Method and device for early diagnosis and management of varicose veins

Abstract

Embodiments provide a method by which a server early diagnoses and manages varicose veins, the method comprising the steps of: acquiring varicose vein-related information from a user device; digitizing a capillary exposure on the basis of analysis of the varicose vein-related information; evaluating the risk of varicose veins on the basis of the digitized capillary exposure; and transmitting, to the user device, information regarding varicose vein evaluation results on the basis of the evaluated risk of varicose veins.

Description

Method and device for early diagnosis and management of varicose veins of the lower extremities

[0001] The embodiments relate to a method and device for managing varicose veins in the lower extremities through early diagnosis of varicose veins. More specifically, the embodiments relate to a method and device for early diagnosis and management of varicose veins in the lower extremities by analyzing images acquired from a user device.

[0002] Varicose veins are a condition in which the superficial veins of the lower extremities swell abnormally due to dysfunction of the unilateral venous valves. Initially, varicose veins may present no symptoms other than discomfort, but if left untreated, they can progress and lead to various complications. The incidence of varicose veins generally increases with age, and it is more common in women than in men.

[0003] The number of patients with varicose veins is steadily increasing, and the resulting social costs are also increasing. Therefore, to reduce the prevalence of varicose veins and the associated social costs, an evaluation system for early diagnosis and management of varicose veins is necessary. Considering the above, the following describes a method for early diagnosis and management of varicose veins through a non-face-to-face service platform.

[0004] [Prior Art Literature]

[0005] [Patent Document]

[0006] (Patent Document 1) Korean Patent Publication No. 10-2022-0019180A

[0007] The present specification can provide a method for early diagnosis and management of varicose veins of the lower extremities.

[0008] The present specification may provide a method for a platform that acquires image information from a user device for early diagnosis of varicose veins of the lower extremities and evaluates the risk level through the image information.

[0009] This specification can provide a method for early diagnosis and management of varicose veins through a non-face-to-face service platform.

[0010] The present specification can provide a method for extracting an image for judging varicose veins in the lower extremities.

[0011] The present specification can provide a method for determining the risk of varicose veins in the lower extremities by analyzing images related to varicose veins in the lower extremities.

[0012] The problem to be solved by this specification is not limited to what has been described above, and can be expanded to various matters that can be derived from the embodiments of the invention described below.

[0013] According to one embodiment of the present specification, a method for early diagnosis and management of varicose veins by a server may include a step of obtaining information related to varicose veins from a user device, a step of quantifying capillary exposure based on analysis of the information related to varicose veins, a step of evaluating a risk of varicose veins based on the quantified capillary exposure, and a step of transmitting information on the result of the evaluation of varicose veins to the user device based on the evaluated risk of varicose veins.

[0014] In addition, according to one embodiment of the present specification, a server for early diagnosis and management of lower extremity varicose veins includes a memory for storing lower extremity varicose vein-related information, a transceiver for communicating with a user device, and a processor for controlling the memory and the transceiver, wherein the processor can obtain lower extremity varicose vein-related information from the user device, quantify capillary exposure based on analysis of the lower extremity varicose vein-related information, evaluate lower extremity varicose vein risk based on the quantified capillary exposure, and transmit lower extremity varicose vein evaluation result information to the user device based on the evaluated lower extremity varicose vein risk.

[0015] In addition, according to one embodiment of the present specification, a method for early diagnosis and management of varicose veins by a user device includes a step of transmitting information related to varicose veins to a server and a step of acquiring varicose vein evaluation result information from the server based on a risk of varicose veins, wherein the server can digitize capillary exposure based on analysis of the information related to varicose veins and evaluate the risk of varicose veins based on the digitized capillary exposure to generate varicose vein evaluation result information.

[0016] Additionally, the following may be commonly applied:

[0017] According to one embodiment of the present specification, the information related to lower extremity varicose veins may include at least one of a lower extremity varicose veins-related image, a lower extremity varicose veins-related video, and an additional image.

[0018] In addition, according to one embodiment of the present specification, when the image related to lower extremity varicose veins is an image of the user's lower body part and the capillary exposure is quantified based on the analysis of information related to lower extremity varicose veins, the server can derive a parameter per pixel for the user's lower body part from the image related to lower extremity varicose veins, derive a standard deviation based on a plurality of parameters per pixel to identify capillaries, and quantify the capillary exposure through capillaries that are higher than a preset value among the identified capillaries.

[0019] In addition, according to one embodiment of the present specification, when evaluating the risk of varicose veins of the lower extremities based on the digitized capillary exposure, multiple capillary lines are identified, and the risk of varicose veins of the lower extremities is evaluated by assigning a weight to the degree of capillary distribution greater than or equal to a preset value within the multiple capillary lines. If a number of capillaries greater than or equal to a preset value are distributed in any one of the multiple capillary lines, the risk of varicose veins of the lower extremities may increase.

[0020] In addition, according to one embodiment of the present specification, the server acquires a plurality of images related to lower extremity varicose veins, wherein the plurality of images related to lower extremity varicose veins are images of the same lower body part of the user, and the exposure of capillaries in each of the plurality of images related to lower extremity varicose veins is quantified and compared, and the risk of lower extremity varicose veins is evaluated by assigning weight to the information of the comparison result.

[0021] In addition, according to one embodiment of the present specification, among a plurality of images related to lower extremity varicose veins, a first image is an image acquired at a first time period, a second image is an image acquired at a second time period, and comparison result information is acquired by comparing the capillary exposure of the first image with the capillary exposure of the second image, and based on the comparison result information, the greater the difference between the capillary exposure of the first image and the capillary exposure of the second image, the greater the risk of lower extremity varicose veins.

[0022] Additionally, according to one embodiment of the present specification, the server may collect user information on user activities between a first time zone and a second time zone through at least one of a user device and a wearable device, and reflect the collected user information in a varicose vein risk assessment.

[0023] Additionally, according to one embodiment of the present specification, the video related to lower extremity varicose veins is a vertically captured video of the user's lower body, and the server can derive a plurality of lower extremity varicose veins-related images from the video related to lower extremity varicose veins.

[0024] Additionally, according to one embodiment of the present specification, the server provides guide information for capturing a video related to varicose veins to a user device, and when a video related to varicose veins captured by the user device based on the guide information is transmitted to the server, the video related to varicose veins may be transmitted in an encrypted manner.

[0025] Additionally, according to one embodiment of the present specification, the server may obtain user questionnaire information from the user device and evaluate the risk of varicose veins by reflecting the user questionnaire information.

[0026] This specification is effective in providing a method for early diagnosis and management of varicose veins of the lower extremities.

[0027] The present specification has the effect of providing a method for a platform that acquires image information from a user device for early diagnosis of varicose veins of the lower extremities and evaluates the risk level through the image information.

[0028] This specification has the effect of providing a method for early diagnosis and management of varicose veins through a non-face-to-face service platform.

[0029] The present specification has the effect of providing a method for extracting an image for judging varicose veins in the lower extremities.

[0030] This specification has the effect of providing a method for determining the risk of varicose veins in the lower extremities by analyzing images related to varicose veins in the lower extremities.

[0031] The effects of this specification are not limited to what has been described above, but can be expanded to various matters that can be derived from the embodiments of the invention described below.

[0032]

[0033] FIG. 1 is a diagram illustrating an example of an operating environment of a system according to one embodiment of the present specification.

[0034] FIG. 2 is a block diagram for explaining the internal configuration of a computing device (200) in one embodiment of the present specification.

[0035] FIG. 3a is a diagram illustrating the operation of a service platform and server for early diagnosis and management of varicose veins in one embodiment of the present specification.

[0036] FIG. 3b is a diagram illustrating the operation of a service platform and server for early diagnosis and management of varicose veins in one embodiment of the present specification.

[0037] FIG. 3c is a diagram illustrating a method for providing information on the risk of varicose veins to a user through a service platform for early diagnosis and management of varicose veins in one embodiment of the present specification.

[0038] FIG. 4 is a diagram illustrating the operation of a user device and a server in one embodiment of the present specification.

[0039] FIG. 5 is a diagram illustrating a method for deriving an image from a video to diagnose varicose veins in the lower extremities, according to one embodiment of the present specification.

[0040] FIG. 6 is a drawing showing an image related to the risk of varicose veins in one embodiment of the present specification.

[0041] FIG. 7 is a drawing showing an image related to the risk of varicose veins in one embodiment of the present specification.

[0042] FIG. 8A is a diagram illustrating a method of utilizing multiple images for diagnosing varicose veins in one embodiment of the present specification.

[0043] FIG. 8b is a diagram illustrating a method of utilizing multiple images for diagnosing varicose veins in one embodiment of the present specification.

[0044] FIG. 9 is a diagram illustrating a method for analyzing an image related to varicose veins of the lower extremities for risk assessment according to one embodiment of the present specification.

[0045] FIG. 10 is a diagram illustrating a method for analyzing an image related to varicose veins of the lower extremities for risk assessment according to one embodiment of the present specification.

[0046] FIG. 11 is a diagram illustrating a method for analyzing an image related to varicose veins of the lower extremities for risk assessment according to one embodiment of the present specification.

[0047] FIG. 12 is a flowchart illustrating a method for early diagnosis and management of varicose veins according to one embodiment of the present specification.

[0048] In describing the embodiments of this specification, if a detailed description of a known configuration or function is judged to obscure the gist of the embodiments of this specification, a detailed description thereof will be omitted. In addition, parts of the drawings that are not related to the description of the embodiments of this specification have been omitted, and similar parts have been designated with similar drawing reference numerals.

[0049] In the embodiments of this specification, when a component is said to be "connected," "coupled," or "connected" to another component, this may include not only a direct connection, but also an indirect connection in which another component exists in between. Furthermore, when a component is said to "include" or "have" another component, unless otherwise specifically stated, this does not exclude the other component, but rather implies that the other component may be included.

[0050] In the embodiments of this specification, the terms first, second, etc. are used only for the purpose of distinguishing one component from another component, and do not limit the order or importance between components unless specifically stated otherwise. Therefore, within the scope of the embodiments of this specification, a first component in an embodiment may be referred to as a second component in another embodiment, and similarly, a second component in an embodiment may be referred to as a first component in another embodiment.

[0051] In the embodiments of this specification, distinct components are used to clearly illustrate their respective characteristics and do not necessarily imply separation. That is, multiple components may be integrated into a single hardware or software unit, or a single component may be distributed into multiple hardware or software units. Therefore, even if not specifically mentioned, such integrated or distributed embodiments are also included within the scope of the embodiments of this specification.

[0052] In this specification, the term "network" may encompass both wired and wireless networks. In this case, the term "network" may refer to a communications network that enables data exchange between devices, systems, and devices, and is not limited to a specific network.

[0053] Embodiments described herein may be entirely hardware, partially hardware and partially software, or entirely software. As used herein, "unit," "device," or "system" refers to a computer-related entity such as hardware, a combination of hardware and software, or software. For example, a unit, module, device, or system as used herein may be, but is not limited to, a running process, a processor, an object, an executable, a thread of execution, a program, and / or a computer. For example, both an application running on a computer and the computer itself may correspond to a unit, module, device, or system as used herein.

[0054] Additionally, in this specification, a device may be a mobile device such as a smartphone, tablet PC, wearable device, or HMD (Head Mounted Display), as well as a fixed device such as a PC or home appliance with display functions. Furthermore, as an example, a device may be an in-vehicle cluster or an IoT (Internet of Things) device. In other words, in this specification, a device may refer to any device capable of operating an application, and is not limited to a specific type. For convenience of explanation, the device on which an application operates is referred to as a device below.

[0055] In this specification, the network communication method is not limited, and connections between each component may not be made using the same network method. The network may include not only communication methods utilizing communication networks (e.g., mobile communication networks, wired Internet, wireless Internet, broadcasting networks, satellite networks, etc.), but also short-range wireless communication between devices. For example, the network may include all communication methods that enable objects to network with each other, and is not limited to wired communication, wireless communication, 3G, 4G, 5G, or other methods. For example, wired and / or networks include Local Area Network (LAN), Metropolitan Area Network (MAN), Global System for Mobile Network (GSM), Enhanced Data GSM Environment (EDGE), High Speed ​​Downlink Packet Access (HSDPA), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth, Zigbee, Wi-Fi, VoIP (Voice over Internet Protocol), LTE Advanced, IEEE802.16m, WirelessMAN-Advanced, HSPA+, 3GPP Long Term Evolution (LTE), Mobile WiMAX (IEEE 802.16e), UMB (formerly EV-DO Rev. C), Flash-OFDM, iBurst and MBWA (IEEE 802.20) It may refer to a communication network using one or more communication methods selected from the group consisting of systems, HIPERMAN, Beam-Division Multiple Access (BDMA), Wi-MAX (World Interoperability for Microwave Access), and ultrasonic communication, but is not limited thereto.

[0056] The components described in various embodiments are not necessarily essential components, and some may be optional. Therefore, embodiments comprising a subset of the components described in the embodiments are also included within the scope of the embodiments of the present disclosure. Furthermore, embodiments including other components in addition to the components described in various embodiments are also included within the scope of the embodiments of the present disclosure.

[0057] Hereinafter, embodiments of the present specification will be described in detail with reference to the drawings.

[0058] FIG. 1 is a diagram illustrating an example of the operating environment of a system according to one embodiment of the present specification. Referring to FIG. 1, one or more user devices (110-1, 110-2) and one or more servers (120, 130, 140) are connected via a network (1). FIG. 1 is merely an example for explaining the invention, and the number of user devices or servers is not limited to that shown in FIG. 1.

[0059] One or more user devices (110-1, 110-2) may be fixed or mobile terminals implemented as a computer system. The one or more user devices (110-1, 110-2) may be, for example, a smart phone, a mobile phone, a navigation device, a computer, a laptop, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), a tablet PC, a game console, a wearable device, an IoT (Internet of Things) device, a VR (Virtual Reality) device, an AR (Augmented Reality) device, etc. For example, in the embodiments, the user device (110) may mean one of various physical computer systems that can communicate with other servers (120 to 140) through a network (1) using a wireless or wired communication method.

[0060] Each server may be implemented as a computer device or multiple computer devices that communicate with one or more user devices (110-1, 110-2) via a network (1) to provide commands, codes, files, contents, services, etc. For example, the server may be a system that provides each service to one or more user devices (110-1, 110-2) connected via the network (1). As a more specific example, the server may be a computer program that is installed and run on one or more user devices (110-1, 110-2), and may provide a service (e.g., provision of information, etc.) intended by the application to one or more user devices (110-1, 110-2). As another example, the server may distribute a file for installing and running the above-described application to one or more user devices (110-1, 110-2) and receive user input information to provide a corresponding service.

[0061] FIG. 2 is a block diagram illustrating the internal configuration of a computing device (200) according to one embodiment of the present specification. This computing device (200) may be applied to one or more user devices (110-1, 110-2) or servers (120-140) described above with reference to FIG. 1, and each device and server may have the same or similar internal configuration by adding or excluding some components.

[0062] Referring to FIG. 2, a computing device (200) may include a memory (210), a processor (220), a communication module (230), and a transceiver (240). The memory (210) is a non-transitory computer-readable recording medium and may include a non-permanent mass storage device such as a random access memory (RAM), a read only memory (ROM), a disk drive, a solid state drive (SSD), a flash memory, etc. Here, the non-permanent mass storage device such as a ROM, an SSD, a flash memory, a disk drive, etc. may be included in the above-described device or server as a separate permanent storage device distinct from the memory (210). In addition, the memory (210) may store an operating system and at least one program code (for example, a browser installed and operated on a user device (110), or a code for an application installed on a user device (110) to provide a specific service). These software components may be loaded from a computer-readable recording medium separate from the memory (210). This separate computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, a memory card, etc.

[0063] In another embodiment, the software components may be loaded into the memory (210) via a communication module (230) rather than a computer-readable recording medium. For example, at least one program may be loaded into the memory (210) based on a computer program (e.g., the application described above) that is installed by files provided by developers or a file distribution system (e.g., the server described above) that distributes the installation files of the application via a network (1).

[0064] The processor (220) may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. Instructions may be provided to the processor (220) by the memory (210) or the communication module (230). For example, the processor (220) may be configured to execute instructions received according to program code stored in a storage device such as the memory (210).

[0065] The communication module (230) can provide a function for the user device (110) and the server (120 - 140) to communicate with each other via the network (1), and can provide a function for each of the device (110) and / or the server (120 - 140) to communicate with other electronic devices.

[0066] The transceiver (240) may be a means for interfacing with an external input / output device (not shown). For example, external input devices may include devices such as a keyboard, mouse, microphone, camera, etc., and external output devices may include devices such as a display, speaker, haptic feedback device, etc. As another example, the transceiver (240) may be a means for interfacing with a device that integrates input and output functions, such as a touchscreen.

[0067] In addition, in other embodiments, the computing device (200) may include more components than the components of FIG. 2 depending on the nature of the device to which it is applied. For example, when the computing device (200) is applied to a user device (110), it may be implemented to include at least some of the above-described input / output devices, or may further include other components such as a transceiver, a Global Positioning System (GPS) module, a camera, various sensors, a database, etc. As a more specific example, when the user device is a smartphone, it may be implemented to further include various components that are generally included in a smartphone, such as an acceleration sensor or a gyro sensor, a camera module, various physical buttons, buttons using a touch panel, input / output ports, and a vibrator for vibration.

[0068] The following description is based on a computing device (200) operating based on FIGS. 1 and 2. As an example, a service platform for early diagnosis of varicose veins of the lower extremities may be provided based on at least one of an application, software, and program running on the computing device (200).

[0069] Here, a service platform for early diagnosis of lower extremity varicose veins may be installed and operated on a user device as a computing device (200), and the platform may be controlled by a server. The server may exchange data with the user device as a computing device (200) via a network to provide services. For example, the server may be equipped with a program or software for acquiring images or videos through the service platform for early diagnosis of lower extremity varicose veins and analyzing them to determine the risk of lower extremity varicose veins. In addition, the server may be capable of building an artificial intelligence model or utilizing an external artificial intelligence model to improve the accuracy of determining the risk of lower extremity varicose veins, which will be described later.

[0070] As another example, the service platform for early diagnosis of lower extremity varicose veins may be a platform managed based on multiple nodes and is not limited to a specific form. That is, the service platform for early diagnosis of lower extremity varicose veins may be managed through a server or other nodes and may provide services to users through applications and other programs driven by a computing device (200), and may not be limited to a specific form. As an example, the service platform for early diagnosis of lower extremity varicose veins may be provided to users in various forms, but for the convenience of explanation, the following description will be based on the service platform for early diagnosis of lower extremity varicose veins as a platform driven by a user device (300). However, this is merely an example for the convenience of explanation and may not be limited thereto.

[0071] FIGS. 3A to 3C are diagrams illustrating the operation of a service platform and a server for early diagnosis and management of lower extremity varicose veins according to one embodiment of the present disclosure. Referring to FIG. 3A, a service platform (or application) (hereinafter, service platform, 310) for early diagnosis of lower extremity varicose veins may operate in a user device (300). For example, the user device (300) may transmit a lower extremity varicose vein-related image (311) to a server (400) through the service platform (310), and the server (400) may provide lower extremity varicose vein assessment result information for evaluating the risk of lower extremity varicose veins through the acquired lower extremity varicose vein-related image (311) to the service platform (310) operated in the user device (300). That is, the user may receive a service for assessing the risk of lower extremity varicose veins through the service platform (310) installed in the user device (300). Here, for example, the risk of lower extremity varicose veins may be assessed through the lower extremity varicose vein-related image (311). More specifically, varicose veins can be a condition in which the superficial veins of the lower extremities become abnormally dilated due to dysfunction of the unilateral venous valves in the lower extremities. Symptoms of this condition can be primarily concentrated in the calves or thighs. In severe cases, the capillaries in these areas can become swollen enough to be visible on a radiograph. Therefore, the degree of capillary exposure in the calves or thighs can serve as a diagnostic or risk assessment tool for diagnosing varicose veins. For example, capillary exposure can be quantified to assess the risk of varicose veins.

[0072] In addition to capillary exposure, the degree of edema may also be used as a criterion for assessing varicose veins. The degree of edema can refer to the volume or volume change of a specific area. Furthermore, the degree of edema can be determined based on the volume or volume change of the calf or the instep, but the present invention is not limited thereto.

[0073] Considering the above, the risk of lower extremity varicose veins can be determined based on the digitized capillary exposure in the lower extremity varicose vein-related image (311). That is, by determining how much capillaries are exposed and displayed in the thigh or calf image transmitted by the user, the digitized capillary exposure is derived, and the risk of lower extremity varicose veins is determined based on this, thereby enabling early diagnosis of lower extremity varicose veins. The server (400) can obtain the lower extremity varicose vein image (311) related to the user from the service platform (310) operated in the user device (300), determine the risk of lower extremity varicose veins therefrom, and then provide the corresponding information through the service platform (310).

[0074] Here, as an example, in order to increase the accuracy of the lower extremity varicose vein risk assessment, the analysis accuracy of the lower extremity varicose vein image (311) may be increased, or multiple lower extremity varicose vein images (311) may be required. As a specific example, the user's status may change in real time. In addition, a specific part of the user may appear to have severe symptoms, while other specific parts may not appear to have severe symptoms. In other words, the lower extremity varicose vein image (311) acquired by the server (400) may have limitations in accurately representing the user's status, and therefore multiple images may be required to accurately assess the user's status. In addition, the lower extremity varicose vein risk assessment is not performed through face-to-face treatment, but through non-face-to-face images, and thus limitations may exist. Therefore, in order to accurately assess the lower extremity varicose vein image (311) risk, a method for increasing the image analysis accuracy may be required.

[0075] Here, as an example, referring to FIG. 3b, the server (400) can obtain not only the varicose vein image (311) but also the varicose vein video (312) and the varicose vein-related additional image (313) through the service platform (310). That is, the server (400) can perform the varicose vein risk analysis through the video (312) or the related additional image (313), which will be described later.

[0076] In addition, as an example, referring to FIG. 3c, the server (400) may further obtain user questionnaire information (314) from the service platform (310) and determine the risk of lower extremity varicose veins by reflecting the same. Specifically, when a user wishes to receive a lower extremity varicose veins risk determination service through the service platform (310) operated on the user device (300), the user may input user questionnaire information (314) and provide it to the server (400), and then obtain a video or image and provide it to the server (400). The server (400) may determine the risk of lower extremity varicose veins through the user questionnaire information (314) and video or image information obtained through the service platform (310) of the user device (300), and provide the lower extremity varicose veins risk assessment result information to the user through the service platform (310). Here, the lower extremity varicose veins risk information may be expressed as a risk score or a risk level as numerical information, but may not be limited to a specific form.

[0077] Specifically, FIG. 4 is a diagram illustrating the operation of a user device and a server in one embodiment of the present specification. Referring to FIG. 4, a user device (300) may transmit a request for lower extremity varicose vein analysis to a server (400). Here, the request for lower extremity varicose vein analysis may be transmitted to the server (400) together with user questionnaire information (314). That is, a user may transmit a request for lower extremity varicose vein analysis together with user questionnaire information to the server (400) through a service platform (310) operated on the user device (300). Thereafter, the server (400) may request the user device (300) to capture at least one of a video and an image in order to determine the risk of lower extremity varicose veins. Here, as an example, a plurality of videos and images may be requested at regular time intervals, which will be described later. The server (400) can obtain at least one of a video and an image from the user device (300), determine the risk of varicose veins based on the video and an image, and transmit the varicose veins evaluation result information to the user device (300).

[0078] For example, FIG. 5 is a diagram illustrating a method for deriving an image from a video to diagnose varicose veins in the lower extremities in one embodiment of the present specification. Referring to FIG. 5, the server (400) may request and acquire a video (312) from the user device (300) to increase the accuracy of the risk assessment of varicose veins in the lower extremities. Here, as an example, the video (312) may be a video of the lower body of a human body, which may be an image taken vertically of the lower body. As a specific example, the video (312) may be an image of the entire lower body, which may be an image taken from all sides, left, right, front, and back. In addition, as an example, the video may be a video taken of the inside of the lower body, and is not limited to a specific form. Here, shooting guide information may be provided through the service platform (310), and the user may acquire the video by shooting the lower body using the shooting guide of the service platform (310). As another example, since the lower body part described above may be personal information, the video may be encrypted through the service platform (310) and transmitted to the server (400). That is, the video may be encrypted so that it cannot be played on the server (400), and may be provided only as input to a program, software, or artificial intelligence for assessing the risk of lower extremity varicose veins. The server (400) may extract images (510, 520, 530) related to lower extremity varicose veins from the acquired video (312). That is, by checking the degree of dilation of capillaries within the video (312), at least one image (510, 520, 530) that is related to lower extremity varicose veins may be extracted. Here, as an example, the server (400) can be connected to artificial intelligence (500), and a video (312) can be provided as input to the artificial intelligence (500) so that the images (510, 520, 530) described above can be derived as output.For example, the artificial intelligence (500) may be equipped with a learning model related to lower extremity varicose veins and may be trained based on multiple images related to lower extremity varicose veins, capillary numerical information, and lower extremity varicose vein risk information. That is, the artificial intelligence (500) may build a learning model related to lower extremity varicose vein diagnosis and extract lower extremity varicose vein-related images through the learning model. Thereafter, the server (400) may analyze the images to assess the risk of lower extremity varicose veins. In addition, the artificial intelligence (500) may delete information unnecessary for assessing the risk of lower extremity varicose veins from the images related to lower extremity varicose veins. For example, the artificial intelligence (500) may delete leg hair or other information unrelated to assessing the risk of lower extremity varicose veins from the images related to lower extremity varicose veins and may also recognize such information through learning. That is, the artificial intelligence (500) may not only derive images for assessing the risk of lower extremity varicose veins but also delete unnecessary portions within the images, and may increase the accuracy of risk assessment through images related to lower extremity varicose veins from which unnecessary information has been removed.

[0079] Here, as an example, FIGS. 6 and 7 are drawings showing images related to the risk of varicose veins in the lower extremities in one embodiment of the present specification. Referring to FIG. 6, the risk of varicose veins in the lower extremities can be determined based on images of varicose veins in the lower extremities (610, 620, 630). For example, in the first image (610), the capillary exposure may not be high and the capillary exposure may not be swollen, with only some capillaries exposed in the corresponding area. That is, the first image (610) may have a low capillary exposure value. On the other hand, the second image (620) may have a higher capillary exposure value than the first image, and the third image (630) may have the highest capillary exposure value. That is, the risk of varicose veins in the lower extremities can be determined based on the capillary exposure value, and there is a need to derive a capillary exposure value, which is the degree to which capillaries are exposed, in each image (610, 620, 630).

[0080] Also, referring to FIG. 7, the risk of varicose veins in the lower extremities can be assessed by considering the distribution of the exposed capillary areas. Here, the first image (710) may be a case where capillaries exist in multiple capillary lines, and the second image (720) may be a case where multiple capillaries are exposed in a single capillary line. Here, considering the symptom of varicose veins in the lower extremities, if multiple capillaries are exposed in a single capillary line, the varicose veins in the lower extremities can be judged to have progressed further. Therefore, the risk of the second image (720) may be higher than that of the first image (710). For example, when analyzing images related to varicose veins in the lower extremities, the exposed capillary areas in the images related to varicose veins can be quantified. Here, considering the location of each exposed capillary area, whether the exposed capillary areas are located in the same capillary line can be reflected in the risk assessment. That is, the above-described information can be weighted, and in such cases, the risk of varicose veins in the lower extremities can be determined to be high. For example, in FIG. 7, the risk level may be set to be higher in the second image (720) than in the first image (710).

[0081] As another example, FIGS. 8A and 8B are diagrams illustrating a method of utilizing multiple images for diagnosing lower extremity varicose veins in one embodiment of the present disclosure. Referring to FIG. 8A, the server (400) may acquire at least one of multiple images (311) and videos (312) related to lower extremity varicose veins through the service platform (310). For convenience of explanation, the following description will be based on the images (311) related to lower extremity varicose veins, but the same may be applied to the videos (312). That is, the server (400) may analyze multiple images (311) related to lower extremity varicose veins to increase the accuracy of lower extremity varicose vein analysis. Here, as an example, with respect to lower extremity varicose vein symptoms, leg swelling may be most evident in the evening after the user performs daily activities. Considering the above, the server (400) may acquire multiple images (311) related to lower extremity varicose veins and analyze the risk of lower extremity varicose veins.

[0082] Here, as a specific example, the server (400) can obtain images (311) related to varicose veins of the lower extremities based on different time zones. For example, since the exposed areas of capillaries may be different in the morning and evening, the server (400) can obtain images (311) related to varicose veins of the lower extremities for each time zone. The server (400) can compare multiple images (311) related to varicose veins of the lower extremities to obtain information on the degree of capillary exposure and reflect it in the risk level. For example, in relation to symptoms of varicose veins of the lower extremities, the degree of capillary exposure may increase due to the user's activities or other actions. In other words, the higher the progression of varicose veins of the lower extremities, the more prominent the symptoms may be due to the user's activities or actions. Considering the above, the greater the change between the morning and evening images of the images related to varicose veins of the lower extremities for the same area, the higher the risk of varicose veins of the lower extremities. The server (400) can analyze multiple images of varicose veins (311) acquired at different times, assign weights to the differences, and set the risk so that a larger difference indicates a higher level of risk. Here, as an example, referring to FIG. 8B, user information may be collected between the times of acquiring the images of varicose veins (311), and the risk may be assessed by reflecting the information. As an example, the service platform (310) may be operated in the user device (300) and the user's wearable device (800). Here, the service platform (310) may collect user information between the time intervals of acquiring the images of varicose veins (311) to acquire information related to the user's activities and motions. For example, when the user's activity level is low between the times of acquiring the images of varicose veins (311), the difference in the change in the exposure of capillaries may be small. On the other hand, when the user's activity level is high, such as when hiking or engaging in other activities, between the times of acquiring the images of varicose veins (311), the difference in the change in the exposure of capillaries may be large.That is, the user's activity level needs to be taken into account when determining the risk of varicose veins, and for this purpose, the server (400) can obtain user collected information and reflect the weight. The server (400) can determine the risk of varicose veins based on the user numerical information weight, and can obtain user information through the user device (300) or wearable device (800) for the above-described operation.

[0083] FIG. 9 is a diagram illustrating a method for analyzing an image related to lower extremity varicose veins for risk assessment according to one embodiment of the present specification. Referring to FIG. 9, when the server (400) evaluates the risk of lower extremity varicose veins through an image related to lower extremity varicose veins (311), the server (400) can derive parameters for each pixel unit of a human body part in the image (311) and obtain standard deviation information for each pixel parameter value. Here, information on the degree of capillary distribution can be determined based on each pixel parameter value and standard deviation, and the degree of capillary exposure can be quantified. For example, in FIG. 9, by reflecting information (920) obtained by calculating the standard deviation for each pixel of the photographed area, information (910) on values ​​above a certain level can be used to derive lower extremity varicose vein risk information (930, 940). That is, based on the standard deviation between skin pixels, pixels exceeding a preset value are judged to have exposed capillaries, and the capillary exposure is quantified based on the number of the pixels, and the risk of varicose veins of the lower extremities can be determined accordingly. Here, as an example, in the judgment of the risk of varicose veins of the lower extremities, whether there are multiple capillary exposures in a capillary line as described above or whether multiple capillary exposures are reflected in multiple capillary lines can be reflected based on the pixel information described above. In addition, as an example, the information described above can be calculated for a plurality of images of varicose veins of the lower extremities, and information on differences in pixel changes quantified in a plurality of images can be reflected in the risk assessment, as described above.

[0084] As another example, when an image related to varicose veins of the lower extremities is acquired by the user device (300), it may not be easy to secure an image suitable for analysis. For example, when the user takes a picture of the back of the calf, the user may bend the waist or the legs, which may limit the acquisition of multiple images in the same posture, and compensation for this may be necessary. Considering the above, the image related to varicose veins of the lower extremities (311) and information related to the user's posture may be further considered. For example, the server (400) may obtain information on changes in the exposed capillaries according to the user's posture in advance and correct the image based on this. That is, the server (400) may further reflect the user's shooting posture information in the acquired image related to varicose veins of the lower extremities (311) to perform image compensation, thereby improving the accuracy of the risk assessment. For example, when the user's posture is bent, the skin color may be reflected differently, so the accuracy of the risk assessment may be improved by correcting the skin color based on a pre-captured image.

[0085] As another example, the artificial intelligence (500) described above may be utilized to assess the risk of varicose veins. Here, the artificial intelligence (500) may be initially trained based on a doctor's clinical judgment information, and may then be trained based on reinforcement learning or other deep learning methods. That is, an artificial intelligence (500) model may be constructed to assess the risk of varicose veins, and the artificial intelligence (500) may output a risk assessment value by reflecting the aforementioned risk weights and other learning information.

[0086] As another example, user linkage information may be provided based on the server's (400) assessment of the risk of lower extremity varicose veins. For example, the server (400) may provide a notification to a user whose lower extremity varicose veins risk assessment value is output high through the service platform (310). In addition, the server (400) may be associated with a hospital or other facility. The server (400) may allow a user to check for lower extremity varicose veins by checking for biomarkers through a sample (e.g., saliva, urine, etc.) at a hospital or other facility, and may enable lower extremity varicose vein management for the user. For example, the server (400) may provide a lower extremity varicose vein specialized hospital reservation system linkage, a lower extremity varicose vein check service, and other programs to the user through the service platform (310), and the user may manage the lower extremity varicose veins through the service platform (310).

[0087] As another example, the server (400) may obtain additional information by linking with another device (e.g., a body composition analyzer). For example, the server (400) may obtain additional lower body blood flow analysis information measured from another device and reflect it in the assessment of the risk of varicose veins in the lower extremities, but is not limited to a specific embodiment.

[0088] FIGS. 10 and 11 are diagrams illustrating a method for analyzing images related to lower extremity varicose veins for risk assessment according to one embodiment of the present disclosure. Referring to FIG. 10, a server (400) may obtain images related to lower extremity varicose veins (1011, 1012), obtain analysis result images (1021, 1022) through analysis as described above, and assess risk based on the images. Here, as described above, other information may be further utilized for risk assessment, but this is as described above. Through this, an early diagnosis tool for patients with lower extremity varicose veins can be provided, treatment effectiveness can be increased, and social costs can be reduced. For example, lower extremity varicose veins are often neglected, so when diagnosed at a hospital, the progression of the disease may already be high, and treatment effectiveness may be low. Accordingly, through the service platform (310) and server (400) described above, it is possible to check the risk of varicose veins before or when the initial symptoms of varicose veins appear, thereby reducing treatment costs and duration. In addition, through the service platform (310) and server (400) described above, it is possible to perform varicose vein management remotely without the hassle of visiting a hospital. In addition, even if the initial symptoms appear, the hassle of visiting a hospital can delay diagnosis, which not only makes treatment difficult and reduces the effectiveness of the treatment, but also increases the treatment cost. Through the service platform (310) and server (400) described above, simple testing can be performed without visiting a hospital, which can have a positive effect on preventing and treating varicose veins in daily life. In addition, as an example, the discovery of diagnostic biomarkers and factors can be performed based on the data acquired through the service platform (310) and server (400) described above, and reference can be made to FIG. 11.

[0089] FIG. 12 is a flowchart illustrating a method for early diagnosis and management of varicose veins according to one embodiment of the present specification.

[0090] Referring to FIG. 12, the server (400) can obtain information related to varicose veins from the user device (300). (S1210) Then, the server (400) can quantify the capillary exposure based on the analysis of the information related to varicose veins (S1220) and evaluate the risk of varicose veins based on the quantified capillary exposure. (S1230) Then, the server (400) can transmit the result information of the varicose vein evaluation based on the evaluated risk of varicose veins to the user device (300). (S1240) Here, the information related to varicose veins may include at least one of a varicose vein-related image, a varicose vein-related video, and an additional image. For example, the additional image may be an image of another body part of the user or another image, and is not limited to a specific form.

[0091] In addition, as an example, the image related to varicose veins may be an image of the user's lower body. When the capillary exposure is quantified based on the analysis of information related to varicose veins, the server can derive a pixel-by-pixel parameter for the user's lower body from the image related to varicose veins, derive a standard deviation based on a plurality of pixel-by-pixel parameters to identify capillaries, and quantify the capillary exposure through capillaries that are higher than a preset value among the identified capillaries, as described above.

[0092] As another example, when assessing the risk of varicose veins in the lower extremities based on quantified capillary exposure, multiple capillary lines can be identified, and the risk of varicose veins in the lower extremities can be assessed by assigning weights to the degree of capillary distribution exceeding a preset value within the multiple capillary lines. Here, if a number of capillaries exceeding a preset value are distributed within any one of the multiple capillary lines, the risk of varicose veins in the lower extremities may increase.

[0093] In addition, the server (400) can obtain a plurality of images related to lower extremity varicose veins. Here, the plurality of images related to lower extremity varicose veins are images of the same lower body part of the user, and the capillary exposure in each of the plurality of images related to lower extremity varicose veins is quantified and compared, and the risk of lower extremity varicose veins can be assessed by assigning a weight to the comparison result information. As a specific example, among the plurality of images related to lower extremity varicose veins, the first image may be an image acquired in a first time period, and the second image may be an image acquired in a second time period. The server (400) can obtain comparison result information by comparing the capillary exposure of the first image with the capillary exposure of the second image. Here, based on the comparison result information, the risk of lower extremity varicose veins can increase as the difference between the capillary exposure of the first image and the capillary exposure of the second image increases.

[0094] Additionally, the server (400) may collect user information on user activities between the first time zone and the second time zone through at least one of the user device (300) and the wearable device (800), and may reflect the collected user information in the risk assessment of varicose veins.

[0095] As another example, the video related to lower extremity varicose veins may be a vertically captured image of the user's lower body. The server (400) may derive multiple images related to lower extremity varicose veins from the video related to lower extremity varicose veins. In addition, the server (400) may provide guide information for capturing the video related to lower extremity varicose veins to the user device. Here, when the video related to lower extremity varicose veins captured by the user device based on the guide information is transmitted to the server, the video related to lower extremity varicose veins may be transmitted in an encrypted form. In addition, the server (400) may obtain user questionnaire information from the user device (300) and assess the risk of lower extremity varicose veins by reflecting the user questionnaire information, as described above.

[0096] The embodiments described above can be implemented at least in part as computer programs and recorded on a computer-readable recording medium. A computer-readable recording medium on which a program for implementing the embodiments is recorded includes any type of recording device that stores data that can be read by a computer. Examples of computer-readable recording media include ROMs, RAMs, CD-ROMs, magnetic tapes, and optical data storage devices. In addition, the computer-readable recording medium can be distributed across network-connected computer systems, so that computer-readable codes can be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present embodiments will be readily understood by those skilled in the art to which the present embodiments pertain.

[0097] Although the present specification has been described with reference to the embodiments illustrated in the drawings, these are merely exemplary, and those skilled in the art will understand that various modifications and variations of the embodiments are possible. However, such modifications should be considered within the technical protection scope of the present specification. Therefore, the true technical protection scope of the present specification should be determined to include other implementations, other embodiments, and equivalents to the patent claims by the technical spirit of the appended claims.

[0098]

[0099] The present specification can be applied industrially as it provides a method for a platform that acquires image information from a user device for early diagnosis of varicose veins of the lower extremities and evaluates the risk level based on the image information.

Claims

1. In a method for early diagnosis and management of varicose veins by a server, A step of obtaining information related to varicose veins from a user device; A step of quantifying capillary exposure based on the analysis of information related to the above varicose veins; A step of evaluating the risk of varicose veins in the lower extremities based on the above digitized capillary exposure; and A method comprising the step of transmitting information on the results of the lower extremity varicose vein evaluation based on the assessed risk of lower extremity varicose veins to the user device.

2. In paragraph 1, A method wherein the information related to lower extremity varicose veins comprises at least one of a lower extremity varicose veins-related image, a lower extremity varicose veins-related video, and an additional image.

3. In paragraph 2, The above image related to varicose veins is an image of the user's lower body area. When the capillary exposure is quantified based on the analysis of the information related to the varicose veins above, the server derives parameters for each pixel of the user's lower body area from the image related to the varicose veins above. Identify capillaries by deriving standard deviations based on multiple above pixel unit parameters, A method for quantifying the capillary exposure through capillaries having a preset value or higher among the above-mentioned confirmed capillaries.

4. In paragraph 3, When evaluating the risk of varicose veins of the lower extremities based on the above-mentioned digitized capillary exposure, multiple capillary lines are identified, and the risk of varicose veins of the lower extremities is evaluated by assigning a weight to the degree of capillary distribution greater than the preset value within the multiple capillary lines. A method in which the risk of varicose veins in the lower extremities increases when a number of capillaries exceeding the preset value is distributed in any one of the plurality of capillary lines.

5. In paragraph 3, The above server obtains a plurality of images related to varicose veins of the lower extremities, wherein the plurality of images related to varicose veins of the lower extremities are images of the same lower body part of the user, A method for evaluating the risk of varicose veins in the lower extremities by comparing the capillary exposure in each of the plurality of images related to varicose veins and assigning weights to the information resulting from the comparison.

6. In paragraph 5, Among the above multiple images related to varicose veins, the first image is an image acquired at a first time point, and the second image is an image acquired at a second time point. By comparing the capillary exposure of the first image with the capillary exposure of the second image, the above comparison result information is obtained. A method in which the risk of varicose veins in the lower extremities increases as the difference between the capillary exposure of the first image and the capillary exposure of the second image increases based on the comparison result information.

7. In paragraph 6, The server collects user information about user activities between the first time zone and the second time zone through at least one of the user device and the wearable device, A method for reflecting the collected user information in the risk assessment of varicose veins.

8. In paragraph 2, A method wherein a video related to lower extremity varicose veins is a video vertically filmed of a user's lower body, and the server derives a plurality of lower extremity varicose vein-related images from the video related to lower extremity varicose veins.

9. In paragraph 8, A method wherein the server provides guide information for filming a video related to varicose veins to the user device, and when the video related to varicose veins filmed by the user device based on the guide information is transmitted to the server, the video related to varicose veins is transmitted in an encrypted form.

10. In paragraph 1, A method in which the server obtains user questionnaire information from the user device and evaluates the risk of varicose veins by reflecting the user questionnaire information.

11. A computer program stored on a computer-readable medium that is combined with hardware and executes the method according to any one of claims 1 to 10.

12. In a server that diagnoses and manages varicose veins early, Memory that stores information related to varicose veins; A transceiver unit that performs communication with a user device; and Including a processor that controls the above memory and the above transceiver, The above processor, Obtaining information related to varicose veins from the user device, Based on the analysis of the above information related to varicose veins, the degree of capillary exposure is quantified, Based on the above digitized capillary exposure, the risk of varicose veins in the lower extremities is assessed, and A server that transmits information on the results of the varicose vein evaluation to the user device based on the assessed risk of varicose veins.

13. In a method for early diagnosis and management of varicose veins by a user device, A step of transmitting information related to varicose veins to a server; and Including a step of obtaining information on the results of a varicose vein evaluation based on the risk of varicose veins from the server, A method in which the server quantifies capillary exposure based on analysis of information related to varicose veins, evaluates the risk of varicose veins based on the quantified capillary exposure, and generates varicose vein evaluation result information.

14. In paragraph 13, A method wherein the information related to lower extremity varicose veins comprises at least one of a lower extremity varicose veins-related image, a lower extremity varicose veins-related video, and an additional image.

15. In paragraph 14, The above image related to varicose veins is an image of the user's lower body area. When the capillary exposure is quantified based on the analysis of the information related to the varicose veins above, the server derives parameters for each pixel of the user's lower body area from the image related to the varicose veins above. Identify capillaries by deriving standard deviations based on multiple above pixel unit parameters, A method for quantifying the capillary exposure through capillaries having a preset value or higher among the above-mentioned confirmed capillaries.

16. In paragraph 15, When evaluating the risk of varicose veins of the lower extremities based on the above-mentioned digitized capillary exposure, multiple capillary lines are identified, and the risk of varicose veins of the lower extremities is evaluated by assigning a weight to the degree of capillary distribution greater than the preset value within the multiple capillary lines. A method in which the risk of varicose veins in the lower extremities increases when a number of capillaries exceeding the preset value is distributed in any one of the plurality of capillary lines.

17. In paragraph 13, The user device obtains user questionnaire information and transmits it to the server, A method in which the risk of varicose veins in the lower extremities is evaluated by reflecting the user questionnaire information.

Images