Early diagnosis and management method and device for varicose veins of lower limbs

Abstract

The method for early diagnosing and managing varicose veins of lower limbs by a server according to an embodiment of the present invention comprises: a step for acquiring, from a user device, information relating to varicose veins of lower limbs; a step for analyzing and numeralizing the degree of capillary exposure on the basis of the information relating to varicose veins of lower limbs; a step of assessing the risk degree of varicose vein of the lower limb based on the numeralized capillary exposure degree; and a step of transmitting assessment result information of varicose vein of the lower limb to the user device based on the assessed risk degree of varicose vein of the lower limb.

Description

Technical Field

[0001] Embodiments relate to methods and devices for managing varicose veins of the lower extremities through early diagnosis of varicose veins of the lower extremities, and more particularly, to methods and devices for early diagnosis and management of varicose veins of the lower extremities by analyzing images acquired from a user device. Background Art

[0002] Varicose veins in the lower limbs may be a disease in which the superficial veins in the lower limbs are abnormally enlarged due to dysfunction of the one-way valves in the lower limb veins. Varicose veins in the lower limbs may not have any special symptoms except for the discomfort in the early stage, but if left untreated and gradually progress, various complications will occur. Generally speaking, the incidence of varicose veins in the lower limbs increases with age, and it is a disease that occurs more often in women than in men.

[0003] The number of patients with varicose veins in the lower extremities is gradually increasing, and the resulting social costs are also increasing. Therefore, in order to reduce varicose vein diseases in the lower extremities and the resulting social costs, it is necessary to build and manage an evaluation system for early diagnosis and management of varicose veins in the lower extremities in advance. Considering the above situation, the following describes a method for early diagnosis and management of varicose veins in the lower extremities through a non-face-to-face service platform.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Korean Patent Publication No. 10-2022-0019180A Summary of the invention

[0007] Technical issues

[0008] This manual can provide a method for early diagnosis and management of varicose veins in the lower limbs.

[0009] The present specification may provide a method for a platform for early diagnosis of varicose veins in the lower limbs, wherein the platform acquires image information from a user device and assesses the degree of risk through the image information.

[0010] This instruction manual can provide a method for early diagnosis and management of varicose veins of the lower limbs through a non-face-to-face service platform.

[0011] The present specification may provide a method for extracting an image for determining varicose veins in the lower limbs.

[0012] This manual can provide a method for determining the risk level of varicose veins in the lower limbs by analyzing images related to varicose veins in the lower limbs.

[0013] The problems to be solved by this specification are not limited to the above-mentioned problems, but can be extended to various matters that can be derived from the embodiments of the invention described below.

[0014] Solution to the problem

[0015] According to one embodiment of the present specification, a method for a server to perform early diagnosis and management of varicose veins in the lower limbs may include: a step of obtaining information related to varicose veins in the lower limbs from a user device, a step of quantifying the degree of capillary exposure based on analysis of information related to varicose veins in the lower limbs, a step of assessing the risk level of varicose veins in the lower limbs based on the quantified degree of capillary exposure, and a step of transmitting the varicose vein assessment result information of the lower limbs to the user device based on the assessed risk level of varicose veins in the lower limbs.

[0016] In addition, according to one embodiment of the present specification, a server for early diagnosis and management of varicose veins in the lower limbs may include: a memory for storing information related to varicose veins in the lower limbs, a transceiver for communicating with a user device, and a processor for controlling the memory and the transceiver, and the processor may obtain information related to varicose veins in the lower limbs from the user device, quantify the degree of capillary exposure based on analysis of information related to varicose veins in the lower limbs, assess the risk level of varicose veins in the lower limbs based on the quantified degree of capillary exposure, and transmit the varicose veins in the lower limbs assessment result information to the user device based on the assessed risk level of varicose veins in the lower limbs.

[0017] In addition, according to one embodiment of the present specification, a method for a user device to perform early diagnosis and management of varicose veins in the lower limbs may include: a step of transmitting information related to varicose veins in the lower limbs to a server, and a step of obtaining varicose vein assessment result information of the lower limbs from the server based on the risk level of varicose veins in the lower limbs, and the server may quantify the exposure level of capillaries based on the analysis of information related to varicose veins in the lower limbs, and evaluate the risk level of varicose veins in the lower limbs based on the quantified capillary exposure level to generate varicose vein assessment result information of the lower limbs.

[0018] In addition, the following matters may also apply.

[0019] According to one embodiment of the present specification, the information related to varicose veins of lower limbs may include at least any one of an image related to varicose veins of lower limbs, a video related to varicose veins of lower limbs, and an additional image.

[0020] In addition, according to one embodiment of the present specification, the image related to varicose veins of the lower limbs is an image of the lower body of the user. When the exposure degree of the capillaries is quantified based on the analysis of the information related to varicose veins of the lower limbs, the server can derive parameters in pixel units for the lower body of the user from the image related to varicose veins of the lower limbs, confirm the capillaries based on the standard deviation derived from multiple parameters in pixel units, and quantify the exposure degree of the capillaries through the capillaries above the preset value among the confirmed capillaries.

[0021] In addition, according to an embodiment of the present specification, when evaluating the risk level of varicose veins in the lower limbs based on the quantified capillary exposure level, multiple capillary lines are confirmed, and a weighted value is assigned to the capillary distribution level above a preset value in the multiple capillary lines to evaluate the risk level of varicose veins in the lower limbs, and when a capillary line among the multiple capillary lines has a plurality of capillaries above a preset value, the risk level of varicose veins in the lower limbs may increase.

[0022] In addition, according to one embodiment of the present specification, the server can obtain multiple images related to varicose veins in the lower limbs, and the multiple images related to varicose veins in the lower limbs can be images of the same lower body part of the user. The degree of capillary exposure in the multiple images related to varicose veins in the lower limbs is quantified and compared, and a weighted value is assigned to the comparison result information to evaluate the risk level of varicose veins in the lower limbs.

[0023] In addition, according to an embodiment of the present specification, among multiple lower limb varicose veins related images, the first image is an image acquired in a first time period, and the second image is an image acquired in a second time period, and the capillary exposure degree of the first image is compared with the capillary exposure degree of the second image to obtain comparison result information, and based on the comparison result information, the greater the difference between the capillary exposure degree of the first image and the capillary exposure degree of the second image, the greater the risk degree of varicose veins in the lower limbs.

[0024] In addition, according to one embodiment of the present specification, the server can collect user information about user activities between the first time period and the second time period through at least any one of the user device and the wearable device, and reflect the collected user information in the risk assessment of varicose veins in the lower limbs.

[0025] In addition, according to an embodiment of the present specification, the video related to varicose veins in the lower limbs is an image of the lower body of the user shot vertically, and the server can export multiple images related to varicose veins in the lower limbs from the video related to varicose veins in the lower limbs.

[0026] In addition, according to one embodiment of the present specification, the server can provide the user device with guide information for shooting videos related to varicose veins in the lower limbs. When the video related to varicose veins in the lower limbs shot by the user device according to the guide information is transmitted to the server, the video related to varicose veins in the lower limbs can be transmitted in encrypted form.

[0027] In addition, according to an embodiment of the present specification, the server may obtain user consultation information from the user device, and reflect the user consultation information to assess the risk level of varicose veins in the lower limbs.

[0028] Effects of the Invention

[0029] This manual has the effect of providing a method for early diagnosis and management of varicose veins of the lower limbs.

[0030] The present specification has the effect of providing a method for a platform for early diagnosis of varicose veins of lower extremities, the platform acquiring image information from a user device and evaluating the degree of risk through the image information.

[0031] This specification has the effect of providing a method for early diagnosis and management of varicose veins of the lower limbs through a non-face-to-face service platform.

[0032] The present specification has the effect of providing a method for extracting an image for determining varicose veins of the lower limbs.

[0033] The present specification has the effect of providing a method for determining the risk level of varicose veins in the lower limbs by analyzing images related to varicose veins in the lower limbs.

[0034] The effects of the present description are not limited to the above-described contents, but can be extended to various matters that can be derived from the embodiments of the invention described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a diagram showing an example of a system operating environment according to one embodiment of the present specification.

[0036] Figure 2 It is a block diagram used to illustrate the internal structure of the computing device 200 in one embodiment of the present specification.

[0037] Figure 3a It is a diagram showing the operation of a service platform and server for early diagnosis and management of varicose veins of lower limbs in one embodiment of the present specification.

[0038] Figure 3b It is a diagram showing the operation of a service platform and server for early diagnosis and management of varicose veins of lower limbs in one embodiment of the present specification.

[0039] Figure 3c2 is a diagram showing a method for providing lower limb varicose vein risk level information to users through a service platform for early diagnosis and management of lower limb varicose veins in one embodiment of the present specification.

[0040] Figure 4 It is a diagram showing the operation of a user device and a server in one embodiment of the present specification.

[0041] Figure 5 This is a diagram showing a method of deriving an image from a video for diagnosing varicose veins of the lower limbs in one embodiment of the present specification.

[0042] Figure 6 This is a diagram showing an image related to the risk level of varicose veins in the lower limbs in one embodiment of the present specification.

[0043] Figure 7 This is a diagram showing an image related to the risk level of varicose veins in the lower limbs in one embodiment of the present specification.

[0044] Figure 8a This is a diagram showing a method of using a plurality of images for diagnosing varicose veins of the lower extremities in one embodiment of the present specification.

[0045] Figure 8b This is a diagram showing a method of using a plurality of images for diagnosing varicose veins of the lower extremities in one embodiment of the present specification.

[0046] Fig. 9 2 is a diagram showing a method for analyzing images related to varicose veins of the lower limbs to assess the degree of risk according to an embodiment of the present specification.

[0047] Fig.10 2 is a diagram showing a method for analyzing images related to varicose veins of the lower limbs to assess the degree of risk according to an embodiment of the present specification.

[0048] Fig.11 2 is a diagram showing a method for analyzing images related to varicose veins of the lower limbs to assess the degree of risk according to an embodiment of the present specification.

[0049] Fig.12 is a flow chart showing a method for early diagnosis and management of varicose veins of the lower extremities according to one embodiment of the present specification. DETAILED DESCRIPTION

[0050] When describing the embodiments of this specification, if it is considered that the specific description of a known structure or function may confuse the main purpose of the embodiments of this specification, the detailed description thereof will be omitted. In addition, parts not related to the description of the embodiments of this specification are omitted in the drawings, and similar parts are marked with similar reference numerals.

[0051] In the embodiments of this specification, when a certain component is "connected", "combined" or "connected" to another component, this includes not only a direct connection relationship, but also an indirect connection relationship between other components. In addition, when a certain component "includes" or "has" other components, unless there is a special statement to the contrary, it means that other components may also be included, rather than excluding other components.

[0052] In the embodiments of this specification, the terms "first" and "second" are only used to distinguish one component from another component, and do not limit the order or importance of the components unless otherwise specified. Therefore, within the scope of the embodiments of this specification, the first component in an embodiment can be named as the second component in another embodiment, and similarly, the second component in an embodiment can be named as the first component in another embodiment.

[0053] In the embodiments of this specification, the constituent elements that are distinguished from each other are for the purpose of clearly illustrating the various features, and do not mean that the constituent elements must be separated. That is, multiple constituent elements can be integrated together to form a hardware or software unit, and one constituent element can be dispersed to form multiple hardware or software units. Therefore, even if not separately mentioned, such integrated or dispersed embodiments are also included in the scope of the embodiments of this specification.

[0054] In this specification, the network may include both wired and wireless networks. In this case, the network may refer to a communication network in which data can be exchanged between devices and systems, or between devices, and is not limited to a specific network.

[0055] The embodiments described in this specification may have aspects that are entirely hardware, partially hardware, partially software, or entirely software. In this specification, "unit", "device", or "system" etc. refer to hardware, a combination of hardware and software, or software and other entities related to computers. For example, in this specification, a unit, module, device, or system etc. may be an executing process, a processor, an object, an executable file, a thread of execution, a program, and / or a computer, but is not limited thereto. For example, both an application executed in a computer and a computer may correspond to a unit, module, device, or system etc. of this specification.

[0056] In addition, in this specification, a device can be a mobile device such as a smartphone, tablet, wearable device, and HMD (Head Mounted Display), or a fixed device such as a PC or a home appliance with a display function. In addition, as an example, a device can be a vehicle cluster or an IoT (Internet of Things) device. That is, in this specification, a device can refer to a machine that can run an application, and is not limited to a specific type. In the following, for the sake of convenience, the machine that runs the application is referred to as a device.

[0057] In this specification, the communication mode of the network is not limited, and the connection between the components may not be connected by the same network mode. The network may include not only the communication mode using the communication network (for example, mobile communication network, wired Internet, wireless Internet, broadcast network, satellite network, etc.), but also short-range wireless communication between machines. For example, the network may include all communication methods that can be networked between objects, not limited to wired communication, wireless communication, 3G, 4G, 5G or other methods. For example, wired and / or network may refer to a communication network utilizing one or more communication methods selected from the group consisting of LAN (local area network), MAN (metropolitan area network), GSM (global system for mobile networks), EDGE (Enhanced Data GSM Environment), HSDPA (High Speed ​​Downlink Packet Access), W-CDMA (Wideband Code Division Multiple Access), CDMA (Code Division Multiple Access), TDMA (Time Division Multiple Access), 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) systems, HIPERMAN, Beam Division Multiple Access (BDMA), Wi-MAX (Worldwide Interoperability for Microwave Access) and ultrasonic application communications, but is not limited thereto.

[0058] The constituent elements described in various embodiments do not necessarily mean essential constituent elements, and a part may be an optional constituent element. Therefore, an embodiment consisting of a partial set of constituent elements described in the embodiments is also included in the scope of the embodiments of this specification. In addition, an embodiment in which other constituent elements are added to the constituent elements described in various embodiments is also included in the scope of the embodiments of this specification.

[0059] Hereinafter, embodiments of the present specification will be described in detail with reference to the accompanying drawings.

[0060] Figure 1 FIG. 1 is a diagram showing an example of a system operating environment according to an embodiment of the present specification. Figure 1 , one or more user devices 110-1, 110-2 are connected to one or more servers 120, 130, 140 via a network 1. Figure 1 This is an example used to illustrate the invention. The number of user devices or the number of servers is not limited to Figure 1 shown.

[0061] One or more user devices 110-1, 110-2 may be fixed terminals or mobile terminals implemented as computer systems. One or more user devices 110-1, 110-2 may include, for example, smart phones, mobile phones, navigators, computers, laptops, digital broadcast terminals, PDAs (personal digital assistants), PMPs (portable multimedia players), tablet computers, game consoles, wearable devices, IoT (Internet of Things) devices, VR (virtual reality) devices, AR (augmented reality) devices, etc. As an example, in an embodiment, the user device 110 may actually mean one of various physical computer systems that can communicate with other servers 120-140 through the network 1 using wireless or wired communication methods.

[0062] Each server may be implemented by a computer device or multiple computer devices that communicate with one or more user devices 110-1, 110-2 through the network 1 to provide instructions, codes, files, content, services, etc. For example, the server may be a system that provides various services to one or more user devices 110-1, 110-2 connected through the network 1. As a more specific example, the server is a computer program installed and driven on one or more user devices 110-1, 110-2, and can provide target services of corresponding applications (e.g., providing information, etc.) to one or more user devices 110-1, 110-2 through the application. As another example, the server may distribute files for installing and driving the above-mentioned applications to one or more user devices 110-1, 110-2, and receive user input information to provide corresponding services.

[0063] Figure 2 is a block diagram for explaining the internal structure of a computing device 200 in one embodiment of the present specification. Such a computing device 200 can be applied to reference Figure 1 The one or more user devices 110 - 1 , 110 - 2 or servers 120 - 140 described above may have the same or similar internal structure by adding or removing some components.

[0064] Reference Figure 2 , the 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-temporary computer-readable recording medium, and may include non-volatile large-capacity storage devices (permanent mass storage devices) such as RAM (random access memory), ROM (read-only memory), a disk drive, an SSD (solid-state drive), and a flash memory. Here, non-volatile large-capacity storage devices such as ROM, SSD, flash memory, and a disk drive are separate permanent storage devices distinguished from the memory 210 and may be included in the above-mentioned device or server. In addition, the memory 210 may store an operating system and at least one program code (for example, a browser installed and driven on the user device 110, etc., or an application program installed on the user device 110, etc. to provide a specific service, etc.). Such software components may be loaded by a computer-readable recording medium independent of the memory 210. Such a separate computer-readable recording medium may include a computer-readable recording medium such as a floppy disk drive, a disk, a tape, a DVD / CD-ROM drive, and a memory card.

[0065] In other embodiments, the software constituent elements may also be loaded into the memory 210 via the communication module 230 of the non-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 above-mentioned application) installed based on a file provided by a developer or a file distribution system (e.g., the above-mentioned server) that distributes the installation file of the application via the network 1.

[0066] The processor 220 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input-output operations. The instructions may be provided to the processor 220 via the memory 210 or the communication module 230. For example, the processor 220 may be configured to execute the received instructions according to a program code stored in a recording device such as the memory 210.

[0067] The communication module 230 may provide a function for the user device 110 and the servers 120 - 140 to communicate with each other via the network 1 , and may provide a function for the user device 110 and / or the servers 120 - 140 to communicate with other electronic devices, respectively.

[0068] The transceiver 240 may be a means for interfacing with an external input / output device (not shown). For example, an external input device may include a keyboard, a mouse, a microphone, a camera, and the like, and an external output device may include a display, a speaker, a haptic feedback device, and the like. As another example, the transceiver 240 may also be a means for interfacing with a device that integrates input and output functions, such as a touch screen.

[0069] In addition, in other embodiments, the computing device 200 may include a plurality of Figure 2 More constituent elements. For example, when the computing device 200 is applied to the user device 110, it can be embodied as including at least a part of the above-mentioned input and output devices, or also including other constituent elements such as a transceiver, a GPS (Global Positioning System) module, a camera, various sensors, and a database. As a more specific example, when the user device is a smart phone, it can be embodied as also including various constituent elements commonly included in a smart phone, such as an acceleration sensor or a gyroscope sensor, a camera module, various physical buttons, buttons using a touch panel, input and output ports, and a vibrator for vibration.

[0070] Below, based on Figure 1 and Figure 2 The description is based on the running computing device 200. As an example, a service platform for early diagnosis of varicose veins in the lower limbs can be provided based on at least any one of the applications, software and programs driven in the computing device 200.

[0071] Here, the service platform for early diagnosis of varicose veins of the lower limbs is a computing device 200, which can be installed on a user device for driving, and the platform can be controlled by a server. The server can provide services by exchanging data with the user device as the computing device 200 through a network. As an example, a program or software can be constructed in the server for obtaining images or videos through the service platform for early diagnosis of varicose veins of the lower limbs and analyzing them to determine the risk level of varicose veins of the lower limbs. In addition, the server can also construct an artificial intelligence model or use an external artificial intelligence model to improve the accuracy of judging the risk level of varicose veins of the lower limbs, which will be described later.

[0072] As another example, the service platform for early diagnosis of varicose veins of the lower limbs can be a platform based on multiple node management, and is not limited to a specific form. That is, the service platform for early diagnosis of varicose veins of the lower limbs can be managed by a server or other nodes, and provide services to users through applications and other programs driven by the computing device 200, and is not limited to a specific form. As an example, the service platform for early diagnosis of varicose veins of the lower limbs can be provided to users in various forms, but for the sake of convenience of explanation below, it is described as a platform driven in the user device 300, based on the service platform for early diagnosis of varicose veins of the lower limbs. However, this is just an example for the convenience of explanation and is not limited to this.

[0073] Figure 3a to Figure 3c is a diagram showing the operation of a service platform and server for early diagnosis and management of varicose veins of lower extremities in one embodiment of the present specification. Figure 3a , a service platform (or application) for early diagnosis of varicose veins in the lower extremities (hereinafter referred to as the service platform 310) can be run in the user device 300. As an example, the user device 300 can transmit the image 311 related to varicose veins in the lower extremities to the server 400 through the service platform 310, and the server 400 can provide the varicose veins in the lower extremities assessment result information for assessing the risk level of varicose veins in the lower extremities through the acquired image 311 related to varicose veins in the lower extremities to the service platform 310 driven in the user device 300. That is, the user can receive a service for judging the risk level of varicose veins in the lower extremities through the service platform 310 installed in the user device 300. Here, as an example, the risk level of varicose veins in the lower extremities can be judged through the image 311 related to varicose veins in the lower extremities. Here, as an example, the risk level of varicose veins in the lower extremities can be judged through the image 311 related to varicose veins in the lower extremities. In more detail, varicose veins in the lower extremities may be a disease caused by abnormal swelling of the superficial veins in the lower extremities due to dysfunction of the one-way valve of the lower extremity veins, and most of the symptoms of the disease may be concentrated in the calf or thigh. Here, when the symptoms are severe, the capillaries in the calf or thigh may swell to a degree that can be confirmed by the naked eye. That is, the exposure degree of the capillaries in the calf or thigh can be an indicator for diagnosing varicose veins in the lower limbs or judging the risk level. As an example, in order to judge the risk level of varicose veins in the lower limbs, the exposure degree of the capillaries can be quantified.

[0074] In addition, as a criterion for judging varicose veins in the lower extremities, in addition to the degree of capillary exposure, the degree of edema can also be used. The degree of edema can refer to the volume or volume change of a specific part. In addition, regarding the degree of edema, the volume or volume change of the calf or dorsum of the foot can also be used as a judgment object, but the present invention is not limited to this.

[0075] Considering the above situation, the risk level of varicose veins in the lower extremities can be determined based on the digitized capillary exposure level in the image 311 related to varicose veins in the lower extremities. That is, by determining how many capillaries are exposed and visible in the thigh or calf image transmitted by the user, the digitized capillary exposure level is derived, and the risk level of varicose veins in the lower extremities is determined based on this, thereby performing early diagnosis of varicose veins in the lower extremities. The server 400 obtains the varicose vein image 311 of the lower extremities related to the user from the service platform 310 driven by the user device 300, thereby determining the risk level of varicose veins in the lower extremities, and then provides corresponding information through the service platform 310.

[0076] Here, as an example, in order to improve the accuracy of the risk level judgment of varicose veins in the lower limbs, the analysis accuracy of the varicose vein images 311 of the lower limbs can be improved, or multiple varicose vein images 311 of the lower limbs are required. As a specific example, the state of the user can change in real time. In addition, the symptoms of a specific part of the user may appear to be severe, but the symptoms of other specific parts may not appear to be serious. That is, since the varicose vein images 311 of the lower limbs obtained by the server 400 may have limitations in accurately expressing the user's state, multiple images may be required to accurately judge the user's state. In addition, the risk level judgment of varicose veins in the lower limbs is not performed through face-to-face diagnosis and treatment, but through non-face-to-face images, so there may be limitations. Therefore, in order to accurately judge the risk level of varicose vein images 311 of the lower limbs, a solution to improve the accuracy of image analysis may be required.

[0077] Here, as an example, refer to Figure 3b The server 400 can obtain not only the lower limb varicose vein image 311, but also the lower limb varicose vein video 312 and the additional image 313 related to the lower limb varicose vein through the service platform 310. That is, the server 400 can perform the risk level analysis of the lower limb varicose vein through the video 312 or the related additional image 313, which will be described later.

[0078] In addition, as an example, see Figure 3c, the server 400 can further obtain the user consultation information 314 from the service platform 310, and reflect the information to determine the risk level of varicose veins in the lower limbs. Specifically, when the user wants to receive the risk level determination service of varicose veins in the lower limbs through the service platform 310 driven by the user device 300, the user can input the user consultation information 314 and provide it to the server 400, and then obtain the video or image and provide it to the server 400. The server 400 can determine the risk level of varicose veins in the lower limbs through the user consultation information 314 and the video or image information obtained by the service platform 310 of the user device 300, and provide the varicose vein risk level assessment result information of the lower limbs to the user through the service platform 310. Here, the risk level information of varicose veins in the lower limbs is numerical information, which can be expressed as a risk level score or a risk level, but is not limited to a specific form.

[0079] Specifically, Figure 4 FIG. 1 is a diagram showing the operation of a user device and a server in one embodiment of the present specification. Figure 4 As shown, the user device 300 can transmit a lower extremity varicose vein analysis request to the server 400. Here, the lower extremity varicose vein analysis request can be transmitted to the server 400 together with the user consultation information 314. That is, the user can transmit the lower extremity varicose vein analysis request together with the user consultation information to the server 400 through the service platform 310 driven in the user device 300. Afterwards, the server 400 can request the user device 300 to shoot at least one of the video and the image to determine the risk level of varicose veins in the lower extremities. Here, as an example, multiple videos and images can be requested at a certain time interval, which will be described later. The server 400 can obtain at least any one of the video and the image from the user device 300, judge the risk level of varicose veins in the lower extremities based on this, and transmit the lower extremity varicose vein assessment result information to the user device 300.

[0080] As an example, Figure 5 FIG. 1 is a diagram showing a method for deriving an image from a video for diagnosing varicose veins of the lower extremities in one embodiment of the present specification. Figure 5, the server 400 may request and obtain the video 312 from the user device 300 to improve the accuracy of the risk assessment of varicose veins in the lower extremities. Here, as an example, the video 312 is a video of the lower body of the human body, which may be an image of the lower body shot vertically. As a specific example, the video 312 is an image of the entire lower body, which may be an image of the left, right, front and back. In addition, as an example, it may be a video shot on the inside of the lower body, not limited to a specific form. Here, the shooting guide information may be provided by the service platform 310, and the user may obtain the video by shooting the lower body according to the shooting guide of the service platform 310. As another example, the lower body part may be personal body information, so the video may be encrypted and transmitted to the server 400 through the service platform 310. That is, it may be encrypted so that the corresponding image cannot be played in the server 400, and it may be provided only through the input of the program, software or artificial intelligence used to determine the risk of varicose veins in the lower extremities. The server 400 can extract images 510, 520, 530 related to varicose veins of the lower limbs from the acquired video 312. That is, at least one image 510, 520, 530 related to varicose veins of the lower limbs can be extracted by confirming the degree of capillary enlargement in the video 312. Here, as an example, the server 400 can be connected to the artificial intelligence 500, and the video 312 can be provided through the input of the artificial intelligence 500, and the above-mentioned images 510, 520, 530 can be derived through the output. As an example, the artificial intelligence 500 can have a learning model related to varicose veins of the lower limbs, and learn based on multiple images related to varicose veins of the lower limbs, capillary quantification information, and varicose vein risk information of the lower limbs. That is, the artificial intelligence 500 can construct a learning model related to the diagnosis of varicose veins of the lower limbs, and extract images related to varicose veins of the lower limbs through the learning model. Afterwards, the server 400 can evaluate the risk level of varicose veins of the lower limbs by analyzing the corresponding images. In addition, artificial intelligence 500 can delete unnecessary information for judging the risk level of varicose veins in the lower limbs from images related to varicose veins in the lower limbs. As an example, artificial intelligence 500 can delete leg hair or other information irrelevant to the risk level judgment of varicose veins in the lower limbs from images related to varicose veins in the lower limbs, and the corresponding information can also be recognized through learning. That is, artificial intelligence 500 can not only derive images for judging the risk level of varicose veins in the lower limbs, but also delete unnecessary parts from the images. By deleting unnecessary information from images related to varicose veins in the lower limbs, the accuracy of risk level judgment can be improved.

[0081] Here, as an example, Figure 6 and Figure 7 : is a diagram showing an image related to the risk level of varicose veins in the lower extremities in one embodiment of the present specification. Figure 6, the risk level of varicose veins in the lower limbs can be determined based on the varicose vein images 610, 620, and 630 of the lower limbs. As an example, the first image 610 only exposes part of the capillaries in the corresponding part, and the capillary exposure level is not high, and may not be swollen. That is, the capillary exposure level value of the first image 610 may be small. On the other hand, the capillary exposure level of the second image 620 may be higher than that of the first image, and in the third image 630, the capillary exposure level value may be the highest. That is, the risk level of varicose veins in the lower limbs can be determined based on the capillary exposure level value, and it is necessary to derive the capillary exposure level value from each image 610, 620, and 630.

[0082] In addition, refer to Figure 7 , the risk level of varicose veins in the lower limbs can be assessed by considering the distribution of exposed capillary sites. Here, the first image 710 may be a case where capillaries are multiple and exist in multiple capillary lines, and the second image 720 may be a case where multiple capillaries are exposed on one capillary line. Here, considering the symptoms of varicose veins in the lower limbs, when multiple capillaries are exposed on one capillary line, it can be judged that varicose veins in the lower limbs are more advanced. Therefore, compared with the first image 710, the risk level of the second image 720 may be higher. As an example, in the case of analyzing images related to varicose veins in the lower limbs, the exposed capillary sites can be quantified in the images related to varicose veins in the lower limbs. Here, considering the location of each exposed capillary site, whether the exposed capillary site is located on the same capillary line can be reflected in the risk level assessment. That is, a weighted value can be assigned to the above information, in which case the risk level of varicose veins in the lower limbs can be displayed as high. As an example, in Figure 7 In the example, the risk level in the second image 720 may be set to be higher than that in the first image 710 .

[0083] As another example, Figure 8a and Figure 8b FIG. 1 is a diagram showing a method for diagnosing varicose veins of the lower extremities using a plurality of images in one embodiment of the present specification. Figure 8a, the server 400 can obtain at least any one of multiple lower limb varicose veins related images 311 and videos 312 through the service platform 310. For the sake of convenience, the following description will be based on the lower limb varicose veins related images 311, and the same applies to the video 312. That is, the server 400 can analyze multiple lower limb varicose veins related images 311 to improve the accuracy of lower limb varicose veins analysis. Here, as an example, regarding the symptoms of lower limb varicose veins, the user may experience leg swelling most obviously at night after performing daily activities. Taking the above into account, the server 400 can analyze the risk level of lower limb varicose veins by obtaining multiple lower limb varicose veins related images 311.

[0084] Here, as a specific example, the server 400 can obtain lower limb varicose vein related images 311 based on different time periods. As an example, since the capillary exposure sites may be different in the morning and evening time periods, the server 400 can obtain lower limb varicose vein related images 311 for each time period. The server 400 can obtain capillary exposure degree information by comparing multiple lower limb varicose vein related images 311, and reflect it in the risk level. As an example, regarding the symptoms of lower limb varicose veins, the capillary visibility may increase due to the user's activities or other actions. That is, the higher the degree of progression of lower limb varicose veins, the more prominent the symptoms due to user activities or actions may be. Taking the above into account, for the lower limb varicose vein related images 311 for the same part, the greater the change between the morning time period image and the evening time period image, the higher the risk level of lower limb varicose veins may be. The server 400 can be set to analyze multiple lower limb varicose vein images 311 obtained in different time periods and assign weighted values ​​to the differences. The greater the difference, the higher the risk level. Here, as an example, refer to Figure 8b, user information can be collected between the time periods for acquiring the lower extremity varicose vein images 311, and the corresponding information can be reflected to assess the risk level. As an example, the service platform 310 can be driven in the user device 300 and the wearable device 800 of the user. Here, the service platform 310 can collect user information between the time periods for acquiring the lower extremity varicose vein images 311, and obtain the user's activity and action related information. As an example, between the time periods for acquiring the lower extremity varicose vein images 311, when the user's activity is small, the difference in the change in the capillary exposure level may be small. On the contrary, between the time periods for acquiring the lower extremity varicose vein images 311, when the user's activity is large, such as mountaineering or other activities, the difference in the change in the capillary exposure level may be large. That is, when judging the risk level of varicose veins in the lower extremities, the user's activity level needs to be considered, and for this purpose, the server 400 can obtain the user's collected information and reflect the weighted value. The server 400 can judge the risk level of varicose veins in the lower extremities based on the weighted value of the user's numerical information, and can obtain the user information through the user device 300 or the wearable device 800 to perform the above operation.

[0085] Fig. 9 is a diagram showing a method for analyzing images related to varicose veins of the lower extremities to assess the risk level according to an embodiment of the present specification. Fig. 9 , when the server 400 uses the lower extremity varicose vein related image 311 to evaluate the risk of varicose veins in the lower extremities, the server 400 can derive the parameters in pixel units for the human body parts in the image 311 and obtain the standard deviation information for each pixel parameter value. Here, the information about the distribution of capillaries can be obtained based on each pixel parameter value and the standard deviation, and the exposure degree of capillaries can be quantified. As an example, in Fig. 9 In the information 920 reflecting the standard deviation calculated for each pixel of the photographed part, the risk level information 930 and 940 of varicose veins in the lower limbs can be derived through the information 910 for values ​​above a certain level. That is, for pixels that are above a preset value based on the standard deviation between skin pixels, it is judged that the capillaries are exposed, and the capillary exposure level is digitized based on the number of corresponding pixels, thereby determining the risk level of varicose veins in the lower limbs. Here, as an example, when determining the risk level of varicose veins in the lower limbs, as described above, it is possible to reflect whether there are multiple capillary exposures in the capillary line or whether the capillary exposure is reflected in multiple capillary lines based on the above pixel information. In addition, as an example, the above information can be calculated for multiple varicose vein images of the lower limbs, and the information on the numerical pixel change differences in multiple images can be reflected in the risk level assessment, as described above.

[0086] As another example, in the case where the user device 300 acquires images related to varicose veins of the lower extremities, it may not be easy to ensure an image suitable for analysis. As an example, when the user takes a photo of the back of the calf, the user bends the waist or the legs, so there may be limitations in acquiring multiple images in the same posture, and correction may be required. In view of the above situation, the association information between the image 311 related to varicose veins of the lower extremities and the user's posture can be further considered. As an example, the server 400 can pre-acquire the change information of the capillary exposure part of the user in different postures, and correct the image based on this. That is, the server 400 can correct the image by further reflecting the user's shooting posture information in the acquired image 311 related to varicose veins of the lower extremities, thereby improving the accuracy of risk assessment. As an example, when the user's posture is bent, the skin color may be reflected differently, so the skin color can be corrected based on the pre-captured image to improve the accuracy of risk judgment.

[0087] As another example, the artificial intelligence 500 can be used to assess the risk of varicose veins in the lower extremities. Here, the artificial intelligence 500 can perform initial learning based on the clinical judgment information of the doctor, and then can perform learning based on reinforcement learning or other deep learning. That is, in order to assess the risk of varicose veins in the lower extremities, an artificial intelligence 500 model can be constructed, and the artificial intelligence 500 can reflect the weighted value for the above risk level and other learning information, and derive the risk level assessment value in an output manner.

[0088] As another example, it can be set to provide user-related information based on the risk level of varicose veins in the lower limbs determined by the server 400. As an example, the server 400 can send a notification to a user who has output a high risk level assessment value of varicose veins in the lower limbs through the service platform 310. In addition, the server 400 can be associated with a hospital or other facilities. The server 400 can allow users to check the biomarkers of samples (such as saliva, urine, etc.) in hospitals or other facilities to confirm varicose veins in the lower limbs, and the user can be managed for varicose veins in the lower limbs. As an example, the server 400 can be set to provide users with a lower limb varicose vein specialist hospital reservation system connection, lower limb varicose vein inspection services and other programs through the service platform 310, and users can manage varicose veins in the lower limbs through the corresponding service platform 310.

[0089] As another example, the server 400 may be linked with other devices (such as a body composition meter) to obtain additional information. As an example, the server 400 may further obtain lower body blood flow analysis information measured by other devices and reflect it in the risk assessment of varicose veins in the lower extremities, which is not limited to a specific embodiment.

[0090] Fig.10 and Fig.11 is a diagram showing a method for analyzing images related to varicose veins of the lower extremities to assess the risk level according to an embodiment of the present specification. Fig.10 , the server 400 can obtain the images 1011 and 1012 related to varicose veins of the lower limbs and obtain the analysis result images 1021 and 1022 through the analysis as described above, and evaluate the risk level based on this. Here, as described above, in order to evaluate the risk level, other information can also be used, as described above. Thus, an early diagnosis tool (tool) can be provided for patients with varicose veins of the lower limbs, improving the treatment effect and reducing social costs. As an example, since varicose veins of the lower limbs are often left unattended, when diagnosed in the hospital, it may be in a state where the degree of progression is already high, and the treatment effect may be poor. Therefore, the risk level of varicose veins of the lower limbs can be confirmed from a preventive perspective before the early symptoms of varicose veins of the lower limbs or the symptoms appear, thereby shortening the treatment cost and time. In addition, the management of varicose veins of the lower limbs can be carried out in a non-face-to-face manner through the service platform 310 and the server 400, without the cumbersomeness of going to the hospital. In addition, even if the initial symptoms appear, the diagnosis is delayed due to the trouble of going to the hospital, which may become the main reason for not only making treatment difficult and reducing the treatment effect, but also increasing the cost of treatment. However, through the above-mentioned service platform 310 and server 400, even if you do not go to the hospital, you can easily test, so it can have a positive impact on the prevention and treatment of varicose veins in the lower limbs in daily life. In addition, as an example, based on the data secured by the above-mentioned service platform 310 and server 400, the discovery of diagnostic biomarkers and factors can be carried out, which can be referred to Fig.11 .

[0091] Fig.12 is a flow chart showing a method for early diagnosis and management of varicose veins of the lower extremities according to one embodiment of the present specification.

[0092] Reference Fig.12 , the server 400 may obtain information related to varicose veins in the lower limbs from the user device 300. After S1210, the server 400 may digitize the capillary exposure degree based on the analysis of the information related to varicose veins in the lower limbs S1220, and evaluate the risk level of varicose veins in the lower limbs based on the digitized capillary exposure degree. After S1230, the server 400 may transmit the varicose veins in the lower limbs assessment result information to the user device 300 based on the assessed risk level of varicose veins in the lower limbs. In S1240, the information related to varicose veins in the lower limbs may include at least one of images related to varicose veins in the lower limbs, videos related to varicose veins in the lower limbs, and additional images. As an example, the additional image may be an image or other image for other body parts of the user, not limited to a specific form.

[0093] In addition, as an example, the image related to varicose veins of the lower limbs may be an image of the lower body of the user. In the case where the capillary exposure degree is quantified based on the analysis of the information related to varicose veins of the lower limbs, the server may derive pixel-based parameters for the lower body of the user from the image related to varicose veins of the lower limbs, derive standard deviations based on a plurality of pixel-based parameters to confirm the capillaries, and quantify the capillary exposure degree through the capillaries above the preset value among the confirmed capillaries, as described above.

[0094] In addition, as another example, when assessing the risk of varicose veins in the lower extremities based on the numerical capillary exposure, multiple capillary lines can be identified, and a weighted value can be assigned to the capillary distribution degree above a preset value in the multiple capillary lines to assess the risk of varicose veins in the lower extremities. Here, when a capillary line among the multiple capillary lines has a plurality of capillaries above a preset value, the risk of varicose veins in the lower extremities may increase.

[0095] In addition, the server 400 can obtain multiple images related to varicose veins of the lower limbs. Here, the multiple images related to varicose veins of the lower limbs can be images of the same lower body part of the user, and the capillary exposure degrees are numerically compared in the multiple images related to varicose veins of the lower limbs, and a weighted value is assigned to the comparison result information to evaluate the risk degree of varicose veins of the lower limbs. As a specific example, the first image of the multiple images related to varicose veins of the lower limbs can be an image acquired in a first time period, and the second image can be an image acquired in a second time period. The server 400 can compare the capillary exposure degree of the first image with the capillary exposure degree of the second image to obtain the comparison result information. Here, based on the comparison result information, the greater the difference between the capillary exposure degree of the first image and the capillary exposure degree of the second image, the higher the risk degree of varicose veins of the lower limbs may be.

[0096] In addition, the server 400 can collect user information about user activities between the first time period and the second time period through at least one of the user device 300 and the wearable device 800, and can reflect the collected user information in the risk assessment of varicose veins in the lower limbs.

[0097] In addition, as another example, a video related to varicose veins in the lower limbs is an image of the lower body of the user shot vertically. The server 400 can derive multiple images related to varicose veins in the lower limbs from the video related to varicose veins in the lower limbs. In addition, the server 400 can provide the user device with guide information for shooting videos related to varicose veins in the lower limbs. Here, in the case where the video related to varicose veins in the lower limbs shot by the user device according to the guide information is transmitted to the server, the video related to varicose veins in the lower limbs can be encrypted and transmitted. In addition, the server 400 can obtain user consultation information from the user device 300, and reflect the user consultation information to assess the risk level of varicose veins in the lower limbs, as described above.

[0098] The embodiments described above can be implemented at least in part by a computer program and recorded in a computer-readable recording medium. The recording medium that records the program for implementing the embodiment and is computer-readable includes all kinds of recording devices that store computer-readable data. As examples of computer-readable recording media, there are ROM, RAM, CD-ROM, magnetic tape, optical data storage devices, etc. In addition, the computer-readable recording medium can be dispersed in a computer system connected via a network to store and execute computer-readable codes in a decentralized manner. In addition, the functional program, code, and code segment (segment) used to implement the present embodiment can be easily understood by a person of ordinary skill in the technical field to which the present embodiment belongs.

[0099] The above-viewed description is described with reference to the embodiments shown in the accompanying drawings, but this is only exemplary, and anyone with common knowledge in the art can understand that various modifications and variations of the embodiments can be made. However, such variations should be deemed to be within the technical protection scope of this description. Therefore, the true technical protection scope of this description should be determined according to the technical ideas of the attached claims to include other implementation methods, other embodiments, and equivalents to the claims.

[0100] Industrial Applicability

[0101] The present specification can provide a method for a platform for early diagnosis of varicose veins in the lower limbs, which acquires image information from a user device and evaluates the risk level based on the image information, and is therefore industrially applicable.

Claims

1. A method for early diagnosis and management of varicose veins of lower extremities by a server, characterized in that: include: The step of obtaining information related to varicose veins of lower extremities from a user device; The step of quantifying the exposure degree of capillaries based on the analysis of the information related to varicose veins of the lower extremities; The step of assessing the risk of varicose veins in the lower extremities based on the quantified capillary exposure level; as well as The step of transmitting the lower limb varicose vein assessment result information to the user device based on the assessed lower limb varicose vein risk level.

2. The method according to claim 1, characterized in that: The information related to varicose veins of lower limbs includes at least any one of an image related to varicose veins of lower limbs, a video related to varicose veins of lower limbs, and an additional image.

3. The method according to claim 2, characterized in that The lower limb varicose vein related image is an image of the user's lower body. In the case where the capillary exposure degree is quantified based on the analysis of the lower limb varicose vein related information, the server derives the parameters in pixel units for the lower body part of the user from the lower limb varicose vein related image, deriving a standard deviation based on the plurality of pixel-based parameters to identify capillaries, The capillary exposure degree is quantified based on the capillaries exceeding a preset value among the confirmed capillaries.

4. The method according to claim 3, characterized in that In the case of evaluating the risk of varicose veins in the lower extremities based on the numerical capillary exposure degree, a plurality of capillary lines are identified, and a weighted value is assigned to the capillary distribution degree above a preset value in the plurality of capillary lines to evaluate the risk of varicose veins in the lower extremities, and When a number of capillaries exceeding a preset value is distributed in one of the plurality of capillary lines, the risk level of varicose veins in the lower limbs increases.

5. The method according to claim 3, characterized in that: The server obtains a plurality of images related to varicose veins of lower limbs, and the plurality of images related to varicose veins of lower limbs are images of the same lower body part of the user, The capillary exposure levels in the plurality of lower limb varicose vein related images are numerically compared, and a weighted value is assigned to the comparison result information to evaluate the risk level of lower limb varicose veins.

6. The method according to claim 5, characterized in that Among the multiple lower extremity varicose vein related images, the first image is an image acquired during a first time period, and the second image is an image acquired during a second time period. comparing the capillary exposure level of the first image with the capillary exposure level of the second image to obtain comparison result information, and Based on the comparison result information, the greater the difference between the capillary exposure level of the first image and the capillary exposure level of the second image, the higher the risk level of varicose veins in the lower limbs.

7. The method according to claim 6, characterized in that The server collects user information about user activities between a first time period and a second time period through at least any one of the user device and the wearable device, The collected user information is reflected in the risk assessment of varicose veins in the lower limbs.

8. The method according to claim 2, characterized in that: The video related to varicose veins in the lower limbs is an image of the lower body of the user shot vertically, and the server derives multiple images related to varicose veins in the lower limbs from the video related to varicose veins in the lower limbs.

9. The method according to claim 8, characterized in that The server provides the user device with guide information for shooting the video related to varicose veins of the lower limbs. When the video related to varicose veins of the lower limbs shot by the user device according to the guide information is transmitted to the server, the video related to varicose veins of the lower limbs is encrypted and transmitted.

10. The method according to claim 1, characterized in that The server obtains user consultation information from the user device and uses the user consultation information to assess the risk level of varicose veins in the lower limbs.

11. A computer program stored in a computer readable medium, which is combined with hardware to execute the method according to any one of claims 1 to 10.

12. A server for early diagnosis and management of varicose veins of lower extremities, characterized in that: include: A memory for storing information related to varicose veins of lower extremities; a transceiver unit for communicating with a user device; as well as a processor controlling the memory and the transceiver, and The processor obtains information related to varicose veins in the lower limbs from the user device, quantifies the capillary exposure level based on the analysis of the information related to varicose veins in the lower limbs, evaluates the risk level of varicose veins in the lower limbs based on the quantified capillary exposure level, and transmits the varicose veins in the lower limbs evaluation result information to the user device based on the evaluated risk level of varicose veins in the lower limbs.

13. A method for early diagnosis and management of varicose veins of lower extremities by a user device, characterized in that: include: The step of transmitting information related to varicose veins of lower extremities to a server; as well as The step of obtaining lower limb varicose vein assessment result information from a server based on the risk level of lower limb varicose veins, The server quantifies the capillary exposure degree based on the analysis of the lower limb varicose vein related information, evaluates the risk degree of lower limb varicose veins based on the quantified capillary exposure degree, and generates lower limb varicose veins evaluation result information.

14. The method according to claim 13, characterized in that The information related to varicose veins of lower limbs includes at least any one of an image related to varicose veins of lower limbs, a video related to varicose veins of lower limbs, and an additional image.

15. The method according to claim 14, characterized in that The lower limb varicose vein related image is an image of the user's lower body. In the case where the capillary exposure degree is quantified based on the analysis of the lower limb varicose vein related information, the server derives the parameters in pixel units for the lower body part of the user from the lower limb varicose vein related image, deriving a standard deviation based on the plurality of pixel-based parameters to identify capillaries, The capillary exposure degree is quantified based on the capillaries exceeding a preset value among the confirmed capillaries.

16. The method according to claim 15, characterized in that In the case of evaluating the risk of varicose veins in the lower extremities based on the numerical capillary exposure degree, a plurality of capillary lines are identified, and a weighted value is assigned to the capillary distribution degree above a preset value in the plurality of capillary lines to evaluate the risk of varicose veins in the lower extremities, and When a number of capillaries exceeding a preset value is distributed in one of the plurality of capillary lines, the risk level of varicose veins in the lower limbs increases.

17. The method according to claim 13, characterized in that The user device obtains the user's medical consultation information and transmits it to the server, The user's medical consultation information is reflected to assess the risk level of varicose veins in the lower limbs.

Images