Implant tooth printing system based on 3D printing technology

Abstract

The invention discloses an implant tooth printing system based on a 3D printing technology, and belongs to the technical field of implant teeth, the system comprises a data acquisition module, a dynamic modeling module and an execution module, communication connection is established among the data acquisition module, the dynamic modeling module and the execution module, the dynamic modeling module comprises a reconstruction unit and an adjustment unit, the reconstruction unit is used for reversely reconstructing an original alveolar ridge three-dimensional model according to the three-dimensional scanning unit; the adjusting unit is used for repairing the original alveolar ridge three-dimensional model, simulating the stress distribution of the implanted implant in the repaired original alveolar ridge three-dimensional model, and automatically adjusting the parameters of the implant in combination with the dynamic occlusal force distribution to generate a complete implant three-dimensional image; and the implant parameters and the complete implant three-dimensional image are transmitted to the execution module. Dynamic modeling is carried out on alveolar bone density and occlusal force distribution of a patient, and it is ensured that the mechanical performance of the implant is matched with physiological needs.

Description

Technical Field

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

[0002] As people's living standards continue to improve, more and more people are paying attention to oral health. Many patients have damaged or missing teeth due to lack of hygiene habits or unexpected situations. For teeth with less damage, they can often be repaired, but for teeth with severe damage or missing, the problem can only be solved through artificial dental implants.

[0003] After searching, it was found that the Chinese patent publication number is: CN114612541B, which discloses a dental implant printing method based on 3D printing technology, including: grouping and comparing oral feature maps extracted from a target patient's oral image 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 oral modeling; based on the oral modeling, obtaining the number and occupied space of the target patient's teeth to be implanted, and thereby obtaining a three-dimensional modeling of the dental implant from a dental implant model library; importing the three-dimensional modeling into a 3D printing device, and performing batch printing on a standard substrate to obtain dental implants.

[0004] Although the above scheme has the advantage of improving the production efficiency of dental implants, it does not take into account that the bone at the site where the teeth have been extracted is absorbed over a long period of time, resulting in a reduction in the overall thickness of the alveolar bone. When implantation is performed when there is sufficient bone volume, if the effect of regional density differences in the alveolar bone on the bite force distribution is ignored, and there is a lack of dynamic modeling of the patient's alveolar bone density and bite force distribution, it is easy to lead to a mismatch between the mechanical properties of the implant and physiological needs.

[0005] Therefore, there is an urgent need to provide a dental 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 shortcomings of the above-mentioned prior art and provide a dental implant printing system based on 3D printing technology.

[0007] In order to solve the above technical problems, a technical solution adopted by the present invention is: providing a dental implant printing system based on 3D printing technology, including a data acquisition module, a dynamic modeling module and an execution module, wherein communication connections are established among the data acquisition module, the dynamic modeling module and the execution module; A data acquisition module, the data acquisition module 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, 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 of the implant after 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 implant parameters and the complete implant three-dimensional image to the execution module; An execution module is used to receive the parameters of the implant and the three-dimensional image of the complete implant, and execute a corresponding printing action.

[0008] The present invention is further configured as follows: the three-dimensional scanning unit uses cone beam CT to obtain 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.

[0009] The present invention is further configured as follows: 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.

[0010] The present invention is further configured as follows: a piezoelectric sensor is preset in the bite force measurement unit in the data acquisition module, 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.

[0011] The present invention is further configured as follows: 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.

[0012] The present invention is further configured as follows: the step of calculating the bone loss caused by absorption in step Q3 is 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.

[0013] The present invention is further configured as follows: the specific steps of the adjustment unit generating a complete three-dimensional image of the implant 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.

[0014] The present invention is further configured as follows: 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.

[0015] The present invention is further configured as follows: 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 zone of the implant.

[0016] The present invention is further configured as follows: the execution module includes a receiving unit, a multi-print head coordination unit and a real-time monitoring unit, the receiving unit is used to receive the implant parameters and the complete implant three-dimensional image, convert them 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 molten pool temperature through an infrared thermal imager, and dynamically adjusts the printing parameters to control the defect rate.

[0017] The beneficial effects of the present invention are as follows: 1. The present invention uses cone beam CT scanning combined with deep learning image segmentation to accurately divide the high, medium and low density areas of the alveolar bone, and reversely reconstructs the original alveolar ridge three-dimensional model to quantify the total amount of bone resorption. Combined with dynamic bite force distribution data, the system simulates the stress field after implantation, dynamically adjusts the thread parameters according to the difference in bone density, ensures that the elastic modulus gradient of the implant matches the bone tissue, and dynamically models the patient's alveolar bone density and bite force distribution to ensure that the mechanical properties of the implant match physiological needs; 2. The present invention records the three-dimensional dynamic bite force data of the patient during chewing through a piezoelectric sensor array, decomposes it into a time-space load spectrum, and superimposes it with the static stress field to generate a dynamic stress cloud map. The system identifies periodic high stress areas and automatically adjusts parameters based on the material fatigue limit. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a system flow chart of the present invention; Figure 2 is a flow chart of a bone density analysis unit of the present invention; Figure 3 A flowchart of the reconstruction unit of the present invention for reversely reconstructing the original alveolar ridge three-dimensional model; Figure 4 A flow chart of bone loss caused by absorption of the present invention; Figure 5 A flow chart for generating a three-dimensional image of a complete implant for the adjustment unit of the present invention; Figure 6 A flow chart for adjusting parameters of the implant of the present invention; In the figure: 1. Data acquisition module; 2. Dynamic modeling module; 3. Execution module. DETAILED DESCRIPTION

[0019] The preferred embodiments of the present invention are described in detail below 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.

[0020] See also Figure 1-Figure 6 , a dental implant printing system based on 3D printing technology, including a data acquisition module 1, a dynamic modeling module 2 and an execution module 3, wherein communication connections are established among the data acquisition module 1, the dynamic modeling module 2 and the execution module 3; Data acquisition module 1, data acquisition module 1 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 volume 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; Dynamic modeling module 2, dynamic modeling module 2 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 of the implant after implantation 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, generate a complete implant three-dimensional image, and transmit the implant parameters and the complete implant three-dimensional image to the execution module 3; Execution module 3, execution module 3 is used to receive the parameters of the implant and the complete three-dimensional image of the implant, and execute corresponding printing actions.

[0021] The three-dimensional scanning unit uses 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.

[0022] Cone beam CT acquires multi-angle two-dimensional projection images by emitting a cone-shaped X-ray beam and rotating it around the patient's jaw, 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 edentulous area. The anterior tooth area is selected to be 4×4 cm², and the posterior tooth area is expanded to 8×8 cm² to cover the maxillary sinus and mental foramen. After denoising and artifact correction by a preset processor, the three-dimensional volume data generates a three-dimensional bone mass image, which is then converted into a mesh model in 3D printing format through a voxel-level reconstruction method.

[0023] The steps of dividing the alveolar bone into a high-density area, a medium-density area, and a low-density area by the bone density analysis unit are as follows: S1, inputting the acquired three-dimensional bone mass image into a preset image segmentation network to obtain a segmented image set; Preferably, the image segmentation network adopts an improved 3D U-Net structure, specifically including an encoder and a decoder; 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 segmented image set; S3, obtaining the density classification result of the segmented image set by area proportion; The segmentation results of each segmented image are divided into multiple categories, and the number of voxels in each category is counted (voxels are small cubic units with fixed size and position in each category in three-dimensional space), and the proportion of voxels in the total alveolar bone is calculated. The formula is:

[0024] The density classification results of the segmented image set are determined based on the area ratio of high, medium and low density areas: high density area: area ratio ≥ 40%; medium density area: 20% ≤ area ratio <40%; low density area: area ratio <20%; S4, determining a gray value distribution map corresponding to each density classification result by graying the three-dimensional bone mass image; The specific methods are 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; (2) HU value normalization mapping: linearly compress the original HU value to the grayscale range of 0-255, set a clinically relevant threshold (such as bone tissue HU>200), and filter non-target areas (air, soft tissue); (3) Adaptive contrast enhancement: Block-limited contrast histogram equalization (CLAHE) is used to independently enhance the trabecular texture and suppress noise for each 3D sub-block (e.g., 32×32×32 voxels); (4) Channel grayscale mapping: According to the density classification results (high / medium / low), gamma correction is performed on the grayscale distribution of each density area (gamma value <1 in high-density area brightens details, and gamma value >1 in low-density area reduces noise); (5) Generate grayscale distribution map: Output the optimized three-dimensional grayscale image of each density area, and overlay it as a pseudo-color distribution map (such as high density red, medium density yellow, and low density blue) to facilitate visual verification.

[0025] S5. Optimize each grayscale value distribution map to obtain a corresponding optimized distribution map, map the grayscale of the three-dimensional bone mass image according to the optimized distribution map, 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.

[0026] Among them, the calculation formula for determining the high-density area, medium-density area and low-density area of ​​the alveolar bone according to the corresponding weights assigned to the enhanced image is as follows: First, weights are assigned to different density areas according to clinical needs to generate a comprehensive enhanced image:

[0027] Typical weight distribution: =0.6; =0.3; =0.1; highlighting the influence of high-density area on implant stability; To comprehensively enhance the image; It is a high-density area of ​​the alveolar bone; It is the medium density area of ​​the alveolar bone; It is a low-density area of ​​the alveolar bone; Finally, the three-dimensional boundaries of high, medium and low density areas are extracted from the enhanced image through threshold segmentation or region growing method to obtain the high density area, medium density area and low density area of ​​the alveolar bone.

[0028] Among them, 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; The dynamic bite force distribution data include the real-time change curve of the bite force, the start and end time of a single bite action, the total chewing cycle length, the maximum vertical force in a single chewing, the periodic frequency of the bite action (such as 1-3Hz) and harmonic components, etc. There are multiple piezoelectric sensors in the bite force measurement unit, and the multiple piezoelectric sensors are distributed in an array; The piezoelectric sensor array consists of 16 micro sensors (2 mm in diameter) embedded in a custom bite pad, covering the occlusal surface of the dentition. The sensor sampling frequency is 1 kHz, dynamically recording the temporal-spatial distribution of the bite force (vertical, buccal-lingual, mesiodistal). After the data is de-noised by Kalman filtering, it is mapped to the alveolar bone force area through the inverse dynamics model.

[0029] For example, the peak vertical bite force in the first molar area can reach 700 N, and the lateral force of the anterior teeth is about 50 N. The spatial registration of the sensor data and the three-dimensional bone mass image is achieved through landmark points (such as tooth anatomical feature points), with an error of <0.1mm.

[0030] The method for the reconstruction unit to reversely reconstruct the original alveolar ridge three-dimensional model is as follows: Q1. Preset the model construction network, input the patient's tooth loss time into the model construction network, and calculate the vertical absorption amount and horizontal absorption amount according to the preset bone absorption time function; The model construction network is a two-branch deep learning structure: 1) The time branch processes the tooth missing time series and outputs the bone absorption rate coefficient; 2) The image branch extracts the current bone mass image features; 3) The fusion layer associates the time and space features through the attention mechanism to generate the vertical / horizontal absorption prediction value; the preset bone absorption time function is improved based on the Ribeiro model, and the vertical absorption , horizontal absorption t, is the bone density correlation coefficient, t is the edentulous time (month), and the predicted values ​​of vertical / horizontal absorption were compared with the vertical absorption and horizontal absorption calculated by the bone absorption time function to ensure the accuracy of the data; Q2. According to the vertical absorption and horizontal absorption, the original alveolar ridge contour is reversely deduced based on the three-dimensional bone mass image; The deduction steps are as follows: locate the current alveolar ridge absorption area, superimpose the absorption amount in the vertical direction to restore the original height; extrapolate the bone plate to the width before absorption in the horizontal direction, and correct the morphology in combination with the anatomical database; fuse the extended geometric structure to generate a continuous contour, and eliminate step artifacts through curvature smoothing; Q3. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone mass image, calculate the bone loss caused by absorption, and determine whether the bone loss caused by absorption exceeds the set threshold. If the bone loss caused by absorption exceeds the set threshold, the result will be transmitted to the doctor's terminal for subsequent implantation of bone powder, etc.; if it does not exceed, reconstruct the original alveolar ridge three-dimensional model based on the bone loss data.

[0031] The steps for calculating the bone loss caused by absorption in step Q3 are as follows: 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; Q32. Compare the original alveolar ridge contour with the corresponding alveolar ridge contour in the three-dimensional bone volume image, and mark the areas of depression or volume loss caused by resorption; Q33. Then use an algorithm to calculate the volume of the marked depression or volume reduction area to obtain the total amount of bone resorption.

[0032] Example: Patient information: A 50-year-old female with the right mandibular first molar missing for 3 years and planned to undergo implant restoration.

[0033] Data acquisition: CBCT scanning (slice thickness 0.2 mm, resolution 0.076 mm³) was used to obtain three-dimensional bone images of the edentulous area.

[0034] Step Q31: Three-dimensional space alignment Algorithm selection: Iterative closest point algorithm (ICP), which compares the original alveolar ridge model reconstructed by reverse engineering with the alveolar ridge in the current bone mass image ( Figure 1 blue outline) are aligned.

[0035] Alignment accuracy: Root mean square error <0.1 mm, ensuring that anatomical landmarks (such as mental foramen and alveolar ridge top) match.

[0036] Step Q32: Absorption area marking Surface distance analysis: Calculate the distance between the two model surfaces and mark the area with a distance > 2 mm as the absorption area.

[0037] Morphological processing: Close the difference area (3×3 kernel) to smooth the boundary and eliminate noise interference.

[0038] Results: The absorption area was concentrated in the center of the edentulous area and the buccal bone plate, with a vertical absorption depth of 3.2 mm and a horizontal absorption width of 4.5 mm.

[0039] Step Q33: Calculation of total bone resorption Volume integration method: The volume of the absorption area was calculated by voxel counting. The original alveolar ridge volume was 1200 mm³, the current bone volume was 900 mm³, and the total bone absorption volume was ΔV=300 mm³.

[0040] Regional statistics: vertical absorption accounts for 60% (180 mm³) and horizontal absorption accounts for 40% (120 mm³).

[0041] The specific steps of adjusting the unit to generate 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, 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; 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; 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.; The initial geometric parameters include: implant diameter and length: preset standard size according to the bone volume in the edentulous area (such as diameter 3.5-5.0mm, length 8-14mm); neck transition zone shape: taper (such as 1°-3°), neck diameter reduction ratio (such as 10%-20%); thread parameters: pitch (0.6-1.2mm), thread depth (0.2-0.5mm), thread angle (30°-60°); material parameters: elastic modulus (such as titanium alloy 110GPa, zirconium oxide 200GPa); Implant placement simulation steps 3D model registration: Align the implant geometry model with the reconstructed original alveolar ridge model and locate the implant position (based on the occlusal axis and bone density distribution); Finite element meshing: Generate high-precision tetrahedral meshes (element size ≤ 0.1 mm) for the implant-bone interface; Boundary condition loading: Fixed alveolar bone bottom freedom (simulating mandibular fixation); Apply vertical static load (e.g. 300N) and dynamic bite force (three-dimensional force vector decomposed according to step M31); Stress field calculation: solve stress distribution through finite element analysis and identify stress concentration areas (such as the neck or root apex); Example (Restoration of missing mandibular molars), patient data: 45-year-old male, missing right lower first molar for 2 years, CBCT showed vertical bone loss of 3.5 mm and horizontal bone loss of 4.0 mm.

[0042] Steps to execute: Reverse reconstruction of the original alveolar ridge: The model construction network input the edentulous time of 24 months and calculated ΔV = 3.2 mm, ΔH = 4.1 mm; Generate the original alveolar ridge contour, with a total bone absorption of 320 mm³; Virtual model repair and verification: Difference value detection (volume difference 5%), optimized ΔV=3.0mm, ΔH=3.8mm to meet the standard; Implant matching and implantation simulation: Initial parameters: diameter 4.5mm, length 10mm, pitch 0.8mm; Finite element analysis shows that the peak stress of the neck is 180MPa (the safety threshold of super titanium alloy is 150MPa); Dynamic adjustment of parameters: Increase the thread depth from 0.3mm to 0.4mm and adjust the neck taper to 2°; After optimization, the peak stress value was reduced to 135MPa, and the final implant model was generated; M3. According to the stress distribution data of the implant after implantation and combined with the dynamic occlusal force distribution data, the parameters of the implant are adjusted to generate a complete three-dimensional image of the implant.

[0043] The specific steps of combining the dynamic bite force distribution data in step M3 are as follows: M31. The dynamic bite force distribution data of the patient during chewing is recorded by a piezoelectric sensor, which is decomposed into three-dimensional force vectors at discrete time points according to the chewing cycle. Based on the static stress field after implantation, the dynamic bite force is superimposed frame by frame on the three-dimensional force vector according to the time step to generate a dynamic stress cloud map. M32. Identify the periodic high stress areas in the dynamic stress cloud diagram 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 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.

[0044] 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 zone of the implant.

[0045] Among them, the execution module 3 includes a receiving unit, a multi-print head coordination unit and a real-time monitoring unit. The receiving unit is used to receive implant parameters and a complete implant three-dimensional image, convert them 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 molten pool temperature through an infrared thermal imager, and dynamically adjusts the printing parameters to control the defect rate.

[0046] The receiving unit converts the thread parameters (pitch, depth) and geometric structure into G-code paths by parsing the STL file of the implant's three-dimensional image, and generates a three-dimensional printing coordinate matrix (accuracy ±0.05mm) based on the voxelization algorithm; the multi-print head collaborative unit adopts a dual-process integration strategy: selective laser melting prints the titanium alloy body with a layer thickness of 20-50μm, and electron beam melting simultaneously processes the high-density zirconia coating (for biocompatibility optimization), and dynamic path planning is used to avoid nozzle collision; the real-time monitoring unit deploys an infrared thermal imager (sampling rate 60Hz) to capture the molten pool temperature field. When local overheating (>1500℃) or cold shut (<800℃) is detected, the laser power (±50W) and scanning speed (±20mm / s) are immediately adjusted, combined with the online defect detection algorithm (such as porosity >2% triggers reprinting) to control the overall defect rate below 0.3%.

[0047] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also 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 ratio 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. A 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 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 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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