Oral maxillofacial implant design method based on computer vision technology

Abstract

The invention relates to the technical field of image processing, in particular to an oral maxillofacial implant design method based on a computer vision technology, which comprises the following steps of: based on a current maxillofacial image of a patient, identifying maxillofacial structure positioning, identifying key features of the image, and obtaining a key maxillofacial structure diagram; and inputting the key maxillofacial structure diagram into maxillofacial change prediction to obtain a maxillofacial structure change prediction diagram. According to the method, the maxillofacial structure is accurately positioned, fine features are captured and three-dimensional modeling is performed through an image processing technology, an oral maxillofacial implant design is analyzed and optimized and an image edge detection technology, so that the image analysis precision is improved, accurate data support is provided for implant design, and jaw bone density and bone change are analyzed; high matching between the implant design and the maxillofacial structure of a patient is ensured, the mismatching risk is reduced, the practicability, safety and durability of the design are improved through three-dimensional reconstruction and mechanical analysis, visual feedback is provided for design verification through real-time simulation testing, and the design reliability is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to an oral and maxillofacial implant design method based on computer vision technology. Background Art

[0002] The field of image processing technology involves the use of algorithms and mathematical methods to analyze, process and improve image signals in order to improve image quality, extract useful information or achieve specific visual effects. This field covers everything from basic image enhancement, compression and restoration processing techniques to more advanced feature extraction, image recognition and computer vision applications. In medicine and biomedical engineering, image processing technology pays special attention to how to extract and use image data to support medical activities such as diagnosis, monitoring and treatment, and is often used for key tasks such as enhancing image clarity, identifying lesion areas, and performing three-dimensional reconstruction.

[0003] Among them, the oral and maxillofacial implant design method mainly uses image processing technology to optimize and assist the design process of implants. Through precise image analysis, this method can perform detailed three-dimensional modeling of the patient's oral structure, thereby providing accurate data support for the customization of implants. In implant design, image processing technology can ensure that the size, shape and position of the implant are highly matched with the patient's specific maxillofacial structure, thereby optimizing the design effect and improving the practicality and aesthetics of the design. Advanced image analysis tools, such as algorithm-driven edge detection, region segmentation and volume measurement, can be used to accurately simulate and predict the performance of implants in actual applications.

[0004] Existing technologies rely on basic image enhancement and reconstruction techniques in oral and maxillofacial implant design. Although they can provide basic image processing functions, they lack sufficient accuracy and adaptability when dealing with more complex maxillofacial structures. For example, traditional image processing technology cannot effectively identify subtle differences in maxillofacial structures, such as slight bone changes or early lesion areas, which will affect the accuracy and safety of implant design. The lack of advanced image analysis tools such as algorithm-driven edge detection and region segmentation limits the personalization and optimization of the design. In actual operation, the limitations of this technology lead to the need for multiple adjustments to the design plan, increasing the complexity of the operation and the risk to the patient. The technology that fails to conduct real-time simulation testing is not sufficient to detect problems in the design in advance. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an oral and maxillofacial implant design method based on computer vision technology.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: an oral and maxillofacial implant design method based on computer vision technology, comprising the following steps:

[0007] S1: Based on the patient's current maxillofacial image, identify the maxillofacial structure location, identify the key features of the image, obtain a key maxillofacial structure map, input the key maxillofacial structure map into the maxillofacial change prediction, and obtain a maxillofacial structure change prediction map;

[0008] S2: Based on the predicted map of maxillofacial structure changes, the jaw bone density is analyzed, including bone changes in the implant area, to obtain a maxillofacial change trend analysis result, and the implant design parameters, including the depth and angle of the implant, are adjusted according to the maxillofacial change trend analysis result to match the predicted structural changes, and an adjusted implant design plan is generated;

[0009] S3: reconstructing the adjusted implant design scheme in three dimensions using computer simulation technology, simulating the implant area, obtaining a three-dimensional implant model, performing mechanical analysis on the three-dimensional implant model, evaluating the stability and adaptability of the implant in real-time application, and generating implant mechanical analysis results;

[0010] S4: Based on the results of the implant mechanical analysis, the design scheme is adjusted to adjust the shape and size of the implant to match the patient's maxillofacial structure to obtain an optimized implant configuration. According to the optimized implant configuration, a real-time operation simulation test is performed to verify the real-time application effect of the design and generate a verified implant design result.

[0011] As a further solution of the present invention, the steps of obtaining the maxillofacial structure change prediction map are specifically as follows:

[0012] S111: Based on the current maxillofacial image of the patient, edge detection is performed, and image edge enhancement is performed by applying a Sobel operator to obtain an enhanced maxillofacial image;

[0013] S112: Based on the enhanced maxillofacial image, locate key maxillofacial structures, identify key points of the structures using a Harris corner detection algorithm, mark the key points, and generate a marked key maxillofacial structure diagram;

[0014] S113: Input the marked key maxillofacial structure diagram into the maxillofacial change prediction model, use the time series analysis model, combined with linear regression technology, to simulate the changes of the maxillofacial structure in the future time period, using the formula:

[0015] V ta =α a ×V t-1a +β a ×X ta +γ a ×ΔX t-1a

[0016] Calculate the predicted maxillofacial changes and obtain the predicted maxillofacial structure change map, where V tarepresents the predicted change of maxillofacial structure at time t, V t-1a Represents the predicted map of maxillofacial structure changes at the previous time point, α a represents the influence weight of maxillofacial changes at the previous time point, β a and γ a Represent the coefficients of key structural changes at the current and previous time points, X ta Represents the key maxillofacial structure diagram at the current time point, ΔX t-1a Represents the change from the previous time point to the current time point.

[0017] As a further solution of the present invention, the steps for obtaining the maxillofacial change trend analysis results are specifically as follows:

[0018] S211: Based on the predicted map of maxillofacial structure changes, jaw bone density analysis is performed, and changes in bone quality in the implantation area are quantitatively analyzed through resolution scanning and pixel intensity measurement to obtain jaw bone density analysis data of the implantation area;

[0019] S212: using the jaw bone density analysis data of the implantation area, performing quantitative calculation, applying the target bone strength assessment algorithm, calculating the amount of bone change in the implantation area, and obtaining a bone change assessment result;

[0020] S213: Combining the jaw bone density analysis data of the implant area with the bone change assessment result, and performing jaw bone density analysis, using the formula:

[0021] R b =β b ×D b +γ b ×C b

[0022] Generate maxillofacial change trend analysis results, where R b represents the analysis result of maxillofacial change trend, β b The weight coefficient of bone quality change in the implant area, D b is the data obtained from jaw bone density analysis, γ b is the adjustment coefficient, C b Indicates the amount of bone change.

[0023] As a further solution of the present invention, the steps for obtaining the adjusted planting design plan are specifically as follows:

[0024] S221: extracting key data from the maxillofacial change trend analysis results, including expected changes in the jaw, performing biomechanical simulation to extract data, determining key parameters of implant design, and generating an adjustment requirement list;

[0025] S222: dynamically adjusting implant parameters according to the adjustment requirement list, simulating the influence of differentiated implant depth and angle on maxillofacial adaptability, dynamically adjusting implant configuration according to input maxillofacial data, and generating an optimized implant design sketch;

[0026] S223: Based on the optimized implant design sketch, matching clinical safety standards and patient needs, the design parameters are calculated using the formula:

[0027] D c =δ c ×S c +γ c ×φ c

[0028] Generate an adjusted planting design plan, where D c represents the adjusted planting design, δ c and γ c is the adjustment weight for depth and angle, S c and φ c Depth and angle parameters recommended in simulation results.

[0029] As a further solution of the present invention, the steps of obtaining the three-dimensional implant model are specifically:

[0030] S311: extracting parameters from the adjusted implant design, including the depth and angle of the implant, converting the parameters into a recognizable format, and generating an initial three-dimensional model sketch;

[0031] S312: The initial three-dimensional model sketch is adjusted, and the geometric and mechanical properties of the model are optimized using numerical optimization technology, using the formula:

[0032] M d =α d ·P d +β d Q d +γ d ·R d

[0033] Generate detailed 3D implant design, where M d Represents the parameters of the three-dimensional model, α d , β d and γ d Represent the adjustment coefficients of depth, angle and structural complexity, P d , Q d and R d are the parameters obtained from the preliminary model;

[0034] S313: Based on the refined three-dimensional implant design, the model is tested and verified, mechanical and functional tests are performed, the real-time application effect of the model is verified, adjustments are made according to the test results, and a three-dimensional implant model is generated.

[0035] As a further solution of the present invention, the steps for obtaining the implant mechanics analysis results are specifically as follows:

[0036] S321: Based on the three-dimensional implant model, initializing the data of the implant model, including the dimensions, material properties and expected load conditions of the model, inputting the model dimensions, defining the material properties, recording the expected load conditions, and generating implant model parameters for mechanical analysis;

[0037] S322: Based on the implant model parameters obtained through the mechanical analysis, a mechanical simulation algorithm is applied to the model to perform stress analysis using the formula:

[0038]

[0039] Generate stress response and failure prediction results, where ρ h represents the material density, v h is the load speed, A h is the force-bearing area, α h and β h is the experience adjustment coefficient, S h Present stress response and failure prediction results;

[0040] S323: Based on the stress response and failure prediction results, the overall stability and adaptability of the implant are evaluated, key stress areas and structural stability are analyzed, and implant mechanical analysis results are generated.

[0041] As a further solution of the present invention, the step of obtaining the optimized implant configuration is specifically:

[0042] S411: Based on the mechanical analysis result of the implant, according to the maxillofacial structure of the patient, targeted size adjustment is performed, stress concentration values ​​of multiple regions in the mechanical analysis are called, the parts that need to be optimized are analyzed, and the size adjustment of the three-dimensional geometry is performed in combination with the maxillofacial CT scanning data to generate a preliminary implant design plan;

[0043] S412: Based on the preliminary implant design, adjust the implant shape and size using the formula:

[0044]

[0045] Calculate the size of the adjusted area and obtain the three-dimensional shape data of the implant, where F g is the mechanical stress before adjustment, E g is the elastic modulus, Lg is the implant length, A g It indicates the size change of the implant area after adjustment;

[0046] S413: Using the three-dimensional shape data of the implant, iterative optimization is performed to verify the matching degree between the shape and size of the implant and the maxillofacial structure by simulating the chewing and dynamic occlusion process of the patient, and fine-tuning is performed according to the simulation results to obtain an optimized implant configuration.

[0047] As a further solution of the present invention, the steps of obtaining the verified implant design result are specifically:

[0048] S421: Based on the optimized implant configuration, a set of mechanical parameters matching the real-time simulation test is selected to set initial conditions for real-time operation simulation, and the implant shape, size and mechanical properties are combined to match the maxillofacial structure of the patient, and mechanical matching is performed by calling previous data combined with pressure variables in the operation environment to establish a preliminary set of operation conditions;

[0049] S422: Perform simulation test according to the preliminary set of operating conditions, using the formula:

[0050]

[0051] Calculate the mechanical response parameters in the simulation operation and generate the mechanical response value of the simulation test, where R v Represents the mechanical response value of the simulated test, F v is the external force applied in real time, A v is the area of ​​force action, ΔT v is the time interval, E v is the elastic modulus of the material;

[0052] S423: Based on the mechanical response value of the simulation test, the real-time operation is verified, and the parameters are adjusted in real time to match the patient's maxillofacial structure by dynamically analyzing the changes in mechanical behavior during the operation. The shape and size of the implant are optimized and corrected by comparing the pressure and the response value, and a verified implant design result is generated.

[0053] Compared with the prior art, the advantages and positive effects of the present invention are:

[0054] In the present invention, the oral and maxillofacial implant design process is optimized through precise image analysis and advanced image processing technology. The maxillofacial structure can be located more accurately through image edge detection technology. This refined image processing can capture more subtle maxillofacial features, thereby performing more detailed three-dimensional modeling of the patient's oral structure, which not only improves the analysis accuracy of the image, but also provides more accurate data support for the customization of implant design. Through in-depth analysis of jaw bone density and bone changes, the design of the implant is more in line with the patient's actual maxillofacial physiological structure, reducing complex adjustments and potential implant failure risks caused by mismatches. The application of three-dimensional reconstruction and mechanical analysis not only improves the practicability and adaptability of implant design, but also improves the safety and durability of the entire design. The introduction of real-time operation simulation testing provides intuitive feedback for design verification and enhances the reliability of the design. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the main steps of the present invention;

[0056] Figure 2 A flowchart of a maxillofacial structure change prediction diagram in the present invention;

[0057] Figure 3 It is a flow chart of the maxillofacial change trend analysis results in the present invention;

[0058] Figure 4 A flow chart of the adjusted planting design scheme in the present invention;

[0059] Figure 5 A flow chart of the three-dimensional implant model in the present invention;

[0060] Figure 6 It is a flow chart of the results of the mechanical analysis of the implant in the present invention;

[0061] Figure 7 A flow chart of the optimized implant configuration of the present invention;

[0062] Figure 8 This is a flow chart of the implant design results verified in the present invention. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0064] In the description of the present invention, it is necessary to interpret that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be interpreted as a limitation on the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0065] Embodiment 1

[0066] See also Figure 1 The present invention provides a technical solution: a method for designing oral and maxillofacial implants based on computer vision technology, comprising the following steps:

[0067] S1: Based on the patient's current maxillofacial image, the image edge detection technology is used to identify the location of the maxillofacial structure, the key features of the image are identified, and the key maxillofacial structure map is obtained. The key maxillofacial structure map is input into the maxillofacial change prediction, and the image data is used to simulate the structure changes of the maxillofacial face in the future time period to obtain the maxillofacial structure change prediction map;

[0068] S2: Based on the predicted map of maxillofacial structure changes, the jaw bone density is analyzed, including the bone changes in the implant area, to obtain the maxillofacial change trend analysis results. According to the maxillofacial change trend analysis results, the implant design parameters, including the depth and angle of the implant, are adjusted to match the predicted structural changes, and the adjusted implant design plan is generated;

[0069] S3: Use computer simulation technology to reconstruct the adjusted implant design in three dimensions, simulate the implant area, obtain a three-dimensional implant model, perform mechanical analysis on the three-dimensional implant model, evaluate the stability and adaptability of the implant in real-time application, and generate implant mechanical analysis results;

[0070] S4: Based on the results of implant mechanics analysis, adjust the design plan, adjust the shape and size of the implant, match the patient's maxillofacial structure, and obtain the optimized implant configuration. According to the optimized implant configuration, perform real-time operation simulation test to verify the real-time application effect of the design and generate the verified implant design results.

[0071] The key maxillofacial structure diagram includes the jaw edge, tooth root position, and nerve channel. The maxillofacial structure change prediction diagram includes the expected bone growth area, expected bone resorption area, and key load points. The maxillofacial change trend analysis results include the bone density change rate, the strength of the key support area, and the potential risk points. The adjusted implant design plan includes the adjusted implant depth, the adjusted implant angle, and the symmetry of the implant area. The three-dimensional implant model includes the maxillofacial bone model, pre-designed implants, and simulated fixtures. The implant mechanical analysis results include the mechanically stable area and the potential unstable area. The optimized implant configuration includes shape optimization design, precise size adjustment, and interface adaptability. The verified implant design results include design stability test, adaptability test results, and user satisfaction survey.

[0072] See also Figure 2 ,The specific steps for obtaining the maxillofacial structure change prediction map are:

[0073] S111: Based on the current maxillofacial image of the patient, edge detection is performed, and image edge enhancement is performed by applying a Sobel operator to obtain an enhanced maxillofacial image;

[0074] Based on the patient's current maxillofacial image, the first task of performing edge detection is to enhance the edges of the maxillofacial structures by applying the Sobel operator through image processing software, and to identify the edges by calculating the gradient intensity of the image brightness to ensure that the important maxillofacial structures in the image are accurately highlighted, which is crucial for subsequent feature extraction and analysis. The enhanced maxillofacial image will be used for the positioning and marking of key maxillofacial structures in the next step to ensure that the key maxillofacial structures in the image can be accurately identified and processed.

[0075] S112: Based on the enhanced maxillofacial image, locate the key maxillofacial structures, use the Harris corner detection algorithm to identify the key points of the structure, mark the key points, and generate a marked key maxillofacial structure map;

[0076] In the enhanced maxillofacial image, when using the Harris corner detection algorithm to identify and locate the key maxillofacial structures, the algorithm first evaluates the corner response value of each pixel by constructing the gradient covariance matrix of the image. This is achieved by detecting the degree of brightness change in the local image area. A higher intensity change indicates that the area is a corner point. The corner point is marked as the representative feature of the key maxillofacial structure. The marked key maxillofacial structure image will provide the necessary input data for the maxillofacial structure change prediction model and provide a basis for accurate prediction of future changes.

[0077] S113: Input the marked key maxillofacial structure diagram into the maxillofacial change prediction model, use the time series analysis model, combined with linear regression technology, to simulate the changes of the maxillofacial structure in the future time period, using the formula:

[0078] Vta =α a ×V t-1a +β a ×X ta +γ a ×ΔX t-1a

[0079] Calculate the predicted maxillofacial changes and obtain the predicted maxillofacial structure change map, where V ta represents the predicted change of maxillofacial structure at time t, V t-1a Represents the predicted map of maxillofacial structure changes at the previous time point, α a represents the influence weight of maxillofacial changes at the previous time point, β a and γ a Represent the coefficients of key structural changes at the current and previous time points, X ta Represents the key maxillofacial structure diagram at the current time point, ΔX t-1a Represents the change from the previous time point to the current time point;

[0080] The benefit of the formula is that by combining the change data of maxillofacial structure at consecutive time points and the corresponding weight parameters, it can dynamically predict future maxillofacial changes, thus providing a basis for clinical treatment and improving the pertinence and effectiveness of treatment;

[0081] Assume that at a certain time point t, the characteristic value of the key structure of the maxillofacial image is X ta = 0.5, the predicted map of maxillofacial structure changes at the previous time point is V t-1a =0.3, the change from the previous time point to the current time point is ΔX t-1a =0.1, weight parameter α a =0.6,β a =0.3,γ a = 0.1, calculate V ta :

[0082] V ta =0.6×0.3+0.3×0.5+0.1×0.1=0.18+0.15+0.01=0.34

[0083] The results show that under the current model parameters and input data, the predicted value of the maxillofacial structure change prediction map at time point t is 0.34. The numerical value can assist doctors in analyzing the changing trend of the patient's maxillofacial structure and thus adjust the plan.

[0084] See also Figure 3 ,The specific steps for obtaining the maxillofacial change trend analysis results are as follows:

[0085] S211: Based on the predicted map of maxillofacial structure changes, the jaw bone density is analyzed. Through resolution scanning and pixel intensity measurement, the changes in bone quality in the implant area are quantitatively analyzed to obtain the jaw bone density analysis data of the implant area.

[0086] Based on the predicted map of maxillofacial structure changes, high-resolution scanning and pixel intensity measurement are used to carefully analyze the jaw bone density in the implant area. This is achieved through image processing software, which performs grayscale value analysis on each pixel in the image to quantitatively evaluate bone density changes. This data processing provides accurate measurement results for subsequent steps, ensuring that bone changes in the implant area are accurately captured and recorded. The jaw bone density analysis data collected in this process will directly affect the final evaluation results and become an important basis for formulating a treatment plan.

[0087] S212: using the jaw bone density analysis data of the implant area, performing quantitative calculation, applying the target bone strength assessment algorithm, calculating the amount of bone change in the implant area, and obtaining a bone change assessment result;

[0088] The jaw bone density analysis data is further processed through professional biomechanical analysis software. The software's built-in quantitative calculation model evaluates bone strength based on the input data and accurately calculates the amount of bone change in the implant area. The calculation is based on biomechanical principles and can predict the bone's ability to support implants. The calculation results will provide the clinic with a basis for decision-making on whether implants are suitable, ensuring the maximization of implant success rates. The bone change assessment results reflect the actual condition of the patient's bone condition and provide key data for subsequent adjustments to treatment plans.

[0089] S213: Combine the jaw bone density analysis data of the implant area with the bone change assessment results, and perform jaw bone density analysis using the formula:

[0090] R b =β b ×D b +γ b ×C b

[0091] Generate maxillofacial change trend analysis results, where R b represents the analysis result of maxillofacial change trend, β b The weight coefficient of bone quality change in the implant area, D b is the data obtained from jaw bone density analysis, γ b is the adjustment coefficient, C b Indicates the amount of bone change;

[0092] The benefit of the formula is that by combining bone density data with the amount of bone change, the accuracy of the prediction model can be dynamically adjusted to ensure that the prediction results are highly consistent with the actual patient condition, thereby providing more personalized recommendations;

[0093] Set the bone density D of the implant area b 2.5g / cm3 and bone mass change C b is 0.3g / cm3, weight coefficient β b is 0.8, and the adjustment coefficient γ b is 0.2, and the calculation process is:

[0094] R b =0.8×2.5+0.2×0.3=2.0+0.06=2.06

[0095] The results showed that according to the current bone density and the amount of change, the maxillofacial change trend analysis result was 2.06. The results were helpful in evaluating the suitability of the implant area and providing a quantitative assessment of the jaw condition for clinical practice.

[0096] See also Figure 4 , the specific steps for obtaining the adjusted planting design plan are:

[0097] S221: Extract key data from the results of maxillofacial change trend analysis, including expected changes in the jaw, perform biomechanical simulation to extract data, determine key parameters for implant design, and generate a list of adjustment requirements;

[0098] Based on the detailed analysis results of maxillofacial change trends, in-depth data analysis was carried out to extract key change indicators, such as the expected movement distance and angle change of the jaw. The data was obtained through advanced biomechanical simulation, and precise numerical analysis technology was used to ensure the high accuracy and operability of the data. The implant design plan can be dynamically adjusted to adapt to the specific biomechanical needs of the individual. The use of real-time feedback mechanism is emphasized to facilitate real-time updating of design parameters to ensure the precise matching of implant design. Data integration processing is also realized to ensure that every step from maxillofacial scanning data to the final design plan is based on actual measurement and calculation, and does not rely on traditional empirical estimates. A detailed list of adjustment needs is generated, listing all necessary adjustment parameters and expected implant effects, providing solid data support for the next step of design adjustment.

[0099] S222: Dynamically adjust implant parameters according to the adjustment requirements list, simulate the impact of differentiated implant depth and angle on maxillofacial adaptability, dynamically adjust implant configuration according to input maxillofacial data, and generate an optimized implant design sketch;

[0100] Continuing with the above implant design process, we entered the actual parameter adjustment stage. Based on the previously generated adjustment requirement list, we used the internally developed dynamic adjustment algorithm to perform detailed adjustments to the implant depth and angle. The algorithm was personalized based on the patient's specific maxillofacial structure changes, and the optimal implant depth and angle were determined through mathematical modeling and mechanical analysis, and then real-time design optimization was performed. By simulating the stress distribution of differentiated implant configurations in the jaw, we ensured that the adjustment measures were not only scientific but also practical. The entire process was completely independent of any external software and was completely driven by proprietary technology. A preliminary draft of the adjusted implant design plan was generated, which recorded in detail each parameter of the implant and the expected structural adaptability, providing sufficient scientific basis and technical documentation for clinical application and further verification tests.

[0101] S223: Based on the optimized implant design sketch, matching clinical safety standards and patient needs, the design parameters are calculated using the formula:

[0102] D c =δ c ×S c +γ c ×φ c

[0103] Generate an adjusted planting design plan, where D c represents the adjusted planting design, δ c and γ c is the adjustment weight for depth and angle, S c and φ c The depth and angle parameters recommended in the simulation results;

[0104] The benefit of the formula is that it can accurately calculate the weight factors of depth and angle in implant design adjustment, dynamically adjust the implant design according to the predicted changes in maxillofacial structure, and adjust the weight δ by setting the depth c = 0.6 and angle adjustment weight γ c = 0.4, combined with the recommended depth S provided by maxillofacial scanning data c =10mm and angle φ c =25°;

[0105] First, substitute the recommended values ​​for depth and angle into the formula to calculate D c=0.6×10+0.4×25=16, and the comprehensive parameters that the adjusted design should achieve are obtained. This calculation process is not only based on a strict mathematical model, but also combines actual biomechanical feedback to ensure the optimal adaptation of the implant design. This result indicates that the adjusted implant design is not only scientific, but also has high individual adaptability, which helps to improve the success rate of the operation and patient satisfaction. The detailed numerical results can also serve as an important basis for clinical decision-making to further optimize the design and implementation strategies of implants.

[0106] See also Figure 5 , the specific steps for obtaining the three-dimensional implant model are:

[0107] S311: extracting parameters from the adjusted implant design, including the depth and angle of the implant, converting the parameters into a recognizable format, and generating an initial three-dimensional model sketch;

[0108] Based on the adjusted implant design plan, the design parameters, such as the depth and angle of the implant, are first extracted. The parameters are digitized and standardized through computer-aided design software and input into the 3D simulation system to generate a preliminary 3D model sketch. The process not only includes simple input of parameters, but also involves a specific analysis of how each parameter affects the implant design. For example, the depth parameter will directly affect the stability of the implant and the degree of integration with the surrounding bone structure, while the angle parameter determines the coordination between the implant and the natural arrangement of the teeth. It is necessary to set the corresponding simulation environment in the software for detailed adjustments to ensure the accuracy and practicality of the model.

[0109] S312: Adjust the initial 3D model sketch and use numerical optimization technology to optimize the geometric and mechanical properties of the model using the formula:

[0110] M d =α d ·P d +β d Q d +γ d ·R d

[0111] Generate detailed 3D implant design, where M d Represents the parameters of the three-dimensional model, α d , β d and γ d Represent the adjustment coefficients of depth, angle and structural complexity, P d , Q d and R d are the parameters obtained from the preliminary model;

[0112] The benefit of the formula is that it allows us to adjust the parameter α d , βd and γ d To precisely control the depth, angle and structural complexity of the model, so as to optimize the design to meet clinical needs. By improving parameter settings, the individualization of implant design can be achieved, and the success rate and patient satisfaction after implantation can be improved.

[0113] Set the initial parameter P d , Q d and R d Set the adjustment coefficient α to 10, 20 and 5 respectively. d =0.5,β d =1.5,γ d =1.0, substitute into the formula to get M d =0.5·10+1.5·20+1.0·5=45;

[0114] The results indicate that the adjusted three-dimensional model will optimize the implant angle and depth while ensuring structural stability to adapt to specific clinical operating environments.

[0115] S313: Based on the detailed 3D implant design, the model is tested and verified, mechanical and functional tests are performed to verify the real-time application effect of the model, adjustments are made according to the test results, and a 3D implant model is generated;

[0116] After completing the initial adjustment of the model, simulation software will be used for further testing and verification, including mechanical property testing and functional simulation. Through testing, the performance of the 3D model in the expected clinical application can be verified, such as whether it can withstand normal chewing forces and the compatibility of the implant with the surrounding tissue. The test results will directly affect the final adjustment of the model. If it is found that the model performs poorly in certain tests, it is necessary to return to the simulation software to adjust the associated parameters, such as increasing the depth of the implant or adjusting the angle, to ensure that the final product can meet clinical needs and patient comfort. This process involves detailed analysis and application of test data to ensure that the final output of the model meets both design requirements and matches the patient's specific anatomical structure.

[0117] See also Figure 6 , the specific steps for obtaining the results of implant mechanics analysis are:

[0118] S321: based on the three-dimensional implant model, initializing the data of the implant model, including the dimensions, material properties and expected load conditions of the model, inputting the model dimensions, defining the material properties, recording the expected load conditions, and generating implant model parameters for mechanical analysis;

[0119] The steps to initialize the implant model begin with acquiring three-dimensional image data from high-precision CT scans. The data is converted through image processing software to generate an accurate three-dimensional geometric model. The stage includes the calibration of material properties, such as elastic modulus and density, as well as predefined load and boundary condition settings to simulate the actual environment of the implant in the oral cavity. Through the preparatory work, a complete model is obtained, which lays a solid foundation for the subsequent mechanical properties analysis, ensures the accuracy and practicality of the subsequent analysis, and finally generates the implant model parameters prepared for mechanical analysis.

[0120] S322: Based on the implant model parameters of mechanical analysis, apply mechanical simulation algorithm to the model and perform stress analysis using the formula:

[0121]

[0122] Generate stress response and failure prediction results, where ρ h represents the material density, v h is the load speed, A h is the force-bearing area, α h and β h is the experience adjustment coefficient, S h Present stress response and failure prediction results;

[0123] This formula provides a method to quantify the stress state of an implant when it is subjected to force;

[0124] ρ h Represents material density, reflecting the basic physical properties of implant materials, such as titanium alloy;

[0125] v h is the applied load velocity, simulating the impact velocity during the implantation process;

[0126] A h It is the force-bearing area of ​​the implant surface and is the key factor affecting the mechanical response;

[0127] α h and β h It is a coefficient adjusted based on empirical data collected in actual applications to make the simulation results closer to the actual application conditions;

[0128] Given ρ h 4500kg / m3 (implant material is lightweight titanium alloy), v h Set to 3m / s (considering the rapid implantation during surgery), A h 0.005m2 (implant contact area), α h Set to 1.1, β h Set it to 0.8 and substitute it into the formula to get:

[0129]

[0130] The stress level that the implant can withstand under preset conditions provides important safety guarantees for clinical operations and guides further implant design and optimization.

[0131] S323: Based on the stress response and failure prediction results, evaluate the overall stability and adaptability of the implant, analyze the key stress areas and structural stability, and generate implant mechanical analysis results;

[0132] The stability and adaptability of the implant are evaluated based on the results of comprehensive mechanical analysis, the stress distribution of key structures is specifically analyzed, structural weaknesses are identified, and suggestions for design improvements are made. During the analysis process, the finite element method is used to simulate the response of the implant under differentiated chewing forces, identify stress concentration areas and potential fatigue failure locations. The analysis results not only support the optimization of implant design, but also provide clinicians with a mechanical reference during operation, ensuring the long-term stability and reliability of the implant, and further promoting the application and development of implant technology.

[0133] See also Figure 7 , the steps to obtain the optimized implant configuration are as follows:

[0134] S411: Based on the results of implant mechanical analysis and the maxillofacial structure of the patient, targeted size adjustment is performed, stress concentration values ​​of multiple regions in mechanical analysis are called, the parts that need to be optimized are analyzed, and the size adjustment of three-dimensional geometry is performed in combination with maxillofacial CT scan data to generate a preliminary implant design plan;

[0135] Based on the results of implant mechanics analysis, the deficiencies in implant shape and size are obtained. Combined with the patient's maxillofacial CT scan data, the stress distribution in each area of ​​the implant is first analyzed in detail, and the stress concentration sites are marked. By calculating the geometric parameters of the patient's maxillofacial structure and comparing them with the initial design dimensions of the implant, the sites that need to be adjusted are further clarified. The bone density data and bite force distribution of the maxillofacial structure are called, and the impact of the data on the shape of the implant is analyzed to determine the specific direction of adjusting the implant shape. Combined with the stress change trend of each site, the shape parameters of each area are adjusted in turn to generate a preliminary implant design plan.

[0136] S412: Based on the preliminary implant design, adjust the implant shape and size using the formula:

[0137]

[0138] Calculate the size of the adjusted area and obtain the three-dimensional shape data of the implant, where F g is the mechanical stress before adjustment, Eg is the elastic modulus, L g is the implant length, A g It indicates the size change of the implant area after adjustment;

[0139] This formula can accurately calculate the size changes of each area of ​​the implant under mechanical effects, so that it matches the patient's maxillofacial structure and avoids errors that occur during traditional size adjustment.

[0140] In this formula, the parameter F g represents the mechanical stress value of each region before adjustment, E g is the elastic modulus of the implant material, L g is the implant length before adjustment, and the mechanical stress F is measured by maxillofacial CT data. g =450N, elastic modulus E g =70GPa, length L g =10mm, substitute into the formula to calculate:

[0141]

[0142] After adjustment, the size of a certain area of ​​the implant should be 0.801 mm, so that the stress in the area is more uniform, meeting the needs of the maxillofacial structure and ensuring the stability and durability of the implant in long-term use.

[0143] S413: Use the implant's 3D shape data to perform iterative optimization. By simulating the patient's chewing and dynamic occlusion process, verify the matching degree between the implant's shape and size and the maxillofacial structure, and make fine adjustments based on the simulation results to obtain the optimized implant configuration.

[0144] Use the adjusted 3D shape data from the previous step for further fine-tuning. By simulating the patient's chewing and dynamic occlusion process, first analyze the stress distribution of the implant shape under differentiated occlusion states, calculate the stress concentration degree of the differentiated area, and evaluate its matching degree with the patient's bite force. Then call the patient's maxillofacial mechanics model, combine the geometric characteristics of the implant, analyze the dynamic stress changes caused by each occlusion, and further adjust the shape and size parameters of each area to eliminate stress concentration. Finally, determine the optimal implant shape and generate an optimized implant configuration.

[0145] See also Figure 8 , the specific steps for obtaining the verified implant design results are:

[0146] S421: Based on the optimized implant configuration, a set of mechanical parameters matching the real-time simulation test is selected to set the initial conditions for real-time operation simulation, and the implant shape, size and mechanical properties are combined to match the patient's maxillofacial structure. Mechanical matching is performed by calling the previous data and combining the pressure variables in the operation environment to establish a preliminary set of operation conditions;

[0147] Based on the optimized implant configuration, the patient's maxillofacial structure parameters are first determined, including the geometric dimensions of the mandible, bone density distribution, angle parameters, etc., and then compared with the geometric shape and size of the implant to analyze the fit of the structure. The patient's maxillofacial mechanical parameters, such as bone elastic modulus and stress distribution, are called and compared with the implant's mechanical parameters. If the match is not high, slight shape adjustments are made to make the implant better fit the maxillofacial structure. Parameters including the width, length, angle, etc. of the implant are adjusted to ensure that the adjusted design can achieve stability in the maxillofacial structure.

[0148] S422: Based on the preliminary set of operating conditions, conduct simulation tests using the formula:

[0149]

[0150] Calculate the mechanical response parameters in the simulation operation and generate the mechanical response value of the simulation test, where R v Represents the mechanical response value of the simulated test, F v is the external force applied in real time, A v is the area of ​​force action, ΔT v is the time interval, E v is the elastic modulus of the material;

[0151] The benefit of the formula is that it can calculate and adjust the mechanical response in real time through the combination of multiple parameters, ensuring that the test results can reflect the mechanical performance of the implant in actual application;

[0152] Set F v is 50N, representing the force applied by the implant during the simulation, A v is 10mm2, indicating the area where the force is applied, ΔT v is 0.05s, indicating the time interval of force action, E v is the bone elastic modulus, which is 10 GPa. The mechanical response is calculated according to the formula:

[0153]

[0154] The results showed that the mechanical response of the implant in the test was 1 MPa, which was able to withstand the normal occlusal force in the maxillofacial structure.

[0155] S423: Based on the simulated test mechanical response value, the real-time operation is verified. By dynamically analyzing the changes in mechanical behavior during the operation, the parameters are adjusted in real time to match the patient's maxillofacial structure. The shape and size of the implant are optimized by comparing the pressure and the response value, and the verified implant design result is generated.

[0156] Based on the mechanical response value of the simulation test, it is compared and analyzed with the stress distribution in the standard maxillofacial structure. If the mechanical response value of the implant is within the standard range, its feasibility is verified. If it does not meet the standard, the material and size of the implant need to be further optimized, including adjusting the material hardness in special areas of the maxillofacial structure, such as the stress concentration area of ​​the occlusal part, and performing simulation verification again until the mechanical response of the implant design is consistent with the standard maxillofacial structure, and the verified implant design result is obtained.

[0157] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An oral and maxillofacial implant design method based on computer vision technology, characterized in that: The following steps are involved: Based on the patient's current maxillofacial image, identify the maxillofacial structure location, identify the key features of the image, obtain a key maxillofacial structure map, input the key maxillofacial structure map into the maxillofacial change prediction, and obtain a maxillofacial structure change prediction map; Based on the predicted map of maxillofacial structure changes, the jaw bone density is analyzed, including bone changes in the implant area, to obtain a maxillofacial change trend analysis result, and the implant design parameters, including the depth and angle of the implant, are adjusted according to the maxillofacial change trend analysis result to match the predicted structural changes, and an adjusted implant design plan is generated; The adjusted implant design scheme is reconstructed in three dimensions using computer simulation technology to simulate the implant area to obtain a three-dimensional implant model, and mechanical analysis is performed on the three-dimensional implant model to evaluate the stability and adaptability of the implant in real-time application and generate implant mechanical analysis results; Based on the results of the implant mechanical analysis, the design scheme is adjusted to adjust the shape and size of the implant to match the patient's maxillofacial structure to obtain an optimized implant configuration. Based on the optimized implant configuration, a real-time operation simulation test is performed to verify the real-time application effect of the design and generate a verified implant design result.

2. The oral and maxillofacial implant design method based on computer vision technology according to claim 1, characterized in that: The steps for obtaining the predicted map of maxillofacial structure changes are specifically as follows: Based on the patient's current maxillofacial image, edge detection is performed, and image edge enhancement is performed by applying the Sobel operator to obtain an enhanced maxillofacial image; Based on the enhanced maxillofacial image, key maxillofacial structures are located, structural key points are identified using a Harris corner detection algorithm, and the key points are marked to generate a marked key maxillofacial structure diagram; The marked key maxillofacial structure diagram is input into the maxillofacial change prediction model, and the time series analysis model is used in combination with linear regression technology to simulate the changes of the maxillofacial structure in the future time period, using the formula: V ta =a a ×V t-1a +b a ×X ta +g a ×ΔX t-1a Calculate the predicted maxillofacial changes and obtain the predicted maxillofacial structure change map, where V ta represents the predicted change of maxillofacial structure at time t, V t-1a Represents the predicted map of maxillofacial structure changes at the previous time point, α a represents the influence weight of maxillofacial changes at the previous time point, β a and γ a Represent the coefficients of key structural changes at the current and previous time points, X ta Represents the key maxillofacial structure diagram at the current time point, ΔX t-1a Represents the change from the previous time point to the current time point.

3. The oral and maxillofacial implant design method based on computer vision technology according to claim 2, characterized in that: The steps for obtaining the maxillofacial change trend analysis results are specifically as follows: Based on the predicted map of maxillofacial structure changes, jaw bone density analysis is performed, and changes in bone quality in the implant area are quantitatively analyzed through resolution scanning and pixel intensity measurement to obtain jaw bone density analysis data in the implant area; Utilizing the jaw bone density analysis data of the implant area, performing quantitative calculation, applying the target bone strength assessment algorithm, calculating the amount of bone change in the implant area, and obtaining a bone change assessment result; Combine the jaw bone density analysis data of the implant area with the bone change assessment results, and perform jaw bone density analysis using the formula: R b =b b ×D b +g b ×C b Generate maxillofacial change trend analysis results, where R b represents the analysis result of maxillofacial change trend, β b The weight coefficient of bone quality change in the implant area, D b is the data obtained from jaw bone density analysis, γ b is the adjustment coefficient, C b Indicates the amount of bone change.

4. The oral and maxillofacial implant design method based on computer vision technology according to claim 3, characterized in that: The steps for obtaining the adjusted planting design plan are specifically as follows: Extract key data from the maxillofacial change trend analysis results, including expected changes in the jaw, perform biomechanical simulation to extract data, determine key parameters for implant design, and generate a list of adjustment requirements; According to the adjustment requirement list, dynamically adjust the implant parameters, simulate the influence of differentiated implant depth and angle on maxillofacial adaptability, dynamically adjust the implant configuration according to the input maxillofacial data, and generate an optimized implant design sketch; Based on the optimized implant design sketch, matching clinical safety standards and patient needs, the design parameters are calculated using the formula: D c =d c ×S c +g c ×φ c Generate an adjusted planting design plan, where D c represents the adjusted planting design, δ c and γ c is the adjustment weight for depth and angle, S c and φ c Depth and angle parameters recommended in simulation results.

5. The oral and maxillofacial implant design method based on computer vision technology according to claim 4, characterized in that: The steps of obtaining the three-dimensional implant model are specifically as follows: Extracting parameters from the adjusted implant design, including the depth and angle of the implant, converting the parameters into a recognizable format, and generating an initial three-dimensional model sketch; The initial 3D model sketch is adjusted, and the geometric and mechanical properties of the model are optimized using numerical optimization techniques, using the formula: M d =a d ·P d +b d ·Q d +g d ·R d Generate detailed 3D implant design, where M d Represents the parameters of the three-dimensional model, α d , β d and γ d Represent the adjustment coefficients of depth, angle and structural complexity, P d , Q d and R d are the parameters obtained from the preliminary model; Based on the refined three-dimensional implant design, the model is tested and verified, mechanical and functional tests are performed to verify the real-time application effect of the model, and adjustments are made according to the test results to generate a three-dimensional implant model.

6. The oral and maxillofacial implant design method based on computer vision technology according to claim 5, characterized in that: The steps for obtaining the implant mechanics analysis results are specifically as follows: Initializing data of the implant model based on the three-dimensional implant model, including model dimensions, material properties, and expected load conditions, inputting model dimensions, defining material properties, recording expected load conditions, and generating implant model parameters for mechanical analysis; Based on the implant model parameters of the mechanical analysis, a mechanical simulation algorithm is applied to the model to perform stress analysis using the formula: Generate stress response and failure prediction results, where ρ h represents the material density, v h is the load speed, A h is the force-bearing area, α h and β h is the experience adjustment coefficient, S h Present stress response and failure prediction results; Based on the stress response and failure prediction results, the overall stability and adaptability of the implant are evaluated, key stress areas and structural stability are analyzed, and implant mechanical analysis results are generated.

7. The oral and maxillofacial implant design method based on computer vision technology according to claim 6, characterized in that: The steps for obtaining the optimized implant configuration are specifically as follows: Based on the mechanical analysis results of the implant, targeted size adjustment is performed according to the maxillofacial structure of the patient, the stress concentration values ​​of multiple regions in the mechanical analysis are called, the parts that need to be optimized are analyzed, and the size adjustment of the three-dimensional geometry is performed in combination with the maxillofacial CT scanning data to generate a preliminary implant design plan; Based on the preliminary implant design, the implant shape and size were adjusted using the formula: Calculate the size of the adjusted area and obtain the three-dimensional shape data of the implant, where F g is the mechanical stress before adjustment, E g is the elastic modulus, L g is the implant length, A g It indicates the size change of the implant area after adjustment; The three-dimensional shape data of the implant is used for iterative optimization. By simulating the chewing and dynamic occlusion process of the patient, the matching degree between the shape and size of the implant and the maxillofacial structure is verified. Fine-tuning is performed according to the simulation results to obtain the optimized implant configuration.

8. The oral and maxillofacial implant design method based on computer vision technology according to claim 7, characterized in that: The steps for obtaining the verified implant design result are specifically as follows: Based on the optimized implant configuration, a set of mechanical parameters matching the real-time simulation test is selected to set initial conditions for real-time operation simulation, and the implant shape, size and mechanical properties are combined to match the patient's maxillofacial structure. Mechanical matching is performed by calling previous data combined with pressure variables in the operation environment to establish a preliminary set of operation conditions; Based on the preliminary set of operating conditions, simulation tests were performed using the formula: Calculate the mechanical response parameters in the simulation operation and generate the mechanical response value of the simulation test, where R v Represents the mechanical response value of the simulated test, F v is the external force applied in real time, A v is the area of ​​force action, ΔT v is the time interval, E v is the elastic modulus of the material; Based on the mechanical response value of the simulation test, the real-time operation is verified. By dynamically analyzing the changes in mechanical behavior during the operation, the parameters are adjusted in real time to match the patient's maxillofacial structure. The shape and size of the implant are corrected and optimized by comparing the pressure and the response value, and a verified implant design result is generated.

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