Method, device, and computer-readable recording medium for providing orthodontic status and orthodontic treatment evaluation information based on patient's dental scan data

Abstract

The present invention relates to a method for providing orthodontic current status and orthodontic treatment evaluation information based on a patient's dental scan data, the method being implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processors, the method including: a first image acquisition step of acquiring a first dental image, which is an image of the patient's dental arrangement, based on the received first dental scan data when first dental scan data, which is 3D scan data acquired by photographing a patient's head, is received; an orthodontic image acquisition step of confirming a dental arrangement state based on the first dental image using a pre-stored algorithm when acquisition of the first dental image is completed, acquiring treatment solution information for correcting the dental arrangement based on the confirmed dental arrangement state, and acquiring a second dental image, which is an image of a predicted dental arrangement at the time of completion of orthodontic treatment based on the acquired treatment solution information; the step of generating an orthodontic device design when acquisition of the first tooth image is completed, generating a design drawing of a transparent orthodontic device for correcting the patient's teeth arrangement to a teeth arrangement corresponding to the second tooth image; the step of acquiring an intermediate image when new 3D scan data, that is, second dental scan data, is received, and acquiring a third dental image, which is an image of the patient's teeth arrangement currently being corrected, based on the received second dental scan data; and the step of acquiring, when acquisition of the third dental image is completed, acquiring tooth movement vector information of the patient from the first tooth image, the second tooth image, and the third tooth image, and generating orthodontic current status information for the patient's orthodontic treatment based on the acquired tooth movement vector information, and providing the orthodontic current status information to a medical professional account.

Description

[Technical Field]

[0001] The present invention relates to a method for providing current orthodontic treatment status and orthodontic treatment evaluation information based on scan data of a patient's teeth. Specifically, the present invention relates to a technology for acquiring an image of the patient's teeth based on scan data obtained by photographing the patient's head, determining the type of malocclusion of the patient based on the acquired image of the patient's teeth, obtaining treatment solution information corresponding to the determined type of malocclusion and an image of the predicted teeth arrangement after correction, and generating a design drawing of a transparent orthodontic appliance. When new scan data of the teeth is acquired during orthodontic treatment, an image of the patient's teeth currently being orthodontic treated is acquired to determine the current orthodontic treatment status for the teeth arrangement, determining the type of malocclusion of the patient's teeth based on the scan data of the teeth, obtaining a target orthodontic value based on treatment solution information for correcting the determined malocclusion, obtaining an orthodontic treatment achievement value for each tooth to be corrected based on second scan data received thereafter, and obtaining orthodontic treatment evaluation information, which is information evaluating the orthodontic treatment, based on the achieved orthodontic value and the target orthodontic value. [Background technology]

[0002] The global transparent orthodontic appliance market is expected to grow at a compound annual growth rate (CAGR) of 23.1% to reach $6 billion by 2027. Market growth is accelerating due to technological advancements and increasing demand for transparent orthodontic appliances that effectively fit the user's teeth alignment. As a result, the dental industry is developing various technologies to meet this trend, most notably technologies to check the progress of patients' teeth alignment.

[0003] As an example, Patent Document 1 (Orthodontic Simulation Method and System for Performing This) discloses a technology for identifying individual teeth from a two-dimensional dentition image, setting virtual positions that will bring the individual teeth closer to adjacent teeth after orthodontic treatment, and repositioning the individual teeth.

[0004] However, the prior art only discloses a technique for virtually setting the position of teeth in proximity to adjacent teeth after orthodontic treatment and repositioning them. It does not disclose a technique for determining the type of malocclusion associated with the patient's dental alignment based on the patient's dental scan data, and generating a design drawing of a transparent orthodontic device that fits the patient's dental alignment by obtaining treatment solution information appropriate for the determined malocclusion and an image of the predicted dental alignment after correction, or a technique for determining the current status of orthodontic treatment for the patient's dental alignment by obtaining an image of the dental alignment during correction when new dental scan data is obtained during the treatment process. Therefore, a technology to solve this problem is needed. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Korean Patent Publication No. 10-2015-0039028 Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention aims to obtain an image of the patient's dental arrangement based on dental scan data obtained by photographing the patient's head, identify the type of malocclusion of the patient based on the obtained image of the patient's dental arrangement, obtain treatment solution information corresponding to the identified type of malocclusion and an image of the predicted dental arrangement after correction, and generate a design drawing of a transparent orthodontic device, and when new dental scan data is obtained during orthodontic treatment, obtain an image of the patient's dental arrangement during orthodontic treatment to determine the current status of orthodontic treatment for the dental arrangement, thereby providing a transparent orthodontic device suitable for the patient's dental arrangement, and providing patients with confidence in the orthodontic treatment for their dental arrangement based on the current orthodontic treatment information. [Means for solving the problem]

[0007] A method for providing orthodontic current status and orthodontic treatment evaluation information based on a patient's dental scan data according to an embodiment of the present invention, implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes: an initial image acquisition step of acquiring a first dental image, which is an image of the patient's dental arrangement, based on first dental scan data, when first dental scan data, which is 3D scan data acquired by photographing the patient's head, is received; an orthodontic image acquisition step of confirming a dental arrangement state based on the first dental image using a pre-stored algorithm upon completion of acquisition of the first dental image, acquiring treatment solution information for correcting the dental arrangement based on the confirmed dental arrangement state, and acquiring a second dental image, which is an image of a predicted dental arrangement at the time of completion of orthodontic treatment, based on the acquired treatment solution information; and The method further comprises: an orthodontic device design generation step of generating a design of a transparent orthodontic device for correcting the patient's dental alignment to a dental alignment corresponding to the second dental image when acquisition of the second dental image is completed; an intermediate image acquisition step of acquiring a third dental image, which is an image of the patient's dental alignment currently being corrected, based on the received second dental scan data when new 3D scan data, i.e., second dental scan data, is received during the process of correcting the patient's dental alignment by having the patient wear the transparent orthodontic device based on the generated design; and an orthodontic current status information provision step of acquiring tooth movement vector information of the patient from the first dental image, the second dental image, and the third dental image when acquisition of the third dental image is completed, and generating orthodontic current status information of the patient's orthodontic treatment based on the acquired tooth movement vector information and providing the orthodontic current status information to a medical professional account.

[0008] The orthodontic image acquisition step includes a process initiation step of starting a malocclusion confirmation process when acquisition of the first tooth image is completed; a malocclusion classification step of analyzing the first tooth image using the pre-stored algorithm at the start of the malocclusion confirmation process, acquiring tooth arrangement status information of the patient, and classifying the acquired tooth arrangement status information into one of a plurality of malocclusion type information; and a solution information acquisition step of acquiring treatment solution information for the classified malocclusion type information using an artificial intelligence solution generation algorithm based on machine learning that derives a solution for orthodontic treatment when the tooth arrangement status information is classified into one of the plurality of malocclusion type information.

[0009] The orthodontic current status information providing step acquires tooth movement vector information for each of the patient's teeth based on a common point included in a first head image corresponding to the first dental scan data and a second head image corresponding to the second dental scan data.

[0010] The common points are common points located on the patient's head included in the first head image and the second head image, and are at least three or more points that do not change even when correcting the patient's dental alignment, and are reference points for overlaying the first dental image, the second dental image, and the third dental image.

[0011] The orthodontic current status information providing step includes an image superimposing step of generating a prognostic image by superimposing the first dental image, the second dental image, and the third dental image based on a common point included in the first head image and the second head image; an orthodontic progress checking step of, when the generation of the prognostic image is completed, comparing the tooth arrangement corresponding to the first dental image with the tooth arrangement corresponding to the third dental image based on the prognostic image to confirm the direction and distance of movement of each tooth, and generating first tooth movement vector information including first tooth movement direction information and first tooth movement distance information; and an orthodontic progress prediction step of generating second tooth movement vector information including second tooth movement direction information and second tooth movement distance information by comparing the tooth arrangement corresponding to the first tooth image with the tooth arrangement corresponding to the second tooth image based on the prognostic image while the function of the recognition step is being performed, and an information generation step of starting an information generation process of generating current orthodontic status information based on the first tooth movement vector information and the second tooth movement vector information after acquisition of the first tooth movement vector information and the second tooth movement vector information is completed.

[0012] The image superimposition step applies a graphic effect to the first tooth image, the second tooth image, and the third tooth image that are superimposed based on the common point so as to visually distinguish them, thereby generating the prognostic image.

[0013] The orthodontic progress prediction step includes a fourth tooth image acquisition step of generating a plurality of fourth tooth images corresponding to a plurality of viewpoints based on the treatment solution information from the first tooth image and the second tooth image, in which the direction and distance of each of the teeth are confirmed, and a second tooth movement vector information generation step of comparing the plurality of fourth tooth images in chronological order and generating the second tooth movement vector information for the tooth arrangement included in each of the plurality of fourth tooth images once generation of the plurality of fourth tooth images is completed, wherein each of the plurality of viewpoints is at least two or more viewpoints inputted via the medical professional account.

[0014] The information generating step includes a direction confirming step, when generation of the first tooth movement vector information and the second tooth movement vector information is completed, comparing the second tooth movement direction information with the first tooth movement direction information to confirm whether an error rate of the movement axis direction based on the first tooth movement direction information with respect to the movement axis direction based on the second tooth movement direction information is equal to or less than a predetermined error rate; a distance confirming step, while the direction confirming step is being performed, comparing the second tooth movement distance information with the first tooth movement distance information to confirm whether an error rate of the movement distance based on the first tooth movement distance information with respect to the movement distance based on the second tooth movement distance information is equal to or less than the predetermined error rate; and an orthodontic current status information generating step, when result information based on execution of the direction confirming step and the distance confirming step is obtained, generating the orthodontic current status information representing the current status of orthodontic treatment for the patient's tooth arrangement based on the result information.

[0015] The method for providing orthodontic current status and orthodontic treatment evaluation information based on the patient's dental scan data further includes an orthodontic treatment evaluation information providing step, which includes, when the function execution of the first image obtaining step is completed, obtaining a malocclusion image of the patient's teeth based on the first dental scan data, obtaining treatment solution information based on the obtained malocclusion image, and obtaining orthodontic target values ​​for correcting the patient's malocclusion based on the obtained treatment solution information. After the orthodontic target values ​​are obtained, the orthodontic treatment evaluation information providing step further includes a target value obtaining step. The method includes a step of receiving third dental scan data, which is new 3D scan data obtained by photographing a patient for whom orthodontic treatment has been completed, and acquiring an orthodontic completion image, which is an image of the corrected tooth arrangement, based on the third dental scan data; and a step of obtaining an orthodontic achievement value for each of the orthodontic teeth based on the obtained orthodontic completion image, comparing the orthodontic achievement value with the orthodontic target value to obtain error information, and generating orthodontic treatment evaluation information, which is evaluation information for the orthodontic treatment, based on the obtained error information and providing the evaluation information to the medical professional account.

[0016] The target value acquisition step includes a malocclusion confirmation start step of starting a malocclusion confirmation process when the first dental scan data is received from the medical professional account; a malocclusion determination step of analyzing the malocclusion image using a pre-stored malocclusion confirmation algorithm when the malocclusion confirmation process starts, confirming the patient's dental alignment from the analyzed malocclusion image, and classifying the confirmed dental alignment into one of a plurality of malocclusion information to determine the patient's malocclusion; and a solution acquisition step of obtaining treatment solution information for the patient's malocclusion using an artificial intelligence solution generation algorithm based on machine learning that derives a solution for orthodontic treatment when the determination of the patient's malocclusion is completed.

[0017] In the malocclusion determination step, in checking the patient's tooth arrangement, at least one of the position, contact relationship with adjacent teeth, perpendicular relationship, whether rotation is possible, and inclination of each of the patient's teeth included in the malocclusion image is checked using the pre-stored malocclusion confirmation algorithm.

[0018] The target value acquisition step includes: a guide application step in which, when acquisition of the treatment solution information is completed by executing the functions of the solution acquisition step, the solution generation algorithm applies an orthodontic guide based on the treatment solution information to the malocclusion image; a virtual orthodontic image acquisition step in which the orthodontic guide based on the treatment solution information is applied to the malocclusion image to arrange each of the patient's teeth in a dental state after orthodontic treatment is completed, thereby acquiring a virtual orthodontic image, which is a virtual image corresponding to the dental arrangement after orthodontic treatment is completed; and a correction value acquisition step in which, when acquisition of the virtual orthodontic image is completed, the virtual orthodontic image is compared with the malocclusion image to acquire orthodontic target direction information and orthodontic target distance information for each tooth, and acquire the orthodontic target value, which is a reference value for correcting the patient's malocclusion.

[0019] The evaluation information providing step includes an achievement value acquisition step in which, when the orthodontic completion image is acquired by executing the function of the orthodontic completion image acquisition step, the orthodontic completion image is analyzed using the previously stored malocclusion confirmation algorithm to acquire the orthodontic achievement value for each of the patient's corrected teeth; an error value confirmation step in which, when acquisition of the orthodontic achievement value is completed, the orthodontic target value is compared with the orthodontic achievement value to acquire an error value of the orthodontic achievement value relative to the orthodontic target value and determine whether the acquired error value is within a predetermined error value range; and an error information analysis step in which error information is generated based on the result determined by executing the function of the error value confirmation step, and the generated error information is analyzed using the artificial intelligence solution generation algorithm to generate the orthodontic treatment evaluation information.

[0020] The orthodontic treatment evaluation information is information that determines the success or failure of orthodontic treatment for each of the patient's teeth based on the error information, and if it is confirmed that the orthodontic treatment for each of the patient's teeth based on the error information has failed, it includes orthodontic improvement information for correcting each of the teeth for which orthodontic treatment has failed, and the orthodontic improvement information is information generated by the artificial intelligence solution generation algorithm and is model treatment information derived based on orthodontic treatment history information of other patients learned by the artificial intelligence solution generation algorithm.

[0021] The evaluation information providing step includes a corrective device design generation step of generating a first design plan, which is design plan information for the transparent corrective device based on the model treatment information, by providing orthodontic treatment evaluation information including the model treatment information to the medical professional account, and a corrective device design providing step of, once generation of the first design plan is complete, obtaining second design plan information, which is design plan information for the transparent corrective device based on the correction target value, and providing an interface to the medical professional account that allows the first design plan and the second design plan to be compared.

[0022] When the interface receives doctor's opinion information for redesigning the transparent correction device from the medical professional account, it modifies the first design plan based on the input doctor's opinion information.

[0023] According to an embodiment of the present invention, there is provided an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on a patient's dental scan data, the apparatus including a computing device including one or more processors and one or more memories for storing instructions executable by the processors, the apparatus comprising: a first image acquisition unit that acquires a first dental image, which is an image of the patient's dental arrangement, based on first dental scan data, when first dental scan data, which is 3D scan data acquired by photographing a patient's head, is received; an orthodontic image acquisition unit that, when acquisition of the first dental image is completed, confirms the dental arrangement status based on the first dental image using a pre-stored algorithm, acquires treatment solution information for correcting the dental arrangement based on the confirmed dental arrangement status, and acquires a second dental image, which is an image of the predicted dental arrangement at the time of completion of orthodontic treatment, based on the acquired treatment solution information; The orthodontic device design generation unit generates a design drawing of a transparent orthodontic device for correcting the patient's dental alignment to a dental alignment corresponding to the second dental image when acquisition of the second dental image is completed; an intermediate image acquisition unit acquires a third dental image, which is an image of the patient's dental alignment during orthodontic treatment, based on the received second dental scan data when new 3D scan data, i.e., second dental scan data, is received during the process of correcting the patient's dental alignment by having the patient wear the transparent orthodontic device based on the generated design drawing; and an orthodontic current status information provision unit acquires tooth movement vector information of the patient from the first dental image, the second dental image, and the third dental image when acquisition of the third dental image is completed, and generates orthodontic current status information of the patient's orthodontic treatment based on the acquired tooth movement vector information and provides it to a medical professional account.

[0024] A computer-readable recording medium according to an embodiment of the present invention, the computer-readable recording medium storing instructions for causing a computing device to perform the following steps, the steps including: an initial image acquisition step of acquiring a first dental image, which is an image of the patient's dental arrangement, based on first dental scan data, when first dental scan data, which is 3D scan data acquired by photographing a patient's head, is received; an orthodontic image acquisition step of confirming a dental arrangement state based on the first dental image using a pre-stored algorithm after acquisition of the first dental image is completed, acquiring treatment solution information for correcting the dental arrangement based on the confirmed dental arrangement state, and acquiring a second dental image, which is an image of a predicted dental arrangement at the time of completion of orthodontics based on the acquired treatment solution information; and an orthodontic image acquisition step of confirming a dental arrangement state based on the first dental image using a pre-stored algorithm after acquisition of the first dental image. The method further comprises: an orthodontic device design generation step, which generates a design drawing of a transparent orthodontic device for correcting the patient's dental alignment to a dental alignment corresponding to the second dental image upon completion of acquisition; an intermediate image acquisition step, which acquires a third dental image, which is an image of the patient's dental alignment currently being corrected, based on the received second dental scan data when new 3D scan data, i.e., second dental scan data, is received during the process of correcting the patient's dental alignment by having the patient wear the transparent orthodontic device based on the generated design drawing; and an orthodontic current status information provision step, which acquires tooth movement vector information of the patient from the first dental image, the second dental image, and the third dental image upon completion of acquisition of the third dental image, and generates orthodontic current status information for the patient's orthodontic treatment based on the acquired tooth movement vector information and provides it to a medical professional account. [Effects of the Invention]

[0025] The method for providing current orthodontic condition and orthodontic treatment evaluation information based on scan data of a patient's teeth according to the present invention can determine the type of malocclusion associated with the patient's dental alignment, and provide the patient with a treatment plan suited to the patient's dental alignment condition.

[0026] Additionally, pre-stored algorithms can quickly analyze each of the patient's teeth to determine the type of malocclusion associated with the patient's dental alignment.

[0027] Furthermore, by correcting the patient's dental alignment using a common point in a head image based on scan data of the patient's teeth as a reference point that does not change due to correction of the dental alignment, it is possible to perform orthodontic treatment without any aesthetic defects.

[0028] In addition, the artificial intelligence solution generation algorithm can analyze the tooth alignment of a patient undergoing orthodontic treatment and provide orthodontic status information, which is current status information on the tooth alignment treatment currently being performed. [Brief explanation of the drawings]

[0029] [Figure 1] FIG. 1 is a sequence diagram illustrating a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 2] FIG. 2 is a sequence diagram illustrating an orthodontic image acquisition step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 3] FIG. 3 is a diagram illustrating a pre-stored algorithm of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 4] FIG. 4 is a diagram illustrating an orthodontic current status information providing step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data of a patient according to an embodiment of the present invention. [Figure 5] FIG. 5 is a view illustrating an orthodontic progress checking unit of an apparatus for providing a current orthodontic condition based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 6]FIG. 6 is a diagram illustrating an orthodontic progress prediction step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 7] FIG. 7 is a diagram illustrating an information generating step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 8] FIG. 8 is a diagram illustrating an orthodontic treatment evaluation information providing unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 9] FIG. 9 is a block diagram illustrating a target value acquisition unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 10] FIG. 10 is a diagram illustrating a malocclusion determination unit of an apparatus for providing current orthodontic condition and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 11] FIG. 11 is another block diagram illustrating a target value acquiring unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 12] FIG. 12 is a block diagram illustrating an evaluation information providing unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 13] FIG. 13 is a diagram illustrating an interface of a device for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention. [Figure 14] FIG. 14 is a diagram illustrating an example of the internal configuration of a computing device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0030] Various embodiments and / or aspects are described below with reference to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth in order to facilitate a general understanding of one or more aspects. However, those skilled in the art will recognize that these aspects may be practiced without such specific details. The following description and the accompanying drawings set forth certain exemplary aspects of one or more aspects in detail. However, such aspects are illustrative, and only a portion of various methods may be utilized in accordance with the principles of the various aspects, and the description is intended to include all such aspects and their equivalents.

[0031] As used herein, "embodiments," "examples," "aspects," "exemplary," and the like may not be construed as constituting any described aspect or design as being better or advantageous over other aspects or designs.

[0032] Additionally, the terms "comprise" and / or "comprising" should be understood to mean that the feature and / or component is present, but not to exclude the presence or addition of one or more other features, components and / or groups thereof.

[0033] Furthermore, terms including ordinal numbers, such as "first," "second," etc., are used to describe various elements, but the elements are not limited by these terms. These terms are used only to distinguish one element from another. For example, a first element can be referred to as a "second element," and similarly, a second element can be referred to as a "first element," without departing from the scope of the present invention. The term "and / or" includes a combination of multiple related listed items or any of multiple related listed items.

[0034] Furthermore, unless otherwise defined in the embodiments of the present invention, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the present invention belongs. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning they have in the context of the related art, and should not be interpreted as idealized or overly formal unless explicitly defined in the embodiments of the present invention.

[0035] FIG. 1 is a sequence diagram illustrating a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0036] As shown in FIG. 1, the method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth, which is implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an initial image acquisition step (S101), an orthodontic image acquisition step (S103), an orthodontic device design generation step (S105), an intermediate image acquisition step (S107), and an orthodontic current status information provision step (S109).

[0037] In step S101, when the one or more processors (hereinafter referred to as processors) receive first dental scan data, which is 3D scan data obtained by photographing the patient's head, they acquire a first dental image, which is an image of the patient's current dental arrangement, based on the received first dental scan data.

[0038] According to one embodiment, the first dental scan data is a radiograph of a patient's head or an MRI image taken by an MRI device. That is, the dental scan data is image data of the patient's dentition contained in an image obtained by photographing the patient's head. Also, the dental scan data is image data of only the patient's dentition.

[0039] According to one embodiment, when the first dental scan data is received, the processor acquires a first dental image, which is an image of the patient's current dental arrangement, based on the dental scan data. The first dental image is an image of an initial dental arrangement, and the first dental image is an image acquired from the first dental scan data including the patient's dental image.

[0040] According to one embodiment, the processor performs the correction image acquisition step (S103) after acquiring the first tooth image.

[0041] In step S103, after acquiring the first tooth image, the processor confirms the tooth alignment state based on the first tooth image using a pre-stored algorithm, and acquires treatment solution information for correcting the tooth alignment based on the confirmed tooth alignment state of the patient. The processor also acquires a second image, which is an image of the predicted tooth alignment after correction based on the acquired treatment solution information. The process of acquiring the treatment solution information will be described in detail with reference to FIG. 2.

[0042] According to one embodiment, after the first dental image is acquired, the processor analyzes the first dental image using a pre-stored algorithm, which is a machine learning-based algorithm that analyzes the first dental image, determines the shape and position of each tooth included in the first dental image, confirms the patient's dental alignment status based on the determination result, and classifies dental alignment status information corresponding to the confirmed dental alignment status into one of a plurality of malocclusion type information.

[0043] For example, the pre-stored algorithm is an automatic cognitive standardization algorithm, which will be described in detail with reference to FIGS.

[0044] For example, the pre-stored algorithm may be a PointNet-based deep learning algorithm. The processor may learn previously acquired or input dental images using the PointNet-based deep learning algorithm, thereby determining the shape and position of each tooth (e.g., tooth no. 1, tooth no. 2) included in the dental image and confirming the patient's dental alignment. The processor may use the first dental image to determine the position of the patient's mandibular condyle, the dental alignment (shape and position), the relationship between the upper and lower jaws, and the position and gradient of the maxillary and maxillary bone complex relative to the cranium. In other words, the pre-stored algorithm may be, but is not limited to, a PointNet-based deep learning algorithm or any other machine learning-based algorithm that can determine the patient's dental alignment and confirm the type of malocclusion from newly input dental images by machine learning previously acquired or input dental images.

[0045] According to one embodiment, after the processor has analyzed the first dental image using the pre-stored algorithm, the processor obtains treatment solution information using an artificial intelligence solution generation algorithm based on machine learning, which derives a solution for correcting the patient's malocclusion based on tooth arrangement state information corresponding to the tooth arrangement state included in the analyzed first dental image.

[0046] According to one embodiment, the processor classifies the confirmed dental alignment condition of the patient into one of a plurality of malocclusion type information. The plurality of malocclusion type information will be described in detail in FIG. 2. The processor can obtain treatment solution information using an artificial intelligence solution generation algorithm based on the classified malocclusion type information. The classification of the malocclusion type information will be described in detail in FIG. 3.

[0047] According to one embodiment, the artificial intelligence solution generation algorithm is an algorithm in which the processor receives orthodontic data from other electronic devices (desktops, tablet PCs, and medical devices) or medical professional accounts, and performs machine learning on the received data to present visualized treatment objectives (VTOs) and an optimal treatment plan for the patient's dental alignment.

[0048] According to one embodiment, when the processor receives the orthodontic data, it performs machine learning on the received data using learning data to obtain information on visualized treatment objectives (VTO) and an optimal treatment plan for the patient's dental alignment, taking into consideration a stabilized condylar position, an appropriate angle of the teeth, the relationship between the maxilla and the mandible, and the appropriate position and gradient of the maxilla and mandible complex relative to the cranium. That is, the treatment solution information includes at least one of the VTO and treatment plan information generated by the AI ​​solution generation algorithm. Thus, the VTO and the treatment plan information include information on the treatment method, treatment period, treatment medication, etc. required to correct the patient's dental alignment. Furthermore, the VTO includes, as visualized treatment objective information, an image (second tooth image) of the patient's predicted dental alignment upon completion of orthodontic treatment based on the treatment plan information.

[0049] According to one embodiment, the second dental image is image information relating to a predicted dental alignment after correction, which is formed when the malocclusion of the patient's teeth is corrected according to the treatment plan information included in the treatment solution information, i.e., the second dental image is an image generated by rearranging each of the teeth included in the first dental image based on the treatment solution information using a solution generation algorithm.

[0050] According to one embodiment, the processor performs an orthodontic device design generation step (S105) after completing acquisition of the second tooth image.

[0051] In step S105, after the acquisition of the second dental image is completed, the processor generates a design plan of a transparent orthodontic appliance to correct the patient's dental alignment to the dental alignment corresponding to the second dental image. The design plan is design plan information necessary for a 3D printer connected to the processor via a wired network and / or a wireless network to manufacture the transparent orthodontic appliance.

[0052] When the processor receives new dental scan data due to a patient visit during treatment, it performs an intermediate image acquisition step (S107).

[0053] In step S107, the processor receives second dental scan data, which is new 3D scan data, during the process of correcting the patient's teeth by having the patient wear the transparent orthodontic appliance based on the generated design. That is, the second dental scan data is data acquired during the process of correcting the patient's malocclusion, and is different from the first dental scan data containing an image of the patient's initial teeth alignment.

[0054] According to one embodiment, when the processor receives the second dental scan data, the processor acquires a third dental image, which is an image of the patient's dental alignment during correction, based on the received second dental scan data. The third dental image is an image of the patient's dental alignment during correction of malocclusion using the transparent orthodontic device. The processor may acquire the third dental image by analyzing the second dental scan data based on the pre-stored algorithm to acquire the third dental image.

[0055] After the acquisition of the third tooth image is completed, the processor performs an orthodontic current status information providing step (S109).

[0056] In step S109, upon completing acquisition of the third tooth image, the processor generates tooth movement path information for the patient from the first tooth image, the second tooth image, and the third tooth image. The tooth movement path information includes movement direction information and movement distance information for each tooth that moves as the patient's tooth alignment is corrected using the transparent orthodontic device. The processor can confirm the current orthodontic status of the patient's tooth alignment based on the tooth movement path information. For example, the processor can obtain post-treatment oral cavity condition information for the corrected tooth alignment by obtaining tooth movement path information based on the first tooth image and the third tooth image. Furthermore, the processor can obtain during-treatment oral cavity condition information for the tooth alignment currently being corrected by obtaining tooth movement path information based on the second tooth image and the third tooth image.

[0057] According to one embodiment, after generating the orthodontic current status information, the processor provides the orthodontic current status corresponding to the generated orthodontic current status information to the healthcare professional account. A detailed description of generating the orthodontic current status information will be given with reference to FIG. 4. Here, the orthodontic current status refers to information on the state of tooth alignment during orthodontic treatment and information on the state of tooth alignment after orthodontic treatment is completed.

[0058] FIG. 2 is a sequence diagram illustrating an orthodontic image acquisition step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0059] As shown in FIG. 2, the method for providing orthodontic status and orthodontic treatment evaluation information based on scan data of a patient's teeth, which is implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an orthodontic image acquisition step (the orthodontic image acquisition step (S103) in FIG. 1).

[0060] According to one embodiment, the one or more processors (hereinafter referred to as processors) receive first dental scan data, which is 3D scan data obtained by photographing a patient's head, and then acquire a first dental image, which is an image of the patient's dental arrangement, based on the received first dental scan data. The first dental scan data can be input via a medical professional account or received from an external device (desktop, tablet PC, medical device).

[0061] According to one embodiment, after the first tooth image has been acquired, the processor performs the correction image acquisition step, which includes a process start step (S201), a malocclusion classification step (S203), and a solution information acquisition step (S205).

[0062] In step S201, when the acquisition of the first dental image is completed, the processor starts a malocclusion confirmation process, which is a process for determining whether the patient's dental arrangement is malocclusion.

[0063] According to one embodiment, the processor performs a malocclusion type confirmation step (step S203) when the malocclusion confirmation process starts.

[0064] In step S203, when the malocclusion confirmation process starts, the processor analyzes the first tooth image using a pre-stored algorithm to obtain information on the patient's tooth arrangement status. The tooth arrangement status information includes shape information and position information for each of the patient's teeth. The processor classifies the obtained tooth arrangement status information into one of a plurality of malocclusion type information. The plurality of malocclusion type information is information that serves as a reference necessary to classify the patient's tooth arrangement into one of a plurality of malocclusion types.

[0065] According to one embodiment, the pre-stored algorithm is an automatic cognitive standardization algorithm. The automatic cognitive standardization algorithm is a machine learning algorithm for classifying tooth alignment status information acquired by the processor by checking the shape and position of each of the patient's teeth included in the first dental image into one of multiple malocclusions. That is, the pre-stored algorithm is an algorithm that provides treatment solution information when an algorithm trained based on a large amount of data (dental images of other patients) receives new 3D scan data. That is, the processor acquires the tooth alignment status information using the pre-stored algorithm, classifies it into malocclusion type information, and provides treatment solution information based on the classified malocclusion type.

[0066] The plurality of malocclusion type information includes at least one of crowding malocclusion, spacing malocclusion, rotation malocclusion, vertical relationship (openbite & deepbite) malocclusion, mesiodistal tipping malocclusion, buccolingual torque malocclusion, and interdigital malocclusion. Each of the plurality of malocclusion type information includes a first dental image of the patient, characteristic information on the patient's dental arrangement derived by the automatic recognition standardization algorithm, and history information up until the dental arrangement status information is classified as malocclusion information by the automatic recognition standardization algorithm. A method for classifying the patient's dental arrangement into any type of malocclusion using the automatic recognition standardization algorithm will be described in detail with reference to FIG. 3.

[0067] According to one embodiment, when the processor has completed classifying the acquired tooth arrangement status information into one of a plurality of malocclusion type information using an automatic recognition standardization algorithm based on the first tooth image, it performs a solution information acquisition step (S205).

[0068] In step S205, when the tooth arrangement status information is classified into one of the plurality of malocclusion type information in step S203, the processor obtains treatment solution information for the classified malocclusion type information using an artificial intelligence solution generation algorithm based on machine learning that derives solutions for orthodontic treatment.

[0069] For example, when the classified malocclusion type information is "crowd- ing malocclusion type information," the processor can use an artificial intelligence solution generation algorithm to derive a solution for orthodontic treatment of the crowding malocclusion corresponding to the patient's "crowd- ing malocclusion type information" and generate treatment solution information. The processor can acquire treatment plan information for the patient's malocclusion based on the patient's first tooth image information included in the crowding malocclusion type information. When the patient's tooth arrangement state is a crowding malocclusion of tooth #11 and tooth #21, the processor includes, as the treatment plan information, treatment method information for changing the position of at least one of tooth #11 and tooth #21 so that they do not come into contact.

[0070] That is, the processor can obtain treatment plan information and VTO information for correcting the tooth alignment corresponding to the first tooth image information using the first tooth image information and an AI solution generation algorithm, where the obtained treatment plan information and VTO information are information derived by the processor learning the previously acquired tooth image using the AI ​​solution generation algorithm to correct the tooth alignment corresponding to the first tooth image.

[0071] FIG. 3 is a diagram illustrating a pre-stored algorithm of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0072] As shown in FIG. 3, the method for providing orthodontic status and orthodontic treatment evaluation information based on scan data of a patient's teeth, which is implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, can classify the type of malocclusion the patient's teeth alignment falls into using a pre-stored algorithm (automatic recognition standardization algorithm).

[0073] According to one embodiment, when one or more processors (hereinafter referred to as processors) acquire a first dental image, they analyze the first dental image using a pre-stored algorithm (automatic recognition standardization algorithm) to acquire dental alignment information corresponding to the patient's current dental alignment. The dental alignment information includes not only the shape and position of each of the patient's teeth, but also the position of the patient's mandibular condyle, the relationship between the maxillary and mandibular bones, and the position and gradient of the maxillary and mandibular complex relative to the cranium.

[0074] According to one embodiment, the processor classifies the obtained tooth alignment status information into one of a plurality of malocclusions.

[0075] For example, the processor may confirm that the patient's tooth #13 and tooth #14 are overlapping based on the first tooth image, and acquire tooth arrangement status information. When the processor acquires the tooth arrangement status information, it performs step S301. When step S301 is performed, the processor may confirm whether the tooth #13 and tooth #14 are in contact with each other.

[0076] When the processor confirms that the 13th tooth and the 14th tooth are in contact and overlapping, it performs step S303. When the processor confirms that the degree of overlap between the 13th tooth and the 14th tooth is 3 mm based on the first tooth image, it can confirm that the patient's tooth arrangement condition is "degree 2 crowding malocclusion" and classify the patient's tooth arrangement condition information as "crowding malocclusion information." The crowding malocclusion information includes the patient's first tooth image information, characteristic information on the patient's tooth arrangement derived by the automatic recognition standardization algorithm (information on the positional relationship formed between the teeth), and history information up to the time when the tooth arrangement condition information was classified as malocclusion information by the automatic recognition standardization algorithm.

[0077] According to one embodiment, the automatic recognition standardization algorithm may perform different steps depending on the type of malocclusion type information, and the configuration required to perform the steps (interdental distance, whether or not the teeth can be rotated, the perpendicular relationship between the teeth, and the gradient for each tooth) differs. That is, Figure 3 shows the steps of the automatic recognition standardization algorithm for classifying the patient's tooth arrangement status information into dental crowding malocclusion, and the corresponding steps differ depending on the malocclusion.

[0078] For example, the processor can identify each of the patient's teeth based on the first tooth image and confirm that tooth 13 and tooth 14 are spaced apart. The processor can obtain tooth arrangement status information that indicates the spaced arrangement status of tooth 13 and tooth 14.

[0079] When the processor acquires the tooth arrangement status information, it can confirm the distance between the 13th tooth and the 14th tooth. If the distance between the 13th tooth and the 14th tooth is 2 mm or less, the processor can classify the patient's tooth arrangement status information as "space malocclusion information" by first determining that there is a space malocclusion. The space malocclusion information includes the patient's first tooth image information, characteristic information on the patient's tooth arrangement derived by the automatic recognition standardization algorithm (inter-tooth positional relationship information), and history information up to the time when the tooth arrangement status information was classified as malocclusion information by the automatic recognition standardization algorithm.

[0080] FIG. 4 is a diagram illustrating an orthodontic current status information providing step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data of a patient according to an embodiment of the present invention.

[0081] As shown in FIG. 4, the method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth, which is implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an orthodontic current status information providing step (the orthodontic current status information providing step (S109) in FIG. 1).

[0082] According to an embodiment, the step of providing current correction status information includes an image superimposing step (S401), a correction progress checking step (S403), a correction progress prediction step (S405), and an information generating step (S407).

[0083] According to one embodiment, in performing the orthodontic current status information providing step, one or more processors (hereinafter referred to as processors) acquire tooth movement vector information of the patient from the first tooth image, the second tooth image, and the third tooth image, generate orthodontic current status information for the patient's orthodontic treatment based on the acquired tooth movement vector information, and provide orthodontic current status corresponding to the generated orthodontic current status information to a medical professional account. The orthodontic current status includes at least one of information on the oral cavity condition (tooth alignment condition) during orthodontic treatment and information on the oral cavity condition (tooth alignment condition) after completion of orthodontic treatment. For a detailed description of steps performed before performing the orthodontic current status information providing step, please refer to FIGS. 1 to 3.

[0084] According to one embodiment, in performing the orthodontic current status information providing step, the processor may acquire tooth movement vector information for each of the patient's teeth based on a common point included in the first head image and the second head image. The first head image is an image including the patient's head that can be extracted from the first dental scan data. That is, the first dental scan data including the first head image is image data including both the patient's head and dental regions. Also, the second head image is an image including the patient's head that can be extracted from the second dental scan data. That is, the second dental scan data including the second head image is image data including both the patient's head and dental regions.

[0085] The tooth movement vector information will be described in detail below.

[0086] In step S401, the processor generates a prognostic image by overlaying the first dental image, the second dental image, and the third dental image based on common points contained in the first head image and the second head image.

[0087] In one embodiment, the first head image is a radiographic image of the patient's head corresponding to the first dental scan data (first dental scan data of FIG. 1 ) and includes a first dental image and a second dental image, and the second head image is a radiographic image of the patient's head corresponding to the second dental scan data (second dental scan data of FIG. 1 ) and includes a third dental image.

[0088] According to one embodiment, the common points are common points located on the patient's head included in the first head image and the second head image, and are at least three points that do not change even when correcting the patient's dental alignment. When the patient's dental alignment is corrected using a transparent orthodontic device, not only do the positions of the teeth change, but the shape of the patient's skull also changes due to the force with which the transparent orthodontic device pushes and pulls each tooth. If the shape of the patient's skull changes, there is a problem that the dental alignment corrected using the transparent orthodontic device will not be corrected according to the treatment plan.

[0089] As a result, in the present invention, the patient's dental alignment is corrected using a transparent orthodontic device, and a point on the skull that does not move due to the pushing and pulling force of the transparent orthodontic device is defined as a "common point." By overlaying an image of the patient's head based on the "common point," it is possible to confirm only the patient's dental alignment after correction.

[0090] That is, the processor may generate a prognostic image that allows confirmation of changes in the arrangement of each of the patient's teeth by overlaying the first and second dental images included in the first head image and the third dental image included in the second head image based on at least three common points included in the first and second head images. That is, the prognostic image is a single image that includes the patient's dental arrangement based on the first, second, and third dental images, overlaid on the common points.

[0091] According to one embodiment, the processor performs a correction progress confirmation step (S403) when the generation of the prognostic image is completed.

[0092] In step S403, after generating the prognostic image, the processor compares the tooth arrangement corresponding to the first tooth image with the tooth arrangement corresponding to the third tooth image based on the prognostic image. By comparing the tooth arrangements, the processor can confirm the direction and distance of movement of each tooth, and extract and obtain first tooth movement vector information including first tooth movement direction information and first tooth movement distance information from the prognostic image.

[0093] According to one embodiment, the first dental image is an initial image of the patient's dental alignment, and the third dental image is an intermediate image acquired during the process of correcting the patient's dental alignment using a transparent orthodontic device. That is, the processor can acquire actual data regarding the correction of the dental alignment by determining the direction and distance of movement of each tooth included in the first dental image due to the pushing and pulling force of the transparent orthodontic device from the position of each tooth included in the third dental image. Here, the processor can identify the teeth included in each image (the first dental image and the third dental image) and determine the vector values ​​of the identified teeth. For a detailed description of how the processor acquires the first tooth movement vector information, see FIG. 5.

[0094] In step S405, while the function of the orthodontic progress confirmation step is being performed, the processor compares the tooth arrangement corresponding to the first tooth image with the tooth arrangement corresponding to the second image based on the prognosis image, confirms the planned movement direction and planned movement distance of each tooth, and generates second tooth movement vector information including second tooth movement direction information and second tooth movement distance information.

[0095] According to one embodiment, the first dental image is an initial image of the patient's tooth arrangement, and the second dental image is an image that predicts the tooth arrangement when the patient's malocclusion is corrected based on treatment solution information. For a detailed description of generating the second tooth movement vector information, please refer to FIG. 6.

[0096] According to an embodiment, when the generation of the second tooth movement vector information is completed, the processor performs an orthodontic current status information generating step (step S407).

[0097] In step S407, when the processor has completed acquiring the first tooth movement vector information and the second tooth movement vector information, the processor can start an information generation processor that generates orthodontic current status information based on the first tooth movement vector information and the second tooth movement vector information. For a detailed description of how the processor generates the orthodontic current status information, please refer to FIG. 7.

[0098] FIG. 5 is a view illustrating an orthodontic progress checking unit of an apparatus for providing a current orthodontic condition based on scan data of a patient's teeth according to an embodiment of the present invention.

[0099] As shown in FIG. 5, the apparatus for providing the current status of orthodontic treatment based on scan data of a patient's teeth, which is implemented as a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an orthodontic progress confirmation unit.

[0100] According to one embodiment, the correction progress confirmation unit 501 is configured to perform the same function as the function performed in the correction progress confirmation step described with reference to FIG.

[0101] According to one embodiment, when the generation of the prognostic image 503 (prognostic image of FIG. 4) is completed, the orthodontic progress checking unit 501 compares the tooth arrangements 503a and 503b corresponding to the first tooth image with the tooth arrangements 503a and 503c corresponding to the third tooth image based on the prognostic image. The tooth arrangements 503a and 503b for the first tooth image and the tooth arrangements 503a and 503c for the third tooth image are images included in the prognostic image 503. The prognostic image is an image to which a graphic effect is applied so that the first tooth image, the second tooth image, and the third tooth image, which overlap based on a common point between the first head image and the second head image, are visually distinguishable.

[0102] According to one embodiment, the orthodontic progress confirmation unit 501 can confirm the direction and distance each tooth has moved by comparing the tooth arrangements of the respective images, and extract and acquire first tooth movement vector information including first tooth movement direction information and first tooth movement distance information from the prognosis image 503.

[0103] According to one embodiment, the first dental image is an initial image of the patient's dental alignment, and the third dental image is an intermediate image acquired during the process of correcting the patient's dental alignment using a transparent orthodontic device. That is, the orthodontic progress confirmation unit 501 compares the position of each tooth included in the first dental image with the position of each tooth included in the third dental image to generate first tooth movement vector information including information on the direction and distance of actual tooth movement due to the pushing and pulling force of the transparent orthodontic device. Here, the orthodontic progress confirmation unit 501 can identify the position of each tooth included in each image (the first dental image and the third dental image) and confirm the vector value of the identified tooth position.

[0104] For example, the orthodontic progress checking unit 501 can check the patient's tooth alignment from the first tooth image. The orthodontic progress checking unit 501 can check from the first tooth image that a space is formed between the thirteenth tooth 503a and the fourteenth tooth 503b. For a detailed description of checking the patient's tooth alignment from the tooth image, please refer to the description of the automatic recognition standardization algorithm in FIG. 2.

[0105] Furthermore, the orthodontic progress checking unit 501 can check the patient's tooth alignment from the third dental image. The orthodontic progress checking unit 501 can check from the third dental image that tooth No. 14 503c has been corrected a predetermined distance in the direction of tooth No. 13 503a. Here, the orthodontic progress checking unit can compare the vector values ​​of tooth No. 14 503b in the first dental image with those of tooth No. 14 503c in the third dental image to check the vector value for tooth No. 14 being corrected using a transparent orthodontic device.

[0106] The orthodontic progress confirmation unit 501 confirms the vector value for the 14th tooth and generates first tooth movement vector information including first tooth movement distance information based on the distance the 14th tooth has moved and first tooth movement direction information based on the direction of movement.

[0107] FIG. 6 is a diagram illustrating an orthodontic progress prediction step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0108] As shown in Figure 6, the method for providing orthodontic status and orthodontic treatment evaluation information based on patient's dental scan data, which is implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an orthodontic progress prediction step (orthodontic progress prediction step (S405) in Figure 4). The orthodontic progress prediction step includes a fourth tooth image acquisition step (S601) and a second tooth movement vector information generation step (S603).

[0109] According to one embodiment, one or more processors (hereinafter referred to as processors) perform the correction progress prediction step while the correction progress confirmation step described with reference to FIG. 4 is performed.

[0110] In step S601, the processor confirms the direction and distance of each tooth to be moved, and then generates a plurality of treatment solution information based on the first tooth image and the second tooth image. time A plurality of fourth tooth images can be acquired corresponding to each of the points.

[0111] More specifically, the processor generates a plurality of second dental images in which each of the teeth in the first dental image is rearranged (corrected) based on the treatment solution information. time A plurality of fourth tooth images can be generated corresponding to each of the points. time Each point must be entered by a medical professional account and must include at least two or more time That is, the processor acquires a plurality of images based on a process of correcting the tooth arrangement corresponding to the first tooth image to the tooth arrangement corresponding to the second tooth image, and among the acquired plurality of images, selects a plurality of images input by the medical professional account. time A fourth tooth image can be acquired, one corresponding to each of the points.

[0112] According to one embodiment, the processor acquires a second dental image of the predicted dental arrangement after correction based on the treatment solution information for the patient's malocclusion type information generated by executing the correction image acquisition step (correction image acquisition step (S103)). Here, the acquired second dental image is an image of the dental arrangement corrected by rearranging the dental arrangement based on the first dental image using an artificial intelligence solution generation algorithm.

[0113] It goes without saying that the processor can thereby acquire a plurality of images including a tooth arrangement based on a process of correcting the tooth arrangement corresponding to the first tooth image to a tooth arrangement corresponding to the second tooth image. Here, the acquired plurality of images are acquired in the order of the progress of the tooth arrangement to be corrected. That is, the plurality of fourth tooth images are acquired by selecting at least two or more images based on the patient's tooth arrangement to be corrected based on the treatment solution information and inputted through the medical professional account. time The image corresponds to the point.

[0114] According to one embodiment, the processor performs a second tooth movement vector information generating step (S603) when the acquisition of the plurality of fourth tooth images is completed.

[0115] In step S603, when the generation of the plurality of fourth tooth images is completed, the processor compares each of the plurality of fourth tooth images in chronological order to generate second tooth movement vector information for the tooth arrangement included in each of the plurality of fourth tooth images. The second tooth movement vector information includes second tooth movement path information and second tooth movement direction information. Here, the second tooth movement vector information is based on the plurality of tooth movement path information and second tooth movement direction information inputted through the medical professional account. time The more points there are, the more time In other words, at least one second tooth movement vector information is generated according to the number of fourth tooth images, and since the tooth arrangements included in the plurality of fourth tooth images are different from each other, the second tooth movement vector is generated by checking the different tooth arrangements.

[0116] According to one embodiment, the second tooth movement direction information is information representing a movement distance of each tooth when correcting the patient's dental alignment based on the treatment solution information. The second tooth movement distance information is information representing a movement direction of each tooth when correcting the patient's dental alignment based on the treatment solution information.

[0117] More specifically, the processor can confirm the positions of the teeth included in each of the plurality of fourth tooth images generated based on the first tooth image and the second tooth image, and can generate second tooth movement vector information related to the distance and direction of movement of the positions of the teeth included in each of the plurality of fourth tooth images by comparing each of the plurality of fourth tooth images in chronological order.

[0118] FIG. 7 is a diagram illustrating an information generating step of a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0119] As shown in Figure 7, a method for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth, which is implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an information generating step (information generating step (S407) in Figure 4), which includes a direction checking step (S701), a distance checking step (S703), and an orthodontic current status information generating step (S705).

[0120] According to one embodiment, one or more processors (hereinafter referred to as processors) perform the direction confirmation step (S701) when the generation of the first tooth movement vector information and the second tooth movement vector information described in FIG. 4 is completed.

[0121] In step S701, when the generation of the first tooth movement vector information and the second tooth movement vector information is completed, the processor may compare the second tooth movement direction information with the first tooth movement direction information. The second tooth movement direction information is information included in the second tooth movement vector information. The first tooth movement direction information is information included in the first tooth movement vector information.

[0122] According to one embodiment, the processor checks whether an error rate of a movement axis direction (first movement axis direction) based on the first tooth movement direction information relative to a movement axis direction (second movement axis direction) based on the second tooth movement direction information is equal to or less than a predetermined error rate. The predetermined error rate referred to in the direction checking step means a coordinate error rate. The movement axis direction means a direction in which each of the patient's teeth should move based on treatment solution information. The predetermined error rate is a reference value for generating orthodontic current status information.

[0123] According to one embodiment, the processor compares the x, y, and z values ​​based on the first movement axis direction with the x, y, and z values ​​based on the second movement axis direction. The processor obtains error values ​​for each of the x, y, and z values ​​based on the first movement axis direction relative to the x, y, and z values ​​based on the second movement axis direction, and obtains absolute values ​​of the obtained error values. The processor may obtain an average value of the obtained absolute values, which is an error rate of the first tooth movement direction information relative to the second tooth movement direction information. The processor checks whether the error rate of the obtained movement direction information is equal to or less than a predetermined error rate.

[0124] According to one embodiment, the processor performs the distance confirmation step (S703) while performing the direction confirmation step.

[0125] In step S703, the processor compares the second tooth movement distance information with the first tooth movement distance information during the direction confirmation step. The second tooth movement distance information is information included in the second tooth movement vector information. The first tooth movement distance information is information included in the first tooth movement vector information.

[0126] According to one embodiment, the processor verifies whether an error rate of a movement distance (first movement distance) based on the first tooth movement distance information relative to a movement distance (second movement distance) based on the second tooth movement distance information is equal to or less than the predetermined error rate. The predetermined error rate referred to in the distance verification step means a predetermined distance error rate. The movement distance means a distance that each of the patient's teeth should move based on the treatment solution information.

[0127] In one embodiment, the processor compares a movement distance value based on the first movement distance of a specific tooth with a movement distance value based on a second movement distance of the specific tooth. The processor then obtains an error value of the first movement distance relative to the second movement distance. The obtained error value is an error rate for the movement distance. The processor then checks whether the error rate for the obtained movement distance is equal to or less than a predetermined error rate.

[0128] According to an embodiment, the processor performs the correction current status information generating step (S705) when the direction confirmation step (S701) and the distance confirmation step (S703) are completed.

[0129] In step S705, the processor acquires result information based on the execution of the direction confirmation step (S701) and the distance confirmation step (S703). The result information is information including a result of confirming whether an error rate for the movement direction is equal to or less than a predetermined error rate, and a result of confirming whether an error rate for the movement distance is equal to or less than a predetermined error rate.

[0130] For example, when the error rate for the movement direction is 4 and the predetermined error rate for the movement direction is 5, the processor determines that the error rate for the movement direction is equal to or less than a predetermined error rate. Also, when the error rate for the movement distance is 4 and the predetermined error rate for the movement distance is 7, the processor determines that the error rate for the movement distance is equal to or less than the predetermined error rate, thereby obtaining result information including the determination result. The result information includes at least one of text information, image information, and video information based on the determination result.

[0131] According to one embodiment, when the processor has completed obtaining the result information, the processor generates orthodontic current status information representing the current status of orthodontic treatment for the patient's tooth alignment based on the treatment solution information and the result information.

[0132] More specifically, the processor can analyze the cause of the error rate based on the result information using an AI solution generation algorithm (AI solution generation algorithm in FIG. 2). The AI ​​solution generation algorithm learns various data (tooth images of other patients, history data acquired during orthodontic treatment of other patients), and can derive information on the cause of the error rate based on the result information. Here, the processor uses the AI ​​solution generation algorithm to analyze each tooth whose error rate is equal to or greater than a predetermined error rate in the result information analysis, and generates orthodontic current status information representing the current status of the patient's tooth alignment based on each analyzed tooth.

[0133] The processor may also analyze the result information using the AI ​​solution generation algorithm to derive element information that may affect the orthodontic treatment of the patient's teeth. The derived information is generated as orthodontic current status information that indicates the current status of the orthodontic treatment of the patient's teeth.

[0134] According to one embodiment, the processor analyzes the result information using the artificial intelligence solution generation algorithm. If the patient's dental alignment based on the result information analyzed by the artificial intelligence solution generation algorithm is not corrected according to the treatment solution information, the processor can obtain new treatment solution information. The processor includes the generated new treatment solution information in the orthodontic current status information.

[0135] FIG. 8 is a diagram illustrating an orthodontic treatment evaluation information providing unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0136] As shown in FIG. 8, an apparatus 800 for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data (hereinafter referred to as an orthodontic current status and treatment evaluation information providing apparatus) implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors includes a target value acquiring unit 801, an orthodontic image acquiring unit 803, and an evaluation information providing unit 805.

[0137] According to one embodiment, the target value acquisition unit 801 may receive first dental scan data 801a, which is 3D scan data acquired by photographing a patient, from a medical professional account. The first dental scan data 801a is a radiological image acquired by photographing a patient. For example, the first dental scan data 801a is image data acquired by photographing a patient's head. Here, the acquired image data includes images of the patient's head and teeth. Furthermore, the first dental scan data 801a is image data acquired by photographing only the patient's teeth, i.e., the patient's teeth.

[0138] According to an embodiment, the target value acquisition unit 801 acquires a malocclusion image of the patient's teeth based on the received first dental scan data 801 a. The malocclusion image is an image of the patient's pre-orthodontic dental alignment acquired based on the first dental scan data 801 a, and is the first image including an image of the patient's malocclusion.

[0139] According to one embodiment, the target value acquisition unit 801 acquires treatment solution information based on the acquired malocclusion image. The treatment solution information is treatment information for correcting the patient's malocclusion based on the malocclusion image. Acquisition of the treatment solution information will be described in detail with reference to FIG. 9.

[0140] According to one embodiment, upon completion of acquisition of the treatment solution information, the target value acquisition unit 801 acquires correction target values ​​for correcting the patient's malocclusion based on the acquired treatment solution information. Here, in order to correct the patient's malocclusion included in the malocclusion image to a normal tooth alignment, the target value acquisition unit 801 acquires correction target direction information and correction target distance information for each of the patient's teeth corresponding to the malocclusion image based on the treatment solution information, and acquires correction target values ​​based on the acquired correction target direction information and correction target distance information. Acquisition of the correction target values ​​will be described in detail with reference to FIG. 11.

[0141] According to one embodiment, the corrected image acquisition unit 803 acquires third dental scan data, which is new 3D scan data, by photographing the patient whose orthodontic treatment has been completed using a transparent orthodontic device after the acquisition of the orthodontic target value has been completed by the target value acquisition unit 801. The third dental scan data is a radiographic image acquired by photographing the patient at the time when orthodontic treatment for the patient's malocclusion has been completed.

[0142] According to an embodiment, when the reception of the third dental scan data is completed, the corrected image acquisition unit 803 acquires a post-correction image 803a, which is an image of the corrected tooth alignment, based on the third dental scan data. The post-correction image is an image of the patient's tooth alignment after orthodontic treatment is completed using a transparent orthodontic device.

[0143] According to one embodiment, when the acquisition of the completed-orthodontic image 803a is completed, the evaluation information providing unit 805 can acquire an orthodontic achievement value for each of the corrected teeth based on the completed-orthodontic image. The orthodontic achievement value is information generated based on the orthodontic distance achievement information and the orthodontic direction achievement information for each of the teeth substantially corrected by the transparent orthodontic device.

[0144] According to one embodiment, upon completion of acquisition of the correction achievement value, the evaluation information providing unit 805 compares the correction achievement value with the correction target value to obtain error information of the correction achievement value relative to the correction target value. The error information is information generated based on whether the correction achievement value satisfies the correction target value. The evaluation information providing unit 805 generates orthodontic treatment evaluation information, which is evaluation information on the orthodontic treatment, based on the error information and provides it to a medical professional account. The orthodontic treatment evaluation information is information generated based on the error information and is information for determining whether the patient's orthodontic treatment is insufficient or effective.

[0145] FIG. 9 is a block diagram illustrating a target value acquisition unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0146] As shown in FIG. 9, an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data (apparatus 800 for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data of FIG. 8) (hereinafter referred to as orthodontic current status and treatment evaluation information providing apparatus) implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes a target value acquiring unit 900 (target value acquiring unit 801 of FIG. 8).

[0147] According to an embodiment, the target value acquisition unit 900 includes a malocclusion confirmation initiation unit 901 , a malocclusion determination unit 903 , and a solution acquisition unit 905 .

[0148] According to an embodiment, the malocclusion confirmation starting unit 901 may start a malocclusion confirmation process when receiving first dental scan data, which is 3D scan data obtained by photographing a patient, from a medical professional account. The malocclusion confirmation process is a process of confirming the patient's dental alignment from the malocclusion image, classifying the patient's dental alignment as malocclusion information among multiple malocclusion information, and determining the patient's malocclusion.

[0149] According to one embodiment, the malocclusion determination unit 903 can determine the shape and position of each tooth included in the malocclusion image using the pre-stored malocclusion confirmation algorithm to confirm the patient's dental alignment state. The malocclusion determination unit 903 classifies the patient's dental alignment into one of a plurality of malocclusion information based on the confirmed dental alignment state. More specifically, when the malocclusion determination unit 903 analyzes the malocclusion image using the pre-stored malocclusion confirmation algorithm to confirm the patient's dental alignment state, it can classify dental alignment state information corresponding to the confirmed dental alignment state into one of a plurality of malocclusion information.

[0150] According to one embodiment, the stored malocclusion confirmation algorithm is a machine learning-based algorithm that analyzes the malocclusion image and determines the shape and position of each tooth included in the malocclusion image. For example, the stored malocclusion confirmation algorithm is a PointNet-based deep learning algorithm. The malocclusion determination unit 903 uses the PointNet-based deep learning algorithm to learn previously acquired or input dental images, thereby determining the shape and position of each tooth (e.g., tooth 1, tooth 2, etc.) included in the dental image and confirming the patient's dental alignment. The stored malocclusion confirmation algorithm is also an algorithm that determines the position of the patient's mandibular condyle, the dental alignment (shape and position), the relationship between the upper and lower jaws, and the position and gradient of the maxillary and maxillary bone complex relative to the cranium from the malocclusion image.

[0151] In other words, the pre-stored malocclusion confirmation algorithm may be, but is not limited to, a deep learning algorithm based on PointNet, or an algorithm based on machine learning that can determine the patient's tooth arrangement from newly input tooth images by performing machine learning on previously acquired or input tooth images, and thereby confirm the type of malocclusion of the patient.

[0152] For example, the pre-stored malocclusion confirmation algorithm is an automatic recognition standardization algorithm, which is an algorithm based on machine learning for classifying tooth arrangement state information acquired by the malocclusion determination unit 903 by checking the shape and position of each of the patient's teeth included in the malocclusion image into one piece of malocclusion information.

[0153] According to one embodiment, when the malocclusion determination unit 903 analyzes the malocclusion image using the pre-stored malocclusion confirmation algorithm to confirm the patient's dental alignment, the unit 903 confirms at least one of the position of each of the patient's teeth included in the malocclusion image, their contact relationship with adjacent teeth, their perpendicular relationship, whether or not they can be rotated, and their inclination, using the pre-stored malocclusion confirmation algorithm. After completing confirmation of the patient's dental alignment, the malocclusion determination unit 903 obtains dental alignment status information corresponding to the confirmed dental alignment using the pre-stored malocclusion confirmation algorithm. That is, the information includes position information, contact relationship information with adjacent teeth, perpendicular relationship information with adjacent teeth, whether or not they can be rotated, and inclination information for each of the patient's teeth based on the dental alignment status information and the malocclusion image. A detailed method of classifying the dental alignment status information into one of multiple malocclusion information will be described with reference to FIG. 3.

[0154] According to one embodiment, when the malocclusion determination unit 903 classifies the tooth condition information into one of a plurality of malocclusion information, it determines that the malocclusion corresponding to the classified malocclusion information is a malocclusion with respect to the patient's tooth arrangement.

[0155] According to one embodiment, when the malocclusion determination unit 903 completes the determination of the patient's malocclusion, the solution acquisition unit 905 obtains treatment solution information for the patient's malocclusion using an AI solution generation algorithm based on machine learning that derives solutions for orthodontic treatment. The AI ​​solution generation algorithm learns various data (dental images of other patients, history data obtained during orthodontic treatment of other patients), and can therefore derive information on the cause of the error rate based on the result information.

[0156] According to one embodiment, the artificial intelligence solution generation algorithm is an algorithm for presenting visualized treatment objectives (VTO) and an optimal treatment plan for the patient's tooth alignment by machine learning the received data received by the solution acquisition unit 905 from other electronic devices (desktop, tablet PC, and medical equipment) or medical professional accounts.

[0157] According to one embodiment, when the solution acquisition unit 905 receives dental image data of another patient, it performs machine learning on the received data using learning data to acquire information regarding VTO (visualized treatment objectives) and an optimal treatment plan for the patient's dental arrangement, taking into consideration the stabilized position of the mandibular condyle, the arrangement of teeth with an appropriate angle, the relationship between the maxillary and mandibular bones, and the appropriate position and gradient of the maxillary and mandibular complex relative to the cranium.

[0158] That is, the treatment solution information includes at least one of VTO and treatment plan information generated by the AI ​​solution generation algorithm, whereby the VTO and treatment plan information include treatment method information, treatment period information, treatment medication information, etc., required to correct the patient's tooth alignment.

[0159] FIG. 10 is a diagram illustrating a malocclusion determination unit of an apparatus for providing current orthodontic condition and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0160] As shown in FIG. 10, when the malocclusion confirmation process starts, the malocclusion determination unit 1001 (the malocclusion determination unit 903 in FIG. 9) can confirm the patient's tooth arrangement from the received malocclusion image 901a.

[0161] According to an embodiment, the malocclusion determination unit 1001 determines the shape and position of each tooth included in the malocclusion image 1001a using the pre-stored malocclusion confirmation algorithm to confirm the state of the patient's tooth alignment. For a detailed description of how the malocclusion determination unit 1001 confirms the patient's tooth alignment using the pre-stored malocclusion confirmation algorithm, please refer to FIG. 9.

[0162] According to one embodiment, the malocclusion determination unit 1001 classifies the patient's dental arrangement into one of a plurality of malocclusion information based on the confirmed dental arrangement state. Here, the malocclusion determination unit 1001 checks the patient's dental arrangement and classifies the patient's dental arrangement into one of a plurality of malocclusion information based on the acquired dental arrangement state information. The plurality of malocclusion type information includes at least one of crowding malocclusion, spacing malocclusion information, rotation malocclusion information, vertical relationship (openbite & deepbite) malocclusion information, mesiodistal tipping malocclusion information, buccolingual torque malocclusion information, and interdigital malocclusion information.

[0163] According to one embodiment, when the malocclusion determination unit 1001 acquires a malocclusion image, it analyzes the malocclusion image using a pre-stored malocclusion confirmation algorithm (automatic recognition standardization algorithm) to acquire tooth arrangement status information corresponding to the patient's tooth arrangement status. The tooth arrangement status information includes not only the shape and position of each of the patient's teeth, but also the position of the patient's mandibular condyle, the relationship between the upper and lower jaw bones, and the position and gradient information of the upper and lower jaw bone complex relative to the cranium.

[0164] For example, when the malocclusion determination unit 1001 acquires the tooth arrangement state information, it starts a determination process 1003 for classifying the tooth arrangement state information into one of a plurality of malocclusion information. The malocclusion determination unit 1001 can confirm that the patient's tooth number 13 is rotated based on the tooth arrangement state information. When the tooth number 13 is rotated, the malocclusion determination unit 1001 performs a process included in 1003a. When the malocclusion determination unit 1001 confirms that the patient's teeth are not rotated based on the tooth arrangement state information, it performs a process included in 1003b. The determination process 1003 is a different process for each of a plurality of malocclusion types.

[0165] FIG. 11 is another block diagram illustrating a target value acquiring unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0166] As shown in FIG. 11, an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data (apparatus 800 for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data of FIG. 8) (hereinafter referred to as orthodontic current status and treatment evaluation information providing apparatus) implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes a target value acquiring unit 1100 (target value acquiring unit 801 of FIG. 8).

[0167] According to an embodiment, the target value acquisition unit 1100 includes a guide application unit 1101 , a virtual correction image acquisition unit 1103 , and a correction value acquisition unit 1105 .

[0168] According to one embodiment, when the solution acquisition unit (solution acquisition unit 905 in FIG. 9) completes acquisition of the treatment solution information 1101a, the target value acquisition unit 1100 can apply an orthodontic guide based on the treatment solution information 1101a to the patient's malocclusion image 1101b using a solution generation algorithm. For a detailed description of the solution generation algorithm, please refer to FIG. 9. The orthodontic guide is information to be applied to the malocclusion image 1101b representing the patient's initial tooth alignment, and is vector information for each tooth to align the patient's malocclusion based on the malocclusion image 1101b to a tooth alignment with an optimal shape that has been completely corrected based on the treatment solution information 1101a.

[0169] According to one embodiment, the virtual orthodontic image acquisition unit 1103 applies an orthodontic guide based on the treatment solution information 1101a to the malocclusion image 1101b to virtually arrange each of the patient's teeth in a dental state after orthodontic treatment, thereby acquiring a virtual orthodontic image 1103a, which is a virtual image corresponding to the dental arrangement after orthodontic treatment.

[0170] According to one embodiment, the virtual orthodontic image acquisition unit 1103 modifies the vector information of each tooth included in the malocclusion image 1101b based on the vector information of each tooth based on the orthodontic guide, and acquires the virtual orthodontic image 1103a corresponding to the patient's corrected tooth arrangement based on the treatment solution information 1101a.

[0171] According to one embodiment, upon completion of acquisition of the virtual correction image 1103a, the correction value acquisition unit 1105 compares the virtual correction image 1103a with the malocclusion image 1101b. More specifically, the correction value acquisition unit 1105 compares vector information for each tooth included in the virtual correction image 1103a with vector information for each tooth included in the malocclusion image 1101b to acquire correction target direction information and correction target distance information for each tooth. The correction target direction information is information regarding the direction in which the maloccluded teeth should move in order to be corrected to the alignment of the maloccluded state. The correction target distance information is information regarding the distance in which the maloccluded teeth should move in order to be corrected to the alignment of the maloccluded state.

[0172] According to one embodiment, the correction value acquisition unit 1105 calculates the correction target direction information and the correction target distance information based on a predetermined formula to acquire the correction target value. The predetermined formula varies depending on the company or institution implementing the present invention. The correction target value is a value indicating the degree to which the maloccluded teeth should be moved in order to be corrected to the corrected alignment. In other words, the correction target value is a target value by which each tooth based on the malocclusion image should be moved in order to be formed into the corrected alignment.

[0173] FIG. 12 is a block diagram illustrating an evaluation information providing unit of an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0174] As shown in FIG. 12, an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data (apparatus 800 for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data of FIG. 8) (hereinafter referred to as orthodontic current status and treatment evaluation information providing apparatus) implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an evaluation information providing unit 1200 (evaluation information providing unit 805 of FIG. 8).

[0175] According to an embodiment, the evaluation information providing unit 1200 includes an achievement value obtaining unit 1201 , an error value checking unit 1203 , and an error information analyzing unit 1205 .

[0176] According to an embodiment, when the acquisition of the post-correction image is completed from the post-correction image acquisition unit (post-correction image acquisition unit 803 in FIG. 8), the achievement value acquisition unit 1201 analyzes the post-correction image using a pre-stored malocclusion confirmation algorithm to acquire a correction achievement value 1201b for each of the patient's corrected teeth. For a detailed description of the pre-stored malocclusion confirmation algorithm, please refer to FIG. 9.

[0177] According to one embodiment, when the acquisition of a post-correction image of the patient's teeth arrangement that has undergone orthodontic treatment using a transparent orthodontic device is completed, the achievement value acquisition unit 1201 can confirm the state of the patient's teeth arrangement based on the post-correction image using a pre-stored malocclusion confirmation algorithm. The achievement value acquisition unit 1201 confirms the state of the patient's teeth arrangement based on the post-correction image, and thereby acquires a post-correction value 1201b for each of the teeth. The post-correction value 1201b is information including information on the direction of post-correction and information on the distance of post-correction, and is vector information for each tooth. The post-correction value 1201b is a value obtained by calculating the information on the direction of post-correction and the information on the distance of post-correction using a predetermined formula.

[0178] According to one embodiment, upon completing acquisition of the correction achievement value 1201b, the error value confirmation unit 1203 compares a correction target value 1201c (the correction target value in FIG. 11) with the correction achievement value 1201b. For a detailed description of the correction target value 1201c, refer to FIG. 11. The error value confirmation unit 1203 compares the correction target value 1201c with the correction achievement value 1201b to acquire an error value 1201d of the correction achievement value 1201b with respect to the correction target value 1201c. The error value confirmation unit 1203 determines whether the acquired error value 1201d is included in a predetermined error value range 1201e.

[0179] The configuration of 1201 in Fig. 12 is a record table stored by the error value confirmation unit 1203. For example, the error value confirmation unit 1203 compares the orthodontic achievement value for tooth No. 13 acquired by the achievement value acquisition unit 1201 with the orthodontic target value for tooth No. 13. The error value confirmation unit 1203 compares the orthodontic achievement value for tooth No. 13 (11,391.16) with the orthodontic target value for tooth No. 13 (12,252.27) to acquire an error value of 207.88. Here, the error value confirmation unit 1203 determines whether the acquired error value is within a predetermined error value range. The predetermined error value differs for each tooth and for each type of malocclusion.

[0180] According to one embodiment, the error information analysis unit 1205 generates error information based on the result determined by executing the function of the error value confirmation unit 1203. The error information is information regarding whether the error value for each tooth is equal to or less than a predetermined error value. That is, the error information includes information regarding the orthodontic achievement value, orthodontic target value, error value, and predetermined error value for each tooth.

[0181] According to one embodiment, the error information analysis unit 1205 analyzes the generated error information using an AI solution generation algorithm to generate orthodontic treatment evaluation information. For a detailed description of the AI ​​solution generation algorithm, see FIG. 9 . The error information analysis unit 1205 analyzes the error information using the AI ​​solution generation algorithm. More specifically, if the error information analysis unit 1205 determines, based on the error information, that an error value is not included in a predetermined error value, it can determine that the orthodontic treatment for the malocclusion has failed. Furthermore, if the error information analysis unit 1205 determines, based on the error information, that an error value is included in a predetermined error value, it can determine that the orthodontic treatment for the malocclusion has been successful.

[0182] According to one embodiment, the error information analysis unit 1205 checks the success or failure of orthodontic treatment for each of the patient's teeth based on the error information, and generates orthodontic treatment evaluation information based on the check result.

[0183] According to one embodiment, when the error information analysis unit 1205 determines based on the error information that the error value is outside a predetermined error range, it generates orthodontic treatment evaluation information indicating that the orthodontic treatment for the malocclusion has not been performed sufficiently. Here, the error information analysis unit 1205 derives, using the AI ​​solution generation algorithm, cause information indicating why the error value is outside a predetermined error value range, and generates orthodontic improvement information for resolving the cause based on the cause information. The orthodontic improvement information is information generated by the AI ​​solution generation algorithm and is model treatment information derived based on orthodontic treatment history information of other patients learned by the AI ​​solution generation algorithm. In other words, the error information analysis unit 1205 can present orthodontic guides for the teeth that have failed to be orthodontic treated based on the model treatment information.

[0184] According to one embodiment, when the error information analysis unit 1205 determines that the error value is within a predetermined error range based on the error information, it generates orthodontic treatment evaluation information indicating that the orthodontic treatment for the malocclusion has been sufficiently performed. Here, the error information analysis unit 1205 may derive complementary point information for each tooth that has been completely corrected using the AI ​​solution generation algorithm. For example, the complementary point information may include information regarding the recommended wearing period of the transparent orthodontic device or information regarding precautions to ensure that each tooth is completely fixed in its corrective position.

[0185] According to one embodiment, the error information analysis unit 1205 checks the error value based on the error information and determines which of a predetermined error value range the checked error value falls within. The predetermined error value range includes at least two status ranges. For example, the predetermined error value range includes an excellent range, a good range, and a further treatment recommended range. If the error information analysis unit 1205 determines that the error value falls within the excellent range, it generates orthodontic treatment evaluation information indicating that the orthodontic treatment for the malocclusion has been effectively performed. For example, if the error information analysis unit 1205 determines that the error value falls within the treatment recommended range, it can determine that the orthodontic treatment for the malocclusion has been performed based on the treatment solution information, but that insufficiencies have occurred. Accordingly, in generating the orthodontic treatment evaluation information, the error information analysis unit 1205 analyzes insufficiencies using the artificial intelligence solution generation algorithm, obtains treatment supplement information to supplement the insufficiencies, and includes the obtained treatment supplement information in the orthodontic treatment evaluation information.

[0186] FIG. 13 is a diagram illustrating an interface of a device for providing orthodontic current status and orthodontic treatment evaluation information based on scan data of a patient's teeth according to an embodiment of the present invention.

[0187] As shown in FIG. 13, an apparatus for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data (apparatus 800 for providing orthodontic current status and orthodontic treatment evaluation information based on dental scan data of FIG. 8) (hereinafter referred to as orthodontic current status and treatment evaluation information providing apparatus) implemented by a computing device including one or more processors and one or more memories storing instructions executable by the processors, includes an evaluation information providing unit (evaluation information providing unit 805 of FIG. 8).

[0188] According to an embodiment, the evaluation information providing unit includes a correction device design generating unit (not shown) and a correction device design providing unit.

[0189] According to one embodiment, the evaluation information providing unit provides orthodontic treatment evaluation information including model treatment information to a medical professional account, and causes the orthodontic device design generating unit to generate a first design plan, which is design plan information for a transparent orthodontic device based on the model treatment information.

[0190] According to one embodiment, the orthodontic device design generation unit generates a first design, which is design information for the patient's corrected tooth alignment, based on the model treatment information. Here, the generated first design is design information for manufacturing a new transparent orthodontic device (second transparent orthodontic device) to compensate for insufficient parts of orthodontic treatment after correcting the patient's initial tooth alignment with a transparent orthodontic device (first transparent orthodontic device).

[0191] According to one embodiment, when the generation of the first design plan is completed, the orthodontic device design providing unit obtains second design plan information, which is a transparent orthodontic device design plan based on the correction target value, and provides the medical professional account with an interface 1300 that allows the medical professional to compare the first design plan and the second design plan. That is, the orthodontic device design providing unit provides the medical professional account with an interface 1300 that allows the medical professional to visually confirm a first transparent orthodontic device 1301 based on the second design plan and a second transparent orthodontic device 1303 based on the first design plan.

[0192] According to one embodiment, while the evaluation information providing unit provides images of the first and second transparent orthodontic devices to the medical professional account via the interface 1300, if doctor's opinion information for modifying the design of the second transparent orthodontic device is received from the medical professional account, the evaluation information providing unit can modify the first design plan based on the input doctor's opinion information. The doctor's opinion information is design modification information for modifying the first design plan. That is, a user of the medical professional account can confirm the patient's dental alignment, and if further design modifications to the design plan are necessary, can modify the design based on the first design plan by inputting the doctor's opinion information into the interface.

[0193] The configuration 1305 in FIG. 13 is a menu for modifying the first design plan and is one of the functions included in the interface 1300. A user of a medical professional account can use the configuration 1305 to enlarge the image of each tooth in detail. When the evaluation information providing unit receives doctor's opinion information, which is input information for modifying the enlarged tooth, from the medical professional account while the tooth image is enlarged in detail, the evaluation information providing unit can modify the position and shape of the enlarged tooth based on the received doctor's opinion information. Here, the tooth included in the image is a 3D modeling image, which can be obtained when analyzing a tooth image using a pre-stored malocclusion confirmation algorithm.

[0194] FIG. 14 is a diagram illustrating an example of the internal configuration of a computing device according to an embodiment of the present invention.

[0195] FIG. 14 shows an example of the internal configuration of a computing device according to an embodiment of the present invention, and in the following description, any description that overlaps with the description regarding FIGS. 1 to 13 will be omitted.

[0196] 14, the computing device 10000 includes at least one processor 11100, a memory 11200, a peripheral device interface 11300, an input / output subsystem 11400, a power circuit 11500, and a communication circuit 11600. Here, the computing device 10000 corresponds to a user terminal (A) connected to a haptic interface device or the computing device (B).

[0197] The memory 11200 may include, for example, high-speed random access memory, a magnetic disk, an SRAM, a DRAM, a ROM, a flash memory, or a non-volatile memory. The memory 11200 may include software modules, command sets, or various other data required for the operation of the computing device 10000.

[0198] Here, access to the memory 11200 from other components such as the processor 11100 and the peripheral device interface 11300 is controlled by the processor 11100.

[0199] The peripheral interface 11300 couples input and / or output peripherals of the computing device 10000 to the processor 11100 and memory 11200. The processor 11100 executes software modules or sets of commands stored in the memory 11200 to perform various functions and process data for the computing device 10000.

[0200] The I / O subsystem 11400 couples various I / O peripherals to the peripheral interface 11300. For example, the I / O subsystem 11400 includes controllers for coupling peripherals such as a monitor, keyboard, mouse, printer, and, if desired, a touch screen or sensor to the peripheral interface 11300. In another aspect, I / O peripherals can also be coupled to the peripheral interface 11300 without going through the I / O subsystem 11400.

[0201] The power circuit 11500 can supply power to all or some of the components of the terminal device. For example, the power circuit 11500 can include a power management system, one or more power sources such as a battery or alternating current (AC), a charging system, a power failure detection circuit, a power converter or inverter, a power status indicator, or any other component for power generation, management, or distribution.

[0202] The communications circuitry 11600 allows for communication with other computing devices using at least one external port.

[0203] Alternatively, as mentioned above, if desired, the communications circuitry 11600 may include RF circuitry to enable communication with other computing devices by sending and receiving RF signals, also known as electromagnetic signals.

[0204] The embodiment of Fig. 14 is merely one example of computing device 10000, and computing device 11000 may omit some of the components in Fig. 14, include additional components in Fig. 14, or have a configuration or arrangement in which two or more components are combined. For example, a computing device for a communication terminal in a mobile environment may further include a touch screen, a sensor, etc. in addition to the components shown in Fig. 14, and communication circuit 11600 may include circuits for RF communication of various communication methods (Wi-Fi, 3G, LTE, Bluetooth (registered trademark), NFC, Zigbee (registered trademark), etc.). The components included in computing device 10000 may be embodied as hardware, software, or a combination of both hardware and software, including one or more signal processing or application-specific integrated circuits.

[0205] Methods according to embodiments of the present invention may be implemented in the form of program instructions executed by various computing devices and recorded on a computer-readable medium. In particular, the program according to this embodiment may be a PC-based program or an application dedicated to mobile terminals. The application to which the present invention is applied is installed in a user terminal through a file provided by a file distribution system. For example, the file distribution system may include a file transmission unit (not shown) that transmits the file at the request of the user terminal.

[0206] The devices described above may be implemented using hardware components, software components, and / or a combination of hardware and software components. For example, the devices and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as a processor, controller, arithmetic logic unit (ALU), digital signal processor, microcomputer, field programmable gate array (FPGA), programmable logic unit (PLU), microprocessor, or any other device that executes and responds to instructions. The processing device may execute an operating system (OS) and one or more software applications that run on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, the processing device may be described as being a single processing element, but those skilled in the art will recognize that the processing device may include multiple processing elements and / or multiple types of processing elements. For example, the processing device may include multiple processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

[0207] Software includes computer programs, codes, instructions, or a combination of one or more of these, which can configure or independently or collectively instruct a processing device to operate as desired. The software and / or data can be permanently or temporarily embodied in any type of machine, component, physical device, virtual device, computer storage medium, or device to be analyzed by the processing device or to provide instructions or data to the processing device. The software can also be distributed across network-coupled computing devices and stored or executed in a distributed manner. The software and data can be stored on one or more computer-readable recording media.

[0208] Methods according to the embodiments may be embodied in the form of program instructions executed by various computer means and recorded on a computer-readable medium. The computer-readable medium may include, alone or in combination, program instructions, data files, data structures, and the like. The program instructions recorded on the medium may be those specially designed and constructed for the embodiments, or may be those known and available to those skilled in the art of computer software. Computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, and flash memory. Program instructions include not only machine language code, such as produced by a compiler, but also high-level language code executable by a computer using an interpreter, for example. The hardware devices may be configured to operate as one or more software modules to perform the operations of the embodiments, or vice versa.

[0209] Although the above embodiments have been described by way of limited examples and drawings, those skilled in the art will appreciate that various modifications and variations may be made from the foregoing description. For example, the described techniques may be performed in a different order than described, and / or the described system, structure, device, circuit, or other components may be combined or combined in a different manner than described, or may be substituted or replaced by other components or equivalents, while still achieving suitable results. Therefore, other implementations, other embodiments, and equivalents of the claims are also within the scope of the following claims.

Claims

1. 1. A method for providing orthodontic status and treatment evaluation information based on scan data of a patient's teeth, the method being implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processors, comprising: an initial image acquisition step of acquiring a first dental image, which is an image of the patient's dental arrangement, based on first dental scan data received when first dental scan data, which is three-dimensional scan data acquired by photographing the patient's head including the patient's dental area, is received; an orthodontic image acquisition step of, when acquisition of the first dental image is completed, confirming a tooth arrangement state based on the first dental image using a pre-stored algorithm, acquiring treatment solution information for correcting the tooth arrangement based on the confirmed tooth arrangement state, and acquiring a second dental image which is an image of a predicted tooth arrangement at the completion of orthodontics based on the acquired treatment solution information; an orthodontic device design generation step of generating a design drawing of a transparent orthodontic device for correcting the patient's dental alignment to a dental alignment corresponding to the second dental image, when acquisition of the second dental image is completed; an intermediate image acquisition step of acquiring a third dental image, which is an image of the patient's dental alignment being corrected, based on the received second dental scan data when new three-dimensional scan data, which is second dental scan data, is received during the process of correcting the patient's dental alignment by having the patient wear the transparent orthodontic device based on the generated design; and (c) providing orthodontic current status information for the patient based on the scan data of the patient's teeth, the orthodontic current status information providing step of obtaining tooth movement vector information for the patient from the first tooth image, the second tooth image, and the third tooth image after the acquisition of the third tooth image is completed, and generating orthodontic current status information for the patient's orthodontic treatment based on the obtained tooth movement vector information and providing the generated orthodontic current status information to a medical professional account, wherein the orthodontic current status information providing step includes a step of comparing the tooth movement vector information for the patient with orthodontic target values ​​derived based on the treatment solution information, and calculating an error rate of the direction and distance that each tooth should move.

2. The correction image acquisition step includes: a process initiation step of initiating a malocclusion confirmation process upon completion of acquisition of the first dental image; a malocclusion classification step of analyzing the first dental image by the pre-stored algorithm at the start of the malocclusion confirmation process, acquiring information on the patient's tooth arrangement state, and classifying the acquired information on the tooth arrangement state into one of a plurality of malocclusion type information; and a solution information obtaining step of obtaining treatment solution information for the classified malocclusion type information by an artificial intelligence solution generation algorithm based on machine learning that derives a solution for orthodontic treatment when the tooth alignment status information is classified into one of the plurality of malocclusion type information.

3. 2. The method of claim 1, wherein the orthodontic current status information providing step obtains tooth movement vector information for each of the patient's teeth based on a common point included in a first head image corresponding to the first dental scan data and a second head image corresponding to the second dental scan data.

4. 4. The method for providing orthodontic current status and orthodontic treatment evaluation information based on a patient's dental scan data according to claim 3, wherein the common points are common points located on the patient's head included in the first head image and the second head image, and are at least three or more points that do not change even when orthodontic treatment is performed on the patient's dental alignment, and are reference points for overlaying the first dental image, the second dental image, and the third dental image.

5. The correction status information providing step includes: an image superimposition step of superimposing the first dental image, the second dental image, and the third dental image based on a common point included in the first head image and the second head image to generate a prognostic image; an orthodontic progress confirmation step of comparing the tooth arrangement corresponding to the first tooth image and the tooth arrangement corresponding to the third tooth image based on the prognostic image when the generation of the prognostic image is completed, confirming the direction and distance of movement of each tooth, and generating first tooth movement vector information including first tooth movement direction information and first tooth movement distance information; an orthodontic progress prediction step of comparing the tooth arrangement corresponding to the first tooth image with the tooth arrangement corresponding to the second tooth image based on the prognosis image while the orthodontic progress confirmation step is being performed, to confirm the direction and distance of each tooth's planned movement, and generating second tooth movement vector information including second tooth movement direction information and second tooth movement distance information; and an information generation step of starting an information generation process for generating orthodontic current status information based on the first tooth movement vector information and the second tooth movement vector information upon completion of acquisition of the first tooth movement vector information and the second tooth movement vector information.

6. 6. The method of claim 5, wherein the image superimposition step applies a graphic effect to the first dental image, the second dental image, and the third dental image, which are superimposed based on the common point, to visually distinguish them from one another to generate the prognostic image.

7. The orthodontic progress prediction step includes: a fourth tooth image acquisition step of generating a plurality of fourth tooth images corresponding to a plurality of time points based on the treatment solution information from the first tooth image and the second tooth image in confirming the direction and distance of the intended movement of each of the teeth; a second tooth movement vector information generating step of comparing each of the fourth tooth images in order of progression when the generation of the fourth tooth images is completed, and generating the second tooth movement vector information for the tooth arrangement included in each of the fourth tooth images; 6. The method for providing orthodontic status and orthodontic treatment evaluation information based on a patient's dental scan data as claimed in claim 5, wherein each of the plurality of time points is at least two or more time points entered by the medical professional account.

8. The information generating step includes: a direction confirmation step of comparing the second tooth movement direction information with the first tooth movement direction information when the generation of the first tooth movement vector information and the second tooth movement vector information is completed, and confirming whether an error rate of the movement axis direction based on the first tooth movement direction information with respect to the movement axis direction based on the second tooth movement direction information is equal to or less than a predetermined error rate; a distance confirmation step of comparing the second tooth movement distance information with the first tooth movement distance information while the direction confirmation step is being performed, and confirming whether an error rate of the movement distance based on the first tooth movement distance information relative to the movement distance based on the second tooth movement distance information is equal to or less than the predetermined error rate; and an orthodontic current status information generating step of generating the orthodontic current status information representing the current status of orthodontic treatment for the patient's teeth alignment based on the result information obtained based on the execution of the direction confirmation step and the distance confirmation step, according to claim 7.

9. The method for providing orthodontic current status and orthodontic treatment evaluation information based on the patient's dental scan data further includes providing orthodontic treatment evaluation information, The orthodontic treatment evaluation information providing step includes: a target value acquisition step of acquiring a malocclusion image of the patient's teeth based on the first dental scan data, acquiring treatment solution information based on the acquired malocclusion image, and acquiring a correction target value for correcting the patient's malocclusion based on the acquired treatment solution information, when the execution of the function of the first image acquisition step is completed; a completed-orthodontic image acquisition step of acquiring a completed-orthodontic image, which is an image of the corrected tooth arrangement, based on third dental scan data, which is new three-dimensional scan data acquired by photographing a patient whose orthodontic treatment has been completed using the transparent orthodontic device, when the acquisition of the orthodontic target value has been completed; 2. The method for providing orthodontic treatment status and orthodontic treatment evaluation information based on the scan data of a patient's teeth according to claim 1, further comprising: acquiring an orthodontic treatment achievement value for each of the orthodontic-treated teeth based on the acquired orthodontic-completed image; comparing the orthodontic treatment achievement value with the orthodontic target value to acquire error information; and generating orthodontic treatment evaluation information, which is evaluation information for the orthodontic treatment, based on the acquired error information and providing the evaluation information to the medical professional account.

10. The target value acquisition step includes: a malocclusion confirmation initiation step of initiating a malocclusion confirmation process upon receiving the first dental scan data from the medical professional account; a malocclusion determination step of analyzing the malocclusion image using a previously stored malocclusion determination algorithm when the malocclusion confirmation process starts, determining the patient's tooth alignment from the analyzed malocclusion image, and classifying the determined tooth alignment into one of a plurality of malocclusion information to determine the patient's malocclusion; and a solution obtaining step of obtaining treatment solution information for the patient's malocclusion using an artificial intelligence solution generation algorithm based on machine learning that derives a solution for orthodontic treatment once the determination of the patient's malocclusion is completed.

11. 11. The method of claim 10, wherein the malocclusion determination step checks at least one of the position, contact relationship with adjacent teeth, perpendicular relationship, rotational possibility, and inclination of each of the patient's teeth included in the malocclusion image using the pre-stored malocclusion confirmation algorithm in checking the patient's tooth alignment.

12. The target value acquisition step includes: a guide application step of applying an orthodontic guide based on the treatment solution information to the malocclusion image by the artificial intelligence solution generation algorithm when acquisition of the treatment solution information is completed by executing the function of the solution acquisition step; a virtual orthodontic image acquisition step of arranging each of the patient's teeth in a dental state after orthodontic treatment is completed by applying an orthodontic guide based on the treatment solution information to the malocclusion image, thereby acquiring a virtual orthodontic image, which is a virtual image corresponding to the dental arrangement after orthodontic treatment is completed; and a correction value acquisition step of acquiring the correction target values, which are reference values ​​for correcting the patient's malocclusion, by comparing the virtual orthodontic image with the malocclusion image to acquire orthodontic target direction information and orthodontic target distance information for each tooth after acquisition of the virtual orthodontic image is completed.

13. The evaluation information providing step includes: an achievement value acquiring step of acquiring the orthodontic achievement value for each of the patient's corrected teeth by analyzing the orthodontic achievement value acquired by acquiring the orthodontic achievement value by the stored malocclusion confirmation algorithm when the orthodontic achievement value is acquired by executing the function of the orthodontic achievement value acquiring step; an error value confirmation step of comparing the correction target value with the correction achieved value when the acquisition of the correction achieved value is completed, acquiring an error value of the correction achieved value relative to the correction target value, and determining whether the acquired error value is within a predetermined error value range; and an error information analysis step of generating error information based on the result determined by executing the function of the error value confirmation step, and analyzing the generated error information using the artificial intelligence solution generation algorithm to generate the orthodontic treatment evaluation information.

14. The orthodontic treatment evaluation information is information that determines whether the orthodontic treatment for each of the patient's teeth has been successful or not based on the error information, and includes orthodontic improvement information for correcting each of the teeth for which the orthodontic treatment has failed, if the orthodontic treatment for each of the patient's teeth based on the error information has been confirmed to be unsuccessful, The method for providing orthodontic current status and orthodontic treatment evaluation information based on a patient's dental scan data, as described in claim 13, wherein the orthodontic improvement information is information generated by the artificial intelligence solution generation algorithm and is model treatment information derived based on orthodontic treatment history information of other patients learned by the artificial intelligence solution generation algorithm.

15. The evaluation information providing step provides orthodontic treatment evaluation information including the model treatment information to the medical professional account, and a corrective device design generating step generates a first design plan, which is design plan information of the transparent corrective device based on the model treatment information. and (c) providing an orthodontic device design, when the generation of the first design plan is completed, by obtaining a second design plan, which is design plan information of a transparent orthodontic device based on the orthodontic target value, and providing an interface for comparing the first design plan and the second design plan to the medical professional account.

16. 16. The method of claim 15, wherein the interface modifies the first design plan based on doctor's opinion information when doctor's opinion information for redesigning the transparent orthodontic device is received from the medical professional account.

17. 1. An apparatus for providing orthodontic status and treatment evaluation information based on dental scan data of a patient, the apparatus comprising: a computing device including one or more processors and one or more memories storing instructions executable by the processors; an initial image acquisition unit that acquires a first dental image, which is an image of the patient's dental arrangement, based on first dental scan data received when first dental scan data, which is three-dimensional scan data acquired by photographing the patient's head including the patient's dental area, is received; an orthodontic image acquisition unit that, when acquisition of the first dental image is completed, confirms a tooth arrangement state based on the first dental image using a pre-stored algorithm, acquires treatment solution information for correcting the tooth arrangement based on the confirmed tooth arrangement state, and acquires a second dental image that is an image of a predicted tooth arrangement at the time of completion of orthodontics based on the acquired treatment solution information; an orthodontic device design generation unit that generates a design drawing of a transparent orthodontic device for correcting the patient's dental alignment to a dental alignment corresponding to the second dental image when acquisition of the second dental image is completed; an intermediate image acquisition unit that, when second dental scan data, which is new 3D scan data, is received during the process of correcting the patient's dental alignment by having the patient wear the transparent orthodontic device based on the generated design, acquires a third dental image, which is an image of the patient's dental alignment being corrected, based on the received second dental scan data; and an orthodontic current status information providing unit that, when acquisition of the third tooth image is completed, acquires tooth movement vector information of the patient from the first tooth image, the second tooth image, and the third tooth image, generates orthodontic current status information for the patient's orthodontic treatment based on the acquired tooth movement vector information, and provides the generated orthodontic current status information to a medical professional account, wherein the orthodontic current status information providing unit compares the tooth movement vector information of the patient with orthodontic target values ​​derived based on the treatment solution information, and calculates an error rate of the direction and distance each tooth should move.

18. A computer-readable recording medium, The computer-readable medium stores instructions for causing a computing device to perform the following steps, the steps comprising: an initial image acquisition step of acquiring a first dental image, which is an image of the patient's dental arrangement, based on first dental scan data received when first dental scan data, which is three-dimensional scan data acquired by photographing the patient's head including the patient's dental area, is received; an orthodontic image acquisition step of, when acquisition of the first dental image is completed, confirming a tooth arrangement state based on the first dental image using a pre-stored algorithm, acquiring treatment solution information for correcting the tooth arrangement based on the confirmed tooth arrangement state, and acquiring a second dental image which is an image of a predicted tooth arrangement at the completion of orthodontics based on the acquired treatment solution information; an orthodontic device design generation step of generating a design drawing of a transparent orthodontic device for correcting the patient's dental alignment to a dental alignment corresponding to the second dental image, when acquisition of the second dental image is completed; an intermediate image acquisition step of acquiring a third dental image, which is an image of the patient's dental alignment being corrected, based on the received second dental scan data when new three-dimensional scan data, which is second dental scan data, is received during the process of correcting the patient's dental alignment by having the patient wear the transparent orthodontic device based on the generated design; and a step of providing orthodontic current status information for the patient, wherein, upon completion of acquisition of the third tooth image, tooth movement vector information of the patient is acquired from the first tooth image, the second tooth image, and the third tooth image, and generating orthodontic current status information for the patient's orthodontic treatment based on the acquired tooth movement vector information and providing the generated orthodontic current status information to a medical professional account, wherein the orthodontic current status information providing step includes a step of comparing the tooth movement vector information of the patient with orthodontic target values ​​derived based on the treatment solution information, and calculating an error rate of the direction and distance each tooth should move.

Images