter data of the fracture area are extracted.

[0010] Furthermore, the SNS activation signal module is also used to: According to the fracture type and injury degree, the initial SNS signal source position and strength are specified in the fracture area of ​​the three-dimensional model, and an SNS network model of the fracture area and its surroundings is constructed, wherein the SNS network model includes neurons, nerve fibers and connection relationships; Define the conduction velocity, attenuation mechanism, signal bifurcation and convergence rules of SNS signals in nerve fibers, and define the interaction mode between different SNS signals, including enhancement, inhibition and antagonism; Starting from the initial signal source, the signal is propagated in the SNS network according to the set conduction rules. In each time step, the intensity, direction and range of the SNS signal are updated according to the cell-to-cell interaction, local environmental conditions and biochemical reactions, and the SNS signal changes are fed back to the cellular level of the fracture area. Transmit changes in SNS activation signals to the cell evolution simulation module in real time.

[0011] Furthermore, the cell evolution simulation module is also used for: Based on the three-dimensional model of the fracture area, the initial distribution and number of cells in and around the fracture area are set, the proliferation rate and conditions are set for each cell type, the proliferation process of cells is simulated according to the cell cycle and growth factors, the migration behavior of cells in the fracture area is simulated, and the differentiation process of cells is simulated according to the stage of fracture healing and local environmental conditions; Constructing a network model of intercellular signal transduction to simulate the transmission, reception and response process of signal molecules between cells. The signal molecules include growth factors, chemokines and cytokines. According to the types and concentrations of signal molecules, simulate their regulatory effects on cell behaviors, including proliferation, migration and differentiation. Receive the SNS signal output by the SNS signal module, adjust the cell proliferation, migration and differentiation rates according to the SNS signal, receive the stress and strain parameters calculated by the fracture area analysis module, and pass the cell proliferation, migration and differentiation results to the callus growth modeling module.

[0012] Furthermore, the callus growth modeling module is also used for: According to the three-dimensional model of the fracture area, initial callus tissue is set between or around the fracture ends, and basic callus parameters are set for the initial callus, wherein the callus parameters include density, strength, elastic modulus and quantity; Receive data on cell types, numbers, distribution and activities from the cell evolution simulation module, map the results of cell proliferation, migration and differentiation onto the callus tissue, update the number, type and position of cells in the callus, and simulate the growth of the callus tissue; Simulate the absorption of old bone tissue by osteoclasts and the formation of new bone tissue by osteoblasts. According to the results of the blood supply simulation module, simulate the expansion and reconstruction of the vascular network in the callus, set the time step, and iteratively update the density, strength, structure and biological properties of the callus.

[0013] Furthermore, the blood supply simulation module is also used for: An initial vascular network is constructed based on the three-dimensional model of the fracture area, and basic parameters of the blood vessels are set, including diameter, length, bifurcation angle, and blood flow velocity; Establish a blood flow model in the vascular network, set the heart's pumping action, the blood flow velocity and pressure distribution at the vascular inlet, and the pressure conditions at the vascular outlet, perform numerical simulation, and calculate the blood flow velocity, pressure distribution, and shear stress parameters at each point in the vascular network; It interacts with the fracture area modeling module to adjust the layout and parameters of the vascular network according to the three-dimensional model of the fracture area, and interacts with the cell evolution simulation module to provide blood flow parameters as input conditions for cell metabolism and activity.

[0014] Furthermore, the program termination judgment module is also used to: Setting simulation parameters, including density, strength, volume percentage of callus tissue, and the number and distribution of specific types of cells, and setting a termination condition threshold in the simulation system; Collect and record simulation parameter data related to the termination conditions in real time, and set the time interval for regular inspection according to the collection frequency of simulation parameter data; At each inspection time point, the current simulation parameters are compared with the set termination condition threshold. If any simulation parameter reaches the termination condition threshold, the termination process is entered; if all simulation parameters do not reach the termination condition threshold, the simulation process continues and waits for the next inspection time point; When entering the termination process, all activities in the simulation process are stopped immediately, and all simulation data in the simulation process are saved, including but not limited to the three-dimensional model of the fracture area, stress-strain distribution, cell distribution and quantity, and callus growth, and a simulation result report is generated.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Through highly simulated three-dimensional modeling and finite element analysis, the present invention can more accurately simulate the mechanical environment and stress-strain state of the fracture area, thereby more accurately predicting the biomechanical changes in the fracture healing process. Combined with the SNS activation signal module, it simulates the complex neural signal conduction process in the body after fracture, which helps to reveal the important role of neural regulation in fracture healing and improve the accuracy of healing process prediction. The cell evolution simulation module simulates in detail the behavior of various cell types in the fracture healing process. The callus growth modeling module simulates the growth and remodeling process of the callus. Based on the output results of the simulation system, it simulates the effects of different treatment plans on the fracture healing process. Doctors can optimize the plan before actual treatment to reduce uncertainty and risk in the treatment process.

[0016] 2. The present invention refines the three-dimensional surface geometric model into a two-dimensional surface mesh, and further generates a three-dimensional volume mesh, which can more accurately reflect the geometric morphology and internal structure of the fracture area and its surrounding tissues, thereby improving the accuracy and reliability of the simulation. Reasonable mesh division can optimize the allocation of computing resources and reduce unnecessary calculations. According to the anatomical structure and mechanical properties of the fracture site, personalized external loads and boundary conditions are set to make the simulation results closer to the actual situation, which helps to more accurately simulate the biomechanical environment in the fracture healing process. Based on finite element analysis, detailed stress and strain calculations are performed, which can comprehensively evaluate the mechanical state of the fracture area and its surrounding tissues, and help to understand the biomechanical mechanism in the fracture healing process. The extracted stress and strain parameter data of the fracture area can provide valuable reference information for clinicians, helping them to better understand the fracture healing situation and formulate more scientific and reasonable treatment plans.

[0017] 3. The present invention accurately sets the initial distribution and number of cells based on the three-dimensional model of the fracture area, sets specific proliferation rates and conditions for different cell types, ensures the authenticity and accuracy of cell behavior during the simulation, and makes the simulation results closer to the actual fracture healing process. By simulating the effects of the cell cycle and growth factors, the module can dynamically display the cell proliferation process. According to the stage of fracture healing and local environmental conditions, the module can simulate the cell differentiation process. The module constructs a network model of intercellular signal transduction, simulates the transmission, reception and response process of signal molecules between cells, receives the SNS signals output by the SNS signal module, and adjusts the cell proliferation, migration and differentiation rates according to these signals, so that the simulation system can more comprehensively simulate the interaction between the nervous system and cell behavior in the fracture healing process, providing a basis for formulating more accurate treatment plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the fracture healing regeneration simulation system module of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In order to solve the technical problems that existing technologies often fail to fully consider the complex mechanical environment and stress-strain state of the fracture area, as well as the important role of neural regulation in fracture healing, traditional treatment plans are often based on experience or limited experimental data, and are difficult to optimize for individual differences. At the same time, existing technologies often simplify the process when simulating cell behavior, ignoring the interaction and signal transduction between cells, and often fail to effectively simulate this process, please refer to Figure 1 , the present invention provides the following technical solutions: The fracture healing regeneration simulation system based on SNS activation includes: Fracture region modeling module for: Acquire a two-dimensional tomographic image from a medical imaging device, and establish a three-dimensional surface geometric model of the fracture site based on three-dimensional reconstruction according to the input two-dimensional tomographic image; Fracture Area Analysis Module for: The three-dimensional model of the fracture area is divided into surface mesh and volume mesh to obtain a finite element model. According to the actual stress conditions of the fracture site, external loads and boundary conditions are set to calculate the stress and strain parameters of the fracture area. SNS activation signal module, used for: The initial SNS signal source is set in the fracture area of ​​the three-dimensional model, and the SNS conduction model is constructed to simulate the interaction between different SNS signals and the activation and conduction process of SNS in vivo after fracture. Cell evolution simulation module for: Define the cell types involved in the fracture healing process, including fibroblasts, macrophages, chondroblasts, osteoblasts, osteoclasts, bone stem cells, and immune cells, and simulate cell proliferation, migration, and differentiation behaviors as well as intercellular signaling; Callus Growth Modeling Module for: Initial callus tissue is set in the fracture area. Based on the results of the cell evolution simulation module, the growth process of the callus tissue is simulated, and the remodeling process of the callus under mechanical stimulation and biological signal regulation is simulated to form new bone tissue. Blood supply simulation module for: Based on the three-dimensional model of the fracture area, the initial vascular network was constructed to simulate the flow of blood in the vascular network and analyze the effects of blood supply on cell metabolism, nutrient supply and waste discharge in the fracture area. The program termination judgment module is used to: According to the biological characteristics of fracture healing and the purpose of simulation, the termination condition is set, and whether the termination condition is met is continuously checked during the simulation process. If the termination condition is met, the simulation result is output, and the simulation result includes the fracture healing time and the callus growth; Visual interaction module for: Provides visual display of simulation results and user interaction interface.

[0021] In the above embodiments, through highly simulated three-dimensional modeling and finite element analysis, the mechanical environment and stress-strain state of the fracture area can be simulated more accurately, thereby more accurately predicting the biomechanical changes in the fracture healing process. Combined with the SNS activation signal module, the complex neural signal conduction process in the body after fracture is simulated, which helps to reveal the important role of neural regulation in fracture healing and improve the accuracy of healing process prediction.

[0022] In the above embodiment, the cell evolution simulation module simulates in detail the behavior of various cell types in the fracture healing process, including cell proliferation, migration, differentiation and signal transduction, which helps to deeply understand the cell biological mechanism of fracture healing. The callus growth modeling module simulates the growth and remodeling process of callus, demonstrating the role of mechanical stimulation and biological signal regulation in bone tissue regeneration. Based on the output results of the simulation system, including fracture healing time, callus growth, etc., doctors can formulate more personalized and accurate treatment plans. For example, adjust the time of external fixation or internal fixation according to the fracture healing time predicted by the simulation, or adjust the rehabilitation exercise plan according to the callus growth. By simulating the impact of different treatment plans on the fracture healing process, doctors can optimize the plan before actual treatment to reduce uncertainty and risk during the treatment process.

[0023] Fracture area modeling module, including: Data import unit for: The two-dimensional tomographic images of the fracture site are obtained through medical imaging equipment and saved in DICOM format. The noise in the image is removed by filtering, and the image is processed by a smoothing algorithm to identify and repair the holes in the image. 3D reconstruction unit for: The two-dimensional tomography images are registered, the two-dimensional image data are divided into three-dimensional voxels, and the three-dimensional surface of the fracture site is extracted from the voxel data according to the set threshold. The extracted three-dimensional surface is optimized, and a three-dimensional surface geometric model of the fracture site is established based on three-dimensional reconstruction.

[0024] In the above embodiment, the precise three-dimensional surface geometry model can more accurately simulate the morphology and characteristics of the fracture site, thereby improving the calculation accuracy of parameters such as stress and strain during the simulation process, making the simulation results more reliable. Based on the precise three-dimensional model, the interaction mechanism of cells, tissues and biomechanical factors in the fracture healing process can be further explored, providing a scientific basis for the formulation and optimization of clinical treatment plans. According to the fracture types and characteristics of different patients, personalized three-dimensional models can be established and simulation analysis can be performed, so as to provide patients with more accurate and personalized treatment plans, improve treatment effects and patient satisfaction.

[0025] Specifically, the process of repairing the cavity includes: Extract the number of pixels contained in the hole area; Comparing the number of pixels contained in the hole area with a preset pixel number threshold; Extracting hole regions in which the number of pixels contained in the hole regions exceeds a preset pixel number threshold as a first hole region group; Extracting hole regions in which the number of pixels contained in the hole regions does not exceed a preset pixel number threshold as a second hole region group; The first weight coefficient corresponding to each hole area of ​​the first hole area group is obtained by using the quantitative relationship between the number of pixels contained in each hole area of ​​the first hole area group and a preset pixel number threshold; wherein the first weight coefficient is obtained by the following formula: Among them, Y 01 represents the first weight coefficient; w 01 represents the position weight value corresponding to each hole region of the first hole region group; w z01 represents the corresponding weights and values ​​in all hole regions of the first hole region group; N 01 represents the number of pixels contained in each hole area of ​​the first hole area group; M represents a preset pixel number threshold; The second weight coefficient corresponding to each hole area of ​​the second hole area group is obtained by using the quantitative relationship between the number of pixels contained in each hole area of ​​the second hole area group and the preset pixel number threshold; wherein the second weight coefficient is obtained by the following formula: Among them, Y 02 represents the second weight coefficient; w 02 represents the position weight value corresponding to each hole area of ​​the second hole area group; z01 represents the corresponding weights and values ​​in all hole regions of the first hole region group; w z02represents the corresponding weights and values ​​in all hole regions of the second hole region group; N 02 represents the number of pixels contained in each hole area of ​​the second hole area group; M represents a preset pixel number threshold; The corresponding hole area is repaired using the first weight coefficient and the second weight coefficient.

[0026] The technical effect of the above technical solution is as follows: the solution first classifies the hole area in detail, and divides the hole area into two groups according to the comparison between the number of pixels contained in the hole area and the preset pixel number threshold: the first hole area group (large hole) and the second hole area group (small hole). This classification helps to adopt different repair strategies for holes of different sizes, and improves the pertinence and accuracy of the repair. For the first hole area group, the first weight coefficient is calculated by using the quantitative relationship between the number of pixels contained in the hole area and the preset threshold, combined with the position weight value. This weight coefficient not only considers the size of the hole, but also considers the position information of the hole in the image, so that the repair process is more in line with the overall structure and texture of the image. For the second hole area group, a similar weight coefficient calculation method is also used, but the calculation of the weight coefficient also considers the difference in weights and values ​​between the two groups of hole areas, which helps to maintain consistency with the surrounding large hole repair when repairing small holes, and reduce the abrupt or inharmonious phenomenon in the repaired image. By introducing the weight coefficient, the scheme can flexibly repair according to the characteristics of different hole areas. The calculation of the weight coefficient takes into account the size and location of the hole, which enables the repair process to better adapt to the texture and structural characteristics of different areas in the image, and improves the flexibility and adaptability of the repair. This scheme can significantly improve the quality of the image by finely processing the hole area and introducing the weight coefficient for repair. The repaired image has a more natural transition between the hole area and the surrounding area, reducing the repair traces and improving the visual effect and usability of the image.

[0027] In summary, this technical solution achieves refined repair of hole areas by classifying and processing hole areas and introducing weight coefficients for repair, thereby improving the accuracy and flexibility of repair and improving the quality of the image.

[0028] Specifically, using the first weight coefficient and the second weight coefficient to repair the corresponding hole area includes: Extracting valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group; Extracting a first weight coefficient corresponding to each hole area in the first hole area group; The first replacement pixel value corresponding to each pixel in the hole area is obtained by using the valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group in combination with the first weight coefficient; wherein the first replacement pixel value is obtained by the following formula: Among them, X t01 represents the first replacement pixel value corresponding to each pixel point of each hole area in the first hole area group; n represents the number of valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group; Y 01 represents the first weight coefficient; X p represents the pixel average value corresponding to n valid pixels; w 01 represents the position weight value corresponding to each hole area of ​​the first hole area group; X 01i represents the pixel value corresponding to the i-th valid pixel point corresponding to the edge area of ​​each hole area in the first hole area group; X 01b represents the standard deviation of the pixel values ​​corresponding to n valid pixels corresponding to the edge area of ​​each hole area in the first hole area group; L 01i represents the straight-line distance between each pixel point in each hole area in the first hole area group and the i-th valid pixel point corresponding to the edge area of ​​each hole area; L 01b represents the standard deviation of the straight-line distance between each pixel point in each hole area in the first hole area group and n valid pixel points corresponding to the edge area of ​​each hole area; Using the first replacement pixel value corresponding to each pixel point contained in the hole area of ​​the first hole area group to replace the pixel value of the corresponding pixel point, so as to complete the hole area repair; Extracting valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; Extracting a second weight coefficient corresponding to each hole area in the second hole area group; The second replacement pixel value corresponding to each pixel in the hole area is obtained by using the valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group in combination with the second weight coefficient; wherein the second replacement pixel value is obtained by the following formula: Among them, X t02 represents the first replacement pixel value corresponding to each pixel point of each hole area in the second hole area group; m represents the number of valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; Y 02 represents the second weight coefficient; X z represents the pixel median value corresponding to m valid pixels; w02 represents the position weight value corresponding to each hole area of ​​the second hole area group; X 02i represents the pixel value corresponding to the i-th valid pixel point corresponding to the edge area of ​​each hole area in the second hole area group; X 02b represents the standard deviation of the pixel values ​​corresponding to the m valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; L 02i represents the straight-line distance between each pixel point in each hole area in the second hole area group and the i-th valid pixel point corresponding to the edge area of ​​each hole area; L 02b represents the standard deviation of the straight-line distance between each pixel point in each hole area in the second hole area group and m valid pixel points corresponding to the edge area of ​​each hole area; The second replacement pixel value corresponding to each pixel point contained in the hole area of ​​the second hole area group is used to replace the pixel value corresponding to the pixel point, so as to complete the hole area repair.

[0029] The technical effect of the above technical solution is as follows: the solution performs a detailed classification process on the hole area, and designs different repair strategies for the first hole area group (large hole) and the second hole area group (small hole). This classification process makes the repair process more refined, and different repair methods can be adopted for holes of different sizes, which improves the pertinence and accuracy of the repair. In the repair process, the solution makes full use of the edge information and weight coefficient of the hole area. By extracting the effective pixel points at the edge of the hole area and calculating the replacement pixel value in combination with the weight coefficient, the repaired pixel value is closer to the pixel value in the original image, reducing the repair traces and improving the repair effect.

[0030] When calculating the replacement pixel value, the scheme comprehensively considers multiple factors, including the number of valid pixels, weight coefficient, pixel average value (or median value), pixel value standard deviation, and the straight-line distance between the pixel and the edge valid pixel. The comprehensive consideration of these factors makes the calculation of the replacement pixel value more scientific and reasonable, and further improves the repair effect. Through the above repair method, the scheme can significantly improve the quality of the hole area in the image. The transition between the hole area and the surrounding area of ​​the repaired image is more natural, reducing the repair traces and image distortion, and improving the visual effect and usability of the image. The scheme is applicable to different types of images and hole areas. Regardless of the size, shape or position of the hole, the scheme can perform effective repair. This wide applicability makes the scheme have broad application prospects in the field of image processing.

[0031] In summary, this technical solution achieves effective repair of hole areas and improves the quality and usability of images through refined classification processing, repair methods based on weights and edge information, and comprehensive consideration of multiple factors.

[0032] Fracture area analysis module, including: Meshing elements for: Receiving the three-dimensional surface geometric model from the fracture area modeling module, meshing the surface of the three-dimensional model to generate a two-dimensional surface mesh, and based on the two-dimensional surface mesh, performing volume meshing to generate a three-dimensional volume mesh; Finite element analysis setup unit for: According to the anatomical structure and mechanical properties of the fracture site, external loads and boundary conditions are set, wherein the external loads include body weight and muscle force, and the boundary conditions include fixed constraints and sliding constraints. Material properties are defined for the fracture area and surrounding tissues, wherein the material properties include elastic modulus and Poisson's ratio, and finite element analysis parameters are configured, wherein the finite element analysis parameters include solver type, solution accuracy, and number of iterations; Stress-strain calculation unit for: The analysis is performed based on finite element analysis to calculate the stress and strain parameters of the fracture area. After the solution is completed, the stress and strain parameter data of the fracture area are extracted.

[0033] In the above embodiment, the meshing unit refines the three-dimensional surface geometric model into a two-dimensional surface mesh, and further generates a three-dimensional volume mesh, which can more accurately reflect the geometric morphology and internal structure of the fracture area and its surrounding tissues, thereby improving the accuracy and reliability of the simulation. Reasonable meshing can optimize the allocation of computing resources and reduce unnecessary computing. At the same time, by generating meshes that adapt to the characteristics of different parts, the computing efficiency can be improved while ensuring the computing accuracy.

[0034] In the above embodiments, personalized external loads and boundary conditions are set according to the anatomical structure and mechanical properties of the fracture site, so that the simulation results are closer to the actual situation, which helps to more accurately simulate the biomechanical environment in the fracture healing process, define precise material properties for the fracture area and its surrounding tissues, and can more realistically reflect the mechanical behavior of the tissue. It is helpful to calculate the stress and strain parameters of the fracture area and configure the finite element analysis parameters, which can be adjusted according to different simulation requirements and computing resources to achieve the optimal simulation effect.

[0035] In the above embodiment, detailed stress and strain calculations based on finite element analysis can comprehensively evaluate the mechanical state of the fracture area and its surrounding tissues, which is helpful to understand the biomechanical mechanism of the fracture healing process. The extracted stress and strain parameter data of the fracture area can provide valuable reference information for clinicians, helping them to better understand the fracture healing situation and formulate more scientific and reasonable treatment plans. In the fracture healing regeneration simulation system based on SNS activation, the effects of different SNS activation strategies can be evaluated through stress and strain calculation results, providing data support for optimizing the activation strategy.

[0036] The SNS activation signal module is also used for: According to the fracture type and injury degree, the initial SNS signal source position and strength are specified in the fracture area of ​​the three-dimensional model, and an SNS network model of the fracture area and its surroundings is constructed, wherein the SNS network model includes neurons, nerve fibers and connection relationships; Define the conduction velocity, attenuation mechanism, signal bifurcation and convergence rules of SNS signals in nerve fibers, and define the interaction mode between different SNS signals, including enhancement, inhibition and antagonism; Starting from the initial signal source, the signal is propagated in the SNS network according to the set conduction rules. In each time step, the intensity, direction and range of the SNS signal are updated according to the cell-to-cell interaction, local environmental conditions and biochemical reactions, and the SNS signal changes are fed back to the cellular level of the fracture area. Transmit changes in SNS activation signals to the cell evolution simulation module in real time.

[0037] In the above embodiment, the initial SNS signal source position and intensity are accurately specified according to the fracture type and degree of injury, so that the simulation is closer to the actual neural response in the fracture healing process, thereby improving the accuracy of the simulation. By constructing the SNS network model of the fracture area and the surrounding area, and defining the conduction speed, attenuation mechanism, signal bifurcation and convergence rules of the SNS signal, and the interaction mode between different SNS signals, the module can deeply reveal the regulatory mechanism of the nervous system in the fracture healing process. This helps researchers to understand the biological process of fracture healing more comprehensively.

[0038] In the above embodiment, the dynamic propagation process of SNS signals in and around the fracture area is simulated. In each time step, the intensity, direction and range of the SNS signal are updated in real time according to the cell-cell interaction, local environmental conditions and biochemical reactions, so that the simulation results are more realistic and reliable, and can more accurately reflect the changes in nerve signals during fracture healing. The module transmits the changes in SNS activation signals to the cell evolution simulation module in real time, so that the simulation at the cell level can be based on the real changes in nerve signals, which helps to more comprehensively understand the interaction between cells and the nervous system during fracture healing, thereby more accurately predicting the progress and results of fracture healing.

[0039] The Cell Evolution Simulation Module is also used for: Based on the three-dimensional model of the fracture area, the initial distribution and number of cells in and around the fracture area are set, the proliferation rate and conditions are set for each cell type, the proliferation process of cells is simulated according to the cell cycle and growth factors, the migration behavior of cells in the fracture area is simulated, and the differentiation process of cells is simulated according to the stage of fracture healing and local environmental conditions; Constructing a network model of intercellular signal transduction to simulate the transmission, reception and response process of signal molecules between cells. The signal molecules include growth factors, chemokines and cytokines. According to the types and concentrations of signal molecules, simulate their regulatory effects on cell behaviors, including proliferation, migration and differentiation. Receive the SNS signal output by the SNS signal module, adjust the cell proliferation, migration and differentiation rates according to the SNS signal, receive the stress and strain parameters calculated by the fracture area analysis module, and pass the cell proliferation, migration and differentiation results to the callus growth modeling module.

[0040] In the above embodiment, according to the three-dimensional model of the fracture area, the initial distribution and number of cells are accurately set, and specific proliferation rates and conditions are set for different cell types, thereby ensuring the authenticity and accuracy of cell behavior during the simulation process, and making the simulation results closer to the actual fracture healing process. By simulating the effects of the cell cycle and growth factors, the module can dynamically display the cell proliferation process, which helps to understand the mechanism of action of cell proliferation in fracture healing and provide a scientific basis for formulating treatment plans to promote fracture healing. The module can simulate the migration behavior of cells in the fracture area. Taking into account the movement characteristics of cells at different stages and local environmental conditions during the fracture healing process, it helps to reveal the important role of cell migration in fracture repair and how to promote fracture healing by regulating cell migration.

[0041] In the above embodiments, according to the stage of fracture healing and local environmental conditions, the module can simulate the differentiation process of cells, which helps to understand the transformation and evolution of different cell types in fracture healing, and provides a new perspective for exploring new mechanisms and treatment methods for fracture healing. The module constructs a network model of intercellular signal transduction, simulates the transmission, reception and response process of signal molecules between cells, and helps to reveal the regulatory effects of signal molecules such as growth factors, chemokines and cytokines on cell behavior, providing theoretical support for optimizing signal transduction pathways in the fracture healing process.

[0042] In the above embodiment, the SNS signal output by the SNS signal module is received, and the proliferation, migration and differentiation rates of the cells are adjusted according to these signals, so that the simulation system can more comprehensively simulate the interaction between the nervous system and cell behavior during fracture healing, and provide a basis for formulating more accurate treatment plans. The module receives the stress and strain parameters calculated by the fracture area analysis module, and transmits the cell proliferation, migration and differentiation results to the callus growth modeling module, so that the entire system can operate more efficiently, thereby improving the accuracy and reliability of the simulation.

[0043] The Callus Growth Modeling Module is also used to: According to the three-dimensional model of the fracture area, initial callus tissue is set between or around the fracture ends, and basic callus parameters are set for the initial callus, wherein the callus parameters include density, strength, elastic modulus and quantity; Receive data on cell types, numbers, distribution and activities from the cell evolution simulation module, map the results of cell proliferation, migration and differentiation onto the callus tissue, update the number, type and position of cells in the callus, and simulate the growth of the callus tissue; Simulate the absorption of old bone tissue by osteoclasts and the formation of new bone tissue by osteoblasts. According to the results of the blood supply simulation module, simulate the expansion and reconstruction of the vascular network in the callus, set the time step, and iteratively update the density, strength, structure and biological properties of the callus.

[0044] In the above embodiment, the callus growth modeling module can set the initial callus tissue between or around the fracture ends according to the three-dimensional model of the fracture area, and set basic callus parameters for it, so that the simulation system can accurately simulate the initial state of the callus tissue, provide an accurate starting point for the subsequent growth process, receive data on cell type, quantity, distribution and activity from the cell evolution simulation module, and map the results of these cell activities to the callus tissue. In this way, as the cells proliferate, migrate and differentiate, the number, type and position of cells in the callus will be continuously updated, thereby truly reflecting the impact of cell activity on callus growth.

[0045] In the above embodiment, the module can simulate the absorption of old bone tissue by osteoclasts and the formation of new bone tissue by osteoblasts, which can provide a more comprehensive understanding of the growth mechanism of callus tissue. By setting the time step and iteratively updating the density, strength, structure and biological characteristics of the callus, the callus growth modeling module can dynamically display the changes in callus tissue during fracture healing, so that the simulation system can more realistically reflect the complexity and dynamics of fracture healing and more accurately evaluate the effect and progress of fracture healing.

[0046] The blood supply simulation module is also used for: An initial vascular network is constructed based on the three-dimensional model of the fracture area, and basic parameters of the blood vessels are set, including diameter, length, bifurcation angle, and blood flow velocity; Establish a blood flow model in the vascular network, set the heart's pumping action, the blood flow velocity and pressure distribution at the vascular inlet, and the pressure conditions at the vascular outlet, perform numerical simulation, and calculate the blood flow velocity, pressure distribution, and shear stress parameters at each point in the vascular network; It interacts with the fracture area modeling module to adjust the layout and parameters of the vascular network according to the three-dimensional model of the fracture area, and interacts with the cell evolution simulation module to provide blood flow parameters as input conditions for cell metabolism and activity.

[0047] In the above embodiment, based on the three-dimensional model of the fracture area, the module can construct an initial vascular network and set the basic parameters of the blood vessels, ensuring the authenticity and accuracy of the vascular network during the simulation process. Through interaction with the fracture area modeling module, the module can adjust the layout and parameters of the vascular network according to the specific shape and position of the fracture area, so that the simulation results are closer to the actual vascular distribution in the fracture healing process.

[0048] In the above embodiment, the module establishes a flow model of blood flow in the vascular network, taking into account the pumping action of the heart, the blood flow velocity and pressure distribution at the blood vessel entrance, and the pressure conditions at the blood vessel outlet. This enables the simulation system to simulate the real blood flow dynamics. By performing numerical simulation, the module can calculate the blood flow velocity, pressure distribution and shear stress parameters at each point in the vascular network, which helps to understand the effect of blood flow on the fracture healing process.

[0049] The program termination judgment module is also used to: Setting simulation parameters, including density, strength, volume percentage of callus tissue, and the number and distribution of specific types of cells, and setting a termination condition threshold in the simulation system; Collect and record simulation parameter data related to the termination conditions in real time, and set the time interval for regular inspection according to the collection frequency of simulation parameter data; At each inspection time point, the current simulation parameters are compared with the set termination condition threshold. If any simulation parameter reaches the termination condition threshold, the termination process is entered; if all simulation parameters do not reach the termination condition threshold, the simulation process continues and waits for the next inspection time point; When entering the termination process, all activities in the simulation process are stopped immediately, and all simulation data in the simulation process are saved, including but not limited to the three-dimensional model of the fracture area, stress-strain distribution, cell distribution and quantity, and callus growth, and a simulation result report is generated.

[0050] In the above embodiment, by clearly setting the simulation parameters and termination condition thresholds, the module provides clear goals and boundaries for the simulation process, helps to ensure that the simulation results meet the expected scientific standards, improves the accuracy of the simulation process, collects and records simulation parameter data related to the termination conditions in real time, and sets the time interval for regular inspections based on the collection frequency. It can promptly detect and respond to changes in the simulation process, avoid unnecessary waste of computing resources, help shorten the simulation cycle, and improve simulation efficiency.

[0051] In the above embodiment, when the module terminates the simulation process, it will save all simulation data including the three-dimensional model of the fracture area, stress-strain distribution, cell distribution and quantity, callus growth, etc. These data provide information support for subsequent data analysis, result verification and scientific research.

[0052] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A fracture healing regeneration simulation system based on SNS activation, characterized in that: include: Fracture region modeling module for: Acquire a two-dimensional tomographic image from a medical imaging device, and establish a three-dimensional surface geometric model of the fracture site based on three-dimensional reconstruction according to the input two-dimensional tomographic image; Fracture Area Analysis Module for: The three-dimensional model of the fracture area is divided into surface mesh and volume mesh to obtain a finite element model. According to the actual stress conditions of the fracture site, external loads and boundary conditions are set to calculate the stress and strain parameters of the fracture area. SNS activation signal module, used for: The initial SNS signal source is set in the fracture area of ​​the three-dimensional model, and the SNS conduction model is constructed to simulate the interaction between different SNS signals and the activation and conduction process of SNS in the body after fracture. Cell evolution simulation module for: Define the cell types involved in the fracture healing process, including fibroblasts, macrophages, chondroblasts, osteoblasts, osteoclasts, bone stem cells, and immune cells, and simulate cell proliferation, migration, and differentiation behaviors as well as intercellular signaling; Callus Growth Modeling Module for: Initial callus tissue is set in the fracture area. Based on the results of the cell evolution simulation module, the growth process of the callus tissue is simulated, and the remodeling process of the callus under mechanical stimulation and biological signal regulation is simulated to form new bone tissue. Blood supply simulation module for: Based on the three-dimensional model of the fracture area, the initial vascular network was constructed to simulate the flow of blood in the vascular network and analyze the effects of blood supply on cell metabolism, nutrient supply and waste discharge in the fracture area. The program termination judgment module is used to: According to the biological characteristics of fracture healing and the purpose of simulation, the termination condition is set, and whether the termination condition is met is continuously checked during the simulation process. If the termination condition is met, the simulation result is output, and the simulation result includes the fracture healing time and the callus growth; Visual interaction module for: Provides visual display of simulation results and user interaction interface.

2. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 1, characterized in that: The fracture area modeling module comprises: Data import unit for: The two-dimensional tomographic images of the fracture site are obtained through medical imaging equipment and saved in DICOM format. The noise in the image is removed by filtering, and the image is processed by a smoothing algorithm to identify and repair the holes in the image. 3D reconstruction unit for: The two-dimensional tomography images are registered, the two-dimensional image data are divided into three-dimensional voxels, and the three-dimensional surface of the fracture site is extracted from the voxel data according to the set threshold. The extracted three-dimensional surface is optimized, and a three-dimensional surface geometric model of the fracture site is established based on three-dimensional reconstruction.

3. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 2, characterized in that: The process of repairing a cavity includes: Extract the number of pixels contained in the hole area; Comparing the number of pixels contained in the hole area with a preset pixel number threshold; Extracting hole regions in which the number of pixels contained in the hole regions exceeds a preset pixel number threshold as a first hole region group; Extracting hole regions in which the number of pixels contained in the hole regions does not exceed a preset pixel number threshold as a second hole region group; The first weight coefficient corresponding to each hole area of ​​the first hole area group is obtained by using the quantitative relationship between the number of pixels contained in each hole area of ​​the first hole area group and a preset pixel number threshold; wherein the first weight coefficient is obtained by the following formula: Among them, Y 01 represents the first weight coefficient; w 01 represents the position weight value corresponding to each hole region of the first hole region group; w z01 represents the corresponding weights and values ​​in all hole regions of the first hole region group; N 01 represents the number of pixels contained in each hole area of ​​the first hole area group; M represents a preset pixel number threshold; The second weight coefficient corresponding to each hole area of ​​the second hole area group is obtained by using the quantitative relationship between the number of pixels contained in each hole area of ​​the second hole area group and the preset pixel number threshold; wherein the second weight coefficient is obtained by the following formula: Among them, Y 02 represents the second weight coefficient; w 02 represents the position weight value corresponding to each hole area of ​​the second hole area group; z01 represents the corresponding weights and values ​​in all hole regions of the first hole region group; w z02 represents the corresponding weights and values ​​in all hole regions of the second hole region group; N 02 represents the number of pixels contained in each hole area of ​​the second hole area group; M represents a preset pixel number threshold; The corresponding hole area is repaired using the first weight coefficient and the second weight coefficient.

4. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 3, characterized in that: Using the first weight coefficient and the second weight coefficient to repair the corresponding hole area includes: Extracting valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group; Extracting a first weight coefficient corresponding to each hole area in the first hole area group; The first replacement pixel value corresponding to each pixel in the hole area is obtained by using the valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group in combination with the first weight coefficient; wherein the first replacement pixel value is obtained by the following formula: Among them, X t01 represents the first replacement pixel value corresponding to each pixel point of each hole area in the first hole area group; n represents the number of valid pixel points corresponding to the edge area of ​​each hole area in the first hole area group; Y 01 represents the first weight coefficient; X p represents the pixel average value corresponding to n valid pixels; w 01 represents the position weight value corresponding to each hole area of ​​the first hole area group; X 01i represents the pixel value corresponding to the i-th valid pixel point corresponding to the edge area of ​​each hole area in the first hole area group; X 01b represents the standard deviation of the pixel values ​​corresponding to n valid pixels corresponding to the edge area of ​​each hole area in the first hole area group; L 01i represents the straight-line distance between each pixel point in each hole area in the first hole area group and the i-th valid pixel point corresponding to the edge area of ​​each hole area; L 01b represents the standard deviation of the straight-line distance between each pixel point in each hole area in the first hole area group and n valid pixel points corresponding to the edge area of ​​each hole area; Using the first replacement pixel value corresponding to each pixel point contained in the hole area of ​​the first hole area group to replace the pixel value of the corresponding pixel point, so as to complete the hole area repair; Extracting valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; Extracting a second weight coefficient corresponding to each hole area in the second hole area group; The second replacement pixel value corresponding to each pixel in the hole area is obtained by using the valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group in combination with the second weight coefficient; wherein the second replacement pixel value is obtained by the following formula: Among them, X t02 represents the first replacement pixel value corresponding to each pixel point of each hole area in the second hole area group; m represents the number of valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; Y 02 represents the second weight coefficient; X z represents the pixel median value corresponding to m valid pixels; w 02 represents the position weight value corresponding to each hole area of ​​the second hole area group; X 02i represents the pixel value corresponding to the i-th valid pixel point corresponding to the edge area of ​​each hole area in the second hole area group; X 02b represents the standard deviation of the pixel values ​​corresponding to the m valid pixel points corresponding to the edge area of ​​each hole area in the second hole area group; L 02i represents the straight-line distance between each pixel point in each hole area in the second hole area group and the i-th valid pixel point corresponding to the edge area of ​​each hole area; L 02b represents the standard deviation of the straight-line distance between each pixel point in each hole area in the second hole area group and m valid pixel points corresponding to the edge area of ​​each hole area; The second replacement pixel value corresponding to each pixel point contained in the hole area of ​​the second hole area group is used to replace the pixel value corresponding to the pixel point, so as to complete the hole area repair.

5. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 1, characterized in that: The fracture area analysis module comprises: Meshing elements for: Receiving the three-dimensional surface geometric model from the fracture area modeling module, meshing the surface of the three-dimensional model to generate a two-dimensional surface mesh, and based on the two-dimensional surface mesh, performing volume meshing to generate a three-dimensional volume mesh; Finite element analysis setup unit for: According to the anatomical structure and mechanical properties of the fracture site, external loads and boundary conditions are set, wherein the external loads include body weight and muscle force, and the boundary conditions include fixed constraints and sliding constraints. Material properties are defined for the fracture area and surrounding tissues, wherein the material properties include elastic modulus and Poisson's ratio, and finite element analysis parameters are configured, wherein the finite element analysis parameters include solver type, solution accuracy, and number of iterations; Stress-strain calculation unit for: The analysis is performed based on finite element analysis to calculate the stress and strain parameters of the fracture area. After the solution is completed, the stress and strain parameter data of the fracture area are extracted.

6. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 1, characterized in that: The SNS activation signal module is also used for: According to the fracture type and injury degree, the initial SNS signal source position and strength are specified in the fracture area of ​​the three-dimensional model, and an SNS network model of the fracture area and its surroundings is constructed, wherein the SNS network model includes neurons, nerve fibers and connection relationships; Define the conduction velocity, attenuation mechanism, signal bifurcation and convergence rules of SNS signals in nerve fibers, and define the interaction mode between different SNS signals, including enhancement, inhibition and antagonism; Starting from the initial signal source, the signal is propagated in the SNS network according to the set conduction rules. In each time step, the intensity, direction and range of the SNS signal are updated according to the cell-to-cell interaction, local environmental conditions and biochemical reactions, and the SNS signal changes are fed back to the cellular level of the fracture area. Transmit changes in SNS activation signals to the cell evolution simulation module in real time.

7. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 1, characterized in that: The cell evolution simulation module is also used for: Based on the three-dimensional model of the fracture area, the initial distribution and number of cells in and around the fracture area are set, the proliferation rate and conditions are set for each cell type, the proliferation process of cells is simulated according to the cell cycle and growth factors, the migration behavior of cells in the fracture area is simulated, and the differentiation process of cells is simulated according to the stage of fracture healing and local environmental conditions; Constructing a network model of intercellular signal transduction to simulate the transmission, reception and response process of signal molecules between cells. The signal molecules include growth factors, chemokines and cytokines. According to the type and concentration of signal molecules, the regulatory effect on cell behavior is simulated. The cell behavior includes proliferation, migration and differentiation. Receive the SNS signal output by the SNS signal module, adjust the cell proliferation, migration and differentiation rates according to the SNS signal, receive the stress and strain parameters calculated by the fracture area analysis module, and pass the cell proliferation, migration and differentiation results to the callus growth modeling module.

8. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 1, characterized in that: The callus growth modeling module is also used for: According to the three-dimensional model of the fracture area, initial callus tissue is set between or around the fracture ends, and basic callus parameters are set for the initial callus, wherein the callus parameters include density, strength, elastic modulus and quantity; Receive data on cell types, numbers, distribution and activities from the cell evolution simulation module, map the results of cell proliferation, migration and differentiation onto the callus tissue, update the number, type and position of cells in the callus, and simulate the growth of the callus tissue; Simulate the absorption of old bone tissue by osteoclasts and the formation of new bone tissue by osteoblasts. According to the results of the blood supply simulation module, simulate the expansion and reconstruction of the vascular network in the callus, set the time step, and iteratively update the density, strength, structure and biological properties of the callus.

9. The fracture healing regeneration simulation system based on SNS activation as claimed in claim 1, characterized in that: The blood supply simulation module is also used for: An initial vascular network is constructed based on the three-dimensional model of the fracture area, and basic parameters of the blood vessels are set, including diameter, length, bifurcation angle, and blood flow velocity; Establish a blood flow model in the vascular network, set the heart's pumping action, the blood flow velocity and pressure distribution at the vascular inlet, and the pressure conditions at the vascular outlet, perform numerical simulation, and calculate the blood flow velocity, pressure distribution, and shear stress parameters at each point in the vascular network; It interacts with the fracture area modeling module to adjust the layout and parameters of the vascular network according to the three-dimensional model of the fracture area, and interacts with the cell evolution simulation module to provide blood flow parameters as input conditions for cell metabolism and activity.

10. The fracture healing regeneration simulation system based on SNS activation according to claim 1, characterized in that: The program termination judgment module is also used for: Setting simulation parameters, including density, strength, volume percentage of callus tissue, and the number and distribution of specific types of cells, and setting a termination condition threshold in the simulation system; Collect and record simulation parameter data related to the termination conditions in real time, and set the time interval for regular inspection according to the collection frequency of simulation parameter data; At each inspection time point, the current simulation parameters are compared with the set termination condition threshold. If the inspection finds that any simulation parameter reaches the termination condition threshold, the termination process is entered; If all simulation parameters do not reach the termination condition threshold, the simulation process continues and waits for the next inspection time point; When entering the termination process, all activities in the simulation process are stopped immediately, and all simulation data in the simulation process are saved, including but not limited to the three-dimensional model of the fracture area, stress-strain distribution, cell distribution and quantity, and callus growth, and a simulation result report is generated.

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