An implant printing system based on 3D printing technology

Abstract

The present invention discloses an implant printing system based on 3D printing technology, belonging to the technical field of dental implants. The system includes a data acquisition module, a dynamic modeling module, and an execution module. Communication connections are established among the data acquisition module, the dynamic modeling module, and the execution module. The dynamic modeling module includes a reconstruction unit and an adjustment unit. The reconstruction unit is used to reversely reconstruct the original alveolar ridge three-dimensional model according to the three-dimensional scanning unit; the adjustment unit is used to repair the original alveolar ridge three-dimensional model, simulate the stress distribution after implant implantation in the repaired original alveolar ridge three-dimensional model, and automatically adjust the parameters of the implant in combination with the dynamic bite force distribution, generate a complete implant three-dimensional image, and transmit the implant parameters and the complete implant three-dimensional image to the execution module. The present invention dynamically models the alveolar bone density and bite force distribution of the patient to ensure that the mechanical properties of the implant match the physiological requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of dental implants, and particularly to an implant printing system based on 3D printing technology. Background Art

[0002] Today, with the increasing improvement of people's living standards, more and more people pay attention to oral health. Many patients have damaged or missing teeth due to the lack of previous hygiene habits or sudden situations. For teeth with less damage, they can often be treated by repair. For teeth with greater damage or missing teeth, only dental implants can solve the problem.

[0003] After retrieval, it is found that the Chinese patent publication number is: CN114612541B, which discloses an implant printing method based on 3D printing technology, including: grouping and comparing oral feature maps extracted from a target patient's oral picture set and calculating matching costs to generate an oral depth sampling map; performing a fusion operation on the oral depth sampling map to obtain oral 3D point cloud data, and visualizing the oral 3D point cloud data to obtain an oral model; obtaining the number and occupied space of the teeth to be implanted of the target patient based on the oral model, and obtaining a three-dimensional model of the dental implant from a dental implant model library based on this; importing the three-dimensional model into a 3D printing device and performing batch printing on a standard substrate to obtain dental implants.

[0004] Although the above solution has the advantage of improving the production efficiency of dental implants, it does not consider that the bone at the site of the extracted tooth is absorbed over a long period of time, resulting in a reduction in the overall thickness of the alveolar bone. When implanting in the case of sufficient bone mass, if the influence of the regional density difference of the alveolar bone on the bite force distribution is ignored and the dynamic modeling of the patient's alveolar bone density and bite force distribution is lacking, it is easy to cause the mismatch between the mechanical properties of the implant and the physiological requirements.

[0005] Therefore, there is an urgent need to provide an implant printing system based on 3D printing technology to solve the above problems. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the above-mentioned disadvantages of the prior art and provide an implant printing system based on 3D printing technology.

[0007] To solve the above technical problem, a technical solution adopted by the present invention is: to provide an implant printing system based on 3D printing technology, including a data acquisition module, a dynamic modeling module, and an execution module, and communication connections are established between the data acquisition module, the dynamic modeling module, and the execution module;

[0008] Data acquisition module, the data acquisition module includes a three-dimensional scanning unit, a bone density analysis unit, and a bite force measurement unit; the three-dimensional scanning unit is used to obtain a three-dimensional bone mass image of the edentulous area; the bone density analysis unit is used to divide the alveolar bone into a high-density area, a medium-density area, and a low-density area;

[0009] Dynamic modeling module, the dynamic modeling module includes a reconstruction unit and an adjustment unit, the reconstruction unit is used to reversely reconstruct the original alveolar ridge three-dimensional model according to the three-dimensional scanning unit; the adjustment unit is used to repair the original alveolar ridge three-dimensional model, and simulate the stress distribution after implant implantation in the repaired original alveolar ridge three-dimensional model, and combine the dynamic bite force distribution measured by the bite force measurement unit to automatically adjust the parameters of the implant, generate a complete implant three-dimensional image, and transmit the parameters of the implant and the complete implant three-dimensional image to the execution module;

[0010] Execution module, the execution module is used to receive the parameters of the implant and the complete implant three-dimensional image, and perform corresponding printing actions.

[0011] The present invention is further configured as: the three-dimensional scanning unit uses a cone beam CT to obtain the bone morphology data of the edentulous area, and processes the bone morphology data of the edentulous area through a preset processor to obtain a three-dimensional bone mass image.

[0012] The present invention is further configured as: the steps for the bone density analysis unit to divide the alveolar bone into a high-density area, a medium-density area, and a low-density area are as follows:

[0013] S1. Input the obtained three-dimensional bone mass image into a preset image segmentation network to obtain a set of segmentation images;

[0014] S2. Calculate the area ratio of each segmentation image in the set of segmentation images in the three-dimensional bone mass image according to the segmentation result of each segmentation image;

[0015] S3. Obtain the density classification result of the set of segmentation images through the area ratio;

[0016] S4. Determine the gray value distribution map corresponding to each density classification result by performing graying processing on the three-dimensional bone mass image;

[0017] S5. Obtain the corresponding optimized distribution map by performing optimization processing on each gray value distribution map, map the gray level of the three-dimensional bone mass image according to the optimized distribution map to obtain an enhanced image, and assign corresponding weights according to the enhanced image to determine the high-density area, medium-density area, and low-density area of the alveolar bone.

[0018] The present invention is further configured such that: a piezoelectric sensor is preset in the bite force measurement unit of the data acquisition module, and the dynamic bite force distribution data during the patient's chewing process is recorded by the piezoelectric sensor;

[0019] The number of piezoelectric sensors in the bite force measurement unit is multiple, and the multiple piezoelectric sensors are distributed in an array.

[0020] The present invention is further configured such that: the method for the reconstruction unit to reversely reconstruct the original alveolar ridge three-dimensional model is as follows:

[0021] Q1. Preset a model construction network, input the patient's tooth loss time into the model construction network, and calculate the vertical absorption amount and the horizontal absorption amount according to the preset bone resorption time function;

[0022] Q2. According to the vertical absorption amount and the horizontal absorption amount, and based on the three-dimensional bone mass image, reversely deduce the original alveolar ridge contour;

[0023] Q3. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, calculate the bone mass loss caused by absorption, and determine whether the bone mass loss caused by absorption exceeds a set threshold.

[0024] The present invention is further configured such that: the steps for calculating the bone mass loss caused by absorption in step Q3 are as follows:

[0025] Q31. Align the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image in three-dimensional space through a preset algorithm;

[0026] Q32. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, and mark the concave or volume reduction area caused by absorption;

[0027] Q33. Then calculate the volume of the marked concave or volume reduction area through the algorithm to obtain the total bone resorption amount.

[0028] The present invention is further configured such that: the specific steps for the adjustment unit to generate a complete implant three-dimensional image are as follows:

[0029] M1. Repair the original alveolar ridge three-dimensional model according to the original alveolar ridge three-dimensional model and in combination with the total amount of bone resorption, generate a virtual alveolar ridge three-dimensional model, and compare the virtual alveolar ridge three-dimensional model with the alveolar ridge three-dimensional model in the three-dimensional bone mass image to obtain the difference value between the two. If the difference value is less than the set value, jump to step M2; if the difference value is greater than the set value, inversely deduce the total amount of bone resorption through the difference value, and repair the original alveolar ridge three-dimensional model again through the total amount of bone resorption. If the difference value is equal to the set value, determine that the matching degree between the virtual alveolar ridge three-dimensional model and the alveolar ridge three-dimensional model in the three-dimensional bone mass image meets the standard, and then directly jump to step M2;

[0030] M2. Match the initial geometric parameters from a preset implant library, select the corresponding implant according to the matched initial geometric parameters, input the structural characteristics of the selected implant into the reconstructed original alveolar ridge three-dimensional model, simulate the implant implantation, and obtain the stress distribution data after the implant is implanted;

[0031] M3. Adjust the parameters of the implant according to the stress distribution data after the implant is implanted and in combination with the dynamic biting force distribution data to generate a complete three-dimensional image of the implant.

[0032] The present invention is further configured as follows: The specific steps of combining the dynamic biting force distribution data in step M3 are as follows:

[0033] M31. Record the dynamic biting force distribution data during the patient's chewing process through the piezoelectric sensor, decompose it into three-dimensional force vectors at discrete time points according to the chewing cycle, and on the basis of the static stress field after the implant is implanted, superimpose the dynamic biting force frame by frame on the three-dimensional force vectors according to the time step to generate a dynamic stress nephogram;

[0034] M32. Identify the periodic high-stress areas in the dynamic stress nephogram and record the stress fluctuation range;

[0035] M33. Mark the areas in the stress fluctuation range that exceed the set safety threshold according to the high-density area, medium-density area, and low-density area of the alveolar bone and in combination with the material fatigue limit of the implant, and modify the implant parameters corresponding to the areas that exceed the set safety threshold.

[0036] The present invention is further configured as follows: The parameters of the implant in step M3 include the thread form of the implant, the diameter and length of the implant, and the form of the neck transition area of the implant.

[0037] The present invention is further configured such that: the execution module includes a receiving unit, a multi-printhead coordination unit, and a real-time monitoring unit. The receiving unit is used to receive the implant parameters and the complete three-dimensional image of the implant, convert them into corresponding three-dimensional coordinates according to the implant parameters and the complete three-dimensional image of the implant, and transmit the three-dimensional coordinates to the multi-printhead coordination unit; the multi-printhead coordination unit integrates a selective laser melting device and an electron beam melting device, and performs multi-material layer-by-layer printing according to the three-dimensional coordinates; the real-time monitoring unit monitors the temperature of the molten pool through an infrared thermal imager, and dynamically adjusts the printing parameters to control the defect rate.

[0038] The beneficial effects of the present invention are as follows:

[0039] 1. Through cone-beam CT scanning combined with deep learning image segmentation, the present invention accurately divides the high, medium, and low-density regions of the alveolar bone, reversely reconstructs the original alveolar ridge three-dimensional model, and quantifies the total bone resorption. Combining the dynamic bite force distribution data, the system simulates the stress field after implant placement, dynamically adjusts the thread parameters according to the bone density difference, ensures the elastic modulus gradient matching between the implant and the bone tissue, dynamically models the patient's alveolar bone density and bite force distribution, and ensures the matching of the mechanical properties of the implant and the physiological requirements;

[0040] 2. The present invention records the three-dimensional dynamic bite force data during the patient's chewing process through a piezoelectric sensor array, decomposes it into a time-space load spectrum, and superimposes it on the static stress field to generate a dynamic stress nephogram. The system identifies the periodic high-stress areas and automatically adjusts the parameters in combination with the material fatigue limit. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is the system flow chart of the present invention;

[0042] Figure 2 is the flow chart of the bone density analysis unit of the present invention;

[0043] Figure 3 is the flow chart of the reconstruction unit reversely reconstructing the original alveolar ridge three-dimensional model of the present invention;

[0044] Figure 4 is the flow chart of the bone mass loss caused by absorption of the present invention;

[0045] Figure 5 is the flow chart of the adjustment unit generating the complete three-dimensional image of the implant of the present invention;

[0046] Figure 6 is the flow chart of adjusting the parameters of the implant of the present invention;

[0047] In the figure: 1. Data acquisition module; 2. Dynamic modeling module; 3. Execution module. DETAILED DESCRIPTION OF THE INVENTION

[0048] The following will elaborate on the preferred embodiments of the present invention in conjunction with the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0049] Please refer to Figures 1-6 , an implant printing system based on 3D printing technology, including a data acquisition module 1, a dynamic modeling module 2, and an execution module 3. Communication connections are established between the data acquisition module 1, the dynamic modeling module 2, and the execution module 3;

[0050] The data acquisition module 1, which includes a three-dimensional scanning unit, a bone density analysis unit, and a bite force measurement unit; the three-dimensional scanning unit is used to obtain the three-dimensional bone mass image of the tooth-deficient area; the bone density analysis unit is used to divide the alveolar bone into a high-density area, a medium-density area, and a low-density area;

[0051] The dynamic modeling module 2, which includes a reconstruction unit and an adjustment unit. The reconstruction unit is used to reversely reconstruct the original alveolar ridge three-dimensional model according to the three-dimensional scanning unit; the adjustment unit is used to repair the original alveolar ridge three-dimensional model, simulate the stress distribution after implant implantation in the repaired original alveolar ridge three-dimensional model, and automatically adjust the parameters of the implant in combination with the dynamic bite force distribution measured by the bite force measurement unit, generate a complete implant three-dimensional image, and transmit the parameters of the implant and the complete implant three-dimensional image to the execution module 3;

[0052] The execution module 3, which is used to receive the parameters of the implant and the complete implant three-dimensional image and perform corresponding printing actions.

[0053] Among them, the three-dimensional scanning unit uses cone beam CT to obtain the bone morphology data of the tooth-deficient area, and processes the bone morphology data of the tooth-deficient area through a preset processor to obtain a three-dimensional bone mass image.

[0054] The cone beam CT emits a cone-shaped X-ray beam and rotates around the patient's jaw to obtain multi-angle two-dimensional projection images, and then reconstructs three-dimensional volume data through a filtered back-projection algorithm. During scanning, the field of view needs to be adjusted according to the range of the tooth-deficient area. The anterior tooth area selects 4×4 cm², and the posterior tooth area is extended to 8×8 cm² to cover the maxillary sinus and mental foramen. After the three-dimensional volume data is denoised and artifact-corrected by a preset processor, a three-dimensional bone mass image is generated and converted into a mesh model in 3D printing format through a voxel-level reconstruction method.

[0055] Among them, the steps for the bone density analysis unit to divide the alveolar bone into a high-density area, a medium-density area, and a low-density area are as follows:

[0056] S1. Input the obtained three-dimensional bone mass image into a preset image segmentation network to obtain a set of segmented images;

[0057] Preferably, the image segmentation network adopts an improved 3D U-Net structure, specifically including an encoder and a decoder;

[0058] S2. Calculate the area proportion of each segmented image in the three-dimensional bone mass image according to the segmentation result of each segmented image in the set of segmented images;

[0059] S3. Obtain the density classification result of the set of segmented images through the area proportion;

[0060] Based on the segmentation result of each segmented image, divide it into multiple categories, count the number of voxels in each category (a voxel is a small cube unit with a fixed size and position in each category in three-dimensional space), and calculate its proportion in the total voxels of the alveolar bone. The formula is:

[0061]

[0062] The density classification result of the set of segmented images is determined according to the area proportion of the high, medium, and low density regions. High density region: area proportion ≥ 40%; Medium density region: 20% ≤ area proportion < 40%; Low density region: area proportion < 20%;

[0063] S4. Determine the grayscale value distribution map corresponding to each density classification result by performing grayscale processing on the three-dimensional bone mass image;

[0064] The specific method is as follows: (1) Data input and preprocessing: Read the three-dimensional bone mass image in DICOM format and extract the original Hounsfield Unit (HU) value of each voxel;

[0065] (2) HU value normalization mapping: Linearly compress the original HU value to the 0 - 255 grayscale range, set a clinically relevant threshold (such as bone tissue HU > 200), and filter non-target regions (air, soft tissue);

[0066] (3) Adaptive contrast enhancement: Adopt Contrast Limited Adaptive Histogram Equalization (CLAHE) to independently enhance the trabecular texture of each three-dimensional sub-block (such as 32×32×32 voxels) and suppress noise;

[0067] (4) Channel-wise grayscale mapping: According to the density classification result (high / medium / low), perform gamma correction on the grayscale distribution of each density region respectively (gamma value < 1 for the high density region to brighten details, gamma value > 1 for the low density region to reduce noise);

[0068] (5)Generate a grayscale distribution map: Output the optimized three-dimensional grayscale image of each density region, and superimpose and display it as a pseudo-color distribution map (such as high density in red, medium density in yellow, and low density in blue) for visual verification.

[0069] S5. By optimizing each grayscale value distribution map, obtain the corresponding optimized distribution map, map the grayscale of the three-dimensional bone mass image according to the optimized distribution map to obtain an enhanced image, and assign corresponding weights to the enhanced image to determine the high-density region, medium-density region, and low-density region of the alveolar bone.

[0070] Among them, the calculation formulas for determining the high-density region, medium-density region, and low-density region of the alveolar bone by assigning corresponding weights to the enhanced image are as follows:

[0071] First, assign weights to different density regions according to clinical needs to generate a comprehensive enhanced image:

[0072]

[0073] Typical weight assignment: = 0.6; = 0.3; = 0.1; Highlight the influence of the high-density region on the stability of the implant; is the comprehensive enhanced image; is the high-density region of the alveolar bone; is the medium-density region of the alveolar bone; is the low-density region of the alveolar bone;

[0074] Finally, through threshold segmentation or region growing method, extract the three-dimensional boundaries of the high, medium, and low density regions from the enhanced image to obtain the high-density region, medium-density region, and low-density region of the alveolar bone.

[0075] Among them, a piezoelectric sensor is preset in the bite force measurement unit in the data acquisition module 1, and the dynamic bite force distribution data during the patient's chewing process is recorded through the piezoelectric sensor;

[0076] Among them, the dynamic bite force distribution data includes the real-time change curve of the bite force, the start and end times of a single bite action, the total chewing cycle duration, the maximum vertical force during a single chewing, the periodic frequency of the bite action (such as 1 - 3 Hz) and harmonic components, etc.;

[0077] The number of piezoelectric sensors in the bite force measurement unit is multiple, and the multiple piezoelectric sensors are distributed in an array;

[0078] The piezoelectric sensor array consists of 16 micro-sensors (2 mm in diameter) embedded in a customized occlusal pad that covers the occlusal surface of the dentition. The sampling frequency of the sensors is 1 kHz, and the time-space distribution of the biting force (vertical, buccolingual, mesiodistal) is dynamically recorded. After the data is denoised by Kalman filtering, it is mapped to the stress area of the alveolar bone through an inverse dynamics model.

[0079] For example, the peak vertical biting force in the first molar area can reach 700 N, and the lateral force on the anterior teeth is about 50 N. The spatial registration of the sensor data and the three-dimensional bone mass image is achieved through fiducial points (such as dental anatomical feature points), with an error <0.1 mm.

[0080] Among them, the method for the reconstruction unit to reverse reconstruct the original three-dimensional model of the alveolar ridge is as follows:

[0081] Q1. Preset a model construction network. Input the tooth extraction time of the patient into the model construction network, and calculate the vertical absorption amount and horizontal absorption amount according to the preset bone resorption time function.

[0082] Among them, the model construction network is a double-branch deep learning structure: 1) The time branch processes the tooth extraction time series and outputs the bone resorption rate coefficient; 2) The image branch extracts the current bone mass image features; 3) The fusion layer correlates the time and space features through an attention mechanism to generate the predicted values of the vertical / horizontal absorption amount; the preset bone resorption time function is improved based on the Ribeiro model, the vertical absorption amount , the horizontal absorption amount t, is the bone density correlation coefficient, t is the tooth extraction time (month), and the predicted values of the vertical / horizontal absorption amount are compared with the vertical absorption amount and horizontal absorption amount calculated by the bone resorption time function to ensure the accuracy of the data.

[0083] Q2. According to the vertical absorption amount and horizontal absorption amount, and based on the three-dimensional bone mass image, reverse deduce the original alveolar ridge contour.

[0084] The deduction steps are as follows: Locate the current alveolar ridge absorption area, stack the absorption amount in the vertical direction to restore the original height; extrapolate the bone plate in the horizontal direction to the width before absorption, and correct the shape in combination with the anatomical database; fuse the extended geometric structure to generate a continuous contour, and eliminate the step artifact through curvature smoothing.

[0085] Q3. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, calculate the bone mass loss caused by absorption, and judge whether the bone mass loss caused by absorption exceeds the set threshold. If the bone mass loss caused by absorption exceeds the set threshold, the result will be transmitted to the doctor's terminal for subsequent implant bone powder, etc.; if not, reconstruct the original three-dimensional model of the alveolar ridge according to the bone mass loss data.

[0086] Among them, the steps for calculating the bone mass loss caused by absorption in step Q3 are as follows:

[0087] Q31. Align the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image in the three-dimensional space through a preset algorithm;

[0088] Q32. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, and mark the concave or volume reduction areas caused by absorption;

[0089] Q33. Then calculate the volume of the marked concave or volume reduction areas through an algorithm to obtain the total bone absorption amount.

[0090] Example:

[0091] Patient information: A 50-year-old female, with the first mandibular right molar missing for 3 years, and planned for implant restoration.

[0092] Data collection: CBCT scan (slice thickness 0.2 mm, resolution 0.076 mm³) to obtain the three-dimensional bone mass image of the toothless area.

[0093] Step Q31: Three-dimensional space alignment

[0094] Algorithm selection: Iterative Closest Point algorithm (ICP) to align the original alveolar ridge model reconstructed in reverse with the alveolar ridge ( Figure 1 blue contour) in the current bone mass image.

[0095] Alignment accuracy: Root Mean Square Error < 0.1 mm to ensure the matching of anatomical landmark points (such as mental foramen, alveolar ridge crest).

[0096] Step Q32: Marking of absorption areas

[0097] Surface distance analysis: Calculate the surface distance between the two models, and mark the areas with a distance > 2 mm as absorption areas.

[0098] Morphological processing: Perform closing operation (3×3 kernel) on the difference area to smooth the boundary and exclude noise interference.

[0099] Result: The absorption areas are concentrated in the center and buccal bone plate of the toothless area, with a vertical absorption depth of 3.2 mm and a horizontal absorption width of 4.5 mm.

[0100] Step Q33: Calculation of total bone absorption amount

[0101] Volume integration method: Calculate the volume of the absorption area through voxel counting. The volume of the original alveolar ridge is 1200 mm³, the volume of the current bone mass is 900 mm³, and the total bone absorption amount ΔV = 300 mm³.

[0102] Regional statistics: vertical absorption accounts for 60% (180 mm³) and horizontal absorption accounts for 40% (120 mm³).

[0103] The specific steps of the adjustment unit generating a complete implant three-dimensional image are as follows:

[0104] M1. According to the original alveolar ridge three-dimensional model and in combination with the total amount of bone absorption, the original alveolar ridge three-dimensional model is repaired to generate a virtual alveolar ridge three-dimensional model, and the virtual alveolar ridge three-dimensional model is compared with the alveolar ridge three-dimensional model in the three-dimensional bone mass image to obtain a difference value between the two. If the difference value is less than a set value, jump to step M2. If the difference value is greater than the set value, the total amount of bone absorption is inferred by the difference value, and the original alveolar ridge three-dimensional model is repaired again by the total amount of bone absorption. If the difference value is equal to the set value, it is determined that the virtual alveolar ridge three-dimensional model and the alveolar ridge three-dimensional model in the three-dimensional bone mass image have a matching degree that meets the standard, and then directly jump to step M2;

[0105] When the difference between the virtual alveolar ridge three-dimensional model and the actual three-dimensional bone mass image exceeds the threshold, the system adjusts the bone absorption parameters through a reverse optimization process. First, the type of difference value (volume difference or morphological deviation) is analyzed to locate the area of ​​excessive absorption. Based on the bone density zoning data (different absorption rates in high, medium and low density areas), the difference value is decomposed in the vertical and horizontal directions, and the bone absorption correction value of each area is reversed. For example, if the vertical difference is significant, the vertical absorption parameters are adjusted first, and the horizontal absorption is corrected to match the anatomical morphology. Subsequently, the optimized absorption amount is substituted into the bone absorption time function, and a new virtual model is generated by extrapolation along the original alveolar ridge contour, and the step artifacts are eliminated by the mesh smoothing algorithm. Finally, the difference value is re-compared. If it meets the standard, it will enter the next process. If it does not meet the standard, it will be iteratively optimized until convergence. This closed-loop feedback mechanism ensures that the model is highly consistent with the actual bone morphology by dynamically adjusting the absorption parameters;

[0106] M2. Matching initial geometric parameters from a preset implant library, selecting corresponding implants according to the matched initial geometric parameters, inputting the structural features of the selected implants into the reconstructed original alveolar ridge three-dimensional model, simulating implant implantation, and obtaining stress distribution data after implant implantation, wherein the stress distribution data includes the direction and amplitude of the principal stress, the dynamic stress fluctuation range, the stress concentration area, the bone-implant interface contact stress, etc.;

[0107] The initial geometric parameters include: implant diameter and length: preset standard sizes according to the bone mass in the tooth-deficient area (such as diameter 3.5 - 5.0 mm, length 8 - 14 mm); morphology of the neck transition area: taper (such as 1° - 3°), reduction ratio of the neck diameter (such as 10% - 20%); thread parameters: pitch (0.6 - 1.2 mm), thread depth (0.2 - 0.5 mm), thread angle (30° - 60°); material parameters: elastic modulus (such as 110 GPa for titanium alloy, 200 GPa for zirconia);

[0108] Steps for implant placement simulation

[0109] Three-dimensional model registration: Align the implant geometric model with the reconstructed original alveolar ridge model to locate the implant position (based on the occlusal axis and bone density distribution);

[0110] Finite element mesh generation: Generate a high-precision tetrahedral mesh for the implant-bone interface (element size ≤ 0.1 mm);

[0111] Loading of boundary conditions:

[0112] Fix the degrees of freedom at the bottom of the alveolar bone (simulating the fixation of the mandible);

[0113] Apply a vertical static load (such as 300 N) and a dynamic biting force (three-dimensional force vector decomposed according to step M31);

[0114] Calculation of stress field: Solve the stress distribution through finite element analysis to identify stress concentration areas (such as the neck or apical area);

[0115] Example (repair of missing mandibular molar), patient data: 45-year-old male, missing the right lower first molar for 2 years, CBCT shows vertical bone resorption of 3.5 mm and horizontal resorption of 4.0 mm.

[0116] Execution of steps:

[0117] Inverse reconstruction of the original alveolar ridge:

[0118] The network for model construction inputs the tooth-deficient time of 24 months, calculates ΔV = 3.2 mm, ΔH = 4.1 mm;

[0119] Generate the contour of the original alveolar ridge, with a total bone resorption volume of 320 mm³;

[0120] Virtual model repair and verification:

[0121] Detection of difference values (volume difference of 5%), reaching the standard after optimizing ΔV = 3.0 mm and ΔH = 3.8 mm;

[0122] Implant matching and placement simulation:

[0123] Initial parameters: diameter 4.5 mm, length 10 mm, pitch 0.8 mm;

[0124] Finite element analysis shows that the peak neck stress is 180 MPa (exceeding the supertitanium alloy safety threshold of 150 MPa);

[0125] Dynamic parameter adjustment:

[0126] Increase the thread depth from 0.3 mm to 0.4 mm and adjust the neck taper to 2°;

[0127] After optimization, the peak stress drops to 135 MPa, and the final implant model is generated;

[0128] M3. Based on the stress distribution data after implanting the implant and combined with the dynamic bite force distribution data, adjust the parameters of the implant to generate a complete three-dimensional image of the implant.

[0129] Among them, the specific steps of combining the dynamic bite force distribution data in step M3 are as follows:

[0130] M31. Record the dynamic bite force distribution data during the patient's chewing process through a piezoelectric sensor, decompose it into three-dimensional force vectors at discrete time points according to the chewing cycle, and on the basis of the static stress field after implanting the implant, superimpose the dynamic bite force frame by frame on the three-dimensional force vector according to the time step to generate a dynamic stress nephogram;

[0131] M32. Identify the periodic high-stress areas in the dynamic stress nephogram and record the stress fluctuation range;

[0132] M33. According to the high-density area, medium-density area, and low-density area of the alveolar bone, and combined with the material fatigue limit of the implant, mark the areas in the stress fluctuation range that exceed the set safety threshold, and modify the implant parameters corresponding to the areas that exceed the set safety threshold.

[0133] Among them, the parameters of the implant in step M3 include the thread shape of the implant, the diameter and length of the implant, and the shape of the neck transition area of the implant.

[0134] Among them, the execution module 3 includes a receiving unit, a multi-printhead coordination unit, and a real-time monitoring unit. The receiving unit is used to receive the implant parameters and the complete three-dimensional image of the implant, convert them into corresponding three-dimensional coordinates according to the implant parameters and the complete three-dimensional image of the implant, and transmit the three-dimensional coordinates to the multi-printhead coordination unit; the multi-printhead coordination unit integrates a selective laser melting and electron beam melting device and performs multi-material layer-by-layer printing according to the three-dimensional coordinates; the real-time monitoring unit monitors the melt pool temperature through an infrared thermal imager and dynamically adjusts the printing parameters to control the defect rate.

[0135] The receiving unit converts the thread parameters (pitch, depth) and geometric structure into a G-code path by parsing the STL file of the three-dimensional image of the implant, and generates a three-dimensional printing coordinate matrix (accuracy ±0.05 mm) based on the voxelization algorithm; the multi-printhead cooperation unit adopts a dual-process integration strategy: selective laser melting prints the titanium alloy body with a layer thickness of 20-50 μm, and electron beam melting synchronously processes the high-density zirconia coating (for biocompatibility optimization), and avoids nozzle collisions through dynamic path planning; the real-time monitoring unit deploys an infrared thermal imager (sampling rate 60 Hz) to capture the molten pool temperature field. When local overheating (>1500 °C) or cold lap (<800 °C) is detected, the laser power (±50 W) and scanning speed (±20 mm / s) are immediately adjusted. Combining with the online defect detection algorithm (such as reprinting is triggered when the porosity > 2%), the overall defect rate is controlled below 0.3%.

[0136] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present invention.

Claims

1. A dental implant printing system based on 3D printing technology, characterized in that: It comprises a data acquisition module (1), a dynamic modeling module (2) and an execution module (3), wherein the data acquisition module (1), the dynamic modeling module (2) and the execution module (3) are all connected in communication; A data acquisition module (1), the data acquisition module (1) comprising a three-dimensional scanning unit, a bone density analysis unit and a bite force measurement unit; the three-dimensional scanning unit is used to obtain a three-dimensional bone mass image of the edentulous area; the bone density analysis unit is used to divide the alveolar bone into a high-density area, a medium-density area and a low-density area; A dynamic modeling module (2), the dynamic modeling module (2) comprising a reconstruction unit and an adjustment unit, the reconstruction unit being used to reversely reconstruct the original alveolar ridge three-dimensional model according to the three-dimensional scanning unit; the adjustment unit being used to repair the original alveolar ridge three-dimensional model, and simulate the stress distribution after implantation of the implant in the repaired original alveolar ridge three-dimensional model, and automatically adjust the parameters of the implant in combination with the dynamic occlusal force distribution measured by the occlusal force measurement unit, to generate a complete implant three-dimensional image, and transmit the parameters of the implant and the complete implant three-dimensional image to the execution module (3); An execution module (3), the execution module (3) is used to receive the parameters of the implant and the three-dimensional image of the complete implant, and execute a corresponding printing action.

2. A dental implant printing system based on 3D printing technology according to claim 1, characterized in that: The three-dimensional scanning unit uses cone beam CT to acquire bone morphology data of the edentulous area, and processes the bone morphology data of the edentulous area through a preset processor to obtain a three-dimensional bone mass image.

3. A dental implant printing system based on 3D printing technology according to claim 2, characterized in that: The bone density analysis unit divides the alveolar bone into a high-density area, a medium-density area, and a low-density area in the following steps: S1, inputting the acquired three-dimensional bone mass image into a preset image segmentation network to obtain a segmented image set; S2. Calculating the area proportion of each segmented image in the three-dimensional bone mass image according to the segmentation result of each segmented image in the segmented image set; S3, obtaining a density classification result of the segmented image set according to the area proportion; S4, determining a grayscale value distribution map corresponding to each density classification result by graying the three-dimensional bone mass image; S5. Optimizing each of the grayscale value distribution maps to obtain a corresponding optimized distribution map, and mapping the grayscale of the three-dimensional bone mass image according to the optimized distribution map to obtain an enhanced image, and assigning corresponding weights according to the enhanced image to determine the high-density area, medium-density area and low-density area of ​​the alveolar bone.

4. The dental implant printing system based on 3D printing technology according to claim 3, characterized in that: The bite force measurement unit in the data acquisition module (1) is preset with a piezoelectric sensor, and the dynamic bite force distribution data of the patient during chewing is recorded by the piezoelectric sensor; There are multiple piezoelectric sensors in the bite force measurement unit, and the multiple piezoelectric sensors are distributed in an array.

5. A dental implant printing system based on 3D printing technology according to claim 4, characterized in that: The method for the reconstruction unit to reversely reconstruct the original alveolar ridge three-dimensional model is as follows: Q1. Preset model construction network, input the patient's tooth loss time into the model construction network, and calculate the vertical absorption amount and the horizontal absorption amount according to the preset bone absorption time function; Q2, according to the vertical absorption amount and the horizontal absorption amount, and based on the three-dimensional bone mass image, reversely deduce the original alveolar ridge contour; Q3. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, calculate the bone mass loss caused by absorption, and determine whether the bone mass loss caused by absorption exceeds a set threshold.

6. A dental implant printing system based on 3D printing technology according to claim 5, characterized in that: The steps for calculating the bone loss caused by absorption in step Q3 are as follows: Q31. Aligning the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image in three-dimensional space by using a preset algorithm; Q32. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, and mark the depression or volume reduction area caused by absorption; Q33. The volume of the marked depressed or volume-reduced area is then calculated using the algorithm to obtain the total amount of bone absorption.

7. A dental implant printing system based on 3D printing technology according to claim 6, characterized in that: The specific steps of the adjustment unit generating a complete implant three-dimensional image are as follows: M1. According to the original alveolar ridge three-dimensional model and in combination with the total amount of bone absorption, the original alveolar ridge three-dimensional model is repaired to generate a virtual alveolar ridge three-dimensional model, and the virtual alveolar ridge three-dimensional model is compared with the alveolar ridge three-dimensional model in the three-dimensional bone mass image to obtain a difference value between the two. If the difference value is less than a set value, the process jumps to step M2. If the difference value is greater than a set value, the total amount of bone absorption is inferred by the difference value, and the original alveolar ridge three-dimensional model is repaired again by the total amount of bone absorption. If the difference value is equal to the set value, it is determined that the virtual alveolar ridge three-dimensional model and the alveolar ridge three-dimensional model in the three-dimensional bone mass image meet the matching standard, and the process jumps directly to step M2. M2. Matching initial geometric parameters from a preset implant library, selecting a corresponding implant according to the matched initial geometric parameters, inputting the structural features of the selected implant into the reconstructed original alveolar ridge three-dimensional model, simulating implant implantation, and obtaining stress distribution data after implant implantation; M3. According to the stress distribution data of the implant after implantation and in combination with the dynamic occlusal force distribution data, the parameters of the implant are adjusted to generate a complete three-dimensional image of the implant.

8. The dental implant printing system based on 3D printing technology according to claim 7, characterized in that: The specific steps of combining the dynamic bite force distribution data in step M3 are as follows: M31. Record the dynamic bite force distribution data of the patient during chewing by the piezoelectric sensor, decompose it into three-dimensional force vectors at discrete time points according to the chewing cycle, and superimpose the dynamic bite force on the three-dimensional force vector frame by frame according to the time step on the basis of the static stress field after implantation, so as to generate a dynamic stress cloud map; M32. Identify the periodic high stress area in the dynamic stress cloud map and record the stress fluctuation range; M33. Based on the high-density area, medium-density area and low-density area of ​​the alveolar bone and in combination with the material fatigue limit of the implant, mark the areas in the stress fluctuation range that exceed the set safety threshold, and modify the implant parameters corresponding to the areas that exceed the set safety threshold.

9. A dental implant printing system based on 3D printing technology according to claim 8, characterized in that: The parameters of the implant in step M3 include the thread shape of the implant, the diameter and length of the implant, and the neck transition zone shape of the implant.

10. A dental implant printing system based on 3D printing technology according to claim 9, characterized in that: The execution module (3) comprises a receiving unit, a multi-print head coordination unit and a real-time monitoring unit, wherein the receiving unit is used to receive the implant parameters and the complete implant three-dimensional image, convert the implant parameters and the complete implant three-dimensional image into corresponding three-dimensional coordinates according to the implant parameters and the complete implant three-dimensional image, and transmit the three-dimensional coordinates to the multi-print head coordination unit; The multi-print head coordination unit integrates selective laser melting and electron beam melting devices, and performs multi-material layer-by-layer printing according to the three-dimensional coordinates; the real-time monitoring unit monitors the temperature of the molten pool through an infrared thermal imager, and dynamically adjusts the printing parameters to control the defect rate.

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