Tooth preparation system and method based on AI medical image

Abstract

The invention discloses a tooth preparation system and method based on AI medical images, and belongs to the technical field of false tooth preparation, and the tooth preparation system comprises a tooth data acquisition module, an AI data processing modeling module and a 3D printing preparation module. A tooth data acquisition module is established based on a hospital intranet system to acquire tooth data of a patient, the tooth data is converted into a basic size sample through an AI data processing unit based on a computer, and the basic size is converted into coordinate data of a 3D printing machine tool system; based on basic coordinate data of the tooth gum, a tooth model blank is processed in advance in a 3D additive processing mode, tooth data is adjusted according to abnormal tooth data of a patient in an intranet of a hospital while 3D additive processing is carried out, and material reduction processing is carried out on the tooth model blank through a 3D printing machine tool, so that the tooth model blank is obtained. And compared with a traditional 3D printing and model reversing mode, the preparation process can be synchronously carried out in multiple items, so that the preparation efficiency is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of denture preparation, and in particular to a tooth preparation system and method based on AI medical imaging. Background Art

[0002] Dentures are what people often call "false teeth". Just like "false legs" and "false limbs" are called "artificial limbs", "dentures" mean teeth that fulfill "duties" for humans. In medicine, it is a general term for restorations made after partial or complete tooth loss in the upper and lower teeth. Dentures are divided into removable and fixed. Fixed dentures (commonly known as "fixed dentures") cannot be removed and put on by the patient himself, while removable dentures (commonly known as "removable dentures") can be easily removed and put on by the patient.

[0003] In the preparation method of dentures, the commonly used method is to prepare them by sintering zirconium dioxide materials into models. This method is complicated to process and time-consuming. In addition, since the size is determined by the model during the firing process, the pass rate is very low. With the continuous advancement of technology, 3D printing technology is increasingly used in the preparation of dentures. The existing preparation methods on the market lack an effective preparation system, which makes the molding efficiency of dentures low and the pass rate low. Based on this, a tooth preparation system and method based on AI medical imaging are proposed. Summary of the invention

[0004] The purpose of the present invention is to solve the problems existing in the prior art and to propose a tooth preparation system and method based on AI medical imaging.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A tooth preparation system based on AI medical imaging, including a tooth data acquisition module, an AI data processing modeling module and a 3D printing preparation module. The tooth data acquisition module is established based on the hospital intranet system and is used to obtain tooth data;

[0007] The AI ​​data processing modeling module is established based on a computer system and is used for data processing, calculation and simulation modeling;

[0008] The 3D printing preparation module is established based on a 3D printer bed numerical control system and is used for additive and subtractive processing of tooth models.

[0009] Preferably, the dental data acquisition module obtains the patient's dental data through AI medical imaging data and oral scan data, and connects to the hospital's internal data network through the Internet of Things to obtain the patient's dental data.

[0010] Preferably, the 3D printer bed numerical control system comprises a 3D printer bed, an HMI main control numerical control module and a workpiece scanning module.

[0011] The preparation method proposed by the tooth preparation system based on AI medical imaging includes the following steps:

[0012] S1. Dental data collection: The patient's dental data is obtained through AI medical imaging data and oral scan data, and the patient's dental data is uploaded through the Internet of Things;

[0013] S2. Tooth data preprocessing: uploading the acquired patient tooth data to the AI ​​data processing unit, which acquires a basic size sample of the tooth data and extracts size data of the basic size sample;

[0014] S3, 3D additive embryo processing: convert the size data into coordinate data, upload the coordinate data to the HMI main control module, control the 3D printer bed for additive processing through the CNC system, and make the raw materials into a tooth model embryo through 3D additive processing;

[0015] S4, data integration and calibration: obtaining tooth abnormality data and user oral data, integrating them into adjustment data, and recalibrating and checking the adjustment data that needs to be adjusted through the processing unit to form preparation molding data;

[0016] S5, simulation model establishment: the preparation molding data is divided into tooth image data, gum image data and attached gingiva image data, corresponding regional simulation modules are formed according to different image data, and the simulation modules are integrated to form an overall tooth simulation model;

[0017] S6, coordinate data acquisition: the processor calculates the size of the simulation module models in different regions, obtains the regional coordinate data of the simulation modules, and simultaneously forms the corresponding overall coordinate data according to the overall tooth simulation model, and obtains the coordinate size data required for subtractive processing according to the integration degree of the regional coordinate data and the overall coordinate data;

[0018] S7, 3D subtractive processing: upload the subtractive processing coordinate size data to the HMI main control module, and control the subtractive processing module of the 3D printer bed through the numerical control system to perform subtractive processing on the tooth model blank made by additive manufacturing to make a tooth model;

[0019] S8, data scanning calibration: perform three-dimensional laser high-precision scanning on the manufactured tooth model through the workpiece scanning module of the 3D printer bed to obtain the size data of the tooth model;

[0020] S9, data verification and checking: the size data of the tooth model is divided into tooth model image data, gum model image data and attached gingiva model image data through a processor, and corresponding regional model modules are formed according to different image data;

[0021] Compare the manufactured regional model module with the regional simulation module model, find out the difference point K1 between the two, check the size of the difference point K1, calculate the size data of the difference point K1, and obtain the size coordinates of the difference point K1;

[0022] S10, repair and remanufacturing: repair and manufacture with additive and subtractive materials through a 3D printer according to the size coordinate data of the difference point K1;

[0023] S11, data recalibration: repeat steps S8 and S9 until the difference point K1 is smaller than the predetermined threshold value K, and the calibration of the tooth model is completed;

[0024] S12. Fine processing and improvement: Perform detailed processing on the calibrated tooth model to complete the preparation of the teeth.

[0025] Preferably, the data involved in the dental data collection process in S1 includes one or more of the following: clinical test data, panoramic dental radiographs and cephalographic radiographs, oral scanning equipment, and dental models.

[0026] Preferably, in S4, the tooth feature points are judged by stomatology, and the tooth feature points include the long axis, mesiodistal direction and buccolingual direction of the teeth. The patient's tooth defect points are supplemented with data by stomatology, and discrete Gaussian curvature is used to reflect the degree of curvature of each vertex of the tooth, thereby describing the characteristics of the tooth surface and obtaining tooth abnormality data and user oral data.

[0027] Preferably, the size data of the difference point K1 in S9 has two types, "+" and "-", corresponding to subtractive processing and additive processing in 3D printing respectively;

[0028] The coordinate reference point of the size coordinate of the difference point K1 is adjusted according to the “vertex” of the difference point K1 of the tooth model.

[0029] Preferably, the threshold value K in S11 is the difference percentage between the regional simulation module model and the regional model module model. A tooth model lower than the difference percentage can be considered as a qualified tooth model.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. The present invention establishes a tooth data acquisition module based on the hospital intranet system to acquire the patient's tooth data, converts the tooth data into basic size samples through a computer-based AI data processing unit, and converts the basic size into coordinate data of a 3D printer system, and processes the basic coordinate data of the tooth bed into a tooth model blank in advance through 3D additive processing, and while performing 3D additive processing, adjusts the tooth data according to the abnormal tooth data of the patient in the hospital intranet, establishes a tooth simulation model based on the adjusted tooth data, obtains the optimal state of the denture, and converts the data of the simulation model into coordinate data to perform subtractive processing on the tooth model blank through a 3D printer. Compared with traditional 3D printing and model casting, the preparation process can be performed simultaneously in multiple steps, thereby significantly improving the preparation efficiency.

[0032] 2. The present invention performs three-dimensional laser high-precision scanning on the manufactured tooth model through the workpiece scanning module in the 3D printer bed system, obtains the dimensional data of the prepared tooth model, and establishes a simulation model of the model for comparison with the original data. For the dimensional data of the difference point K1, the tooth model is repaired and remanufactured through additive and subtractive processing of the 3D printer bed to ensure the integrity and consistency of the manufactured tooth model. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a diagram of the tooth preparation system based on AI medical imaging proposed by the present invention;

[0034] Figure 2 This is a flow chart of the tooth preparation method based on AI medical imaging proposed in the present invention. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0036] In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "top / bottom" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific position, be constructed and operated in a specific position, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0037] Example, see Figure 1 to Figure 2 , a tooth preparation system and method based on AI medical imaging, including a tooth data acquisition module, an AI data processing modeling module and a 3D printing preparation module, wherein the tooth data acquisition module is established based on the hospital intranet system and is used to obtain tooth data and obtain hospital intranet authorization for data extraction;

[0038] The AI ​​data processing modeling module is established based on a computer system and is used for data processing, calculation and simulation modeling;

[0039] The 3D printing preparation module is established based on the 3D printer bed numerical control system and is used for additive and subtractive processing of tooth models.

[0040] The dental data acquisition module obtains the patient's dental data through AI medical imaging data and oral scan data, and connects to the hospital's internal data network through the Internet of Things to obtain the patient's dental data.

[0041] The 3D printer bed CNC system includes a 3D printer bed, an HMI main control CNC module and a workpiece scanning module.

[0042] The preparation method proposed by the tooth preparation system based on AI medical imaging obtains the patient's tooth data through AI medical imaging data and oral scan data, and uploads the patient's tooth data through the Internet of Things;

[0043] The data involved in the dental data collection process include one or more of the following: clinical test data, panoramic dental and cephalographic radiographs, oral scanning equipment, and dental models.

[0044] The acquired patient tooth data is uploaded to the AI ​​data processing unit, and the AI ​​data processing unit acquires a basic size sample of the tooth data and extracts size data of the basic size sample;

[0045] Convert the dimension data into coordinate data, upload the coordinate data to the HMI main control module, control the 3D printer bed to perform additive processing through the CNC system, and make the raw materials into a tooth model embryo through 3D additive processing; obtain tooth abnormality data and user oral data, integrate them into adjustment data, and recalibrate and check the adjustment data that needs to be adjusted through the processing unit to form preparation molding data;

[0046] The prepared molding data is divided into tooth image data, gum image data and attached gingiva image data, corresponding regional simulation modules are formed according to different image data, and the simulation modules are integrated to form an overall tooth simulation model;

[0047] Dental feature points are judged through stomatology. The tooth feature points include the long axis, mesiodistal direction and buccolingual direction of the tooth. Dental defect points of the patient are supplemented through stomatology. Discrete Gaussian curvature is used to reflect the degree of curvature of each vertex of the tooth, so as to describe the characteristics of the tooth surface and obtain tooth abnormality data and user oral data.

[0048] The processor calculates the size of the simulation module models in different regions, obtains the regional coordinate data of the simulation modules, and simultaneously forms the corresponding overall coordinate data according to the overall tooth simulation model. According to the integration degree of the regional coordinate data and the overall coordinate data, the coordinate size data required for subtractive processing is obtained;

[0049] Upload the coordinate dimension data of the subtractive processing to the HMI main control module, and control the subtractive processing module of the 3D printer bed through the numerical control system to perform subtractive processing on the tooth model blank made by additive manufacturing to make a tooth model;

[0050] The workpiece scanning module of the 3D printer bed performs a three-dimensional laser high-precision scanning on the manufactured tooth model to obtain the size data of the tooth model;

[0051] The size data of the tooth model is divided into tooth model image data, gum model image data and attached gingiva model image data by a processor, and corresponding regional model modules are formed according to different image data;

[0052] Compare the manufactured regional model module with the regional simulation module model, find out the difference point K1 between the two, check the size of the difference point K1, calculate the size data of the difference point K1, and obtain the size coordinates of the difference point K1;

[0053] There are two types of difference point K1 size data, "+" and "-", which correspond to subtractive processing and additive processing in 3D printing respectively; the coordinate reference point of the difference point K1 size coordinate is adjusted according to the "vertex" of the difference point K1 of the tooth model. Additive and subtractive restoration manufacturing is performed through the 3D printer bed according to the difference point K1 size coordinate data;

[0054] Repeat the above steps until the difference point K1 is smaller than the predetermined threshold value K, and the calibration of the tooth model is completed;

[0055] The threshold K is the difference percentage between the regional simulation module model and the regional model module model. If the difference percentage is lower than the threshold K, the tooth model can be considered as a qualified tooth model. The calibrated tooth model is processed in detail to complete the preparation of the tooth.

[0056] The present invention establishes a tooth data acquisition module based on the hospital intranet system to acquire the patient's tooth data, converts the tooth data into a basic size sample through a computer-based AI data processing unit, and converts the basic size into coordinate data of a 3D printer bed system, and processes the basic coordinate data of the tooth bed into a tooth model blank in advance through 3D additive processing, and while performing 3D additive processing, adjusts the tooth data according to the abnormal tooth data of the patient in the hospital intranet, establishes a tooth simulation model based on the adjusted tooth data, obtains the best state of the denture, and converts the data of the simulation model into coordinate data to perform subtractive processing on the tooth model blank through a 3D printer bed, so that the tooth model can be performed simultaneously in multiple steps compared with the traditional 3D printing and model casting methods, thereby significantly improving the preparation efficiency;

[0057] During the preparation process, the workpiece scanning module performs three-dimensional laser high-precision scanning on the manufactured tooth model, obtains the dimensional data of the prepared tooth model, and establishes a simulation model of the model for comparison with the original data. Based on the dimensional data of the difference point K1, the tooth model is repaired and remanufactured through additive and subtractive processing of the 3D printer to ensure the integrity and consistency of the manufactured tooth model, ensure that the manufactured teeth can meet the needs of tooth replacement, and ensure that the processing accuracy meets the requirements of use.

[0058] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The tooth preparation system based on AI medical imaging is characterized by: It includes a tooth data acquisition module, an AI data processing modeling module and a 3D printing preparation module. The tooth data acquisition module is established based on the hospital intranet system and is used to obtain tooth data; The AI ​​data processing modeling module is established based on a computer system and is used for data processing, calculation and simulation modeling; The 3D printing preparation module is established based on the 3D printer bed numerical control system and is used to process the tooth model.

2. The tooth preparation system based on AI medical imaging according to claim 1, characterized in that: The dental data acquisition module obtains the patient's dental data through AI medical imaging data and oral scan data, and connects with the hospital's internal data network through the Internet of Things to obtain the patient's dental data.

3. The tooth preparation system based on AI medical imaging according to claim 1, characterized in that: The 3D printer bed numerical control system comprises a 3D printer bed, an HMI main control numerical control module and a workpiece scanning module.

4. The preparation method proposed by the tooth preparation system based on AI medical imaging according to any one of claims 1 to 3, characterized in that: The following steps are involved: S1. Dental data collection: The patient's dental data is obtained through AI medical imaging data and oral scan data, and the patient's dental data is uploaded through the Internet of Things; S2. Tooth data preprocessing: uploading the acquired patient tooth data to the AI ​​data processing unit, which acquires a basic size sample of the tooth data and extracts size data of the basic size sample; S3, 3D additive embryo processing: convert the size data into coordinate data, upload the coordinate data to the HMI main control module, control the 3D printer bed for additive processing through the CNC system, and make the raw materials into a tooth model embryo through 3D additive processing; S4, data integration and calibration: obtaining tooth abnormality data and user oral data, integrating them into adjustment data, and recalibrating and checking the adjustment data that needs to be adjusted through the processing unit to form preparation molding data; S5, simulation model establishment: the preparation molding data is divided into tooth image data, gum image data and attached gingiva image data, corresponding regional simulation modules are formed according to different image data, and the simulation modules are integrated to form an overall tooth simulation model; S6, coordinate data acquisition: the processor calculates the size of the simulation module models in different regions, obtains the regional coordinate data of the simulation modules, and simultaneously forms the corresponding overall coordinate data according to the overall tooth simulation model, and obtains the coordinate size data required for subtractive processing according to the integration degree of the regional coordinate data and the overall coordinate data; S7, 3D subtractive processing: upload the subtractive processing coordinate size data to the HMI main control module, and control the subtractive processing module of the 3D printer bed through the numerical control system to perform subtractive processing on the tooth model blank made by additive manufacturing to make a tooth model; S8, data scanning calibration: perform three-dimensional laser high-precision scanning on the manufactured tooth model through the workpiece scanning module of the 3D printer bed to obtain the size data of the tooth model; S9, data verification and checking: the size data of the tooth model is divided into tooth model image data, gum model image data and attached gingiva model image data through a processor, and corresponding regional model modules are formed according to different image data; Compare the manufactured regional model module with the regional simulation module model, find out the difference point K1 between the two, check the size of the difference point K1, calculate the size data of the difference point K1, and obtain the size coordinates of the difference point K1; S10, repair and remanufacturing: repair and manufacture with additive and subtractive materials through a 3D printer according to the size coordinate data of the difference point K1; S11, data recalibration: repeat steps S8 and S9 until the difference point K1 is smaller than the predetermined threshold value K, and the calibration of the tooth model is completed; S12. Fine processing and improvement: Perform detailed processing on the calibrated tooth model to complete the preparation of the teeth.

5. The tooth preparation method based on AI medical imaging according to claim 4, characterized in that: The data involved in the dental data collection process in S1 includes one or more of the following: clinical test data, panoramic dental radiographs and cephalographic radiographs, oral scanning equipment, and dental models.

6. The tooth preparation method based on AI medical imaging according to claim 4, characterized in that: In the S4, the tooth feature points are judged by stomatology, and the tooth feature points include the long axis, mesiodistal direction and buccolingual direction of the teeth. The patient's tooth defect points are supplemented by stomatology, and discrete Gaussian curvature is used to reflect the degree of curvature of each vertex of the tooth, so as to describe the characteristics of the tooth surface and obtain tooth abnormality data and user oral data.

7. The tooth preparation method based on AI medical imaging according to claim 4, characterized in that: The difference point K1 size data in S9 has two types: "+" and "-", which correspond to subtractive processing and additive processing in 3D printing respectively; The coordinate reference point of the size coordinate of the difference point K1 is adjusted according to the "apex" of the difference point K1 of the tooth model.

8. The tooth preparation method based on AI medical imaging according to claim 4, characterized in that: The threshold value K in S11 is the difference percentage between the regional simulation module model and the regional model module model. If the difference percentage is lower than the threshold value K, the tooth model can be considered as a qualified tooth model.

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