KR20230161625A - A computer program for executing a 3D prosthesis fabrication service for dental restorations - Google Patents

Abstract

A computer program for performing a 3D prosthesis fabrication service for dental restoration is provided. A computer program for executing a 3D prosthesis manufacturing service for tooth restoration according to an embodiment of the present invention includes a function of acquiring a 3D modeling image scanned of a patient's oral cavity; A generator that generates a fake image based on the 3D modeling image; and a function for generating a 2D dental prosthesis design using a first artificial intelligence model including a discriminator that compares the fake image and the real image to determine whether the fake image is authentic. and a function of generating the dental prosthesis model using a second artificial intelligence model based on the 2D dental prosthesis design.

Description

A computer program for executing a 3D prosthesis fabrication service for dental restorations}

The present invention relates to a computer program for executing a dental prosthesis manufacturing service. More specifically, it is about a computer program for running a 3D prosthesis manufacturing service for dental restoration that can design and manufacture dental prosthesis more quickly and easily based on artificial intelligence.

DSO (Dental service organization) is leading the growth of the global dental market by leading the popularization of expensive dental procedures (aesthetic treatment, implants, orthodontics) through corporate operation through franchising of dental hospitals.

In particular, the growth of DSO has recently begun in earnest due to the inflow of investment capital. At the same time, in most developed countries, the digitalization of dental treatment is accelerating and the related market is growing rapidly due to the shortage and high wages of skilled dentists, dental hygienists, and technicians. I'm doing it.

However, compared to the growth rate of dentists and dental hospitals, the growth of actual prosthesis manufacturing sites is still slow. For example, in dental labs that design and manufacture prosthetics, manufacturing prosthetics still takes a considerable amount of time due to a lack of skilled manpower.

To solve this problem, various methods have been attempted, but no effective alternative has yet been developed.

For example, 3Shape proposed a method to quickly design a prosthesis by setting a default model through a software tool called Autoworkflow, but this method is applicable only to orthotopic and ideal tooth structures, making it difficult to use in actual clinical practice.

As another example, a method of performing CAD design of a prosthesis through a deep learning-based artificial intelligence model has been proposed, but it is still at the level of implementing 2D objects and is not technologically mature enough to be directly applied in actual dental settings.

The technical problem to be solved through embodiments of the present invention is to provide a computer program for executing a 3D prosthesis manufacturing service for dental restoration that can reduce the manufacturing time and cost of prosthetic doors by automating the CAD design of dental prosthesis. .

Another technical problem to be solved through embodiments of the present invention is to perform CAD design of dental prosthesis based on artificial intelligence, and provide a 3D prosthesis manufacturing service for tooth restoration that can be implemented up to 3D clinical teeth and can also be applied to special tooth designs. It provides a computer program to run.

The technical problems of the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below.

A computer program for executing a 3D prosthesis manufacturing service for tooth restoration according to an embodiment of the present invention to solve the problems described above includes a function of acquiring a 3D modeling image scanned of the patient's oral cavity; A generator that generates a fake image based on the 3D modeling image; and a function for generating a 2D dental prosthesis design using a first artificial intelligence model including a discriminator that compares the fake image and the real image to determine whether the fake image is authentic. and a function of generating the dental prosthesis model using a second artificial intelligence model based on the 2D dental prosthesis design.

As an example, the generator may include a u-net image auto encoder.

As an example, the discriminator may be a convolutional neural network (CNN)-based model.

As an embodiment, the second artificial intelligence model may be a model based on an auto encoder, brancher, and neural implicit function.

As an embodiment, the post-correction function may include a function of setting a margin line for the dental prosthesis model, and a function of post-correction of the dental prosthesis model based on the margin line.

According to the above-described embodiments of the present invention, the manufacturing time and cost of the prosthetic door can be reduced by automating the CAD design of the dental prosthesis.

In addition, a CAD design of dental prosthesis is performed based on artificial intelligence, and a dental prosthesis design and manufacturing solution that can be implemented up to 3D clinical teeth and can also be applied to special tooth design can be provided.

In addition, it may be possible to implement high-quality dental prosthesis that meets dental design requirements.

1 is a flowchart showing a method of manufacturing a dental prosthesis according to an embodiment of the present invention.
FIG. 2 is a diagram for further explaining the embodiment of FIG. 1.
FIG. 3 is a flowchart illustrating an embodiment of step S200 of FIG. 1 in more detail.
Figures 4 to 6 are diagrams to further explain the embodiment of Figure 3.
FIG. 7 is a flowchart illustrating an embodiment of step S300 of FIG. 1 in more detail.
FIG. 8 is a diagram for further explaining the embodiment of FIG. 7.
FIG. 9 is a diagram illustrating an exemplary hardware configuration of a computing device in which various embodiments of the present invention can be implemented.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the technical idea of the present invention is not limited to the following embodiments and may be implemented in various different forms. The following examples are merely intended to complete the technical idea of the present invention and to be used in the technical field to which the present invention pertains. It is provided to fully inform those skilled in the art of the scope of the present invention, and the technical idea of the present invention is only defined by the scope of the claims.

When adding reference numerals to components in each drawing, it should be noted that identical components are given the same reference numerals as much as possible even if they are shown in different drawings. Additionally, in describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description will be omitted.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings that can be commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless clearly specifically defined. The terminology used herein is for describing embodiments and is not intended to limit the invention. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context.

Additionally, when describing the components of the present invention, terms such as first, second, A, B, (a), and (b) may be used. These terms are only used to distinguish the component from other components, and the nature, sequence, or order of the component is not limited by the term. When a component is described as being “connected,” “coupled,” or “connected” to another component, that component may be directly connected or connected to that other component, but there is another component between each component. It will be understood that elements may be “connected,” “combined,” or “connected.”

Hereinafter, several embodiments of the present invention will be described in detail with reference to the attached drawings.

1 is a flowchart showing a method of manufacturing a dental prosthesis according to an embodiment of the present invention. The dental prosthesis manufacturing method of FIG. 1 may be performed by the computing device 500, which will be described later with reference to FIG. 15 . Therefore, if the performing entity is not specified in the following steps, it is assumed that the performing entity is the computing device 500.

In step S100, a 3D modeling image of the patient's oral cavity is obtained.

In step S200, a dental prosthesis model corresponding to the 3D modeling image is designed using an artificial intelligence model machine-learned based on the 3D modeling image.

In step S300, the dental prosthesis model is post-edited using web CAD.

In step S400, a dental prosthesis corresponding to the post-corrected dental prosthesis model is output.

Refer to FIG. 2 for further explanation of this embodiment.

FIG. 2 is a diagram for further explaining the embodiment of FIG. 1. Referring to Figure 2, the method of manufacturing a dental prosthesis is performed through four steps (10, 20, 30, and 40).

In the first process 10, a 3D modeling image obtained by scanning the patient's oral cavity is obtained. The 3D modeling image may be acquired through a hospital terminal or a doctor's user terminal.

In the second process (20), a dental prosthesis model is automatically designed based on the 3D modeling image obtained by scanning the patient's oral cavity.

In the third process 30, post-editing work is performed on the automatically designed dental prosthesis model using web CAD.

In the fourth process 40, an actual dental prosthesis product is printed based on the post-corrected dental prosthesis model using a 3D printer or milling machine.

FIG. 3 is a flowchart illustrating an embodiment of step S200 of FIG. 1 in more detail.

In step S210, a 2D dental prosthesis design is created using the first artificial intelligence model based on the 3D modeling image.

In step S220, a dental prosthesis model is created using a second artificial intelligence model based on the generated 2D dental prosthesis design.

Refer to FIGS. 4 to 6 for detailed description of this embodiment.

Figures 4 to 6 are diagrams to further explain the embodiment of Figure 3.

First, referring to FIG. 4, a 2D model is rendered based on the 3D modeling image in (a) of FIG. 4. And, in Figure 4(b), an intermediate result is generated from the 2D model using the first artificial intelligence model machine-learned using 2D learning data. And, in Figure 4(c), a dental prosthesis model is created from the intermediate result using a second artificial intelligence model machine-learned using 2D and 3D learning data. Lastly, the dental prosthesis model created in (d) of Figure 4 is provided as a webcad module.

Meanwhile, the first artificial intelligence model may be a model created based on GAN (Genarative Adversarial Network). For a detailed explanation, refer to FIG. 5.

Figure 5 is a model conceptually representing the first artificial intelligence model. Referring to Figure 5, the first artificial intelligence model includes a generator and a discriminator.

The generator is a module that generates virtual 2D data and generates multiple fake images based on input data (50).

The discriminator compares the previously generated fake image with the real image (60) and determines whether the fake image is genuine (70).

In one embodiment, the generator may include a u-net image auto encoder.

As an example, the discriminator may be a model based on a convolutional neural network (CNN).

The first artificial intelligence model is based on the GAN model implemented through adversarial learning between the generator and discriminator. Since the specific details of the concept and structure of the GAN model are widely known in the technical field, their description is omitted here.

Meanwhile, the second artificial intelligence model, as shown in FIG. 6, may be a model based on an auto encoder, brancher, and neural implicit function.

FIG. 7 is a flowchart illustrating an embodiment of step S300 of FIG. 1 in more detail.

In step S310, a margin line for the dental prosthesis model is set.

In step S320, the dental prosthesis model is post-corrected based on the margin line.

For further explanation, please refer to FIG. 8.

The left image 80 of FIG. 8 shows a margin line for a dental prosthesis model set according to the judgment of a user, for example, a dental technician.

The right image 90 of FIG. 8 shows the final modification (post-correction) of the dental prosthesis model on WebCAD according to the user's judgment based on the explained margin line.

In the case of the present invention, it can be applied to the production of prosthesis for a bridge case in addition to the production of prosthesis for a single crown.

Specifically, it is a tooth selection program for bridge design. Once the design target tooth is selected, the information is processed into a form that can be input into a deep learning-based artificial intelligence model.

Afterwards, the first artificial intelligence model and the second artificial intelligence model described above are modified and applied to the prosthesis manufacturing algorithm.

Specifically, for the first artificial intelligence model, additional information can be input and the first artificial intelligence model is modified and learned in a form so that it can be processed appropriately.

Next, for the second artificial intelligence model, additional information is input, and the second artificial intelligence model is modified and trained in a way to prevent this information from being damaged during calculation.

According to this method, the prosthesis manufacturing method designed for existing single crowns can be easily expanded to bridge cases.

According to the embodiments of the invention described above, the manufacturing time and cost of the prosthetic door can be reduced by automating the CAD design of the dental prosthesis. In addition, a CAD design of dental prosthesis is performed based on artificial intelligence, and a dental prosthesis design and manufacturing solution that can be implemented up to 3D clinical teeth and can also be applied to special tooth design can be provided. In addition, it may be possible to implement high-quality dental prosthesis that meets dental design requirements.

Hereinafter, an exemplary computing device 500 in which a method for manufacturing a dental prosthesis according to various embodiments of the present invention is implemented will be described with reference to FIG. 9 .

9 is an exemplary hardware configuration diagram showing the computing device 500.

As shown in FIG. 9, the computing device 500 loads one or more processors 510, a bus 550, a communication interface 570, and a computer program 591 performed by the processor 510. It may include a memory 530 that stores a computer program 591 and a storage 590 that stores a computer program 591. However, only components related to the embodiment of the present invention are shown in Figure 9. Accordingly, a person skilled in the art to which the present invention pertains can see that other general-purpose components other than those shown in FIG. 9 may be further included.

The processor 510 controls the overall operation of each component of the computing device 500. The processor 510 is at least one of a Central Processing Unit (CPU), Micro Processor Unit (MPU), Micro Controller Unit (MCU), Graphic Processing Unit (GPU), or any type of processor well known in the art of the present invention. It can be configured to include. Additionally, the processor 510 may perform operations on at least one application or program to execute methods/operations according to various embodiments of the present invention. Computing device 500 may include one or more processors.

The memory 530 stores various data, commands and/or information. The memory 530 may load one or more programs 591 from the storage 590 to execute methods/operations according to various embodiments of the present invention. An example of the memory 530 may be RAM, but is not limited thereto.

Bus 550 provides communication functionality between components of computing device 500. The bus 550 may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

The communication interface 570 supports wired and wireless Internet communication of the computing device 500. The communication interface 570 may support various communication methods other than Internet communication. To this end, the communication interface 570 may be configured to include a communication module well known in the technical field of the present invention.

Storage 590 may non-transitory store one or more computer programs 591. The storage 590 is a non-volatile memory such as Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk, a removable disk, or a device well known in the technical field to which the present invention pertains. It may be configured to include any known type of computer-readable recording medium.

The computer program 591 may include one or more instructions implementing methods/operations according to various embodiments of the present invention. When the computer program 591 is loaded into the memory 530, the processor 510 can perform methods/operations according to various embodiments of the present invention by executing the one or more instructions.

The method according to the present invention described above can be produced as a program to be executed on a computer and stored in a computer-readable recording medium. Examples of computer-readable recording media include ROM, RAM, CD-ROM, and magnetic tape. , floppy disks, optical data storage devices, etc.

In addition, although preferred embodiments of the present invention have been shown and described above, the present invention is not limited to the specific embodiments described above, and the technical field to which the invention pertains without departing from the gist of the present invention as claimed in the claims. Of course, various modifications can be made by those skilled in the art, and these modifications should not be understood individually from the technical idea or perspective of the present invention.

Claims (6)

Ability to acquire 3D modeling images scanned of the patient's oral cavity;
A generator that generates a fake image based on the 3D modeling image; and a function for generating a 2D dental prosthesis design using a first artificial intelligence model including a discriminator that compares the fake image and the real image to determine whether the fake image is authentic. and
A function of generating the dental prosthesis model using a second artificial intelligence model based on the 2D dental prosthesis design; including;
A computer program for performing 3D prosthesis fabrication services for dental restoration. According to claim 1,
After the function of creating the dental prosthesis model,
A function to post-edit the dental prosthesis model using web CAD; and
Further comprising a function of outputting a dental prosthesis corresponding to the post-corrected dental prosthesis model.
A computer program for performing 3D prosthesis fabrication services for dental restoration. According to claim 1,
The generator is,
Including a u-net image auto encoder,
A computer program for performing 3D prosthesis fabrication services for dental restoration. According to claim 1,
The discriminator is,
A model based on a convolutional artificial neural network (CNN),
A computer program for performing 3D prosthesis fabrication services for dental restoration. According to claim 1,
The second artificial intelligence model is,
A model based on auto encoder, brancher, and neural implicit function,
A computer program for performing 3D prosthesis fabrication services for dental restoration. According to clause 2,
The post-editing function above is,
A function to set a margin line for the dental prosthesis model; and
Including a function of post-correction of the dental prosthesis model based on the margin line,
A computer program for performing 3D prosthesis fabrication services for dental restoration.