WO2019132109A1 - 인공지능기술을 이용한 단계별 자동 교정 시스템 및 방법 - Google Patents
인공지능기술을 이용한 단계별 자동 교정 시스템 및 방법 Download PDFInfo
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- WO2019132109A1 WO2019132109A1 PCT/KR2018/001681 KR2018001681W WO2019132109A1 WO 2019132109 A1 WO2019132109 A1 WO 2019132109A1 KR 2018001681 W KR2018001681 W KR 2018001681W WO 2019132109 A1 WO2019132109 A1 WO 2019132109A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61C—DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
- A61C7/00—Orthodontics, i.e. obtaining or maintaining the desired position of teeth, e.g. by straightening, evening, regulating, separating, or by correcting malocclusions
- A61C7/002—Orthodontic computer assisted systems
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61C—DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
- A61C19/00—Dental auxiliary appliances
- A61C19/06—Implements for therapeutic treatment
- A61C19/063—Medicament applicators for teeth or gums, e.g. treatment with fluorides
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61C—DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
- A61C7/00—Orthodontics, i.e. obtaining or maintaining the desired position of teeth, e.g. by straightening, evening, regulating, separating, or by correcting malocclusions
- A61C7/08—Mouthpiece-type retainers or positioners, e.g. for both the lower and upper arch
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y80/00—Products made by additive manufacturing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61C—DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
- A61C7/00—Orthodontics, i.e. obtaining or maintaining the desired position of teeth, e.g. by straightening, evening, regulating, separating, or by correcting malocclusions
- A61C7/002—Orthodontic computer assisted systems
- A61C2007/004—Automatic construction of a set of axes for a tooth or a plurality of teeth
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
- G06F3/1203—Improving or facilitating administration, e.g. print management
- G06F3/1208—Improving or facilitating administration, e.g. print management resulting in improved quality of the output result, e.g. print layout, colours, workflows, print preview
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1223—Dedicated interfaces to print systems specifically adapted to use a particular technique
- G06F3/1237—Print job management
- G06F3/1244—Job translation or job parsing, e.g. page banding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1278—Dedicated interfaces to print systems specifically adapted to adopt a particular infrastructure
- G06F3/1285—Remote printer device, e.g. being remote from client or server
- G06F3/1288—Remote printer device, e.g. being remote from client or server in client-server-printer device configuration
Definitions
- the present invention relates to an automatic tooth movement system using a computer algorithm, and more particularly, to an automatic tooth movement system using a computer learning algorithm, which is an artificial intelligence technology,
- a computer learning algorithm which is an artificial intelligence technology
- a step-by-step automatic calibration system and method using an artificial intelligence technology that defines the patient's orthodontic standards and applies the automatic correction algorithm that meets the calibration recommendation or constraint in the orthodontic manual to reinforcement learning will be.
- the transparent calibrator generally scans a tooth pattern of a dental patient in 3D and then processes the 3D scanning data by a program for generating a calibration tooth to obtain a continuous digital
- the tooth calibration data is generated, a tooth mold is manufactured for each step of the generated tooth calibration data, and a set of transparent calibrators is prepared by vacuum-pressing the tooth mold to gradually move the teeth artificially.
- Artificial intelligence on the other hand, consists of a wide range of disciplines, including voice and visual perception, natural language processing, robotics, expert systems, reasoning, and learning.
- Artificial intelligence is a field of computer engineering and information technology that studies how to make computers, such as thinking, learning, and self-development, possible with human intelligence, by implementing "a system that behaves like a human being”.
- the object of the present invention is to solve the problems of the related art, and it is an object of the present invention to provide a method and apparatus for clustering or grouping orthodontic patients through non-guidance learning based on good orthodontic data excluding patient's personal information, And to provide a step-by-step automatic correction system and method using artificial intelligence technology that establishes a step-by-step tooth movement plan for tooth correction through repeated reinforcement learning that satisfies the tooth correction constraint presented in the calibration manual.
- Another object of the present invention is to provide a step-by-step automatic correction system and method using an artificial intelligence technology for improving the effect of correction and protecting the gums by coating the interior of the synthetic plate with transparent silicone to adhere smoothly to the teeth .
- Good orthodontic data excluding the patient's personal information, data obtained by clustering or grouping the orthodontic patients by non-guidance based on the orthodontic data, and orthodontic constraints presented by the orthodontic manual Database;
- An artificial intelligence calibration data generator for generating the predicted digital calibration data set into a plurality of unit digital calibration data sets
- the unit digital calibration data group includes a plurality of unit digital calibration data groups, and the unit digital calibration data groups are compared with each other to determine whether the unit calibration standard tooth data of the patient after wearing the transparent calibrator corresponding to the unit digital calibration data group coincides with the predicted digital calibration data set A determination unit;
- a positive score is given when the patient's unit calibration tooth condition data matches the predicted digital calibration data set through the artificial intelligence calibration data determination unit, and when the unit calibration tooth condition data of the patient and the predicted digital calibration data set do not match
- an artificial intelligence controller for assigning negative scores and storing the scores in the database.
- the artificial intelligence controller stores the patient's personal information as good tooth correction data in the database when the sum of the given scores is equal to or greater than a predetermined score.
- the artificial intelligence controller determines that the unit calibration tooth condition data of the patient and the predicted digital calibration data set do not match through the calibration data determination unit, And to generate a calibration data set.
- the artificial intelligence controller determines whether the unit calibration tooth condition data of the patient and the predicted digital calibration data set do not coincide with each other through the calibration data determination unit and the difference between the unit calibration tooth condition data of the patient and the predicted digital calibration data set, And generating a new predictive digital calibration data set in response to the received data, and outputting the patient's age, gum status, or cavity information.
- a three-dimensional printing machine for generating and outputting a tooth calibration model using the digital calibration data
- a vacuum molding machine for vacuum-pressing a transparent synthetic resin plate coated with transparent silicone to the generated tooth calibration model to produce a transparent calibrator
- the coater comprises:
- a communication unit for receiving patient information from the artificial intelligence controller
- a fluorine solution storage part for storing a fluorine solution
- a hexamidine solution reservoir storing a hexamidine solution
- a hexamethine dispenser for spraying a hexamethine solution in the hexamethine solution reservoir
- the method comprising the steps of: receiving the patient's age, gum status or cavity information through the communication unit; and controlling the transparent calibrator to coat the hexamethine solution when the patient has gum disease, And a coating control unit for controlling the coating of the fluorine solution.
- the coating control unit receives information on the age, gum status, or cavity information of the patient through the communication unit and adjusts the coating amount of the hexamethine solution to the transparent calibrator according to the change in the gum disease information of the patient And controlling the coating amount of the fluorine solution to be adjusted by controlling the amount of the fluorine solution in accordance with the change in the cavity information of the patient.
- the coating control unit adjusts the amount of the fluorine solution in the transparent calibrator and then controls the amount of the hexamidine solution on the gum contact area of the transparent calibrator .
- the amount of the hexamethine solution is controlled to be coated on the transparent calibrator,
- the amount of the hexamethine solution is increased and coated on the transparent calibrator when it is determined that the gum disease of the patient is exacerbated.
- the coating control unit controls the transparent calibrator to coat the hexamethine solution when the patient is over 40 years of age and controls the transparent calibrator to coat the fluorine solution when the patient is under 40 years of age, do.
- the artificial intelligence controller may provide the patient's unit calibration tooth condition data and the predictive digital calibration data set to the dental terminal when the patient's unit calibration tooth condition data and the predictive digital calibration data set do not match through the calibration data determination unit, And receives control data.
- the artificial intelligence controller determines whether the unit calibration tooth condition data of the patient and the predicted digital calibration data set do not match with each other through the calibration data determination unit and outputs the newly generated prediction data corresponding to the difference between the patient's unit calibration tooth condition data and the predicted digital calibration data set
- a digital calibration data set is provided to the dental terminal, and control data of a doctor is received from the dental terminal.
- the digital calibration data is newly generated corresponding to the movement amount when the patient's unit calibration tooth condition data has moved more than the predicted digital calibration data set.
- the server refers to the determined group of data to incrementally move a tooth requiring calibration to generate a predictive digital correction tooth data set
- the server transmits the calibrating-processed digital orthodontic tooth data set to a three-dimensional printer, and the three-dimensional printing machine generates and outputs a tooth calibration model;
- the method comprises:
- the coater receives the patient's age, gum status or cavitation information from the server through the communication unit;
- the server adjusts the amount of fluorine solution in the transparent calibrator and then coating the transparent calibrator by adjusting the amount of the hexamidine solution in the contact area of the gum .
- the orthodontic patients are clustered or grouped by non-guidance based on the good orthodontic data excluding the patient's personal information, and the grouped data and the orthodontic restraint conditions shown in the orthodontic textbook It is possible to provide a step-by-step automatic correction system and method using an artificial intelligence technology that establishes a tooth movement plan for a tooth correction step by step through repetitive reinforcement learning that satisfies it.
- FIG. 1 is a diagram illustrating a step-by-step automatic calibration system using an artificial intelligence technology according to an embodiment of the present invention.
- FIG. 2 is a view showing the coater of Fig.
- FIG. 3 is a diagram illustrating a process of learning in a step-by-step automatic calibration method using artificial intelligence technology according to an embodiment of the present invention.
- FIG. 4 is a diagram illustrating a process of generating new predictive digital calibration data in a step-by-step automatic calibration method using artificial intelligence technology according to an embodiment of the present invention.
- FIG. 5 is a view showing in detail the step of generating the corrected tooth data of FIG.
- FIG. 6 is a diagram illustrating a process of comparing calibration results after stepwise calibration in a step-by-step automatic calibration method using artificial intelligence technology according to an embodiment of the present invention and generating calibration data again.
- the server described below can be implemented by a processor and a memory.
- FIG. 1 is a diagram illustrating a step-by-step automatic calibration system using an artificial intelligence technology according to an embodiment of the present invention.
- a step-by-step automatic calibration system using an artificial intelligence technology includes:
- Good orthodontic data excluding the patient's personal information, data obtained by clustering or grouping the orthodontic patients by non-guidance based on the orthodontic data, and orthodontic constraints presented by the orthodontic manual A database 140;
- An artificial intelligence calibration data generator 110 for generating a tooth data set and subdividing the predictive digital calibration data set into unit digital calibration data sets;
- the unit digital calibration data group includes a plurality of unit digital calibration data groups, and the unit digital calibration data groups are compared with each other to determine whether the unit calibration standard tooth data of the patient after wearing the transparent calibrator corresponding to the unit digital calibration data group coincides with the predicted digital calibration data set A determination unit 120;
- a positive score is given when the unit calibration tooth condition data of the patient and the predicted digital calibration data set coincide with each other through the artificial intelligence calibration data determination unit 120 and the unit calibration tooth condition data of the patient and the predictive digital calibration data set And an artificial intelligence controller 130 for assigning a negative score to the database and storing the same in the database.
- the artificial intelligence controller 130 stores the patient's personal information in the database 140 as good teeth correction data when the sum of the given scores is equal to or greater than a predetermined score.
- the artificial intelligence controller 140 determines the unit calibration tooth condition data of the patient and the predicted digital calibration data And to generate a new predicted digital calibration data set corresponding to the set difference.
- the artificial intelligence controller 130 may compare the unit calibration tooth condition data of the patient and the predictive digital calibration data Sets a new predictive digital calibration data set corresponding to the set difference and physician's control data, and outputs the age, gum state, or cavity information of the patient.
- the coater 500 may include a coater
- the control unit controls to receive the patient's age, gum status, or cavity information through the communication unit 510 and to coat the transparent calibrator with a hexamethine solution when the patient has gum disease, And a coating control unit 520 for controlling the transparent calibrator to coat the fluorine solution.
- the coating control unit 520 receives the change information of the patient's age, gum status or cavity information through the communication unit, adjusts the amount of the hexamethine solution in the transparent calibrator according to the change in the gum disease information of the patient, And controls the amount of the fluorine solution to be controlled by coating the transparent calibrator according to the change in cavity information of the patient.
- the coating control unit 520 controls the amount of the fluorine solution in the transparent calibrator and controls the amount of the hexamidine solution in the transparent calibrator, Can be coated.
- the amount of the hexamethine solution is controlled to be coated on the transparent calibrator,
- the coating control unit 520 controls the transparent calibrator to coat the hexamethine solution when the patient is over 40 years of age and controls the transparent calibrator to coat the fluorine solution when the patient is under 40 years of age .
- fluoride may be coated on teeth to prevent dental caries and tooth decay.
- fluoride coatings and autofluorescence coatings for coating teeth with fluorine there are expert fluoride coatings and autofluorescence coatings for coating teeth with fluorine, and fluorides for application include fluoride, fluoride and acid fluoride phosphate.
- the artificial intelligence controller 130 determines that the unit calibration tooth condition data of the patient and the predicted digital calibration data set To the dental terminal 200 and to receive the control data of the doctor from the dental terminal 200.
- the dental terminal 200 may be a computer
- new digital calibration data can be generated corresponding to the movement amount.
- the manner in which the artificial intelligence correction data determination unit 120 assigns a positive score or a negative score may be variously embodied.
- a score can be given by comparing the state of the scanned teeth. That is, the compensation score can be given according to the contact surface of the tooth or the bite problem.
- a compensation score may be given according to the occlusal curve.
- the maxilla Smile Line
- the mandible's anterior incisal edge Curve of incisal edge
- the sagittal plane curvature of the curve Curve of Spee Curve of Wilson, etc.
- compensating scores by tooth movement plasticity and patient pain feedback can be considered.
- the tissue is deformed so that the gingiva initially hardened when force is applied to the tooth, the elasticity of the gingle is shifted beyond the elastic limit with time, and the tissue is deformed to facilitate movement, the deformation degree of the fiber tissue is expected to be different by sex and age do.
- the outlier can be reached in a relatively short step.
- this step may be divided into a given allowance step and gradually moving within a certain level may increase the satisfaction of the patient.
- the above-mentioned compensation factors may be weighted, and the compensation points may be calculated comprehensively.
- FIG. 3 is a diagram illustrating a process of learning in a step-by-step automatic calibration method using artificial intelligence technology according to an embodiment of the present invention.
- the server 10 using artificial intelligence technology reads a good practice record in which teeth correction is performed well (S21).
- the server 10 using the artificial intelligence technology has the quantitative characteristics of the teeth arrangement defined in the patient's sex / age / (race) / height / weight / orthodontics (for example, tooth array arch, molar distance, molar teeth, Etc.) are defined as d, replaced with a feature vector, and placed in the d-dimensional space.
- n is the total number of good calibration data previously acquired.
- PCA Principal Component Analysis
- DBSCAN hierarchical cluster
- This grouping allows the patient to know what type of group they are based on newly entered patient data.
- the pre-existing constraints and the primary orthodontic plan can be established with reference to the already completed good orthodontic data.
- the server 10 using the artificial intelligence technology determines the number of steps necessary for the orthodontic treatment of the patient group by referring to the calibration data of the good group (S23).
- the server 10 using the artificial intelligence technology sets up the three-dimensional tooth model from the first step and stores it in the database 140 (S24).
- the server 10 using the artificial intelligence technology determines tooth movement (S25).
- the algorithm of the server 10 using the artificial intelligence technology at each step may attempt various movements for tooth correction.
- the server 10 using the artificial intelligence technology examines the restraint condition for the tooth movement of the step (S26).
- each tooth movement determines whether it meets the constraints or recommendations or guideline suggested by Orthodontics.
- the server 10 using artificial intelligence technology determines whether the predictive digital calibration data set is completed (S27).
- the server 10 using the artificial intelligence technology switches to the next step and repeats the process from the step of setting up the three-dimensional tooth model (S29).
- the server 10 using the artificial intelligence technology stores the tooth movement information and the target tooth model information in the database as a best model for each group before the patient's correction (step S28).
- calibration data of the best model is stored for various tooth models.
- the calibration data generation process of the best model may be performed by the artificial intelligence correction data generation unit 110 of the server 10.
- FIG. 4 is a diagram illustrating a process of generating new predictive digital calibration data in a step-by-step automatic calibration method using artificial intelligence technology according to an embodiment of the present invention.
- the physician in charge of the hospital scans the oral cavity of the patient using the oral scanner to acquire the tooth data in the current state (S110).
- the doctor uses the scanned tooth data to perform a calibration process using the dental terminal to generate corrected tooth data (S120).
- the server 10 performs calibration processing using the scanned tooth data using the artificial intelligence technology to generate corrected tooth data (S120).
- the server 10 receives the calibrated data from the dental terminal 200 and stores it in the database 140 or stores the calibrated tooth data generated by the server in the database 140.
- the server 10 transmits the patient's corrected tooth correction data to the three-dimensional printer 300, and the three-dimensional printer 300 generates a tooth correction model (S130).
- the support attached to the created orthodontic model is firstly removed with strong water pressure in the washer. Then place it in a hot oven to remove the supporters attached to the orthodontic model secondarily. Then, the orthodontic model is perfectly clean.
- the tooth calibration model and the plate are mounted on the vacuum molding machine 400 (S140), the transparent synthetic resin plate is heated on the generated tooth calibration model through the vacuum molding machine 400 (S150) (S160). At this time, if necessary, adjust the end of the transparent bracket with scissors so that it is convenient to wear.
- the transparent correction device is coated with the transparent silicone on the area where the tooth is contacted with the gum (S170).
- the silicon coating process can be omitted if necessary.
- the transparent calibrator is put into the coater and the coater is operated.
- the coater 500 receives the patient's age, gum status, or cavity information from the server 10 via the communication unit 510.
- control unit 520 determines whether the patient has gum disease (S180).
- the coating control unit 520 of the coater 500 controls the transparent calibrator to coat the hexamidine solution according to the change in the gum state of the patient, and the hexamidine jetting unit 540 controls the coating A methine solution is injected (S190). For example, if the patient's gum status improves, the coating control unit 520 reduces the amount of the hexamethine solution to allow coating, and if the gum condition of the patient worsens, the coating control unit 520 controls the concentration of the hexamethine solution Increase the amount to allow coating.
- the coating control unit 520 determines whether the patient has cavities (S200).
- the coating control unit 520 controls the transparent correcting apparatus to coat the fluorine solution according to the change in the cavity state of the patient, and the fluorine solution injector 530 injects the fluorine solution (S210). For example, when the laminating state of the patient is improved, the coating control unit 520 reduces the amount of the fluorine solution to allow the coating to be performed, and when the cavity state of the patient is deteriorated, the coating control unit 520 controls the amount of the fluorine solution To increase the coating.
- the coating controller 520 determines whether the patient is over 40 years of age (S220).
- the coating control unit 520 of the coater controls the hexamethine solution to be coated on the transparent calibrator, and the hexamidine jetting unit 540 injects the hexamidine solution (S230). This can be a preventive effect of gum disease.
- control unit 520 controls the transparent calibrator to coat the fluorine solution, and the fluorine solution injector 530 injects the fluorine solution (S210). This can be a preventive effect of tooth decay.
- This process is made up of a predetermined number of sets and is made up of about five sets.
- a transparent calibrator may be formed by vacuum-pressing a transparent synthetic resin plate coated with transparent silicon on the generated orthodontic model through a vacuum molding machine 400.
- the transparent silicone coating process is omitted.
- the coating controller 520 controls the amount of the fluorine solution to be applied to the transparent calibrator, and then measures the amount of the hexamidine solution at the contact portion of the gum with the transparent calibrator So that the coating can be adjusted.
- FIG. 5 is a view showing in detail the step of generating the corrected tooth data of FIG.
- the server 10 determines the quantitative characteristics (e.g., teeth array, distance between molars, and the like) of a tooth arrangement defined in the sex / age / race / A correlation distance between the molar teeth and the front teeth, and determines which group the current state data of the patient belongs to (S121).
- the quantitative characteristics e.g., teeth array, distance between molars, and the like
- the server 10 determines the number of steps necessary for the orthodontic treatment in order to move the tooth from the current state to the target state (S122) by referring to the good orthodontic data of the best model of the group to which the patient belongs.
- the server 10 sets up the three-dimensional tooth model from the first step and stores it in the database 140 (S123).
- the server 10 makes a tooth movement decision (S124).
- the algorithm of the server 10 at each step may attempt various movements for tooth correction.
- the server 10 reviews constraint conditions for tooth movement of the step (S125). That is, each tooth movement determines whether it meets the constraints or recommendations or guideline suggested by Orthodontics.
- the server 10 determines 126 whether the predicted digital tooth data set is complete.
- the server 10 switches to the next step and repeats the process from the step of setting the three-dimensional tooth model (S128).
- the server 10 stores the tooth movement information and the target tooth model information in the database in step S127 before the calibration of the patient, (S130).
- the patient wears a transparent brace step by step at intervals of about one to two weeks.
- FIG. 6 is a diagram illustrating a process of comparing calibration results after stepwise calibration in a step-by-step automatic calibration method using artificial intelligence technology according to an embodiment of the present invention and generating calibration data again.
- the doctor scans the patient's oral condition with a scanner and transmits the scanned data to the server 10 (S510), and the server 10 reads the predictive digital calibration data stored in the database 140 (S520 ).
- the server 10 compares the scanned tooth data with the predictive digital calibration data stored in the database 140 (S530).
- the AI controller 130 of the server 10 determines whether or not three or more (S560).
- the artificial intelligence controller 130 recognizes that the tooth movement speed is higher than normal when the patient's unit calibration tooth condition data has shifted more than the predicted digital calibration data set and newly generates corresponding to the movement amount And generates digital calibration data (S540).
- the data generation control unit 130 determines whether the unit calibration tooth condition data of the patient and the predicted digital calibration data set are not coincident with each other three times or more through the calibration data determination unit 120, A newly generated predicted digital calibration data set corresponding to the difference of the predicted digital calibration data set may be provided to the dental terminal and the physician's control data may be received from the dental terminal.
- the doctor compares the previously scanned oral data with the predicted digital calibration data stored in the database 140. If the comparison result does not match, the tooth movement is not as expected, so the artificial intelligence controller 130 may be transmitted to generate a new predictive digital calibration data set.
- the data generation control unit 130 gives a penalty point and produces a set of transparent calibrators in the next step using the predictive digital calibration data stored in advance (S570).
- the predicted digital data may reflect the difference between the patient's unit calibration tooth condition data and the predicted digital calibration data set as needed.
- the artificial intelligence controller 130 of the server 10 gives a shop, A set of transparent calibrators of the next stage is prepared as the predicted digital calibration data stored (S550). If necessary, the artificial intelligence controller 130 of the server 10 provides the dental terminal 200 with the fact that the unit calibration tooth condition data of the patient and the predicted digital calibration data set match, so that the doctor can recognize the data.
- a store and a penalty point are given in the course of the patient's treatment, and the server 10 stores the patient's personal information as a good tooth correction data in the database 140 if the store is a certain score or more.
- the server 10 may provide the target tooth condition from the current tooth data with reference to the best model.
- a final calibration image can also be generated by an algorithm.
- the patient can see the post-completion status before starting the treatment and start treatment.
- the orthodontic patients are clustered or grouped by non-guidance based on the good orthodontic data excluding the patient's personal information, and the grouped data and the orthodontic restraint conditions shown in the orthodontic textbook
- the repetitive reinforcement learning that satisfies can be used to establish a step-by-step tooth movement plan for tooth correction.
- the inside of the synthetic plate is coated with transparent silicone so as to be gently adhered to the teeth, thereby enhancing the correction effect and protecting the gums.
- fluoride may be applied inside the synthetic plate to prevent tooth decay.
- hexamethine can be applied inside the synthetic plate to prevent gum inflammation.
Abstract
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Claims (9)
- 환자의 개인정보가 제외된 양호한 치아교정자료, 상기 치아교정자료를 기반으로 비지도학습을 통해 치아교정환자를 클러스터링 또는 소정 개수로 그룹화한 데이터 및 치아교정 교본에서 제시한 치아교정 구속조건을 저장하는 데이터베이스;치과 환자의 치아상태를 3D 스캐닝한 치아데이터에 대하여 상기 데이터베이스의 그룹화한 데이터중 어느 그룹에 속하는지를 결정하고, 결정된 그룹의 데이터를 참조하여 교정이 필요한 치아를 점진적으로 이동시켜 예측 디지털 교정 치아 데이터 세트를 생성하고, 상기 예측 디지털 교정데이터 세트를 단위디지털 교정 데이터 군으로 세분화하는 인공지능 교정데이터 생성부;상기 단위 디지털 교정 데이터 군에 대응되어 제작된 투명교정기의 착용 후의 환자의 단위 교정기초 치아 데이터와 상기 예측 디지털 교정 치아 데이터 세트가 일치하는지 여부를 상기 단위 디지털 교정 데이터 군 단위마다 비교하는 인공지능 교정데이터 판단부;상기 인공지능 교정 데이터 판단부를 통해 환자의 단위 교정 치아상태 데이터와 예측디지털 교정 데이터 세트가 일치하는 경우 플러스 점수를 부여하고, 상기 환자의 단위 교정 치아상태 데이터와 예측디지털 교정 데이터 세트가 일치하지 않는 경우 마이너스 점수를 부여하여 상기 데이터베이스에 저장하는 인공지능 제어부를 포함하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 제1항에 있어서,상기 인공지능 제어부는 부여된 점수의 합계가 일정한 점수 이상이 되면, 환자의 개인정보를 제외하고 양호한 치아교정자료로서 상기 데이터베이스에 저장하는 것을 특징으로 하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 제2항에 있어서,상기 디지털 교정데이터를 이용하여 치아교정 모델을 생성출력하는 3차원 인쇄기;상기 생성된 치아교정 모델에 투명실리콘이 코팅된 투명합성수지 플레이트를 진공압착하여 투명 교정기를 생성하는 진공 성형기;상기 진공성형기에서 생성된 투명 교정기에 불소또는 헥사메딘을 코팅하는 코팅기를 더 포함하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 제3항에 있어서,상기 코팅기는,상기 인공지능 제어부로부터 환자의 정보를 수신하는 통신부;불소용액을 저장하는 불소용액 저장부;헥사메딘용액을 저장하는 헥사메딘 용액 저장부;상기 불소용액 저장부의 불소용액을 분사하는 불소용액 분사부상기 헥사메딘 용액저장부의 헥사메딘 용액을 분사하기 위한 헥사메딘 분사부;상기 환자의 나이, 잇몸상태 또는 충치정보를 상기 통신부를 통해 수신하고, 상기환자가 잇몸 질환이 있는 경우 상기 투명교정기에 헥사메딘 용액을 코팅하도록 제어하고, 상기 환자가 충치가 있는 경우 상기 투명교정기에 불소용액을 코팅하도록 제어하는 코팅 제어부를 포함하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 제4항에 있어서,상기 코팅 제어부는 상기 환자의 나이, 잇몸상태 또는 충치정보의 변화정보를 상기 통신부를 통해 수신하고, 상기 환자의 잇몸 질환 정보의 변동에 따라 상기 투명교정기에 헥사메딘 용액의 양을 조절하여 코팅하도록 제어하고, 상기 환자의 충치정보 변동에 따라 상기 투명교정기에 불소용액의 양을 조절하여 코팅하도록 제어하는 것을 특징으로 하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 제5항에 있어서,상기 코팅 제어부는 상기 환자에게 충치와 잇몸질환이 모두 있는 경우, 상기 투명교정기에 불소용액의 양을 조절하여 코팅한 후, 상기 투명교정기에 잇몸 접촉부위에 헥사메딘 용액의 양을 조절하여 코팅하도록 하는 것을 특징으로 하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 제6항에 있어서,상기 환자의 잇몸 질환이 호전된다고 판단되는 경우, 상기 투명교정기에 헥사메딘 용액의 양을 감소하여 코팅하도록 제어하고,상기 환자의 잇몸 질환이 악화된다고 판단되는 경우, 상기 투명교정기에 헥사메딘 용액의 양을 증가하여 코팅하도록 제어하고,상기 환자의 충치가 호전된다고 판단되는 경우, 상기 투명교정기에 불소 용액의 양을 감소하여 코팅하도록 하고,상기 환자의 충치가 악화된다고 판단되는 경우, 상기 투명교정기에 불소 용액의 양을 증가시켜 코팅하도록 하는 것을 특징으로 하는 인공지능기술을 이용한 단계별 자동 교정 시스템.
- 구강 스캐너를 이용하여 환자의 치아 상태를 스캔하는 단계;서버가 상기 스캔된 치아 데이터에 대하여 상기 데이터베이스의 그룹화한 데이터중 어느 그룹에 속하는지를 결정하는 단계;상기 서버가 상기 결정된 그룹의 데이터를 참조하여 교정이 필요한 치아를 점진적으로 이동시켜 예측 디지털 교정 치아 데이터 세트를 생성하는 단계;상기 서버가 환자의 교정 처리된 상기 디지털 교정 치아 데이터 세트를 3차원 인쇄기에 송신하고, 상기 3차원 인쇄기가 치아 교정모델을 생성하여 출력하는 단계;진공 성형기를 통해 상기 생성된 치아교정 모델에 투명합성수지 플레이트를 진공압착하여 투명 교정기를 생성하는 단계를 포함하는 인공지능기술을 이용한 단계별 자동 교정 방법.
- 코팅기가 상기 환자의 나이, 잇몸상태 또는 충치 정보를 상기 서버로부터 통신부를 통해 수신하는 단계;상기 환자가 잇몸질환이 있는 경우 상기코팅기가 상기 투명교정기에 헥사메딘 용액을 코팅하는 단계;상기 환자가 충치가 있는 경우 상기 코팅기가 상기 투명교정기에 불소용액을 코팅하는 단계를 더 포함하고,상기 환자의 잇몸 질환이 호전된다고 판단되는 경우, 상기 투명교정기에 헥사메딘 용액의 양을 감소하여 코팅하도록 제어하고,상기 환자의 잇몸 질환이 악화된다고 판단되는 경우, 상기 투명교정기에 헥사메딘 용액의 양을 증가하여 코팅하도록 제어하고,상기 환자의 충치가 호전된다고 판단되는 경우, 상기 투명교정기에 불소 용액의 양을 감소하여 코팅하도록 하고,상기 환자의 충치가 악화된다고 판단되는 경우, 상기 투명교정기에 불소 용액의 양을 증가시켜 코팅하도록 하는 것을 특징으로 하는 인공지능기술을 이용한 단계별 자동 교정 방법.
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US20150006465A1 (en) * | 2010-03-17 | 2015-01-01 | ClearCorrect Holdings, Inc. | Methods and systems for employing artificial intelligence in automated orthodontic diagnosis & treatment planning |
KR101212556B1 (ko) * | 2012-01-31 | 2012-12-14 | 주식회사 인피니트헬스케어 | 치아 교정용 고정체 위치 결정 방법 및 그 장치 |
KR101200014B1 (ko) * | 2012-03-19 | 2012-11-12 | 주식회사 리얼오쏘 | 투명 교정기용 교정 데이터 제공 장치 및 방법 |
KR101527953B1 (ko) * | 2015-03-05 | 2015-06-10 | 강제훈 | 3차원 프린터를 이용한 치아 이동 시스템 및 방법 |
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WO2023017401A1 (en) * | 2021-08-12 | 2023-02-16 | 3M Innovative Properties Company | Deep learning for generating intermediate orthodontic aligner stages |
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KR101930062B1 (ko) | 2019-03-14 |
US20190192258A1 (en) | 2019-06-27 |
JP2019115652A (ja) | 2019-07-18 |
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