Orthodontic micro-implant nail implanting method, device and system and storage medium

Abstract

The invention discloses an orthodontic micro-implant nail implanting method, device and system and a storage medium. The method comprises the following steps: S1, acquiring CBCT three-dimensional data; and S2, analyzing CBCT three-dimensional data through AI artificial intelligence to calculate an optimal implantation site and an implantation direction path, and designing an implantation guide plate mounted on the surface of the dental crown. By the adoption of the technical scheme, the success rate of implanting the micro-implant nail is increased, relevant soft and hard tissue indexes in the CBCT three-dimensional image are integrated, and the burden and judgment errors of an orthodontic doctor in measurement and positioning are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of orthodontic medical treatment, and particularly relates to a method and device, system, and storage medium for implanting orthodontic micro-implants. Background Art

[0002] As a revolutionary advancement in modern orthodontics, the micro-screw anchorage system has fundamentally changed the construction mode of biomechanical anchorage. This technology breaks through the limitations of traditional dental anchorage through mini-osseointegrated devices in the jawbone, making three-dimensional precise tooth movement possible, successfully replacing large-sized extraoral anchorage devices such as headgear and transpalatal arches. While significantly improving the treatment efficiency, the orthodontic treatment course is on average shortened by 30-40%. Clinical data shows that the cases using orthodontic micro-implants can significantly reduce the anchorage loss rate compared with traditional anchorage methods, but its clinical popularity is still restricted by the accuracy problem of the core operation technology.

[0003] The existing micro-implant implantation technology faces three clinical dilemmas: First, the lack of anatomical navigation dimensions leads to operation blind spots. Currently, it mainly relies on panoramic two-dimensional images and doctors' experience judgment, but CBCT research has confirmed that there is a large error range between the actual three-dimensional volume of the safe area between tooth roots and the two-dimensional prediction. Especially when the micro-implant needs to be implanted between tooth roots, the operable distance is very narrow. If the judgment is inaccurate, it is easy to damage the tooth roots. Once the tooth roots are damaged or scratched, even if the micro-implant is withdrawn and re-implanted, it is very difficult for the micro-implant implanted in the new position to achieve a high retention rate due to the damaged bone mass in the implantation area, and the damage to the tooth roots is irreversible. Second, the lack of a dynamic mechanical feedback mechanism. When penetrating different bone density regions, the existing technology cannot real-time sense the characteristics of cortical bone penetration, resulting in a significant lack of success rate in bicortical fixation. Third, the lack of personalized biomechanical adaptation. There are large individual differences in the bone surface inclination of the maxillary zygomaticoalveolar crest area, the bicortical thickness of the mandibular external oblique line area, and the actual inclination of the buccal side of the alveolar bone, all of which require millimeter-level real-time dynamic adjustment capabilities.

[0004] Although artificial intelligence-assisted systems have been widely applied in the field of dental implants, the special biomechanical requirements of orthodontic micro-implants prevent their direct application. The main differences in biomechanical requirements between orthodontic micro-implants and dental implant screws are as follows:

[0005] 1) Different spatial dimensions and mechanical characteristics of the implantation positions: Dental implants are all vertically implanted into the alveolar ridge, while micro-implants need to be implanted with an inclination compensation of 15 - 45° within a narrow safety zone of 1.2 - 2.5 mm between the tooth roots (the implantation areas of dental implants mainly include 6 types of implantation sites at the top of the alveolar ridge, such as the maxillary anterior tooth area, maxillary premolar area, maxillary molar area, mandibular anterior tooth area, mandibular premolar area, and mandibular molar area, while the implantation areas of orthodontic micro-implants mainly include the buccal and palatal areas of the alveolar bone, such as the maxillary zygomaticoalveolar crest area, mandibular external oblique line area, maxillary median palatal suture area, maxillary anterior interradicular area, maxillary posterior interradicular area, mandibular anterior interradicular area, and mandibular posterior interradicular area). Due to the different implantation positions of orthodontic micro-implants, during the implantation of micro-implants, it is often necessary to perform personalized dynamic compensation of the inclination angle, achieve millimeter-level avoidance during implantation between adjacent tooth roots at close range, and achieve the feedback of the double-cortex penetration mechanics during implantation in the mandibular external oblique line area. These technical points cannot be achieved in the original artificial intelligence-assisted dental implant system.

[0006] 2) Differences in mechanical characteristics: The implant of a dental implant generally starts to be loaded and stressed 3 - 6 months after osseointegration, while orthodontic micro-implants need to be immediately loaded and stressed. Therefore, it is necessary to obliquely cut the cortical bone for implantation to increase the contact area with the cortical bone as much as possible to enhance stability.

[0007] 3) Differences in risk control: The implantation sites of orthodontic micro-implants are generally located between the tooth roots and at the root tip of the tooth. When the proposed implantation site is close to the adjacent tooth root, it is easy to have problems such as the micro-implant compressing the periodontal membrane of the adjacent tooth during the implantation process, causing pain and early loosening of the implant; when implanting a micro-implant in the maxilla, due to individual differences in the height of the maxillary sinus floor, it is necessary to specifically avoid the risk of piercing the maxillary sinus floor; when implanting in the mandibular external oblique line, due to the requirement of penetrating the double cortical bone and the need to accurately control the implantation depth after piercing the second cortical bone, otherwise, it may cause damage to the lingual mucosa and the tongue body.

[0008] The defects of the existing technology have formed a significant clinical bottleneck: The loosening rate of micro-implants after implantation based on traditional methods is high at 6 months, and the failed cases are mainly attributed to the three-dimensional deviation of the implantation angle. This highlights that the existing two-dimensional empirical operation mode can no longer meet the biomechanical requirements of precise orthodontics, and there is an urgent need to develop an intelligent operating system that integrates multi-modal data perception and real-time mechanical feedback to achieve precise positioning of the implantation site, precise judgment of the implantation direction and depth, so as to break through the technical limitations of the current clinical application of micro-implants. Summary of the Invention

[0009] The technical problem to be solved by the present invention is to provide a method, device, system, and storage medium for implanting orthodontic micro-implants.

[0010] To achieve the above object, the present invention adopts the following technical solutions:

[0011] An orthodontic micro-implant insertion method includes:

[0012] Step S1: Obtain CBCT three-dimensional data;

[0013] Step S2: Analyze the CBCT three-dimensional data through AI artificial intelligence to calculate the optimal implantation site and implantation direction path, and design an implant guide plate installed on the tooth crown surface.

[0014] Preferably, step S2 includes:

[0015] Step S21: Obtain CBCT data and the corresponding intraoral scan STL file;

[0016] Step S22: Determine the implant point and implant path of the implant based on the CBCT data and the corresponding intraoral scan STL file through the U-Net network;

[0017] Step S23: Print an implant guide plate that simultaneously includes the gingival implant point, implant path, and clinical crown retention area through 3D printing based on the CBCT data and the corresponding intraoral scan STL file, install the implant guide plate on the tooth crown, and implant the implant along the implant path on the guide plate.

[0018] Preferably, step S22 includes:

[0019] Based on the CBCT data and the corresponding intraoral scan STL file, determine the coronal plane for implanting the implant at a height of 5 mm from the alveolar ridge crest;

[0020] On the coronal plane, connect the buccal sides of two molars and their midpoints respectively, and then take the midpoint to determine the projection line of the implant path;

[0021] On the sagittal section of the projection line, determine the implant site by a distance of 5 mm from the alveolar ridge edge, and the implant path forms an angle of 45° with the long axis of the tooth.

[0022] The present invention also provides an orthodontic micro-implant implantation device, including:

[0023] An acquisition module for acquiring CBCT three-dimensional data;

[0024] An implantation module for analyzing the CBCT three-dimensional data through AI artificial intelligence to calculate the optimal implantation site and implantation direction path, and designing an implant guide plate installed on the tooth crown surface.

[0025] Preferably, the implantation module includes:

[0026] A first processing module for obtaining CBCT data and the corresponding intraoral scan STL file;

[0027] A second processing module, configured to determine the implanting points and implanting channels of the orthodontic micro-implant pins according to the CBCT data and the corresponding intraoral scanned STL file through a U-Net network;

[0028] A third processing module, configured to 3D print an implant guide plate that simultaneously includes the gingival implanting points, implanting channels, and the clinical crown retention sites according to the CBCT data and the corresponding intraoral scanned STL file, install the implant guide plate on the dental crown, and implant the orthodontic micro-implant pins along the implanting channels on the guide plate.

[0029] Preferably, the second processing unit includes:

[0030] A first processing component, configured to determine the coronal plane for implanting the orthodontic micro-implant pins based on a height of 5 mm from the alveolar ridge crest according to the CBCT data;

[0031] A second processing component, configured to connect the buccal sides and the midpoints of two molars on the coronal plane respectively, and then take the midpoint thereof to determine the projection line of the implanting channel;

[0032] A third processing component, configured to determine the implanting site on the sagittal section of the projection line, and the implanting channel forms an angle of 45° with the long axis of the tooth by a distance of 5 mm from the alveolar ridge edge.

[0033] An embodiment of the present invention further provides an orthodontic micro-implant pin implanting system, including: a memory and a processor, where a computer program run by the processor is stored on the memory, and the computer program executes the orthodontic micro-implant pin implanting method when being run by the processor.

[0034] An embodiment of the present invention further provides a storage medium, where a computer program is stored on the storage medium, and the computer program executes the orthodontic micro-implant pin implanting method when running.

[0035] The present invention overcomes the deficiencies of the current orthodontic anchorage pin implanting analysis method, calculates the optimal implanting site and implanting direction path by analyzing the CBCT three-dimensional data through AI artificial intelligence, and combines a pressure sensor during the implanting process to improve the accuracy during the micro-implant pin implantation and reduce the risk of causing pain to the patient by hitting the periodontal membrane, etc.; meanwhile, it can automatically analyze the oral image data of the patient and generate a personalized implanting plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0037] Figure 1This is a flowchart of the orthodontic micro-implant implantation method according to an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the interradicular area of the posterior teeth in the right maxilla;

[0039] Figure 3 This is a schematic diagram of the process of positioning the implantation point and implantation path in the interradicular area of the posterior teeth in the right maxilla; wherein, A, B, C, and D are reference positioning points respectively, and E is the implantation site;

[0040] Figure 4 This is a schematic diagram of the change in the inclination of the pressure waveform collected by the pressure sensor during the micro-implant process. Detailed implementation manners

[0041] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0043] Embodiment 1:

[0044] As Figure 1 shown, an orthodontic micro-implant implantation method provided by an embodiment of the present invention includes:

[0045] Step S1, obtaining CBCT three-dimensional data;

[0046] Step S2, calculating the optimal implantation site and implantation direction path by analyzing the CBCT three-dimensional data through AI artificial intelligence, and designing an implant guide plate installed on the tooth crown surface.

[0047] As an implementation manner of an embodiment of the present invention, step S2 includes:

[0048] Step S21, obtaining CBCT data and the corresponding intraoral scan STL file;

[0049] Step S22, determining the implant point and implant path of the implant by the U-Net network according to the CBCT data and the corresponding intraoral scan STL file;

[0050] Step S23, printing out an implant guide plate that simultaneously includes the gingival implant point, implant path, and clinical crown retention area by 3D according to the CBCT data and the corresponding intraoral scan STL file, installing the implant guide plate on the tooth crown, and implanting the implant along the implant path on the guide plate.

[0051] Further, in step S21, CBCT data and corresponding intraoral scan STL files of 100 patients are collected. The CBCT data is collected using a conventional oral CBCT scanning device, and the scanning parameters are set as follows: voltage 120 kV, current 5 mA, scanning time about 20 seconds, and image resolution 0.2 mm×0.2 mm×0.2 mm. The intraoral scan STL files are obtained through a high-precision intraoral scanner with a scanning accuracy of 0.05 mm.

[0052] Perform 3D reconstruction on the CBCT data, and then overlap the crowns of the two maxillary central incisors and the first maxillary molars. Fit the intraoral scan STL file onto the CBCT data to obtain data that combines the oral soft and hard tissues.

[0053] Further, in step S22, after matching 100 cases of CBCT data and intraoral scan STL files through deep learning, the result of importing data, that is, directly generating matching data, is achieved.

[0054] Based on the CBCT data, determine the coronal plane for implanting the implant at a height 5 mm from the alveolar ridge crest. The specific method is: in the matched CBCT data, find the position of the alveolar ridge crest, and then move up (or down) 5 mm to determine the coronal plane.

[0055] On the coronal plane, connect the buccal sides of the two molars and their midpoints (the position with the closest distance between the two teeth), and then take the midpoint of it to determine the projection line of the implant path. The specific method is: on the coronal plane, find the buccal side positions of the two molars, calculate the midpoint with the closest distance between the two teeth, and then connect these two midpoints to obtain the projection line of the implant path.

[0056] On the sagittal section of the projection line, determine the implant site by a distance of 5 mm from the alveolar ridge edge. The specific method is: on the sagittal section of the projection line, find the position of the alveolar ridge edge, and then move 5 mm towards the root direction to determine the implant point on the cortical bone surface, and the corresponding position on the mucosal surface is the actual intraoral implant point.

[0057] Pierce the cortical bone surface by inserting the implant along a path perpendicular to the bone surface, and then withdraw the implant from the bone surface. Design the final implant path at an angle of 45 degrees with the cortical bone surface, thereby obtaining the implant point and its implant path on the alveolar bone surface. The specific method is: at the determined implant site, insert the implant perpendicular to the bone surface to pierce the cortical bone surface, and then withdraw the implant from the bone surface. Adjust the angle of the implant path to 45 degrees to finally determine the implant point and the implant path.

[0058] The U-Net network architecture is selected as the basic model. This network consists of an encoder and a decoder. The encoder is used to extract the features of the input data, and the decoder is used to gradually restore the spatial resolution of the image and generate the final matching result.

[0059] In the encoder part, 4 convolutional blocks are set, and each convolutional block contains 2 convolutional layers and 1 max-pooling layer. The convolutional kernel size of the convolutional layer is 3×3×3, the stride is 1, and the padding is 1; the pooling kernel size of the max-pooling layer is 2×2×2, and the stride is 2. In the decoder part, 4 upsampling blocks are set, and each upsampling block contains 1 upsampling layer and 2 convolutional layers. The upsampling layer uses the nearest neighbor interpolation method to double the spatial resolution of the feature map; the parameter settings of the convolutional layer are the same as those of the encoder.

[0060] A feature fusion module is added between the encoder and the decoder. This module contains 1 fully connected layer and 1 activation function layer. The number of input neurons of the fully connected layer is 1024, and the number of output neurons is 512; the ReLU function is used as the activation function. The role of the feature fusion module is to fuse the features of the CBCT data and the STL file, and then locate the ideal implant and the implantation path according to the method of locating the implant point and the implantation path of the implant.

[0061] The model is trained using 100 cases of collected data. After taking the CBCT data and the corresponding STL file as the input, the location is performed according to the method of locating the ideal implant point and the implantation path of the implant, and the location result obtained by manual marking in advance is used as the label. The manual marking process is completed by a professional team of oral doctors. They locate the ideal implant point and the implantation path of the implant one by one according to the morphological characteristics of the CBCT image and the STL model, and convert the marking result into label data that matches the output format of the model.

[0062] The Stochastic Gradient Descent (SGD) optimization algorithm is used to train the model, with a learning rate of 0.001, a momentum of 0.9, and a weight decay coefficient of 0.0005. During the training process, the batch size is set to 4, and the number of iterations is 1000 times. At the end of each iteration cycle, the matching accuracy of the model on the validation set is calculated. When the accuracy does not improve for 10 consecutive iteration cycles, the training is stopped to prevent overfitting of the model.

[0063] To enhance the generalization ability of the model, data augmentation techniques are applied to the training data. For CBCT data, random rotation (rotation angle between -10° and 10°), random scaling (scaling ratio between 0.9 and 1.1), and random cropping (cropping size is 80%-100% of the original size) are performed; for STL files, random perturbation (adding random noise within the range of [-0.02, 0.02] to the coordinates of each vertex) and random resampling (the number of sampling points varies between 80% and 120% of the original number of points) are carried out.

[0064] When a new implant path needs to be calculated, after matching the new CBCT data with the intraoral scanned STL file, the position information of the implant screw to be implanted is input into the trained deep learning model. The model directly generates the results of the most suitable implant points and implant paths between the two required teeth, providing precise guidance for dental implant surgery.

[0065] Furthermore, in step S23, according to the CBCT data and the corresponding intraoral scanned STL file, the implant points on the alveolar bone surface are projected onto the gingival surface. Taking 3 clinical crowns of the same-side dental arch as the fixation points, an implant guide plate that simultaneously includes the gingival implant points, implant paths, and the fixation positions of the clinical crowns is printed by 3D. After installing the implant guide plate on the crown, the implant screw can be implanted along the implant path on the guide plate to achieve the best effect of precise implantation.

[0066] Example 2:

[0067] The embodiment of the present invention provides an orthodontic micro-implant screw implantation method. Taking the implantation of implant screws between the roots of the first and second maxillary molars as an example, through artificial intelligence analysis of CBCT images to learn and define the best implantation route between the roots, and designing a micro-implant screw guide plate that can be installed on the surface of the crown, and combining a pressure display with a pressure sensor and an alarm device to achieve the purpose of the most efficient and safe implantation of micro-implant screws. The specific technical solutions are as follows:

[0068] 1. Construct a hard and soft tissue matching image database

[0069] First, the hard tissue image of the patient's maxillofacial region is fitted with the intraoral surface image. The hard tissue image of the maxillofacial region is a DICOM file exported from CBCT three-dimensional scan data, and the intraoral surface image comes from the STL file exported after intraoral scanning. After matching 100 cases of CBCT data with the intraoral scanned STL file through deep learning, the result of directly generating matching data for importing data is achieved, and clinicians can then make appropriate adjustments according to the situation.

[0070] 2. Determine the implant points and implant paths of the implant screw

[0071] For the implantation of micro-implants, according to the specific implantation sites, they are divided into the following 7 categories, as shown in Table 1. The most reasonable implantation sites and implantation tracks will be designed in combination with artificial intelligence according to the requirements of their respective implantation points and implantation channels, and a micro-implant implant guide plate will be printed with the mature 3D printing technology.

[0072] Table 1

[0073]

[0074]

[0075] In each micro-implant implantation area, after determining the most suitable implantation site with the assistance of artificial intelligence-assisted CBCT for positioning, first implant perpendicularly to the bone surface to break through the cortical bone, and then according to the safest implantation channel designed, the 3D printed implant guide plate contains two implantation channels (the vertical implantation channel and the subsequent actual implantation channel). The following takes the interradicular area of the posterior teeth in the right maxilla (between the roots of the right maxillary second premolar 15 and the first permanent molar 16) as an example to specifically illustrate how to combine artificial intelligence to locate the implantation point and implantation channel, as Figure 2 、 3 shown:

[0076] (1) On the CBCT file that shows the hard tissue image of the maxilla in the Dolphin and Carestream Vue PACS software, the cross-sections of the patient's entire craniofacial region in three-dimensional directions at various positions can be obtained.

[0077] (2) Determine the height 5 mm away from the alveolar ridge on the sagittal section passing through 15 and 16, and then take the corresponding horizontal section at this height.

[0078] (3) On this horizontal section, first connect the most convex points on the buccal sides of the mesial buccal roots of 15 and 16 to obtain line segment AB; then in the interdental space between 15 and 16, determine the shortest line segment CD among all the line segments parallel to AB; after connecting the midpoints of AB and CD, it is used as the projection line of the micro-implant on this horizontal plane. Then obtain the vertical section where this projection line is located.

[0079] (4) On the vertical section where the projection line is located, the implantation site is determined at a distance of 5 mm from the alveolar ridge edge on the buccal cortical bone of the alveolar bone.

[0080] (5) The breakthrough channel 1 is the one that passes through the implantation site (E) and is perpendicular to the buccal bone surface of the alveolar bone. The micro-implant penetrates the cortical bone in this direction; the implantation channel 2 is the one that passes through the implantation site and forms an angle of about 45 degrees with the bone surface and avoids the floor of the maxillary sinus.

[0081] (6) Input the process data of the above-mentioned implant points and implant channels into the system through a deep learning algorithm. Finally, after inputting a new CBCT image and confirmation, it can automatically locate the target implant point, penetration channel 1, and implant channel 2.

[0082] 3. 3D Printed Orthodontic Implant Guide

[0083] Fit the STL file scanned intraorally according to the CBCT image generated in step 1, project the implant points on the alveolar bone surface onto the gingival surface, use the 3 clinical crowns of the ipsilateral dental arch as fixation points, and 3D print an implant guide that simultaneously includes the gingival implant points, penetration channel 1 (double-layer guide limits the implant track), implant channel 2, and the clinical crown fixation sites, and mark the starting points of penetration channel 1 and implant channel 2 with different colors. After installing the implant guide on the crown, first implant the implant screw along penetration channel 1 through the cortical bone, then withdraw the implant screw, and then change to implant channel 2, and continuously implant the implant screw completely to achieve precise implantation and avoid damaging the tooth root.

[0084] In order to better monitor the penetration progress of the micro-implant screw into the cortical bone and prevent the micro-implant screw from penetrating too much perpendicular to the bone surface, a pressure sensor is added to the connection between the implant handle and the micro-implant screw, and on the receiver of the pressure sensor, once the inclination of the pressure waveform is greater than 45 degrees, an alarm will sound automatically. As Figure 4 shown, when the pressure waveform significantly decreases downward with an inclination of more than 45 degrees, it indicates that the tip of the micro-implant screw has passed through the dense and highly resistant cortical bone and reached the spongy bone with low resistance. At this time, the alarm bell prompts to withdraw the micro-implant screw in time and change the implant channel (press the "ring" key after processing to stop the alarm); when the pressure waveform significantly increases upward with an inclination of more than 45 degrees, it indicates that the tip of the screw has encountered a highly resistant tooth root, and the alarm bell will prompt to stop implanting immediately and make adjustments. In the case of designing the implant channel with the assistance of artificial intelligence and combining with CBCT in step 1, the tooth root has been completely avoided, and this situation will not normally occur, but this function is still designed in the embodiments of the present invention to serve as a double insurance.

[0085] When the micro-implant screw penetrates the cortical bone through penetration channel 1 with the cooperation of free hand and gradually increasing pressure, the waveform of the pressure magnitude can be seen on the receiver of the pressure sensor. After penetrating the cortical bone, the pressure rapidly decreases, indicating that the tip of the micro-implant screw has passed through the cortical bone and reached the spongy bone. At this time, it is prompted to withdraw the micro-implant screw in time; then change to implant channel 2 in time, and completely implant the threaded part of the implant screw through the implanted site that has penetrated the cortical bone.

[0086] Example 3:

[0087] The embodiments of the present invention also provide an orthodontic micro-implant device, including:

[0088] An acquisition module for acquiring CBCT three-dimensional data;

[0089] An implantation module for calculating the optimal implantation site and the implantation direction path by analyzing the CBCT three-dimensional data through AI artificial intelligence, and designing an implant guide plate installed on the surface of the dental crown.

[0090] As an implementation manner of an embodiment of the present invention, the implantation module includes:

[0091] A first processing module for acquiring CBCT data and the corresponding intraoral scan STL file;

[0092] A second processing module for determining the implant point and the implant path of the implant screw according to the CBCT data and the corresponding intraoral scan STL file through a U-Net network;

[0093] A third processing module for printing out an implant guide plate that simultaneously includes the gingival implant point, the implant path, and the clinical crown retention site according to the CBCT data and the corresponding intraoral scan STL file through 3D printing, installing the implant guide plate on the dental crown, and implanting the implant screw along the implant path on the guide plate.

[0094] As an implementation manner of an embodiment of the present invention, the second processing unit includes:

[0095] A first processing component for determining the coronal plane of the implant screw implantation based on a height of 5 mm from the alveolar ridge crest according to the CBCT data;

[0096] A second processing component for connecting the buccal sides of two molars and the midpoint thereof on the coronal plane, and then taking the midpoint thereof to determine the projection line of the implant path;

[0097] A third processing component for determining the implant site on the sagittal section of the projection line by a distance of 5 mm from the alveolar ridge edge, and the implant path forms an angle of 45° with the long axis of the tooth.

[0098] Example 4:

[0099] An embodiment of the present invention further provides an orthodontic micro-implant screw implantation system, including: a memory and a processor, where a computer program run by the processor is stored on the memory, and the computer program executes the orthodontic micro-implant screw implantation method when being run by the processor.

[0100] Example 5:

[0101] An embodiment of the present invention further provides a storage medium, where a computer program is stored on the storage medium, and the computer program executes the orthodontic micro-implant screw implantation method when running.

[0102] The embodiments described above are only descriptions of the preferred embodiments of the present invention and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for implanting orthodontic micro-screws, characterized in that: include: Step S1, acquiring CBCT three-dimensional data; Step S2: Analyze CBCT three-dimensional data through AI artificial intelligence to calculate the optimal implant site and implant direction path, and design an implant guide installed on the crown surface.

2. The orthodontic micro-screw implantation method according to claim 1, characterized in that: Step S2 includes: Step S21, obtaining CBCT data and corresponding intraoral scanning STL files; Step S22, determining the implant point and implant tract through the U-Net network according to the CBCT data and the corresponding intraoral scan STL file; Step S23, according to the CBCT data and the corresponding intraoral scanning STL file, an implant guide plate including a gingival implantation point, an implantation canal and a clinical crown retention point is 3D printed, the implant guide plate is installed on the crown, and the implant pin is implanted along the implantation canal on the guide plate.

3. The orthodontic micro-screw implantation method according to claim 2, characterized in that: Step S22 includes: According to the CBCT data and the corresponding intraoral scanning STL file, the coronal plane of the implant was determined based on the height of 5 mm from the alveolar ridge top; Connect the buccal sides of the two molars and their midpoints on the coronal plane, and then take the midpoint to determine the projection line of the implant tract; On the sagittal section of the projection line, the implant site was determined by 5 mm from the edge of the alveolar ridge, and the implant canal was at a 45° angle to the long axis of the tooth.

4. An orthodontic micro-screw implantation device, characterized in that: include: An acquisition module, used for acquiring CBCT three-dimensional data; The implantation module is used to analyze CBCT three-dimensional data through AI artificial intelligence to calculate the optimal implantation site and implantation direction path, and design the implantation guide installed on the surface of the crown.

5. The orthodontic micro-screw implantation device according to claim 4, characterized in that: The implant modules include: A first processing module is used to obtain CBCT data and corresponding intraoral scanning STL files; The second processing module is used to determine the implant point and implant path of the implant screw through the U-Net network according to the CBCT data and the corresponding intraoral scan STL file; The third processing module is used to 3D print an implant guide that includes a gingival implant point, an implant channel, and a clinical crown retention point based on the CBCT data and the corresponding intraoral scan STL file, install the implant guide on the crown, and implant the implant pin along the implant channel on the guide.

6. The orthodontic micro-screw implantation device according to claim 5, characterized in that: The second processing unit comprises: The first processing component is used to determine the coronal plane of the implant pin based on the height of 5 mm from the alveolar ridge top according to the CBCT data; The second processing component is used to connect the buccal sides of the two molars and their midpoints respectively on the coronal plane, and then take the midpoints to determine the projection line of their implantation tracts; The third processing component is used to determine the implant site at a distance of 5 mm from the edge of the alveolar ridge on the sagittal section of the projection line, with the implant canal forming an angle of 45° with the long axis of the tooth.

7. An orthodontic micro-screw implantation system, characterized in that: include: A memory and a processor, wherein the memory stores a computer program executed by the processor, and when the computer program is executed by the processor, the orthodontic micro-screw implantation method as described in any one of claims 1 to 3 is executed.

8. A storage medium, characterized in that: The storage medium stores a computer program, which, when running, executes the orthodontic micro-screw implantation method as described in any one of claims 1 to 3.

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