Diagnostic Image Management System

Abstract

To provide a diagnostic system.SOLUTION: A diagnostic system includes a user terminal configured to capture an image, and a server configured to acquire diagnosis support information on the basis of the image. The user terminal is configured to acquire first imaging parameters, determine whether or not a condition stored beforehand is satisfied, and transmit the first imaging parameters and the captured image to the server when it is determined that the condition stored beforehand is satisfied. The server is configured to acquire first verification parameters, determine whether or not to use the captured image as a diagnosis image including comparison of the first verification parameters with the first imaging parameters, and acquire the diagnosis support information using the diagnosis image when it is determined that the captured image is used as the diagnosis image.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] One embodiment relates to a method for verifying images used in disease diagnosis.

[0002] One embodiment relates to a diagnostic system for performing an image verification method for use in disease diagnosis.

[0003] One embodiment relates to a computer readable recording medium having recorded thereon a method for verifying an image for use in diagnosing a disease. [Background technology]

[0004] With the rapid development of software for analyzing images to diagnose cancer and for the early diagnosis of certain diseases, the definition of a medical device has expanded beyond traditional surgical devices and x-ray imaging devices to include software for diagnostic devices that analyze images to derive information about diseases.

[0005] Even if the software is a diagnostic device for analyzing human health information, approval according to the regulations of each country is essential for the realization and distribution of the software. Therefore, since it is generally necessary to verify the accuracy of the software and the consistency of the results, improving accuracy is very important in the market for medical devices in the form of software.

[0006] Therefore, in the field of software that provides health information through image analysis, it is necessary to devise a consistent image acquisition method that does not degrade the accuracy of medical equipment.

[0007] The above is intended only to aid in understanding the background of the present disclosure, and is not intended to imply that the present disclosure is within the scope of relevant art known to those skilled in the art. Summary of the Invention [Problem to be solved by the invention]

[0008] One embodiment provides a method for obtaining a diagnostic image for use in diagnosis.

[0009] One embodiment provides an image verification method for verifying an image for suitable use as a diagnostic image. [Means for solving the problem]

[0010] According to one embodiment of the present application, a diagnostic system is provided. The diagnostic system includes a user terminal configured to capture an image, and a server configured to obtain diagnostic assistance information based on the image, the user terminal being configured to analyze a first image using a first image analysis algorithm to obtain first imaging parameters including information regarding at least one of a detected position of a diagnostic object and whether or not the diagnostic object is detected, determine whether a pre-stored condition is satisfied including that the first imaging parameters satisfy a first condition, and transmit the first imaging parameters and the captured image to the server when it is determined that the pre-stored condition is satisfied, the server being configured to analyze the captured image using a second image analysis algorithm to obtain first verification parameters including information regarding at least one of a detected position of the diagnostic object and whether or not the diagnostic object is detected, determine whether or not the captured image is used as a diagnostic image including a comparison between the first verification parameters and the first imaging parameters, and obtain the diagnostic assistance information using the diagnostic image when it is determined that the captured image is used as the diagnostic image, the first image analysis algorithm and the second image analysis algorithm being different algorithms, and the diagnostic object is a body part related to a target disease for which the diagnostic assistance information is to be obtained.

[0011] According to an embodiment of the present application, a diagnostic image verification method is provided, the method includes the steps of: acquiring a first image; analyzing the first image using a first image analysis algorithm to acquire first imaging parameters including information on at least one of a detected position of a diagnostic object and whether the diagnostic object is detected; determining whether a pre-stored condition is satisfied including that the first imaging parameters satisfy a first condition; if it is determined that the pre-stored condition is satisfied, storing the first imaging parameters and a captured image; analyzing the captured image using a second image analysis algorithm to acquire first verification parameters including information on at least one of a detected position of the diagnostic object and whether the diagnostic object is detected; determining whether the captured image is used as a diagnostic image including a comparison between the first verification parameters and the first imaging parameters; and if it is determined that the captured image is used as the diagnostic image, acquiring diagnostic support information using the diagnostic image, the first image analysis algorithm and the second image analysis algorithm are different algorithms, and the diagnostic object is a body part related to a target disease for which the diagnostic support information is acquired.

[0012] According to an embodiment of the present application, there is provided a computer-readable recording medium having a program recorded thereon, the program is for executing the steps of acquiring a first image, acquiring first imaging parameters including information regarding at least one of a detected position of a diagnostic object and whether the diagnostic object is detected by analyzing the first image using a first image analysis algorithm, determining whether a pre-stored condition is satisfied including that the first imaging parameters satisfy a first condition, storing the first imaging parameters and the captured image when it is determined that the pre-stored condition is satisfied, acquiring first verification parameters including information regarding at least one of a detected position of the diagnostic object and whether the diagnostic object is detected by analyzing the captured image using a second image analysis algorithm, determining whether the captured image is used as a diagnostic image including a comparison between the first verification parameters and the first imaging parameters, and acquiring diagnostic assistance information using the diagnostic image when it is determined that the captured image is used as the diagnostic image. The first image analysis algorithm and the second image analysis algorithm are different algorithms, and the diagnostic target is a body part related to a target disease from which the diagnostic assistance information is obtained. Effect of the Invention

[0013] The present embodiments provide an improved method of acquiring diagnostic images to ensure accuracy of diagnostic equipment and to enable product approval and distribution.

[0014] According to the present embodiment, in order to enable real-time photography, an image verification method is provided that can obtain accurate images while maintaining the amount of calculation required for the image analysis method of the photography device.

[0015] The present application is not limited to the above effects. From this specification and the accompanying drawings, a person skilled in the art can understand effects that are not described above. [Brief description of the drawings]

[0016] The above and other objects, features, and advantages of the present disclosure will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings. [Figure 1] FIG. 1 is a diagram showing a configuration of a diagnostic system according to an embodiment of the present application. [Figure 2a] FIG. 1 shows an example of a diagnostic DO described in the present application. [Figure 2b] FIG. 1 shows an example of a diagnostic DO described in the present application. [Figure 2c] FIG. 1 shows an example of a diagnostic DO described in the present application. [Diagram 3] FIG. 1 is a diagram showing the configuration of an image capturing device 1000 and a server 2000 according to an embodiment of the present application. [Figure 4] 1 is a flowchart illustrating a captured image acquisition operation of a user terminal 1000 according to an embodiment of the present application. [Diagram 5] FIG. 17 illustrates a first output unit 1700 of a user terminal 1000 in a guide providing operation S110 according to an embodiment of the present application. [Figure 6] FIG. 2 illustrates a method S130 for determining whether a photographing condition is met according to an embodiment of the present application. [Figure 7] FIG. 2 illustrates imaging parameters according to an embodiment of the present application. [Figure 8-10] FIG. 11 illustrates an example of an evaluation target image, an evaluation frequency of the shooting parameters, and stored captured images according to a speed at which it is determined whether a condition corresponding to each shooting parameter is satisfied. [Figure 11] 2 is a flowchart illustrating an image verification operation of the server 2000 according to an embodiment of the present application. [Figure 12]FIG. 2 illustrates a method S220 for determining whether a verification condition is met according to an embodiment of the present application. [Figure 13] FIG. 2 illustrates validation parameters according to an embodiment of the present application. [Figure 14] FIG. 2 illustrates the operation of storing a diagnostic image and using it to obtain diagnostic assistance information according to one embodiment of the present application. [Figure 15a] FIG. 1 illustrates a method for eye disease related imaging according to an embodiment of the present application. [Figure 15b] FIG. 1 illustrates a method for eye disease related imaging according to an embodiment of the present application. [Figure 16a] FIG. 2 illustrates a method for acquiring imbalance-related images of a body according to an embodiment of the present application. [Figure 16b] FIG. 2 illustrates a method for acquiring imbalance-related images of a body according to an embodiment of the present application. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Hereinafter, the embodiments of the present specification will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present application. In addition, various modifications may be made to the present application, and various embodiments of the present application may be practiced. Therefore, specific embodiments will be described in detail below with reference to the accompanying drawings. The technical ideas disclosed in this specification are not limited to the accompanying drawings or the described embodiments, and the exemplary embodiments can be interpreted as including all modifications, equivalents, or alternatives within the technical concept and technical scope of the present application.

[0018] Throughout the specification, the same reference numerals generally represent the same elements, and elements having the same functions to the same extent as those shown in the drawings of the embodiment are described using the same reference numerals, and redundant descriptions are omitted.

[0019] In describing the embodiments disclosed in this specification, detailed descriptions of well-known techniques related to this specification will be omitted if they are deemed to obscure the gist of the embodiments disclosed in this specification. Furthermore, terms such as first, second, etc. are used throughout this specification only to distinguish one element from another element.

[0020] In addition, the terms "module" and "part" used as names of elements in the following description are used only for ease of description in this specification. These terms are not intended to have different special meanings or functions, and therefore may be used individually or interchangeably.

[0021] In the following embodiments, expressions used in the singular encompass plural expressions unless the context clearly indicates otherwise.

[0022] In the following embodiments, it should be understood that the terms "comprise", "have", and the like are intended to indicate the presence of features or elements disclosed in the specification, but are not intended to exclude the possibility that one or more other features or elements may be added.

[0023] Sizes of elements in the drawings may be exaggerated or reduced for convenience of illustration. For example, any size and thickness of each element shown in the drawings is shown for convenience of illustration.

[0024] Methods described below may be performed out of the order described if a particular embodiment is realized in an alternative manner, for example two operations described in succession may be performed substantially simultaneously or in the reverse order from that described.

[0025] According to one embodiment of the present application, a diagnostic system is provided. The diagnostic system includes a user terminal configured to take an image, and a server configured to obtain diagnostic assistance information based on the image, the user terminal being configured to obtain first imaging parameters including information regarding at least one of a detected position of the diagnostic object and whether the diagnostic object is detected by analyzing a first image using a first image analysis algorithm, determine whether a pre-stored condition is satisfied including that the first imaging parameters satisfy a first condition, and transmit the first imaging parameters and the captured image to the server when it is determined that the pre-stored condition is satisfied, the server being configured to obtain first verification parameters including information regarding at least one of a detected position of the diagnostic object and whether the diagnostic object is detected by analyzing the captured image using a second image analysis algorithm, determine whether the captured image is used as a diagnostic image including a comparison between the first verification parameters and the first imaging parameters, and obtain the diagnostic assistance information using the diagnostic image when it is determined that the captured image is used as the diagnostic image, the first image analysis algorithm and the second image analysis algorithm being different algorithms, and the diagnostic object is a body part related to a target disease for which the diagnostic assistance information is to be obtained.

[0026] In the diagnostic system, the first shooting parameters may include information regarding a detected position of the diagnostic object in the first image, and the user terminal may be configured to determine whether a pre-stored condition is satisfied by comparing the first shooting parameters with a pre-stored diagnostic object area.

[0027] In the diagnostic system, the first image analysis algorithm may be a first landmark detection algorithm, the target disease may be thyroid eye disease, the diagnostic object may be an eye, and the first imaging parameter may be an eye landmark.

[0028] In a diagnostic system, the first verification parameter may include information regarding a detected location of a diagnostic object in a captured image.

[0029] In the diagnostic system, the second image analysis algorithm may be a second landmark detection algorithm, the target disease may be thyroid eye disease, the diagnostic object may be an eye, and the first validation parameter may be an eye landmark.

[0030] In the diagnostic system, the second image analysis algorithm may be an image segmentation algorithm, the target disease may be thyroid eye disease, the diagnostic object may be the eye, and the first validation parameter may be the iris area.

[0031] In the diagnostic system, the user terminal may be configured to acquire images according to a preset frame rate, analyze at least a portion of the acquired images using a first image analysis algorithm, store one of the acquired images as a captured image, and transmit the captured image to a server.

[0032] In the diagnostic system, the user terminal may be configured to, upon determining that the first imaging parameters for the first image do not satisfy the first condition, analyze a second image using a first image analysis algorithm, the second image being acquired after determining that the first imaging parameters for the first image do not satisfy the first condition.

[0033] In the diagnostic system, the user terminal may be configured to transmit a second image to the server as a captured image upon determining that the first imaging parameters for the first image satisfy the first condition, the second image being acquired after determining that the first imaging parameters for the first image satisfy the first condition.

[0034] In the diagnostic system, the first image analysis algorithm may have a lower computational complexity than the second image analysis algorithm so as to have the advantage of real-time processing.

[0035] In the diagnostic system, the user terminal may be configured to acquire second shooting parameters for the first image, and the pre-stored conditions further include that the second shooting parameters satisfy a second condition.

[0036] In the diagnostic system, for the user terminal, a period for acquiring the first imaging parameter and a period for acquiring the second imaging parameter may be different from each other.

[0037] In the diagnostic system, the user terminal may be configured to acquire second through Nth imaging parameters for the first image, and the pre-stored conditions include that at least a part of the second through Nth imaging parameters satisfy corresponding second through Nth conditions, respectively, where N may be a natural number equal to or greater than 2.

[0038] In the diagnostic system, the server may be configured to obtain second through Mth validation parameters for the captured image, and determining whether to use the captured image as a diagnostic image further includes determining whether the second through Mth validation parameters are satisfied, where M may be a natural number equal to or greater than 2.

[0039] In the diagnostic system, the server may be configured to obtain diagnostic assistance information using diagnostic images and a diagnostic model, and the diagnostic model may be trained using images including a diagnostic object and information regarding whether a target disease has occurred.

[0040] According to an embodiment of the present application, a diagnostic image verification method is provided, the method includes the steps of: acquiring a first image; analyzing the first image using a first image analysis algorithm to acquire first imaging parameters including information on at least one of a detected position of a diagnostic object and whether the diagnostic object is detected; determining whether a pre-stored condition is satisfied including that the first imaging parameters satisfy a first condition; if it is determined that the pre-stored condition is satisfied, storing the first imaging parameters and a captured image; analyzing the captured image using a second image analysis algorithm to acquire first verification parameters including information on at least one of a detected position of the diagnostic object and whether the diagnostic object is detected; determining whether the captured image is used as a diagnostic image including a comparison between the first verification parameters and the first imaging parameters; and if it is determined that the captured image is used as the diagnostic image, acquiring diagnostic support information using the diagnostic image, the first image analysis algorithm and the second image analysis algorithm are different algorithms, and the diagnostic object is a body part related to a target disease for which the diagnostic support information is acquired.

[0041] In the diagnostic image verification method, the first shooting parameters may include information regarding the detected position of the diagnostic target in the first image, and determining whether the pre-stored condition is satisfied may further include comparing the first shooting parameters with a pre-stored diagnostic target area.

[0042] In the diagnostic image verification method, the first image analysis algorithm may be a first landmark detection algorithm, the target disease may be thyroid eye disease, the diagnostic object may be an eye, and the first imaging parameter may be an eye landmark.

[0043] In the diagnostic image verification method, the first verification parameter may include information regarding a detected location of the diagnostic object in the captured image.

[0044] In the diagnostic image verification method, the second image analysis algorithm may be a second landmark detection algorithm, the target disease may be thyroid eye disease, the diagnostic object may be an eye, and the first verification parameter may be an eye landmark.

[0045] In the diagnostic image verification method, the second image analysis algorithm may be an image segmentation algorithm, the target disease may be thyroid eye disease, the diagnostic object may be the eye, and the first verification parameter may be the iris area.

[0046] The diagnostic image verification method may include acquiring images according to a preset frame rate, analyzing at least some of the acquired images using a first image analysis algorithm, and upon determining that a pre-stored condition is satisfied for at least some of the acquired images, storing one of the acquired images as a captured image.

[0047] The diagnostic image verification method may include a step of acquiring a second image when it is determined that first shooting parameters for the first image do not satisfy a first condition, acquiring first shooting parameters for the second image by analyzing the second image using a first analysis algorithm, and determining whether the first shooting parameters for the second image satisfy the first condition to determine whether a pre-stored condition is satisfied.

[0048] The diagnostic image verification method may include, upon determining that first shooting parameters for the first image satisfy a first condition, acquiring a second image and storing the second image as a captured image.

[0049] In the diagnostic image review method, the first image analysis algorithm may have a lower computational complexity than the second image analysis algorithm so as to have the advantage of real-time processing.

[0050] The diagnostic image verification method may further include obtaining second imaging parameters for the first image, and the pre-stored conditions further include that the second imaging parameters satisfy a second condition.

[0051] In the diagnostic image verification method, the period for acquiring the first imaging parameter and the period for acquiring the second imaging parameter may be different from each other.

[0052] The diagnostic image verification method may further include a step of acquiring second through Nth imaging parameters for the first image, where N is a natural number equal to or greater than 2. The pre-stored conditions further include that at least some of the second through Nth imaging parameters satisfy corresponding second through Nth conditions, respectively.

[0053] The diagnostic image verification method may further include obtaining second through Mth verification parameters for the captured image, where M is a natural number equal to or greater than 2. The step of determining whether to use the captured image may further include determining whether the second through Mth verification parameters are satisfied.

[0054] In the diagnostic image verification method, when it is determined that the captured image is to be used as a diagnostic image, the step of obtaining diagnostic assistance information using the diagnostic image may include obtaining the diagnostic assistance information using the diagnostic image and a diagnostic model, and the diagnostic model may be trained using the image including the diagnostic object and information regarding whether the target disease has occurred.

[0055] According to an embodiment of the present application, a computer-readable recording medium having a program recorded thereon is provided. The program is for executing the steps of acquiring a first image, acquiring first imaging parameters including information on at least one of a detected position of a diagnostic object and whether the diagnostic object is detected by analyzing the first image using a first image analysis algorithm, determining whether a pre-stored condition is satisfied including that the first imaging parameters satisfy a first condition, storing the first imaging parameters when it is determined that the pre-stored condition is satisfied, acquiring first verification parameters including information on at least one of a detected position of the diagnostic object and whether the diagnostic object is detected by analyzing the captured image using a second image analysis algorithm, determining whether the captured image is used as a diagnostic image including a comparison between the first verification parameters and the first imaging parameters, and acquiring diagnostic support information using the diagnostic image when it is determined that the captured image is used as the diagnostic image. The first image analysis algorithm and the second image analysis algorithm are different algorithms, and the diagnostic object is a body part related to a target disease for which the diagnostic support information is acquired.

[0056] This specification describes a diagnostic image verification method, a server using the same, and a diagnostic system that can be used to realize a diagnostic device (including software) or system that uses images, to manufacture products that can derive highly accurate diagnostic results, to secure the clinical data required to comply with each country's product approval procedures, and / or to provide approved products to consumers.

[0057] FIG. 1 is a diagram showing a configuration of a diagnostic system according to an embodiment of the present application.

[0058] As shown in FIG. 1, the diagnostic system may include an imaging device 1000 and a server 2000, and the imaging device 1000 and the server 2000 may be connected to each other for data exchange via a network.

[0059] The photographing device 1000 may perform a function of taking an image. For example, the photographing device 1000 may evaluate whether an image satisfies a photographing condition. The photographing device 1000 may capture an image, and if it is determined that the captured image satisfies the photographing condition, the photographing device 1000 stores the captured image. The process by which the photographing device 1000 determines whether an image satisfies the photographing condition will be described in detail later.

[0060] The image capture device 1000 is an electronic device capable of capturing an image. Examples of the image capture device 1000 include, but are not limited to, a mobile phone, a smart phone, a tablet PC, a laptop, a portable camera with communication capabilities, and / or a standalone camera.

[0061] The image capture device 1000 may communicate with the server 2000 and transmit captured images to the server 2000 .

[0062] The server 2000 may perform a function of validating an image. For example, the server 2000 may evaluate whether a received image meets a validation condition and store the received image as a diagnostic image. The process by which the server 2000 determines whether an image meets a validation condition is described in more detail below.

[0063] When the imaging device 1000 determines whether the target image satisfies the imaging condition, it may evaluate whether the condition for at least one imaging parameter is satisfied, and the at least one imaging parameter may be related to the diagnostic object DO. According to an embodiment, the imaging parameter may include information regarding the detected position of the diagnostic object DO and / or whether the diagnostic object DO is detected.

[0064] When the server 2000 determines whether the captured image satisfies a verification condition, it may evaluate whether a condition for at least one verification parameter is met, and the at least one verification parameter may be associated with the diagnostic object DO. According to one embodiment, the verification parameter may include information regarding the detected position of the diagnostic object DO and / or whether the diagnostic object DO is detected.

[0065] The diagnostic DO described herein may refer to an object (target object) related to the target disease to be diagnosed. For example, the diagnostic DO may refer to a body part related to the target disease.

[0066] According to an embodiment of the present application, the diagnostic object DO evaluated with the verification parameters and the diagnostic object DO evaluated with the imaging parameters may be the same, or the diagnostic object DO evaluated with the verification parameters may be included in the diagnostic object DO evaluated with the imaging parameters, or vice versa.

[0067] The server 2000 may use the image stored as the diagnostic image to obtain information about the target disease, where the information about the target disease may be information for assisting in disease diagnosis, for example, the information about the target disease may be the probability that the person photographed in the image suffers from the target disease, or the probability that the person suffers from one or more other diseases known to be related to the target disease.

[0068] 2a, 2b and 2c show examples of diagnostic DOs according to the present application.

[0069] According to one embodiment, the images used in the diagnostic device for analyzing phenotypic abnormalities by analyzing face images may be verified using the diagnostic image verification method described in this application. The DO to be diagnosed for phenotypic abnormalities may be a "face" (see FIG. 2a).

[0070] According to another embodiment, the images used in the diagnostic device for analyzing the body balance by analyzing the whole body images may be verified using the diagnostic image verification method described in this application. The DO to be diagnosed for the body imbalance may be the "whole body" (see FIG. 2b).

[0071] According to yet another embodiment, the images used in the diagnostic device for analyzing thyroid eye disease by analyzing eye images may be verified using the diagnostic image verification method described in the present application. The DO to be diagnosed for thyroid eye disease may be the "eye" (see FIG. 2c).

[0072] A diagnostic object DO related to a target disease may refer to, but is not limited to, an object commonly known to be used in diagnosing the target disease (e.g., a body part examined for diagnosis), and may also refer to an object indirectly related to obtain information used in diagnosing the target disease.

[0073] As a specific example, when the target disease is "stroke," the first diagnosis target DO may be "face." This technology is also disclosed in Korean Patent No. 10-2274330 filed by Gachon University Industry-Academic Cooperation Foundation.

[0074] As another example, when the target disease is "thyroid eye disease," the first diagnostic target DO may be the "eye," the second diagnostic target DO may be the "eyelid," and the third diagnostic target DO may be the "area including the eye and the area surrounding the eye." This technology is also disclosed in Korean Patent Application No. 10-2021-0085542 filed by Thyroscope INC.

[0075] The above examples of diagnostic DO are provided to help clearly understand the concept of diagnostic DO described herein. Diagnostic DO is not limited to the above examples, and any object (target object, e.g., body part) related to the target disease to be diagnosed may be interpreted as diagnostic DO.

[0076] In the following, in describing some embodiments of the present application, the description is based on the case where the photographing device 1000 takes an image and the server 2000 verifies the captured image. However, for convenience of description, this is specifically described with reference to the embodiments. The technical idea described in the present application is applicable not only to the case of independent operation by the server 2000 or the photographing device 1000, but also to the case of distributed operation by the photographing device 1000, the server 2000, and an external device. Therefore, the implementation form of the concept of the present disclosure is not limited to the embodiments described below.

[0077] FIG. 3 is a diagram showing the configuration of an image capturing device 1000 and a server 2000 according to an embodiment of the present application.

[0078] The photographing device 1000 may include an image acquiring unit 1100, determining units 1201, 1202, . . . , 1299, a first storage unit 1300, a first communication unit 1400, a first controller 1500, a first input unit 1600, and a first output unit 1700.

[0079] The image acquisition unit 1100 may perform a function of taking an image. According to an embodiment of the present application, the image acquisition unit 1100 may acquire an image (e.g., a preview image) according to a preset image frame. The image acquisition unit 1100 may be a module suitable for taking an image, such as a camera, or may be a functional module for performing a similar function.

[0080] The determining units 1201, 1202, ..., 1299 may perform a function of determining whether a target image satisfies a photographing condition. According to an embodiment of the present application, the determining units 1201, 1202, ..., 1299 may determine whether an image acquired via the image acquiring unit 1100 satisfies a photographing condition.

[0081] The photographing device 1000 may include one or more determination units 1201, 1202, ..., 1299. According to an embodiment of the present application, the first determination unit 1201 may determine whether a first photographing parameter of a target image satisfies a first photographing condition, the second determination unit 1202 may determine whether a second photographing parameter of a target image satisfies a second photographing condition, and the Nth determination unit may determine whether an Nth photographing parameter of a target image satisfies an Nth photographing condition. Here, N may be a natural number of 2 or more. This means that there are multiple items evaluated by the photographing parameters, and there is a possibility that there are one or two items evaluated by the photographing parameters.

[0082] According to an embodiment of the present application, the first and second imaging parameters may be different from each other, for example, the first imaging parameter may be related to the diagnostic object DO, and the second imaging parameter may be related to the brightness of the image.

[0083] According to an embodiment of the present application, the first imaging parameter and the second imaging parameter may be the same, and the first imaging condition corresponding to the first imaging parameter and the second imaging condition corresponding to the second imaging parameter may be different from each other. For example, both the first imaging parameter and the second imaging parameter may be related to the diagnostic object DO, the first imaging condition may be a criterion related to the position of the diagnostic object DO, and the second imaging condition may be a criterion related to whether the diagnostic object DO is detected.

[0084] One or more determination units 1201, 1202, ..., 1299 included in the imaging device 1000 determine whether the target image satisfies the respective imaging conditions. When the determination units 1201, 1202, ..., 1299 determine that the target image satisfies all the pre-stored imaging conditions, the first controller 1500 may store the image captured using the image capture unit 1100.

[0085] The first storage unit 1300 may store various types of data and programs necessary for the operation of the photographing device 1000. In order to retain data regardless of the supply of system power, the first storage unit 1300 may be realized as a non-volatile memory such as a flash memory, or a hard disk drive. According to an embodiment of the present application, the first storage unit 1300 may store an algorithm for acquiring photographing parameters, photographing conditions corresponding to the photographing parameters, a program for determining whether the photographing parameters satisfy the stored photographing conditions, and / or a captured image.

[0086] According to an embodiment of the present application, an image analysis algorithm for detecting a diagnostic object DO may be stored in the first storage unit 1300. In other words, the first storage unit 1300 stores an image analysis algorithm for detecting an imaging parameter related to the diagnostic object DO and a corresponding condition. For example, the first image analysis algorithm may be a landmark image analysis algorithm. As another example, the first image analysis algorithm may be a pose estimation algorithm. As yet another example, the first image analysis algorithm may be a color comparison algorithm.

[0087] The first communication unit 1400 may transmit and receive data so that the photographing device 1000 may perform two-way communication with an external device such as a server. The first communication unit 1400 may access an external device (e.g., the server 2000) via a wired / wireless wide / local area network or a local access method according to a preset communication protocol.

[0088] The first communication unit 1400 may be realized by a group of access ports or access modules for each device, so that the access protocol and the external device to be accessed are not limited to one type or format. The first communication unit 1400 may be built into the image capture device 1000, or all or part of the configuration may be provided additionally to the image capture device 1000 in the form of an add-on or dongle.

[0089] The first controller 1500 may perform functions to manage and control the overall operation of the imaging device 1000. The first controller 1500 may operate and process various types of information and control the operation of elements of the terminal.

[0090] The first controller 1500 may be realized as a computer or similar device according to hardware, software, or a combination thereof. Regarding hardware, the first controller 1500 may be provided in the form of an electronic circuit such as a CPU chip for performing control functions by processing electrical signals. Regarding software, the first controller 1500 may be provided in the form of a program for driving the hardware first controller 1500.

[0091] According to an embodiment of the present application, the first controller 1500 may determine, via the determination units 1201, 1202, ..., 1299, whether the image captured by the image capture unit 1100 satisfies the conditions stored in the first storage unit 1300. Furthermore, upon determining that the image satisfies the pre-stored photographing conditions, the first controller 1500 may store the captured image in the first storage unit 1300 and transmit it to the server 2000 via the first communication unit 1400.

[0092] The imaging device 1000 according to an embodiment of the present application may include a first input unit 1600 and / or a first output unit 1700 . The first input unit 1600 may perform a function of obtaining information from a user. The first input unit 1600 may receive a user input from a user. The user input may be provided in various forms, including but not limited to, a key input, a touch input, and / or a voice input.

[0093] The first input unit 1600 may be realized as a commonly used user input device. As an example, the first input unit 1600 may be, but is not limited to, a touch sensor for detecting a user's touch. Here, the "touch sensor" may refer to a piezoelectric touch sensor or a capacitive touch sensor for detecting a touch through a touch film attached to a touch panel or a display panel, and / or an optical touch sensor for detecting a touch by an optical method.

[0094] The first output unit 1700 may perform a function of outputting information so that a user can check the information. The first output unit 1700 may output information acquired from a user, acquired from an external device and / or processed information. The output of information may be provided in various forms, including but not limited to visual, auditory, and / or tactile output.

[0095] The first output unit 1700 may be implemented as a commonly used user output device. For example, the first output unit 1700 may be, but is not limited to, a display for outputting an image and / or a speaker for outputting sound. Here, the term "display" may refer to a broad range of image display devices, including liquid crystal displays (LCDs), light emitting diode (LED) displays, organic light emitting diode (OLED) displays, flat panel displays (FPDs), transparent displays, curved displays, flexible displays, 3D displays, holographic displays, projectors, and / or various other types capable of performing image output functions.

[0096] The first output unit 1700 may be integrated with the first input unit 1600. For example, when the first output unit 1700 is a display, the first output unit 1700 may be in the form of a touch display integrated with the touch sensor of the first input unit 1600.

[0097] The server 2000 may include a second communication unit 2100, verification units 2201, 2202, . . . , 2299, a diagnosis unit 2300, a second controller 2400, a second input unit 2500, a second output unit 2600, and a second storage unit 2700.

[0098] Similar to the above-mentioned first communication unit 1400, the second communication unit 2100 may execute a function of exchanging data with an external device. For example, the second communication unit 2100 may receive an image captured via the first communication unit 1400. Specifically, the second communication unit 2100 may receive the captured image and position information of the diagnostic target DO in the captured image via the first communication unit 1400.

[0099] The verification units 2201, 2202, ..., 2299 may perform a function of determining whether a target image satisfies a verification condition. According to an embodiment of the present application, the verification units 2201, 2202, ..., 2299 may determine whether a captured image received via the second communication unit 2100 satisfies a verification condition.

[0100] The server 2000 may include one or more verification units 2201, 2202, ..., 2299. According to an embodiment of the present application, the first verification unit 2201 may determine whether a first verification parameter of the captured image meets a first verification condition, the second verification unit 2202 may determine whether a second verification parameter meets a second verification condition, and the Mth verification unit 2299 may determine whether an Mth verification parameter meets an Mth verification condition. Here, M may be a natural number equal to or greater than 2. This means that there are multiple items evaluated by the verification parameters, and there may be one or two items evaluated by the verification parameters.

[0101] The first and second validation parameters may be different from each other, for example, the first validation parameter may be related to the diagnostic object DO and the second validation parameter may be related to the brightness of the photograph.

[0102] The first and second verification parameters may be the same, and the first verification condition corresponding to the first verification parameter and the second verification condition corresponding to the second verification parameter may be different from each other. For example, both the first and second verification parameters may be related to the diagnostic target DO, the first verification condition may be a criterion related to the position of the diagnostic target DO, and the second verification condition may be a criterion related to whether the diagnostic target DO is detected.

[0103] The server 2000 may evaluate the verification parameters and verification conditions corresponding to the photographing parameters and photographing conditions evaluated by the photographing device 1000. As a specific example, the first photographing parameters and the first verification parameters may be the same, and the first photographing conditions corresponding to the first photographing parameters and the first verification conditions corresponding to the first verification parameters may be the same.

[0104] According to one embodiment of the present application, the shooting conditions already determined by the shooting device 1000 are re-evaluated as verification conditions by the server 2000, thereby preventing the accuracy of diagnosis by the diagnostic device itself from being reduced due to a lack of quality (or accuracy) of the diagnostic image.

[0105] The server 2000 may not evaluate as the verification parameters and verification conditions some of the photographing parameters and photographing conditions evaluated by the photographing apparatus 1000. As a specific example, the second photographing parameters and the second verification parameters may be different from each other.

[0106] According to an embodiment of the present application, there is no need to perform verification through the verification condition for a parameter already determined in the imaging condition, unless the parameter is related to the diagnostic object DO, so the second imaging parameter may not be the same as the second verification parameter. In this case, when the imaging device 1000 evaluates the first to Nth imaging parameters and the server 2000 evaluates the first to Mth verification parameters, N may be a number greater than M.

[0107] One or more verification units 2201, 2202, ..., 2299 included in the server 2000 may determine whether the target image satisfies the respective verification conditions. When the verification units 2201, 2202, ..., 2299 determine whether the captured image satisfies all the pre-stored verification conditions, the second controller 2400 may determine the captured image as a diagnostic image, and perform an operation for obtaining diagnostic assistance information via the diagnosis unit 2300, or may store the diagnostic image via the second storage unit 2700.

[0108] The diagnostic unit 2300 may execute a function of acquiring diagnostic assistance information using an image. The diagnostic unit 2300 may execute a function of acquiring information (e.g., diagnostic assistance information) on a target disease based on a diagnostic image by using a diagnostic algorithm stored in the second storage unit 2700. As a specific example, the second storage unit 2700 may store a diagnostic model trained using both an image including a diagnostic target DO and information on whether or not the target disease has occurred, and the diagnostic unit 2300 may execute a function of acquiring diagnostic assistance information based on the diagnostic model and the diagnostic image under the control of the second controller 2400. The diagnostic model may mean an artificial intelligence model in which functions and / or parameters are stored.

[0109] According to another embodiment of the present application, the diagnostic unit 2300 may be included in a separate server, and the server 2000 may obtain diagnostic assistance information by sending diagnostic images to the separate server via the second communication unit 2100.

[0110] Similar to the first controller 1500, the second controller 2400 may perform a function of managing and controlling the operation of the server 2000. Similar to the first input unit 1600, the second input unit 2500 may perform a function of obtaining information from a user. Similar to the first output unit 1700, the second output unit 2600 may perform a function of outputting information so that the user can check the information.

[0111] Similar to the first storage unit 1300, the second storage unit 2700 may store various types of data and programs necessary for the operation of the server 2000.

[0112] According to an embodiment of the present application, the second storage unit 2700 may be in the form of a database. The database is structured for each keyword category, and desired information can be found by a specific keyword. A structured database may be realized in various ways depending on the design and construction method of the database, and therefore a detailed description of the structured database is omitted.

[0113] According to an embodiment of the present application, an image analysis algorithm for detecting the diagnostic object DO may be stored in the second storage unit 2700. In other words, the second storage unit 2700 stores an image analysis algorithm for detecting a verification parameter related to the diagnostic object DO and a corresponding condition. For example, the second image analysis algorithm may be a landmark image analysis algorithm. As another example, the second image analysis algorithm may be a pose estimation algorithm. As yet another example, the second image analysis algorithm may be a color comparison algorithm.

[0114] According to an embodiment, the image analysis algorithm stored in the server 2000 and the image analysis algorithm stored in the user terminal 1000 may be algorithms for detecting the same object. However, the calculation amount of the image analysis algorithm stored in the server 2000 and the calculation amount of the image analysis algorithm stored in the user terminal 1000 may be different from each other. As a specific example, the two image analysis algorithms may be selected such that the calculation amount of the image analysis algorithm in the user terminal 1000, which needs to perform calculations in real time while taking pictures, is less than the calculation amount of the image analysis algorithm in the server 2000.

[0115] Descriptions of redundant functions / modules related to the second controller 2400, the second input unit 2500, the second output unit 2600, and the second storage unit 2700 will be omitted.

[0116] The server 2000 according to an embodiment of the present application may be one physical single server, or may be a distributed server in which throughput or roles are distributed across multiple servers.

[0117] Hereinafter, unless otherwise specified, the operation of the photographing device 1000 may be interpreted as being performed by the first controller 1500, and the operation of the server 2000 may be interpreted as being performed by the second controller 2400.

[0118] The operation of the image capture device 1000 (hereinafter referred to as a user terminal) and / or the server 2000 according to some embodiments of the present application will now be described in detail.

[0119] FIG. 4 is a flow chart illustrating a captured image acquisition operation of the user terminal 1000 according to one embodiment of the present application.

[0120] User terminal 1000 may provide a guide in step S110, obtain a preview image in step S120, perform decisions about imaging conditions in step S130, store a candidate diagnosis image in step S140, and transmit the candidate diagnosis image in step S150.

[0121] The first controller 1500 of the user terminal 1000 may execute control such that a guide is provided using the first output unit 1700 in step S110.

[0122] Here, the guide performs a function of assisting in taking an image. For example, the guide may be in the form of lines or characters output together with a preview image output on a display of the user terminal 1000. As another example, the guide may be in the form of sound output through a speaker of the user terminal 1000 to assist in taking a picture. However, the guide is not limited thereto.

[0123] The guide may be provided to support a part of the imaging parameters set for the imaging condition, or may be provided to support all of the imaging parameters set for the imaging condition. The imaging parameters supported by the guide may include imaging parameters related to the diagnostic target DO.

[0124] The guide may be provided in a form of presenting shooting conditions corresponding to the shooting parameters, may be provided in a form of visualizing the current state of the person to be photographed, or may be provided in a form of outputting both the shooting conditions and the current state. As a specific example, the guide provided to the user terminal may include a first guide for indicating an appropriate position of the eye and a second guide for indicating the current position of the eye.

[0125] FIG. 5 is a diagram illustrating a first output unit 1700 of the user terminal 1000 in a guide providing operation S110 according to an embodiment of the present application.

[0126] The guide output to the user terminal 1000 may include a first guide IG1, a second guide IG2, and a third guide IG3. The first guide IG1 may be a guidance indicator for positioning the user's face inside the first guide IG1 so that the user's face is kept at an appropriate distance from the user terminal 1000. The second guide IG2 may be an indicator for guiding the alignment of the user's eye position with the second guide IG2 so that an image is acquired in which the user's eyes are in a predetermined position. The third guide IG3 may be a guidance indicator showing where the user's nose line should be so that the left-right angle (yaw) of the user's face does not deviate from a pre-stored reference.

[0127] According to one embodiment of the present application, when the guide shown in FIG. 5 is provided when taking an image for diagnosing (predicting) thyroid eye disease, the second guide IG2 may be a guide regarding the diagnostic object DO.

[0128] Returning to FIG. 4, the first controller 1500 of the user terminal 1000 may execute control such that a preview image is acquired using the image acquisition unit 1100 in step S120.

[0129] Here, the preview image may refer to an image acquired according to the frame rate determined in the image capture step. Specifically, the image capture operation is started according to a user input, or an automatic capture operation is started when a pre-stored condition is met, and the captured image is stored accordingly. The image captured before this storage step may refer to the preview image.

[0130] The first controller 1500 of the user terminal 1000 may use the determination units 1201, 1202, . . . , 1299 to determine whether the acquired preview image satisfies the capture condition.

[0131] Upon determining that the target image (e.g., the preview image to be checked) meets the shooting conditions, the first controller 1500 of the user terminal 1000 may store the captured image using the first storage unit 1300 in step S140, and may transmit the captured image to the server 2000 using the first communication unit 1400 in step S150.

[0132] If it is determined that the target image does not satisfy the shooting conditions, the first controller 1500 of the user terminal 1000 may, in step S130, use the determination units 1201, 1202, ..., 1299 to determine whether another image acquired in step S120 satisfies the shooting conditions.

[0133] FIG. 6 illustrates a method S130 for determining whether a photographing condition is met according to an embodiment of the present application.

[0134] The first storage unit 1300 may store one or more imaging parameters determined to evaluate whether the target image satisfies the imaging conditions and conditions corresponding to the imaging parameters. The imaging parameters evaluated when determining whether the imaging conditions are satisfied in step S130 may be one imaging parameter related to the diagnostic target DO, or multiple imaging parameters at least some of which are related to the diagnostic target DO.

[0135] According to an embodiment of the present application, the imaging conditions related to the diagnostic object DO may relate to the entire detection of the diagnostic object DO. For example, if the diagnostic object DO is an "eye", the first controller 1500 may evaluate whether the eye is completely (i.e., entirely) detected in the preview image. As another example, if the diagnostic object DO is a "whole body", the first controller 1500 may evaluate whether all of the determined joints are detected in the preview image.

[0136] According to an embodiment of the present application, the imaging condition related to the diagnostic object DO may be determined by comparing the diagnostic object DO with a pre-stored reference area. For example, when the detection area of ​​the diagnostic object DO is located in the target area, the imaging condition related to the diagnostic object DO may be set to be satisfied. As a specific example, when the diagnostic object DO is an "eye", the first controller 1500 may evaluate whether the detected eye outline overlaps with the area stored as the eye position.

[0137] FIG. 7 is a diagram illustrating imaging parameters according to an embodiment of the present application.

[0138] As a specific example, when the first shooting parameter DP1 is an eye landmark in an image acquired by driving a landmark detection algorithm, the landmarks of both eyes in a preview image may be acquired as the first shooting parameter DP1, as shown in FIG. 7. The first controller 1500 may compare the first shooting parameter DP1 with the second image guide IG2. Alternatively, the first controller 1500 may compare the first shooting parameter DP1 with a pre-stored eye position. The first controller 1500 may evaluate whether the detected eye contour (i.e., the first shooting parameter DP1) overlaps with the area stored as the eye position, and determine whether the first shooting parameter DP1 satisfies the first shooting condition.

[0139] As another specific example, when the diagnostic object DO is an "eye", the first controller 1500 may evaluate whether or not the center of the detected eye contour is included in the area stored as the position of the pupil.

[0140] According to an embodiment of the present application, the shooting parameters evaluated when determining whether the shooting conditions are satisfied in step S130 may include general indicators related to shooting quality. For example, the first controller 1500 may evaluate whether the ambient brightness at the time when the target image is captured is equal to or greater than a reference value. As another example, the first controller 1500 may evaluate whether the acceleration sensor value of the user terminal at the time when the target image is captured is equal to or greater than a reference value.

[0141] Referring back to FIG. 6, when determining whether the target image satisfies the photographing conditions in step S130, it may be possible to evaluate whether each of the pre-set photographing parameters is satisfied.

[0142] As a specific example, in step S131, the first controller 1500 may analyze the preview image using the first determination unit 1201, obtain first shooting parameters, and evaluate whether a first shooting condition corresponding to the first shooting parameters is satisfied.

[0143] In step S132, the first controller 1500 may use the second determination unit 1202 to analyze the preview image, obtain second shooting parameters, and evaluate whether a second shooting condition corresponding to the second shooting parameters is satisfied.

[0144] In step S133, the first controller 1500 may use the Nth determination unit 1299 to analyze the preview image, obtain the Nth shooting parameter, and evaluate whether the Nth shooting condition corresponding to the Nth shooting parameter is satisfied.

[0145] Determining whether a first shooting condition corresponding to a first shooting parameter is satisfied in step S131, determining whether a second shooting condition corresponding to a second shooting parameter is satisfied in step S132, ..., and determining whether an Nth shooting condition corresponding to an Nth shooting parameter is satisfied in step S133 may be performed sequentially or in parallel.

[0146] According to an embodiment of the present application, when it is determined that all of the first to Nth shooting parameters satisfy the first to Nth conditions, respectively, the first controller 1500 may store the captured image. In this case, the condition in which all of the first to Nth conditions are satisfied may be defined as a pre-stored condition. That is, when the first controller 1500 determines that the pre-stored condition is satisfied, it may store the captured image. More specifically, satisfying the pre-stored condition may mean that all of the first to Nth shooting parameters satisfy the first to Nth conditions, respectively.

[0147] According to another embodiment of the present application, when it is determined that some of the first to Nth shooting parameters satisfy the first to Nth conditions, respectively, the first controller 1500 may store the captured image. In this case, the condition under which some of the first to Nth conditions are satisfied may be defined as a pre-stored condition. That is, when the first controller 1500 determines that a pre-stored condition is satisfied, it may store the captured image. More specifically, satisfying the pre-stored condition may mean that some of the first to Nth shooting parameters satisfy the first to Nth conditions, respectively.

[0148] The pre-stored conditions are not limited to the above embodiment. For example, when only the first shooting parameter is acquired, the condition in which the first condition is satisfied may be defined as the pre-stored condition.

[0149] According to one embodiment of the present application, the first memory unit 1300 may store algorithms for detecting several shooting parameters to be evaluated when determining whether the shooting conditions are satisfied in step S130, and the amount of calculation and / or processing speed of the algorithms for detecting each shooting parameter may be different from each other.

[0150] 8, 9 and 10 are diagrams illustrating the evaluation target images, the evaluation frequency of the shooting parameters, and the stored captured images according to the speed of determining whether the condition corresponding to each shooting parameter is satisfied.

[0151] User terminal 1000 may acquire preview images according to a preset frame rate. Preferably, during a break between the time when a preview image is acquired and the time when the next preview image is acquired, it may be evaluated for each preview image whether a condition corresponding to the shooting parameter is satisfied when determining whether the condition corresponding to each shooting parameter is satisfied.

[0152] However, if the user terminal 1000 cannot determine whether a condition corresponding to at least one of several shooting parameters is satisfied within the break time between the time a preview image is captured and the time the next preview image is captured, it is necessary to set a determination period for the shooting conditions of each shooting parameter and a reference to the relationship between the determination periods.

[0153] According to an embodiment of the present application, the determination period of the imaging parameters may be synchronized based on the imaging parameter that takes the longest time to determine whether the imaging parameter condition is satisfied.

[0154] Referring to FIG. 8, the first image frame IF1, the second image frame IF2, the third image frame IF3, ..., the tenth image frame IF10 may be acquired according to a preset frame rate.

[0155] Assuming that the operation S133 of evaluating whether the Nth shooting parameter of the first image frame IF1 is satisfied is completed after acquiring the first image frame IF1 and acquiring the second image frame IF2, but before acquiring the third image frame IF3, all of the first to Nth shooting parameters may be designed to evaluate whether the conditions of each shooting parameter are satisfied once every three image frames.

[0156] The first image frame IF1, the fourth image frame IF4, the seventh image frame IF7, and the tenth image frame IF10 may be evaluated as to whether they satisfy the conditions of their respective shooting parameters, and the second image frame IF2, the third image frame IF3, the fifth image frame IF5, the sixth image frame IF6, etc. do not need to be evaluated as to whether they satisfy the conditions of their respective shooting parameters.

[0157] According to another embodiment of the present application, for the imaging parameters, each imaging parameter may independently have a time period to determine whether the condition is met, and the conditions for each imaging parameter may be evaluated in parallel to determine whether they are met.

[0158] Referring to FIG. 9, a first image frame IF1, a second image frame IF2, a third image frame IF3, ..., a tenth image frame IF10 may be acquired according to a preset frame rate.

[0159] The operation S131 of evaluating whether the first shooting parameter is satisfied may be performed for each frame. The operation S132 of evaluating whether the second shooting parameter is satisfied may be performed for each frame. The operation S133 of evaluating whether the Nth shooting parameter is satisfied may be performed every three image frames to evaluate whether the condition is satisfied.

[0160] When it is evaluated whether or not the conditions corresponding to the individual shooting parameters are satisfied according to the period described with reference to FIG. 9, the result of determining whether or not the conditions are satisfied may be obtained as shown in the table in FIG. 10.

[0161] In S134 for determining whether the first to Nth shooting parameters are satisfied, the determination may be made based on whether the conditions corresponding to the first to Nth shooting parameters are satisfied.

[0162] According to an embodiment of the present application, as shown in Fig. 10, the first controller 1500 may determine whether to store the captured image based on whether the latest first to Nth shooting parameters are satisfied. As a specific example, whether to store the captured image may be determined based on whether an operation S131 for the ninth image frame IF9 is satisfied, whether an operation S132 for the ninth image frame IF9 is satisfied, and whether an operation S133 for the seventh image frame IF7 is satisfied.

[0163] According to another embodiment of the present application, the first controller 1500 may determine whether to store the captured image based on whether the first shooting parameter or the Nth shooting parameter is satisfied at least once within the latest determined period. As a specific example, whether to store the captured image may be determined based on whether the operation S131 for the seventh image frame IF7, the eighth image frame IF8, or the ninth image frame IF9 is satisfied, whether the operation S132 for the seventh image frame IF7, the eighth image frame IF8, or the ninth image frame IF9 is satisfied, and whether the operation S133 for the seventh image frame IF7 is satisfied.

[0164] 6, upon determining that the first through Nth imaging parameters satisfy their corresponding respective conditions, a diagnostic candidate image may be selected in step S141 and stored in step S142. The selection of the diagnostic candidate image may correspond to the determination of the captured image.

[0165] According to one embodiment of the present application, the captured image (i.e., the diagnostic candidate image) may be an image that is determined to satisfy the imaging condition. With reference to FIG. 10, the seventh image frame IF7 may be stored as the captured image (i.e., the diagnostic candidate image). According to another embodiment of the present application, the captured image (i.e., the diagnostic candidate image) may be an image obtained immediately after the imaging condition is determined to be satisfied. With reference to FIG. 10, the tenth image frame IF10 may be stored as the captured image (i.e., the diagnostic candidate image).

[0166] 6, when it is determined that the first to Nth shooting parameters do not satisfy the conditions, the shooting conditions of an image other than the image whose shooting conditions have been checked may be checked. Here, the image whose shooting conditions are checked may be an image newly acquired after the image whose shooting conditions have been checked is acquired.

[0167] According to one embodiment of the present application, the image for which it is determined whether the shooting parameters are satisfied may be the image next to the image for which the shooting conditions are checked. With reference to FIG. 10, the shooting conditions of the first image frame IF1 may be checked, and then the shooting conditions of the third image frame IF3 may be checked. According to another embodiment of the present application, the image for which it is determined whether the shooting parameters are satisfied may be the image first acquired after the time it is determined whether the shooting conditions are satisfied based on the first to Nth shooting parameters. With reference to FIG. 10, the shooting conditions of the first image frame IF1 may be checked, and then the shooting conditions of the fourth image frame IF4 may be checked.

[0168] When the user terminal 1000 obtains the captured image, the user terminal 1000 may transmit the obtained captured image to the server 2000. The user terminal 1000 may transmit the captured image and information related to at least a part of the first to Nth shooting parameters. For example, the user terminal 1000 may transmit the captured image and information related to the detected position of the diagnostic object DO to the server 2000. As a specific example, when the diagnostic candidate image is a "face image including eyes" and information related to the "eye position" is obtained via an image analysis algorithm, the information related to the eye position and the face image including the eyes may be transmitted to the server.

[0169] FIG. 11 is a flow chart illustrating an image verification operation of the server 2000 according to one embodiment of the present application.

[0170] The second controller 2400 of the server 2000 may receive the diagnosis candidate image using the second communication unit 2100. The second controller 2400 of the server 2000 may receive the captured image using the second communication unit 2100.

[0171] According to an embodiment of the present application, the second controller 2400 may store the captured image (i.e., the diagnosis candidate image) and the detection values ​​of the user terminal 1000 related to the captured image in the second storage unit 2700. The detection values ​​of the user terminal 1000 may be related to the imaging parameters.

[0172] In step S220, the second controller 2400 of the server 2000 may use the verification units 2201, 2202, ..., 2299 to determine whether the captured image (ie, the diagnosis candidate image) satisfies a diagnostic condition.

[0173] According to an embodiment of the present application, the criteria for determining whether the diagnostic condition is satisfied may correspond to all or part of the criteria determined as the imaging condition. The determination of whether the diagnostic condition is satisfied may include a condition regarding the diagnostic object DO to determine whether the captured image can be used as a diagnostic image. However, since it is not necessary to determine again in the diagnostic condition all the imaging parameters determined in the imaging condition, the criteria for determining whether the diagnostic condition is satisfied may correspond to all or part of the criteria determined as the imaging condition.

[0174] As a specific example, the diagnostic target DO related to the criteria for determining whether the diagnostic condition is satisfied may be the same as the diagnostic target DO related to the criteria for determining whether the imaging condition is satisfied. If the diagnostic target DO determined by the imaging condition is the "whole body", the diagnostic target DO determined by the diagnostic condition may also be the "whole body". If the diagnostic target DO determined by the imaging condition is the "eye", the diagnostic target DO determined by the diagnostic condition may also be the "eye".

[0175] If it is determined that the captured image (i.e., the diagnostic candidate image) satisfies the diagnostic condition, the second controller 2400 of the server 2000 may store the image as a diagnostic image using the second storage unit 2700 in step S230, and may obtain diagnostic assistance information using the diagnosis unit 2300. If it is determined that the captured image (i.e., the diagnostic candidate image) does not satisfy the diagnostic condition, the second controller 2400 of the server 2000 may request the user terminal S240 to perform re-imaging in step S240.

[0176] FIG. 12 illustrates a method S220 for determining whether a diagnostic condition is met according to one embodiment of the present application.

[0177] One or more validation parameters determined to evaluate whether the captured image satisfies a diagnostic condition and conditions corresponding to the validation parameters may be stored in the second storage unit 2700. The validation parameters evaluated when determining whether the diagnostic condition is satisfied in step S220 may be one validation parameter related to the diagnostic target DO or multiple validation parameters, at least some of which are related to the diagnostic target DO.

[0178] According to an embodiment of the present application, the verification condition related to the diagnostic target DO may relate to the entire detection of the diagnostic target DO. For example, if the diagnostic target DO is an "eye", the second controller 2400 may evaluate whether the eye is completely (i.e., entirely) detected in the captured image. As another example, if the diagnostic target DO is a "whole body", the second controller 2400 may evaluate whether all of the determined joints are detected in the captured image.

[0179] According to an embodiment of the present application, the verification condition associated with the diagnostic target DO may be determined by comparing the diagnostic target DO with the imaging parameters received from the user terminal 1000. For example, the verification condition associated with the diagnostic target DO may be set as being satisfied if the detection area of ​​the diagnostic target DO acquired in the imaging condition checking step differs from the detection area of ​​the diagnostic target DO acquired in the verification condition checking step by less than a threshold value.

[0180] As a specific example, when the diagnostic object DO is an “eye”, the second controller 2400 may evaluate whether the eye contour detected by the user terminal 1000 is at a different position from the eye contour detected by the server 2000 by less than a threshold value.

[0181] FIG. 13 is a diagram illustrating validation parameters according to one embodiment of the present application.

[0182] When the first verification parameter VP1 is an eye landmark in an image acquired by driving a landmark detection algorithm, as shown in FIG. 13, both eye landmarks in the captured image may be acquired as the first verification parameter VP1.

[0183] The second controller 2400 may compare the first verification parameter VP1 with the first imaging parameter DP1. As a specific example, when the diagnostic object DO is an “eye”, the second controller 2400 may evaluate whether the eye contour detected as the first verification parameter VP1 is included in the eye contour detected as the first imaging parameter DP1 by the user terminal 1000.

[0184] Alternatively, the second controller 2400 may compare the first verification parameter VP1 with a reference area when the first imaging parameter DP1 is evaluated. As a specific example, when the diagnostic object DO is an "eye", the second controller 2400 may evaluate whether the center of the eye outline detected as the first verification parameter VP1 includes an area stored as the position of the iris.

[0185] According to an embodiment of the present application, the verification parameters evaluated when determining whether the diagnostic condition is met in step S220 may include general indicators related to the image capture quality. For example, the second controller 2400 may evaluate whether the captured image includes an area corresponding to shaking caused by the movement of the user terminal 1000 during capture.

[0186] The amount of calculation of the algorithm used in the server 2000 may be greater than the amount of calculation of the algorithm used in the user terminal 1000. This is because real-time shooting is performed when the user terminal 1000 checks the shooting parameters, and an algorithm that requires excessive operations is not suitable for operation. As a result, in the process of acquiring a diagnostic image, the diagnostic object DO analyzed using the shooting parameters is analyzed again by the server 2000, so that an accurate picture is acquired.

[0187] According to an embodiment of the present application, the image analysis algorithm for detecting the diagnostic target DO in the server 2000 and the image analysis algorithm for detecting the diagnostic target DO in the user terminal 1000 may be different types of image analysis algorithms. As a specific example, the image analysis algorithm for detecting the diagnostic target DO in the server 2000 may be an image segmentation algorithm, and the image analysis algorithm for detecting the diagnostic target DO in the user terminal 1000 may be a landmark detection algorithm.

[0188] According to another embodiment of the present application, the image analysis algorithm for detecting the diagnostic object DO in the server 2000 and the image analysis algorithm for detecting the diagnostic object DO in the user terminal 1000 may be the same type of image analysis algorithm, and the amount of calculation of the image analysis algorithm in the user terminal 1000 may be less than the amount of calculation of the image analysis algorithm in the server 2000. As a specific example, the image analysis algorithm for detecting the diagnostic object DO in the server 2000 uses Dlib for landmark detection. TM The image analysis algorithm for detecting the diagnosis target DO on the user terminal 1000 uses the get_frontal_face_detector of Google TM ML kit-Face detection may be used, but there is no restriction.

[0189] Referring back to FIG. 12, in step S220, when determining whether the captured image meets a diagnostic condition, it may be evaluated whether each of the predefined validation parameters is met.

[0190] As a specific example, in step S221, the second controller 2400 may analyze the image captured using the first verification unit 2201, obtain a first verification parameter, and evaluate whether a first verification condition corresponding to the first verification parameter is satisfied.

[0191] In step S222, the second controller 2400 may analyze the captured image using the second verification unit 2202, obtain a second verification parameter, and evaluate whether a second verification condition corresponding to the second verification parameter is satisfied.

[0192] In step S223, the second controller 2400 may analyze the captured image using the Mth verification unit 2299, obtain an Mth verification parameter, and evaluate whether an Mth verification condition corresponding to the Mth verification parameter is satisfied.

[0193] Determining whether a first verification condition corresponding to a first verification parameter is satisfied in step S221, determining whether a second verification condition corresponding to a second verification parameter is satisfied in step S222, ..., and determining whether an Mth verification condition corresponding to an Mth verification parameter is satisfied in step S223 may be performed sequentially or in parallel.

[0194] If it is determined that all of the first to Mth verification parameters are satisfied, the second controller 2400 may store the captured image as a diagnostic image in step S230. Storing the diagnostic image may mean that the captured image is determined as a target image from which diagnostic assistance information is obtained, or may mean that the captured image is stored after performing preprocessing required for obtaining diagnostic assistance information.

[0195] When the captured image is determined as the target image from which diagnostic assistance information is to be acquired, the server 2000 may acquire the diagnostic assistance information related to the target image via the diagnosis unit 2300. However, without being limited thereto, it is also possible to realize a form in which the captured image is transmitted to a doctor so that the doctor can perform remote medical care.

[0196] According to another embodiment of the present application, if the target image is used as a diagnostic image, the image may be cropped and stored with reference to validation parameters associated with the diagnostic object DO, as will be described in more detail below with reference to FIG.

[0197] According to one embodiment of the present application, if it is determined that the first to Mth verification parameters do not satisfy the condition, the user terminal 1000 may be requested to perform re-imaging. According to another embodiment of the present application, if it is determined that the first to Mth verification parameters do not satisfy the condition but the position of the diagnostic object DO detected by the user terminal 1000 and the position of the diagnostic object DO detected by the server 2000 are slightly different from each other, post-processing of the captured image may be performed in the form of translation, such that the position of the diagnostic object DO detected by the server 2000 is located in the reference region.

[0198] FIG. 14 is a diagram illustrating the operation of storing a diagnostic image and using it to obtain diagnostic assistance information according to one embodiment of the present application.

[0199] The second controller 2400 may perform pre-processing on the image captured in step S231 to obtain a diagnostic image, and store the obtained diagnostic image in step S232. The second controller 2400 may also provide the diagnostic image to a diagnostic algorithm to obtain information about a target disease.

[0200] Pre-processing performed on the captured images may take the form of cropping, so that areas other than the area of ​​the diagnostic DO are not used as noise in the diagnostic algorithm.

[0201] In step S231, the second controller 2400 may pre-process the diagnostic image based on a verification parameter related to the diagnostic object DO. As a specific example, the second controller 2400 may acquire the diagnostic image by performing cropping with reference to a first verification parameter VP1, which is a verification parameter related to the diagnostic object DO, so that only a region including the diagnostic object DO remains. Alternatively, in step S231, the second controller 2400 may pre-process the diagnostic image based on the verification parameter related to the diagnostic object DO and the imaging parameter related to the diagnostic object DO.

[0202] A specific method for acquiring diagnostic images used for diagnosis is described. The above method for acquiring diagnostic images may be applied to any diagnostic device that acquires information regarding a disease by analyzing images.

[0203] In order to facilitate understanding of the above method for obtaining a diagnostic image, the technical ideas disclosed in the present application will be elucidated below with reference to several specific embodiments.

[0204] The user terminal 1000 may evaluate whether at least a first imaging parameter satisfies a first imaging condition. The first imaging parameter may be related to a diagnostic object DO. The user terminal 1000 may obtain the first imaging parameter based on a preview image, and evaluate whether the obtained first imaging parameter satisfies the first imaging condition.

[0205] When the first imaging parameters are acquired, a first image analysis algorithm may be used, which may be a detection model trained by labeling DOs of interest in the image.

[0206] The user terminal 1000 may acquire first shooting parameters based on the preview image, evaluate whether the acquired first shooting parameters satisfy first shooting conditions, and acquire a captured image if it is determined that the first shooting conditions are satisfied.

[0207] The user terminal 1000 may transmit the captured image and the analysis results of the first image analysis algorithm to the server 2000 .

[0208] The server 2000 may evaluate whether at least a first validation parameter satisfies a first validation condition. The first validation parameter may be related to a diagnostic target DO. The server 2000 may obtain the first validation parameter based on the captured image, and evaluate whether the obtained first validation parameter satisfies a first validation condition.

[0209] If the first validation parameters are obtained, a second image analysis algorithm may be used, which may be a detection model trained by labeling the DOs of interest in the image.

[0210] The server 2000 may obtain a first verification parameter based on the captured image, evaluate whether the obtained first verification parameter satisfies a first verification condition, and store the captured image as a diagnostic image if it evaluates that the first verification condition is satisfied.

[0211] 15a and 15b are diagrams illustrating a method for eye disease related imaging according to one embodiment of the present application.

[0212] According to an embodiment of the present application, the first image analysis algorithm may be a first landmark detection algorithm, the target eye disease may be thyroid eye disease, the diagnosis target DO may be an eye, and the first shooting parameter may be an eye landmark. For the first shooting parameter, an eye landmark may be selected from the face landmarks obtained through the first landmark detection algorithm, or only an eye landmark may be obtained through the first landmark algorithm (see FIG. 15a). According to an embodiment of the present application, if the first landmark detection algorithm detects a pupil landmark and / or an iris landmark, the first shooting parameter may be a pupil position based on the pupil landmark and / or the iris landmark. According to another embodiment of the present application, if the first landmark detection algorithm detects an eye-eyelid boundary, the first shooting parameter may be a range of possible positions of the pupil based on the eye-eyelid boundary.

[0213] The second image analysis algorithm may be a second landmark detection algorithm, the target eye disease may be thyroid eye disease, the diagnosis target DO may be an eye, and the first validation parameter may be an eye landmark. Similarly, for the first validation parameter, an eye landmark may be selected from the face landmarks obtained through the second landmark detection algorithm, or only eye landmarks may be obtained through the second landmark algorithm. According to an embodiment of the present application, if the second landmark detection algorithm detects a pupil landmark and / or an iris landmark, the first validation parameter may be a pupil position based on the pupil landmark and / or the iris landmark. According to another embodiment of the present application, if the second landmark detection algorithm detects an eye-eyelid boundary, the first validation parameter may be a range of possible positions of the pupil based on the eye-eyelid boundary.

[0214] Here, according to one embodiment of the present application, the first photographing condition may be set to a condition in which i) the eye landmark obtained via the first landmark detection algorithm and ii) the pre-stored eye area are different from each other by a threshold or less. According to another embodiment of the present application, the first photographing condition may be set to a condition in which i) the pupil position and / or the range of possible pupil positions obtained via the first landmark detection algorithm and ii) the pre-stored pupil position and / or the range of possible pupil positions are different from each other by a threshold or less.

[0215] According to one embodiment of the present application, the first verification condition may be set to a condition in which i) an eye landmark obtained via the first landmark detection algorithm and ii) an eye landmark obtained via the second landmark detection algorithm are different from each other by a threshold or less. According to another embodiment of the present application, the first verification condition may be set to a condition in which i) a pupil position and / or a range of possible pupil positions obtained via the first landmark detection algorithm and ii) a pupil position and / or a range of possible pupil positions obtained via the second landmark detection algorithm are different from each other by a threshold or less.

[0216] According to another embodiment of the present application, the first image analysis algorithm may be a first landmark detection algorithm, the target eye disease may be thyroid eye disease, the diagnosis target DO may be an eye, and the first shooting parameter may be an eye landmark. For the first shooting parameter, an eye landmark may be selected from the face landmarks obtained through the first landmark detection algorithm, or only an eye landmark may be obtained through the first landmark algorithm (see FIG. 15a). According to an embodiment of the present application, if the first landmark detection algorithm detects a pupil landmark and / or an iris landmark, the first shooting parameter may be a pupil position based on the pupil landmark and / or the iris landmark. According to another embodiment of the present application, if the first landmark detection algorithm detects an eye-eyelid boundary, the first shooting parameter may be a range of possible positions of the pupil based on the eye-eyelid boundary.

[0217] The second image analysis algorithm may be an image segmentation algorithm, the target eye disease may be thyroid eye disease, the diagnosed DO may be an eye, and the first validation parameter may be an iris area predicted using the image segmentation algorithm (see FIG. 15b). According to one embodiment of the present application, if the image segmentation algorithm predicts the eye area, the first validation parameter may be a range of possible positions of the pupil based on the area inside the eye-lid boundary (i.e., the eye area). According to another embodiment of the present application, if the image segmentation algorithm predicts the cornea area, the first validation parameter may be a pupil position based on the area inside the cornea boundary (i.e., the cornea area).

[0218] Here, according to one embodiment of the present application, the first photographing condition may be set to a condition in which i) the eye landmark obtained via the first landmark detection algorithm and ii) the pre-stored eye area are different from each other by a threshold or less. According to another embodiment of the present application, the first photographing condition may be set to a condition in which i) the pupil position and / or the range of possible pupil positions obtained via the first landmark detection algorithm and ii) the pre-stored pupil position and / or the range of possible pupil positions are different from each other by a threshold or less.

[0219] According to one embodiment of the present application, the first verification condition may be set to a condition that the center of the iris region predicted using the image segmentation algorithm is included within the eye landmark obtained via the first landmark detection algorithm. According to another embodiment of the present application, the first verification condition may be set to a condition that i) the range of possible pupil positions and / or pupil positions obtained via the first landmark detection algorithm and ii) the range of possible pupil positions and / or pupil positions obtained via the image segmentation algorithm differ from each other by less than a threshold value.

[0220] According to an embodiment of the present application, a diagnostic module for obtaining diagnostic assistance information based on a diagnostic image may be trained using images verified by the above procedure. In other words, even when training a diagnostic module, images are obtained through the above image verification method, so that the diagnostic module is trained using more consistent data to improve accuracy.

[0221] 16a and 16b are diagrams illustrating a method for acquiring imbalance-related images of a body according to an embodiment of the present application.

[0222] According to an embodiment of the present application, the first image analysis algorithm may be an object detection algorithm, the target disease may be a body imbalance, the diagnostic object DO may be the whole body, and the first imaging parameter may be a bounding box corresponding to the whole body (see FIG. 16a). The second image analysis algorithm may be an object detection algorithm, the target disease may be a body imbalance, the diagnostic object DO may be the whole body, and the first verification parameter may be a bounding box corresponding to the whole body.

[0223] Here, the first photographing condition may be set to a condition in which i) the bounding box obtained via the first image analysis algorithm and ii) the pre-stored whole body region are different from each other by less than a threshold value.

[0224] Here, the first verification condition may be set to a condition in which i) the bounding box obtained via the second image analysis algorithm and ii) the bounding box obtained via the first image analysis algorithm are different from each other by less than a threshold value.

[0225] According to another embodiment of the present application, the first image analysis algorithm may be an object detection algorithm, the target disease may be a body imbalance, the diagnostic object DO may be the whole body, and the first imaging parameter may be a bounding box corresponding to the whole body (see FIG. 16a). The second image analysis algorithm may be a posture detection algorithm, the target disease may be a body imbalance, the diagnostic object DO may be the whole body, and the first verification parameter may be a line corresponding to a joint.

[0226] Here, the first photographing condition may be set to a condition in which i) the bounding box obtained via the first image analysis algorithm and ii) the pre-stored whole body region are different from each other by less than a threshold value.

[0227] Here, the first verification condition may be set to a condition that a line corresponding to a joint obtained via the second image analysis algorithm is inside a bounding box obtained via the first image analysis algorithm.

[0228] Although not shown separately, the following aspects may be realized without being limited to the above description: The user terminal 1000 and the server 2000 may determine whether or not facial feature points are detected for stroke diagnosis, or the user terminal 1000 may determine whether or not facial feature points are detected, and the server 2000 may determine the aspect ratio of a specific part based on the facial feature points. However, the present invention is not limited thereto.

[0229] In addition, in the description of the concept of this specification, it has been described that the user terminal 1000 performs image capture and the server 2000 performs image verification, but this is merely an example for convenience of description. The following forms may be realized. The user terminal 1000 may perform all operations described in this specification. Or, the user terminal 1000 only performs image acquisition and storage, and the server 2000 determines whether the capture parameters meet the criteria and whether the verification parameters meet the criteria. However, this is not limited to this.

[0230] In addition, in the explanation of the concept of this specification, the above explanation is given on the assumption that the photographing device 1000 is a user terminal, but this is merely an example for convenience of explanation. The photographing device 1000 may be a user terminal for taking images, a user terminal for taking fundus images or X-ray images, or a medical device other than a user terminal.

[0231] The method according to the above-mentioned embodiment may be written as a computer executable program, and may be implemented in a general-purpose digital computer that executes the program using a computer readable recording medium. Also, data structures, program instructions, or data files that may be used in the embodiments of the present disclosure may be recorded in a computer readable recording medium through various means. Examples of computer readable recording media may include all types of storage devices in which data readable by a computer system is stored. Examples of computer readable recording media include magnetic media, such as hard disks, floppy disks, and magnetic tapes, optical media, such as CD-ROMs and DVDs, magneto-optical media, such as floptical disks, and hardware devices, such as ROMs, RAMs, and flash memories, that are specifically configured to store and implement program instructions. Also, the computer readable recording medium may be a transmission medium for transmitting signals that specify program instructions, data structures, and the like. Examples of program instructions include high-level language codes, such as those generated by a compiler, and executed by a computer using an interpreter.

[0232] Although the embodiments of the present application have been described with reference to limited embodiments and drawings, the technical ideas or embodiments disclosed in this specification are not limited to the above-mentioned embodiments, and those skilled in the art will understand that various modifications and changes can be made from the specification. Therefore, the scope of the present application is defined by the claims rather than the above description, and all equivalents thereof are included in the scope and spirit of the present disclosure.

Claims

1. A diagnostic image management system for managing diagnostic images used as input data to a diagnostic model for generating diagnostic support information for an eye as the object of diagnosis, Capture the image only if the pre-saved capture conditions for the preview image are met. Using the first algorithm, the preview position information of the target to be diagnosed, represented in the preview image, is determined for the aforementioned preview image. The preview location information and the captured image are sent to the server. A user terminal configured as follows, The server is configured to save diagnostic images based on the captured images, Equipped with, The aforementioned server, The captured image and the preview position information are received from the user terminal. Using the captured image, the verified location information of the object to be diagnosed, represented in the captured image, is determined using the second algorithm. If it is determined that the captured image satisfies the pre-saved verification conditions, the captured image is saved as the diagnostic image. If it is determined that the captured image does not satisfy the pre-saved verification conditions, a recapture request is sent to the user terminal. It is configured in such a way, The aforementioned pre-saved verification conditions are: The verification conditions include a comparison between the preview position information of the target to be diagnosed, as shown in the preview image, and the verified position information of the target to be diagnosed, as shown in the captured image. Not all of the aforementioned pre-saved capture conditions are exactly the same. It is set up to do so, The second algorithm used to determine the verified position information from the captured image requires a higher computational load than the first algorithm used to determine the preview position information from the preview image. Diagnostic image management system.

2. The preview position information includes information regarding the detection position of the region including the diagnostic target in the preview image generated by the user terminal, The user terminal is configured to compare the preview position information with a first region that has been stored in advance. The diagnostic image management system according to claim 1.

3. The preview position information includes information regarding the angle of the region in the preview image that includes the object to be diagnosed, The user terminal is configured to compare the preview position information with the angle of the region including the diagnostic target, which has been stored in advance. The diagnostic image management system according to claim 1.

4. The first algorithm used to determine the preview position information includes a first landmark detection algorithm, The second algorithm used to determine the verified location information includes a second landmark detection algorithm, The aforementioned preview position information is The first landmark of the aforementioned eye, This includes information regarding the detection location of the target to be diagnosed in the preview image, The verified location information is, The second landmark of the aforementioned eye, This includes information regarding the detection location of the object to be diagnosed in the captured image, The diagnostic image management system according to claim 1.

5. The first algorithm used to determine the preview position information includes a first landmark detection algorithm, The second algorithm used to determine the verified location information includes an image segmentation algorithm, The aforementioned preview position information is The aforementioned eye landmark, Includes information regarding the detection location of the target to be diagnosed in the preview image, The verified location information is, The aforementioned region of the eye, This includes information regarding the detection location of the target to be diagnosed in the captured image, The diagnostic image management system according to claim 1.

6. The server is configured to determine whether the first verification condition is met by comparing the difference between the verified location information and the preview location information with a threshold value. The diagnostic image management system according to claim 1.

7. The user terminal is A preview image is acquired according to a pre-set frame rate. One of the aforementioned preview images is sent to the server as the captured image. It is configured in such a way. The diagnostic image management system according to claim 1.

8. The user terminal is If it is determined that the pre-saved capture conditions for the preview image are not met, the second preview image is analyzed to determine whether or not the pre-saved capture conditions are met. It is configured in such a way, The second preview image is acquired after it is determined that the pre-saved capture conditions for the preview image are not met. The diagnostic image management system according to claim 1.

9. The user terminal is When it is determined that the pre-saved capture conditions for the preview image are met, the second preview image is sent to the server as the captured image. It is configured in such a way, The second preview image is captured after it is determined that the pre-saved capture conditions for the preview image have been met. The diagnostic image management system according to claim 1.

Images