KR20210083478A - Mobile based self-oral examination device - Google Patents

Abstract

The present invention relates to a mobile-based self-oral examination apparatus that enables a user to examine his or her oral conditions by easily performing self-oral examination through a mobile application, and enables the user to manage the oral cavity of every family member. In accordance with the present invention, a user terminal corrects an oral image of a user, provides the corrected oral image and makes a request for oral examination diagnosis. An oral management service server transmits the oral image provided from the user terminal to make a request for oral examination diagnosis, and transmit an oral examination diagnosis result to the user. An oral health management server generates oral health information through diagnosis on the transmitted oral image, and encrypts the oral health information to transmit the same to the oral management service server as an oral examination diagnosis result. Therefore, real-time oral diagnosis is possible through oral images, and family oral management can be integrally performed through a mobile-based oral examination application.

Description

Mobile based self-oral examination device

The present invention relates to a mobile-based self-oral examination device, and more particularly, to a mobile-based self-examination device that allows a user to easily self-examine the oral cavity through a mobile application to check the oral condition, and to manage the oral cavity of all family members. It relates to a self-examination device.

Although oral diseases can be highly preventable through proper preventive treatment and continuous management, many patients with oral diseases are still aware of oral prevention, such as not receiving a diagnosis or referral to a doctor unless there is a problem with oral health. This is insufficient.

In addition, in predicting the patient's current oral condition, accurate examination and diagnosis results and objective numerical information are required, not the subjective opinion of a dentist or dental hygienist, but there is no system for objectively calculating the oral health condition. .

The two major diseases of the oral cavity are tooth decay (dental caries) and periodontal disease. In particular, periodontal disease, which means periodontitis and gingivitis, is difficult to prevent in advance because there is no pain in the initial stage and is delayed because it progresses chronically.

Therefore, various methods for diagnosing the condition of oral diseases in advance, and based on this, various methods for improving oral health and preventing oral diseases have been studied and proposed, and the conventionally proposed technology based on these studies is described in the following <Patent Document 1> to <Patent Document 3> are disclosed.

<Patent Document 1> receives user condition information including information on at least one of a user's gender, age, periodontal disease, and goal setting information from a user terminal and treatment information at a user's affiliated medical institution. In addition, information on oral care products is received from an oral care product store. Thereafter, information on a specific oral care product included in a specific category corresponding to the user's condition information and treatment information is provided to the user terminal to provide a user-customized oral care service.

In addition, <Patent Document 2> examines the oral condition of the patient, converts the oral examination index calculation standard data including the oral examination data of the patient into big data, and analyzes it and analyzes the patient's oral examination index data including the patient's oral examination data at the present time. The influence of the oral examination index calculation standard data on oral health is determined according to the region of residence and age. Then, weight is given to the oral examination index calculation standard data to digitize the reference data for oral examination index calculation to manage oral health.

In addition, <Patent Document 3> collects the user's personal information, the user's oral hygiene behavior data and oral questionnaire data, and oral examination data generated by the user visiting a specialized medical institution. By integrating and analyzing each information collected in this way, the user's risk of oral disease is evaluated and personalized service is provided.

However, the conventional oral disease management systems as described above are a method of generating oral disease management information by analyzing the user's personal information, oral data and questionnaire data, and oral examination data generated through a specialized medical institution. Since it is not a method to analyze oral images, there is a disadvantage in that it lacks accuracy in the analysis of oral diseases.

In addition, conventional techniques have a disadvantage in that it is difficult for a user to recognize his or her periodontal disease state in real time.

In addition, conventional techniques have a disadvantage in that the oral care of the family cannot be managed integrally.

Republic of Korea Patent Publication 10-2017-0050467 (published on May 11, 2017) (User-customized oral care service providing method and oral care service providing server) Republic of Korea Patent Registration 10-1868979 (registered on June 12, 2018) (Oral health management system and method using deep learning algorithm) Republic of Korea Patent Registration 10-1788030 (Registered on October 13, 2017) (Oral disease risk diagnosis and oral care system and method)

Therefore, the present invention has been proposed to solve all the problems occurring in the prior art as described above, and through a mobile application, a user can easily self-examine the oral cavity to check the oral condition, and to manage the oral cavity of all family members. The purpose is to provide a mobile-based self-examination device that allows

In order to achieve the above object, the "mobile-based self-oral examination apparatus" according to the present invention provides a user terminal for providing a corrected oral image after correcting the user's oral image and requesting an oral examination diagnosis; an oral care service server for requesting an oral examination diagnosis by transmitting an oral image provided from the user terminal, and transmitting an oral examination diagnosis result to the user; An oral health management server that generates oral health information by diagnosing the oral image transmitted from the oral care service server, and encrypts the generated oral health information to transmit the oral health checkup diagnosis result to the oral care service server do it with

In the above, the user terminal, the oral care service server, and the oral health management server improve security even when data is leaked by hacking through the transmission and reception of the encrypted oral examination diagnosis result.

In the above, the oral health management server is characterized in that it improves security by limiting the authority of the access target by using an access token using the user terminal ID and user information when transmitting the oral examination diagnosis result.

In the above, the user terminal includes: a photo input unit for inputting a photograph of the taken oral image as an oral health examination target image; a photo correction unit for increasing the sharpness by correcting the oral image input from the photo input unit; The oral image corrected by the photo correction unit is transmitted to the oral care service server to request an oral examination diagnosis, and the received oral examination diagnosis result is displayed on the screen, and according to the request through the user's key input, a hospital reservation or family It is characterized in that it includes an oral care service processing unit that provides oral care services.

In the above, the user terminal is characterized in that it further comprises a questionnaire response unit for generating the questionnaire response information by using the user's answer information to the oral examination questionnaire.

In the above, the oral care service processing unit requests an oral health checkup using only the oral image corrected by the photo correction unit and user personal information when the user selects a simple checkup in the checkup mode, and the user performs a general checkup in the checkup mode When selected, the oral health examination is requested using the oral image corrected by the photo correction unit, the questionnaire response information generated by the questionnaire response unit, and the user's personal information.

In the above, the oral health management server learns the received oral photograph with a CNN (Convolutional Neural Network) algorithm, which is an artificial intelligence algorithm, determines whether the photograph can be analyzed, whether or not to correct it, and whether or not to extract it, and uses the determined result information to detect objects (Object Detection). ) to obtain dental caries state information and prosthesis state information, and an oral health calculation unit for learning the acquired dental caries state information and prosthesis state information with an Artificial Neural Network (ANN) algorithm to determine the oral health state; and an oral health information providing unit that generates the oral health information determined by the oral health calculation unit as an oral examination diagnosis result, and encrypts the generated oral examination diagnosis result and transmits it to the user terminal.

The oral health calculation unit includes: a photo registration unit for registering an oral photograph transmitted from the user terminal as an oral health prediction target; The image registered in the photo register is learned with a CNN (Convolutional Neural Network) algorithm to determine whether the photo can be analyzed, whether to correct or not, and whether or not to extract, and analyze the determined result information by object detection to obtain dental caries status information. and an oral diagnostic unit that acquires prosthesis status information and determines oral health status by learning the acquired orthodontic status information, tooth extraction status information, dental caries status information, and prosthesis status information with an Artificial Neural Network (ANN) algorithm. do it with

According to the present invention, the user can diagnose the oral condition in real time only by uploading an oral picture through the mobile application and provide the oral examination diagnosis result, so that the user can self-diagnose the oral health in real time. There are advantages to doing

In addition, according to the present invention, it promotes the oral health management of the family through the mobile application in an integrated manner, and there is an effect that the hospital reservation can be conveniently performed.

1 is an overall configuration diagram of a mobile-based self-oral examination device according to the present invention;
Figure 2 is a configuration diagram of an embodiment of the user terminal of Figure 1;
3 is a block diagram of an embodiment of the oral health calculation unit of FIG. 1;
4 to 7 is an example of an artificial intelligence algorithm for analyzing an oral image in the present invention;
8 to 12 are diagrams illustrating a process of performing self-oral examination, hospital reservation, and family health management through a mobile application in the present invention.

Hereinafter, a mobile-based self-oral examination device according to a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

The terms or words used in the present invention described below should not be construed as being limited to conventional or dictionary meanings, and the inventor may appropriately define the concept of terms in order to best describe his invention. It should be interpreted as meaning and concept consistent with the technical idea of the present invention based on the principle that it can be

Therefore, the embodiments described in this specification and the configurations shown in the drawings are only preferred embodiments of the present invention, and do not represent all of the technical spirit of the present invention, so various equivalents and It should be understood that there may be variations.

1 is an overall configuration diagram of a mobile-based self-oral examination apparatus according to a preferred embodiment of the present invention, and may include a user terminal 100 , an oral care service server 200 , and an oral health management server 300 .

The user terminal 100, the oral care service server 200, and the oral health management server 300 improve security even in case of data leakage due to hacking through transmission and reception of the encrypted oral examination diagnosis result.

In addition, the oral health management server 300 can improve security by limiting the authority of the access target by using a web access token using a user terminal ID and user information when transmitting an oral examination diagnosis result.

The user terminal 100 and the oral health service server 200 may be connected to various wired and wireless networks, and a communication interface may be established with real-time properties. The reason for implementing a plurality of servers as the oral care service server 200 and the oral health management server 300 is to increase the security of the diagnosis result to prevent leakage of personal information. Actual health management and personal information are all managed by the oral health management server 300, but the security is improved by transmitting information through a web token, and the oral care service server 200 is simply an interface of information and simple such as hospital reservations. By processing only the service, prompt service was made.

The user terminal 100 serves to provide a corrected oral image after correcting the user's oral image and to request an oral examination diagnosis. Here, the user may provide user personal information and general data such as questionnaire data using the user terminal 100 . There are two types of oral examination: simple examination and general examination. In the case of simple examination, it is only necessary to provide user personal information (device ID, user information) and oral image. In the case of general examination, user personal information, questionnaire data, and oral cavity Just provide an image.

The user receives the oral examination diagnosis result through the user terminal 100, recognizes his or her oral health through this, and if it is predicted that the oral health state is not good, visit a dental hospital, etc., and take follow-up measures to improve oral health It is desirable to manage The user terminal 100 may be implemented as a mobile device such as a smart phone and a smart pad, a personal computer or a notebook computer capable of the Internet, etc., and in the present invention, it is assumed that it is implemented as a smart phone using a mobile application as an embodiment.

The user terminal 100 includes a photo input unit 101 for inputting a photograph of the taken oral image as an oral health examination target image, and a photo correction unit 102 to improve clarity by correcting the oral image input from the photo input unit 101. ), transmits the oral image corrected by the photo correction unit 102 to the oral care service server 200 to request an oral health diagnosis, displays the received oral examination diagnosis result on the screen, and receives the user's key input It may include an oral care service processing unit 103 that services a hospital reservation or family oral care according to a request through.

In addition, the user terminal 100 may further include a questionnaire response unit 103 for generating questionnaire response information by using the user's response information to the oral examination questionnaire.

The oral care service processing unit 103 requests an oral examination using only the oral image corrected by the photo corrector 102 and user personal information when the user selects a simple examination among examination modes, and the user selects the examination mode If a general checkup is selected, an oral examination is requested using the oral image corrected by the photo correction unit 102 and the questionnaire response information and user personal information generated by the questionnaire response unit 103 . Here, the user personal information may include user information and device ID information. Such user personal information may be used as issuance information of a web token (access token) for security when transmitting oral examination result information later.

The oral care service server 200 transmits the oral image provided from the user terminal 100 to request an oral examination diagnosis result, and serves to transmit the oral examination diagnosis result to the user.

The oral health management server 300 generates oral health information by diagnosing the oral image transmitted from the oral care service server 200, and encrypts the generated oral health information as an oral examination diagnosis result as the oral care service server ( 200) to transmit.

The oral health management server 300 learns the received oral photograph with a CNN (Convolutional Neural Network) algorithm, which is an artificial intelligence algorithm, determines whether the photograph can be analyzed, whether or not to correct it, and whether or not to extract, and detects the determined result information ( Object Detection) to obtain dental caries status information and prosthesis status information, and learn the acquired dental caries status information and prosthesis status information with ANN (Artificial Neural Network) algorithm to determine oral health status 310 ), an oral health information providing unit 320 that generates the oral health information determined by the oral health calculation unit 310 as an oral examination diagnosis result, and encrypts the generated oral examination diagnosis result and transmits it to the user terminal 100; It may include a database 330 in which big data for oral diagnosis, personal information, encryption algorithm, and the like are stored.

The oral health calculation unit 310, as shown in FIG. 3, a photo registration unit 311 for registering an oral photograph transmitted from the user terminal 100 as an oral health prediction target, the image registered in the photo registration unit 311 is learned with a CNN (Convolutional Neural Network) algorithm to determine whether a photo can be analyzed, whether or not to correct it, and whether or not to extract, and analyzes the determined result information with object detection to obtain dental caries status information and prosthesis status information. , may include an oral diagnosis unit 312 for determining oral health status by learning the acquired orthodontic information and tooth extraction information, dental caries status information, and prosthesis status information using an Artificial Neural Network (ANN) algorithm.

The operation of the mobile-based self-oral examination apparatus according to the present invention configured as described above will be described in detail as follows.

First, the user self-examines and manages his or her oral health state, and downloads a mobile-based oral examination application for integrated management of the oral health of all family members from the oral care service server 200 and receives the user terminal 100 ) is stored in

Here, the oral examination application is an artificial intelligence (AI)-based oral self-diagnosis application, which allows you to easily check your oral health by yourself at any time, anywhere. By preventing oral diseases through periodic oral examinations, it is also helpful in preventing systemic diseases, and by simply installing the oral examination application, which is one application, on the user terminal 100, which is a smartphone, the oral health of not only yourself but also your family. will be able to manage

The user executes the oral examination application to check the oral health state, and logs in to the oral care service server 200 . For login, register information such as ID and PW through normal membership registration. At this time, through items such as adding family members, information about family members who want to manage oral health in addition to themselves is registered.

Here, for login, basic personal information of the user (name, gender, date of birth, blood type, etc.) and medical history, medications being taken, or body specific information (high blood pressure, low blood pressure, diabetes, heart disease, constipation, pregnancy, etc.) Register. You can also register your profile picture, etc.

When the login is made, the main screen as shown in FIG. 8 is displayed, and through the main screen, the setting family dentistry reservation status or medication information can be checked, and the reservation details view or medication check can be performed.

For example, reservation and medication information can be checked by filtering by family through the family selection item. 9 is an example of a screen for confirming a reservation while checking a schedule for each family, and FIG. 10 is an example of a screen for taking medication. Through the detailed menu for each family, you can check the medical appointment status and prescription list for each family, and you can proceed with an artificial intelligence-based oral self-examination. In addition, you can check the reservation information and medication for the selected date by checking the calendar, and you can check detailed information by clicking on it. By selecting the main menu, you can go to Home, Find a dentist, your regular dentist, and My Information page.

In addition, it is also possible to add a family through the Add New Family item in the main menu. 11 is a screen showing an example of adding a new family.

Next, the user selects an oral examination target from the main menu for oral examination, and selects an item to ask a question. Here, if the target for oral examination is a family, you can designate and select a family member to be examined from among the registered family members, and in the case of yourself, simply select the option to ask questions. Since both family members and their own oral examinations are performed in the same way, it is assumed that the person is designated as the target for oral examinations for convenience of explanation below. When the item to ask a question is selected, a checkup list is displayed on a detailed screen, and the user selects a checkup mode on this detailed screen. Here, the checkup list includes a simple checkup and a general checkup mode.

The simple check-up is a mode that provides only the user's personal information and a picture of the oral cavity to be diagnosed, and requests a self-examination, and the general check-up is a mode that provides the user's personal information, an oral picture and questionnaire information and requests a self-examination. Here, device ID information of the user terminal 100 may be provided when a self-examination is requested, or ID information of the user device may be checked when registering a user member and matched to the user's personal information.

When a self-examination is requested, the user uses the photographing guide information guided through the oral examination application to photograph the oral cavity or selects a pre-photographed oral image. That is, when the user acquires an oral image by taking a picture through the user terminal or selects a pre-registered oral image, the selected photo or the photographed photo in the photo input unit 101 is set as the oral examination target image. Then, the photo correction unit 102 increases the sharpness by correcting the set oral image. That is, the input oral photograph is an atypical photograph, and the image quality or the photographing position may be changed by the camera or the photographer, and thus the examination result may vary.

Therefore, correction is necessary for atypical photos.

In order to correct an atypical photo, the input photo image is divided into a preset size, and the direction is adjusted to become a front image. Directional control is recognized as a method of recognizing the position through the oral structure and can be adjusted in the front. Then, the image sharpen filter (Image Sharpen Filter) to filter the direction-adjusted segmented image to increase the sharpness. Here, since the technique of increasing the sharpness of a picture with an image chaffine filter is a known technique in the image processing field, a detailed description thereof will be omitted.

In a state where the image correction is made for the atypical photo, the oral care service processing unit 104 checks the diagnosis item selected by the user, and if the simple diagnosis is selected, the oral examination is performed using only the corrected image and the user's personal information. request. Contrary to this, if a general diagnosis is selected by checking the diagnosis item selected by the user, the oral examination is requested using the corrected image, the user's personal information, and the questionnaire response information. Here, as for the questionnaire response information, when the oral examination application installed by the user is executed, the user sees the questionnaire linked to the menu item displayed on the main screen, and responds (checks) for each item through the key input unit. When the response to the questionnaire is completed, the questionnaire response unit 103 generates questionnaire response information using the questionnaire including the response.

When the oral care service server 200 receives an oral photograph and personal information and/or questionnaire response information from the user terminal 100 accessed through the network, it transmits it to the oral health management server 300 .

The photo registration unit 311 of the oral health calculation unit 310 of the oral health management server 300 registers the transmitted oral photograph as an oral health examination target image in the internal database. Here, since the oral image is taken by an individual, the shooting environment is different, so there is no standard for the color of the actual shot image. Therefore, after setting the reference point, color correction is automatically performed so that all photos are the same as the reference point, and then saved.

Next, the oral diagnosis unit 312 learns an oral photograph (image) with a CNN (Convolutional Neural Network) algorithm to determine whether the photograph can be analyzed, whether or not to correct it, and whether to extract it, and use the determined result information to detect an object (Object Detection). to obtain dental caries status information, periodontitis status information, and prosthetic status information by analyzing with ANN (Artificial Neural Network) algorithm to learn the acquired dental caries status information and prosthesis status information to determine oral health status.

For example, by learning an oral image with a Convolutional Neural Network (CNN) algorithm, it is determined whether there is an oral photograph. The process of determining the presence or absence of an oral photograph by learning an oral image with a CNN algorithm is shown in FIG. For this purpose, it is assumed that a CNN model that determines whether a photo taken in advance and requested to be registered is an oral photo is built. It is preferable to use the pre-trained CNN model by adding the oral picture category to the already known CNN models such as VGG16 (https://neurohive.io/en/popular-networks/vgg16/) and ResNet50. The training data may be oral photo data or photo data of a category to be added.

The presence or absence of an oral photograph can be determined by learning with a CNN model using this oral photograph data, but in this case, it may cause a disadvantage in that it takes a lot of learning time depending on the amount of added learning data.

Therefore, as another method of determining the presence or absence of an oral photograph, the process of determining the presence or absence of an oral photograph can be omitted by inducing the user not to register an image other than an oral photograph by using the oral examination application instead of using the CNN algorithm. have. Here, as a method of inducing not to register an image other than an oral photograph, a guide phrase may be used.

As a result of checking the presence of an oral photograph, if it is determined as an oral image, the oral image is learned by a CNN (Convolutional Neural Network) algorithm shown in FIG. 5 to determine whether or not correction is made. Here, Figure 5 is an example of a CNN model that determines whether or not correction from the input oral image. These CNN models can be built using AutoKeras. Transfer learning using pre-trained VGG16, ResNet50, etc. can also be used. Required data is oral photo data with/without braces, and by adding two categories of oral photos (with/without braces) to the CNN model, it is possible to simply determine whether or not correction is made.

Correction can be determined using this CNN model, but this also requires sufficient learning time and data, and an increase in the training data results in an increase in the amount of computation. Therefore, the learning process of a CNN (Convolutional Neural Network) algorithm for determining whether to calibrate may be omitted by inducing the user to select whether to calibrate by writing a questionnaire.

When the questionnaire information is provided through the preparation of the questionnaire, the questionnaire information is classified by the FFNN (Feed Forward Neural Network) algorithm. Here, the FFNN algorithm is a machine learning algorithm in which a questionnaire response (user information) is an input and a diagnosis result is an output. It is desirable to design and use an FFNN suitable for the input/output structure using a Python-based library such as Tensorflow or Keras. For activation function, loss function, optimization method, parallel computing structure, overfitting problem, etc., FFNN algorithms that have been recently studied and analyzed can be used. The input data (survey response) is preprocessed, and the preprocessed data is divided into training data and verification data. Then, learning data is learned through neural network learning, and the validation data and learning result data are verified and supplemented through a newly designed neural network. And when verification and supplementation are completed, the final model is output as a questionnaire diagnosis result.

It is also possible to determine whether or not correction is made using the CNN model constructed here, but it is also possible to determine whether tooth extraction is performed using the same CNN model in addition. By adding the category of extracted oral photos to the CNN model, it is also possible to simply determine whether or not tooth extraction has occurred.

Next, the determined orthodontic information and tooth extraction information are analyzed by object detection to obtain dental caries status information and prosthesis status information. To this end, an object detection algorithm for determining oral disease (dental caries) and prosthesis detection from the input section photo (image) as shown in FIG. 6 is constructed. The object detection algorithm that determines the detection of oral diseases and prostheses uses the previously developed Faster R-CNN, SSD, YOLO (W.Liu et al., 2015, arXiv (http://arxiv.org/abs/1512.02325)), etc. Available. As data required for obtaining dental caries status information and prosthesis status information with the object detection algorithm, photo data showing oral diseases and prostheses may be used. Accuracy can be improved by classifying whether or not to wear braces and learning. It has the advantage of being able to detect both dental caries and prostheses with one algorithm. Here, the dental caries status information may include information on the presence or absence of dental caries and information on the number of dental caries when there is dental caries, and the prosthesis status information includes information on the presence or absence of a prosthesis and information on the number of prostheses when there is a prosthesis. . Dental caries image learning checks which part of the entire oral region the oral photo provided by the user is, and performs image learning after confirming the position of the oral region image, and through this, the presence or absence of dental caries and the number of dental caries are extracted. . In the same way, the presence or absence of the prosthesis and the number of prostheses are also extracted.

Then, the oral health status by learning the orthodontic information, tooth extraction information, dental caries status information, and prosthesis status information with the ANN (Artificial Neural Network) algorithm (2019 NIMS industrial math problem solving workshop proposal model) as shown in FIG. judge Here, the ANN algorithm, which is an artificial intelligence algorithm, determines an oral health state (oral health) by inputting the correction information, tooth extraction information, dental caries state information, and prosthesis state information as inputs. For this purpose, the patient's oral health evaluation data corresponding to reliable photographic data obtained from a specialist or a specialist may be used. When the oral health state determination is completed, oral health prediction information is generated and stored in an internal database.

Next, the oral health information providing unit 320 transmits the oral examination diagnosis result obtained through the determination to the user terminal 100 . At this time, in order to prevent unauthorized leakage of the oral examination diagnosis result, the oral examination diagnosis result is encrypted using an encryption module. Encryption uses a method of generating a 256-bit web access token using the device ID and user information of the received or pre-registered user terminal.

The encrypted oral examination diagnosis result is transmitted to the user terminal 100 through the oral care service server 200 . Here, the oral examination diagnosis result may be in the form of an oral examination report.

Even if the oral health management server 300 is leaked to unauthorized persons by hacking before the oral examination diagnosis result is transmitted to the user terminal 100, the web token is encrypted with the user device ID and user information. Therefore, a person who does not know the user device ID and user information cannot check the oral examination result information, so that security can be improved.

When the oral examination diagnosis result, which is the oral examination diagnosis result information, arrives, the oral care service processing unit 104 of the user terminal 100 decrypts the web access token using the registered user device ID and user information using the decryption module. . Decryption is the reverse of encryption.

If the user device ID and user information match, the encrypted oral examination result can be opened.

By using encryption information when issuing web tokens in this way, it is possible to fundamentally prevent unauthorized users from accessing the oral examination diagnosis results.

The oral care service processing unit 104 stores the decoded oral examination result information in the internal memory, and displays it on the screen so that the user can check the oral examination result in real time.

Based on the oral diagnosis result, if the oral condition is in a dangerous situation, a dental appointment is displayed on the screen of the examination report, which is the oral examination result. 12 is an example of an oral examination diagnosis result screen. When the dental appointment is selected, dental information is displayed on the screen through a map search based on the current location. Searching for dental information based on a map search may display dental information in the order of the nearest distance from the current location. If the user selects a specific location (selecting a district or a dong based on Seoul), dental information is displayed on the screen in order of the distance of the selected specific location based on the current location.

According to the present invention, when a user uploads a photograph of his/her own oral cavity, the user diagnoses the oral health condition using an artificial intelligence algorithm and provides an oral health report to the user in real time by encrypting the diagnosis result. You can easily manage your oral health and prevent deterioration of your oral health in advance.

In addition, since oral care is possible for a registered family in the same way, it is possible to conveniently perform oral care not only for oneself but also for all songs and songs with one mobile-based application.

Although the invention made by the present inventor has been described in detail according to the above embodiment, the present invention is not limited to the above embodiment, and it is common knowledge in the art that various changes can be made without departing from the gist of the present invention. self-evident to those who have

100: user terminal
101: photo input unit
102: photo retouching unit
103: Questionnaire response unit
104: Oral care service processing department
200: oral health service server
300: oral health management server
310: oral health calculation unit
311: photo register
312: oral diagnostic unit
320: oral health information provider
330: database

Claims (8)

As a device for diagnosing oral health by analyzing oral photos with an artificial intelligence algorithm,
a user terminal providing a corrected oral image after correcting the user's oral image and requesting an oral examination diagnosis;
an oral care service server that transmits an oral image provided from the user terminal to request an oral examination diagnosis, and transmits an oral examination diagnosis result to the user; and
An oral health management server that generates oral health information by diagnosing the oral image transmitted from the oral care service server, and encrypts the generated oral health information to transmit the oral health checkup diagnosis result to the oral care service server A mobile-based self-examination device.
The method according to claim 1, The user terminal, oral care service server and oral health management server through the transmission and reception of the encrypted oral examination diagnosis result, mobile-based self-examination device characterized in that it improves security even in case of data leakage due to hacking. .
The mobile device of claim 1, wherein the oral health management server improves security by limiting the authority of an access target using an access token using a user terminal ID and user information when transmitting an oral examination diagnosis result. Based self-oral examination device.
The method according to claim 1, The user terminal is a photo input unit for inputting the photograph of the oral health examination target image as a photographed oral image; a photo correction unit for increasing the sharpness by correcting the oral image input from the photo input unit; The oral health examination is requested by sending the oral image corrected by the photo corrector to the oral care service server, the received oral examination diagnosis result is displayed on the screen, and the hospital reservation or family member according to the request through the user's key input A mobile-based self-examination device comprising an oral care service processing unit that provides oral care services.
The mobile-based self-oral examination apparatus of claim 4, wherein the user terminal further comprises a questionnaire response unit for generating questionnaire response information by using the user's response information to the oral examination questionnaire.
The method according to claim 4, The oral care service processing unit, when the user selects a simple checkup in the checkup mode, requests an oral checkup diagnosis using only the oral image corrected by the photo corrector and the user's personal information, and the user selects a simple checkup in the checkup mode. When a general examination is selected, an oral examination diagnosis is requested using the oral image corrected by the photo correction unit, the questionnaire response information generated by the questionnaire response unit, and the user's personal information.
The method according to claim 1, wherein the oral health management server is an artificial intelligence algorithm CNN (Convolutional Neural Network) algorithm by learning the received oral photograph to determine whether the photograph can be analyzed, whether or not to correct and whether to extract, and detects the determined result information An oral health calculation unit that obtains dental caries status information and prosthesis status information by analyzing (Object Detection), and determines oral health status by learning the acquired dental caries status information and prosthesis status information with an Artificial Neural Network (ANN) algorithm; Mobile-based self-oral examination device, characterized in that it generates the oral health information determined by the oral health calculation unit as an oral examination diagnosis result, and an oral health information providing unit that encrypts the generated oral examination diagnosis result and transmits it to the user terminal. .
The method according to claim 7, wherein the oral health calculation unit is a photo registration unit for registering the oral photograph transmitted from the user terminal as an oral examination diagnosis target; The image registered in the photo register is learned with a CNN (Convolutional Neural Network) algorithm to determine whether the photo can be analyzed, whether to correct or not, and whether or not to extract, and analyze the determined result information by object detection to obtain dental caries status information. and an oral diagnostic unit that acquires the prosthesis status information and determines the oral health status by learning the acquired orthodontic status information and tooth extraction status information, dental caries status information, and prosthesis status information with an Artificial Neural Network (ANN) algorithm. A mobile-based self-examination device.

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