Medical image data management system and method

Abstract

A medical image data management system of the present invention comprises: an image data receiving unit that receives medical image data captured by at least one photographing device; an original image storage unit that stores an original image of the medical image data; a correction image generating unit that generating a correction image by reducing the volume of the medical image data; and a correction image transmitting unit that transmits the correction image to a storage device within a predetermined hospital. Due to this feature, the medical image data management system has the effect of establishing a more efficient medical treatment and research environment in the field of medical technology by correcting medical image data received from any imaging device according to a predetermined standard and then separating and storing the original image and the correction image in an optimized state according to usability.

Description

Medical image data management system and method thereof

[0001] The present invention relates to a storage technology for medical image data, and more specifically, to a system and method for optimizing and managing high-resolution medical image data according to its usability.

[0002] In the medical field, doctors utilize various clinical photographs for diagnosis, and as the resolution of photographs using photographic devices such as digital cameras increases with the development of such devices, the resolution of medical clinical photographs is also increasing.

[0003] In relation to this, Korean Patent No. 10-2020531 discloses a technology that can generate a blur model for a detector of a medical imaging device using a linear gamma ray source and can generate a high-resolution medical image using the generated blur model.

[0004] However, these high-resolution images are typically only used in specific fields (e.g., artificial intelligence learning data, academic conference research, etc.) and are not used by doctors to diagnose patients or check their symptoms.

[0005] However, there was a problem that the storage devices for storing medical images in hospitals contained high-resolution original photos, which occupied a lot of computer resources and made it difficult to build an efficient treatment environment due to the slow processing speed, such as loading data.

[0006] [Prior Art Literature]

[0007] [Patent Document]

[0008] (Patent Document 1) Korean Patent No. 10-2020531

[0009] Accordingly, in order to solve the above problem, the present invention provides a medical image data management system and method that corrects medical image data received from any photographing device according to a predetermined standard, and then separates and stores the original image and the corrected image in an optimized state according to their usability, thereby enabling more efficient construction of a medical treatment environment and a research environment in the field of medical technology.

[0010] In addition, the present invention provides a medical image data management system and method that performs a correction to down-convert the capacity of medical image data and then transmits the corrected image to a storage device within a hospital, thereby saving the storage space of the storage device within a hospital and efficiently utilizing the computer resources within the hospital.

[0011] In addition, the present invention provides a medical image data management system and method that can speed up the data processing speed for searching and loading necessary image data by referring to the corrected image stored in a storage device in a hospital when a doctor diagnoses a patient or checks the patient's symptoms, thereby enabling the establishment of an efficient treatment environment.

[0012] In addition, the present invention provides a medical image data management system and method that can effectively manage a large amount of original images at low cost by storing high-resolution original images of the medical image data in a cloud storage device and providing information corresponding to a request from an expert in a specific field requiring the original images.

[0013] In addition, the present invention provides a medical image data management system and method that can safely manage the original image by storing verification information for verifying whether the original image of the medical image data stored in a cloud storage device has been falsified or altered in a blockchain server.

[0014] In order to achieve the above object, the medical image data management system provided by the present invention is characterized by including an image data receiving unit for receiving medical image data captured by at least one photographing device; an original image storage unit for storing an original image of the medical image data; a correction image generating unit for generating a correction image by reducing the capacity of the medical image data; and a correction image transmitting unit for transmitting the correction image to a storage device within a predetermined hospital.

[0015] Preferably, the image data receiving unit provides a communication interface with the photographing devices and can receive the medical image data in real time from the photographing devices via wired / wireless communication.

[0016] Preferably, the original image storage unit can be implemented as a cloud storage device.

[0017] Preferably, the correction image generation unit stores a second resolution change reference value preset for each object to be photographed in advance, analyzes the original image of the received medical image data to automatically recognize the object to be photographed, and then down-converts the resolution of the medical image data based on the second resolution change reference value corresponding to the automatically recognized object, thereby reducing its capacity.

[0018] Preferably, the system may further include a blockchain server interface unit that provides a communication interface with an external blockchain server via a wired / wireless communication method; and a control unit that controls the blockchain server interface unit to store verification information for monitoring forgery / alteration of the original image in the blockchain server.

[0019] Meanwhile, in order to achieve the above object, the medical image data management method provided by the present invention is characterized in that the medical image data management method using a medical image data management system that receives and manages medical image data from a remote location includes an image correction information storage step in which the medical image data management system stores image correction information for optimizing and storing the medical image data; an image data reception step in which the medical image data management system receives medical image data captured by at least one photographing device; an original image storage step in which the medical image data management system stores an original image of the medical image data; a correction image generation step in which the medical image data management system generates a correction image in which the capacity of the medical image data is reduced; a correction image transmission step in which the medical image data management system transmits the correction image to a predetermined in-hospital storage device; and a correction image storage step in which the in-hospital storage device stores the correction image.

[0020] Preferably, the image data receiving step can receive the medical image data in real time by communicating with the photographing devices via wired / wireless communication.

[0021] Preferably, the original image storage step may store the original image in a cloud storage device connected to the medical image data management system via a communication network.

[0022] Preferably, the image correction information storage step stores a second resolution change reference value preset for each object to be photographed, and the correction image generation step is an object recognition step that automatically recognizes the object to be photographed by analyzing the original image of the medical image data received in the image data receiving step; and the capacity can be reduced by down-converting the resolution of the medical image data based on the second resolution change reference value corresponding to the automatically recognized object.

[0023] Preferably, the medical image data management system may further include a verification information generation step for generating verification information for monitoring forgery / alteration of the original image; and a verification information storage step for communicating with an external blockchain server via wired / wireless communication to store the verification information in the blockchain server.

[0024] The medical image data management system and method of the present invention as described above corrects medical image data received from any photographing device according to a predetermined standard, and then separates and stores the original image and the corrected image in an optimized state according to their usability, thereby enabling more efficient construction of a medical treatment environment and a research environment in the field of medical technology.

[0025] In addition, the present invention has the effect of enabling efficient use of computer resources within a hospital by saving storage space within a hospital storage device by performing correction to down-convert the capacity of medical image data and then transmitting the corrected image to a hospital storage device.

[0026] In addition, the present invention has the effect of enabling a doctor to quickly process data for searching and loading necessary image data by referring to the corrected image stored in a storage device within a hospital when diagnosing a patient or checking the patient's symptoms, thereby creating an efficient treatment environment.

[0027] In addition, the present invention has the effect of enabling effective management of a large amount of original images at low cost by storing high-resolution original images of the medical image data in a cloud storage device and providing information corresponding to a request from an expert in a specific field who requires the original images.

[0028] In addition, the present invention has the effect of enabling the safe management of the original image by storing verification information for verifying whether the original image of medical image data stored in a cloud storage device has been falsified or altered in a blockchain server.

[0029] FIG. 1 is a drawing for explaining a medical image data management system and devices linked thereto according to one embodiment of the present invention.

[0030] FIG. 2 is a schematic block diagram of a medical image data management system according to an embodiment of the present invention.

[0031] FIG. 3 is a diagram illustrating an example of a field structure for an original image management DB according to one embodiment of the present invention.

[0032] FIGS. 4 to 8 are drawings for explaining a medical image data management method according to one embodiment of the present invention.

[0033] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings so that those skilled in the art can easily practice the present invention. However, the present invention can be implemented in various different forms and is not limited to the embodiments described herein. Meanwhile, in the drawings, parts that are not related to the description are omitted in order to clearly explain the present invention, and similar parts are designated with similar reference numerals throughout the specification. In addition, the description of parts that can be easily understood by those skilled in the art even if a detailed description is omitted is omitted.

[0034] Throughout the specification and claims, whenever a part is said to include a certain component, this does not mean that it excludes other components, but rather that it may include other components, unless specifically stated otherwise.

[0035] FIG. 1 is a diagram illustrating a medical image data management system and devices linked thereto according to an embodiment of the present invention. Referring to FIG. 1, the medical image data management system (100) of the present invention operates in conjunction with a cloud storage device (200), a blockchain server (300), and a hospital system (400). To this end, the medical image data management system (100) may be connected to the cloud storage device (200), the blockchain server (300), and the hospital system (400) via a communication network (10).

[0036] At this time, the hospital system (400) may include at least one photographing device (410) connected to an internal network within the hospital, at least one hospital storage device (420), and at least one hospital terminal device (430). The photographing device (410) is a device for photographing medical image data, and may include not only general medical photographing devices such as X-ray equipment, but also general optical cameras such as DSLR cameras and smartphones. The device may photograph a patient's affected area or diagnostic area through the operation of a doctor or a medical institution's photographing expert, and generate high-resolution medical image data. To this end, the photographing device (410) may be a device fixedly installed within the hospital, or a terminal device (e.g., a portable camera, etc.) certified to be able to access the hospital's internal system.

[0037] When the medical image data management system (100) receives high-resolution medical image data from the imaging device (410), it optimizes the medical image data according to its usability and stores it separately.

[0038] For example, the medical image data management system (100) stores the original image of the medical image data in a cloud storage device (200) in an original image state optimized for artificial intelligence learning or research, or down-converts the capacity of the medical image data to create a corrected image optimized for patient diagnosis or examination, and then stores the corrected image in a hospital storage device (420).

[0039] This is because medical image data for artificial intelligence learning or research requires high precision rather than urgency, but medical image data used to diagnose patients or check their symptoms requires fast loading with precision that allows doctors to check the patient's condition with the naked eye, so the goal is to satisfy each of these needs.

[0040] That is, in the former case, since it requires high-resolution precision even if it takes up a lot of storage space and has a slow execution speed, it is stored in a cloud storage device (200) that can be operated at low cost / high capacity so that it can be provided to terminal devices (e.g., a hospital terminal device (430) connected to an external network, or a specialized diagnostic device (500) (see FIG. 8)) that access it through a communication network (10), and in the latter case, it is stored in a hospital storage device (420) after being corrected to a low capacity so that it can be provided to a hospital terminal device (430) that requires urgency.

[0041] Accordingly, the medical image data management system (100) of the present invention can prevent waste of computer resources within a hospital and resolve inefficiencies in the treatment environment caused by delays in processing speed. In addition, the medical image data management system (100) of the present invention can store high-resolution medical image data with large capacity in a cloud storage device (200) and access and use it whenever necessary, thereby reducing the costs of purchasing or maintaining physical storage devices.

[0042] In addition, the medical image data management system (100) stores verification information for verifying whether each of the original images stored in the cloud storage device (200) is forged or altered in the blockchain server (300), thereby enabling verification of whether a specific original image is forged or altered at a later time upon request from a device that has downloaded the specific original image.

[0043] FIG. 2 is a schematic block diagram of a medical image data management system according to an embodiment of the present invention. Referring to FIG. 2, a medical image data management system (100) according to an embodiment of the present invention may include an original image management DB (110), a user interface unit (I / F) (120), an image data receiving unit (130), a correction image generating unit (140), a correction image transmitting unit (150), a blockchain server interface unit (I / F) (160), and a control unit (170).

[0044] Referring to FIGS. 1 and 2, the configuration and operation of the medical image data management system (100) of the present invention are described as follows.

[0045] The original image management DB (110) stores the original images of medical image data received from the photographing device (410). At this time, the original image management DB (110) may be implemented within the medical image data management system (100), as illustrated in FIG. 2, or may be a cloud storage device (200) implemented separately from the medical image data management system (100), as illustrated in FIG. 1.

[0046] In addition, the original image management DB (110) can store the corresponding image identification code information together with the original image. At this time, the image identification code can include image identification information / shooting date / hospital code / device type code / patient code / treatment subject code, and for this purpose, the image data receiving unit (130) to be described later can receive the image identification code information together when receiving medical image data from the photographing device (410), and the image identification code can be generated by combining metadata set as the default value of the photographing device and information input by the operator of the photographing device (410).

[0047] FIG. 3 is a diagram illustrating an example of a field structure for an original image management DB according to an embodiment of the present invention. Referring to FIG. 3, the original image management DB (110) may include an identification information storage field (111) for storing identification information for identifying an original image, a shooting date storage field (112) for storing the shooting date and time of the original image, a hospital code storage field (113) for storing a hospital code to which the shooting device that shot the original image belongs, a device type code storage field (114) for storing code information indicating the type of the shooting device that shot the original image, a patient code storage field (115) for storing a patient code that is the shooting target of the original image, a medical department code storage field (116) for storing a medical department code, and an original image storage field (117) for storing the original image. At this time, each of the image identification code information may be utilized as a keyword for searching for the corresponding original image.

[0048] The user interface unit (I / F) (120) provides an interface with a user (e.g., a medical image data management system (100) administrator) to control the operation of the medical image data management system (100) or to receive user selection information for presetting operation information.

[0049] The image data receiving unit (130) receives medical image data captured by at least one photographing device (410). To this end, the image data receiving unit (130) provides a communication interface with a plurality of photographing devices (410) and can receive medical image data from each of the photographing devices (410) via a communication network (10). In particular, the image data receiving unit (130) performs real-time communication with each of the photographing devices (410), so that the photographing device (410) can simultaneously capture medical image data and receive the medical image data together with a corresponding image identification code. To this end, the photographing device (410) can simultaneously capture the medical image data by combining preset metadata and input information input by the photographer to generate the image identification code, and then transmit the medical image data and the image identification code to the image data receiving unit (130).

[0050] The correction image generation unit (140) generates a correction image by reducing the capacity of the medical image data received from the image data reception unit (130).

[0051] To this end, the correction image generation unit (140) can generate the correction image based on preset image correction information to optimize and store the medical image data.

[0052] For example, the correction image generation unit (140) can store a first resolution change reference value preset for each photographing device (e.g., X-ray photographing equipment, DSLR camera, smartphone, etc.) in advance, and down-convert the resolution of the medical image data based on the first resolution change reference value corresponding to the photographing device of the received medical image data, thereby reducing its capacity.

[0053] Alternatively, the correction image generation unit (140) may store a second resolution change reference value preset for each object to be captured (e.g., face, torso, teeth, etc.) in advance, and may down-convert the resolution of the medical image data based on the second resolution change reference value corresponding to the object to be captured included in the original image of the received medical image data, thereby reducing its capacity. To this end, the correction image generation unit (140) may store a preset correction algorithm, and may perform a series of processes including a process of searching and recognizing the object to be captured from the original image based on the correction algorithm, a process of automatically classifying the recognized object, and a process of down-converting the resolution of the corresponding medical image data based on the second resolution change reference value corresponding to the result. At this time, the correction algorithm may be implemented as an AI algorithm.

[0054] Meanwhile, the first and second resolution change reference values ​​may be values ​​determined by resolution selection information of doctors who have chosen not to be able to perceive a difference in quality with the naked eye for each type of photographing device or each object to be photographed. For example, the first and second resolution change reference values ​​may be determined by an average or minimum value of threshold resolutions selected by two or more doctors, respectively, for each type of photographing device (e.g., X-ray photographing equipment, DSLR camera, smartphone, etc.) or each object to be photographed (e.g., face, torso, teeth, etc.).

[0055] In addition, these first and second resolution change reference values ​​may be set in advance and stored in the correction image generation unit (140), or may be generated in the correction image generation unit (140) using information received from the doctors' terminal devices (not shown). Alternatively, when the image data receiving unit (130) receives medical image data, it may also receive reference value information for the down conversion.

[0056] The correction image transmission unit (150) transmits the correction image generated by the correction image generation unit (140) to the hospital storage device (420). To this end, the correction image transmission unit (150) can identify the hospital information that took the original image from the image identification code of the original image corresponding to the correction image, and transmit the correction image to the corresponding hospital storage device (420). To this end, the correction image transmission unit (150) may store in advance connection information for connecting to the internal network of the corresponding hospital or its storage device (420), or may be controlled by the control unit (170) that stores the connection information.

[0057] In addition, the correction image transmission unit (150) can transmit the correction image by adding an image identification code of the corresponding original image when transmitting the correction image.

[0058] The blockchain server interface unit (I / F) (160) provides a communication interface with the blockchain server (300) and, under the control of the control unit (170) described below, can store verification information for monitoring forgery / alteration of the original image in the blockchain server (300).

[0059] At this time, the verification information may be generated by the control unit (170) by encrypting a portion of the image identification code of the corresponding medical image data, or may be a hash code received together when the image data receiving unit (130) receives the medical image data.

[0060] The control unit (170) controls the overall operation of the medical image data management system (100) based on a preset medical image data management algorithm. That is, the control unit (170) can control the operation of each of the original image management DB (110), the user interface unit (I / F) (120), the image data receiving unit (130), the corrected image generating unit (140), the corrected image transmitting unit (150), and the blockchain server interface unit (I / F) (160) based on the medical image data management algorithm.

[0061] In particular, the control unit (170) can control the blockchain server I / F (160) to generate verification information for monitoring forgery / alteration for each original image and store it in the blockchain server (300).

[0062] FIGS. 4 to 8 are drawings for explaining a medical image data management method according to an embodiment of the present invention, wherein FIG. 4 illustrates a processing procedure for optimizing and separating and storing medical image data according to its usability, FIGS. 5 and 6 illustrate first and second embodiments of the correction image generation process illustrated in FIG. 4, and FIGS. 7 and 8 illustrate a utilization or verification procedure of the separately stored medical image data.

[0063] A medical image data management method according to an embodiment of the present invention will be described with reference to FIGS. 1 to 8 as follows.

[0064] First, in step S110, the medical image data management system (100) sets image correction information for optimizing and storing the medical image data. At this time, in step S110, the medical image data management system (100) may set a first resolution change reference value for down-converting the resolution of at least one photographing device (410) installed in the hospital system (400) or each type of photographing device (410), or may set a second resolution change reference value that is preset for each target object to be photographed (e.g., face, torso, teeth, etc.).

[0065] The first and second resolution change reference values ​​may be values ​​determined by resolution selection information of doctors who have chosen not to be able to perceive a difference in quality with the naked eye, for each type of photographing device or each type of photographing target object (e.g., face, torso, teeth, etc.). For example, the first and second resolution change reference values ​​may be determined by the correction image generation unit (140) or the control unit (170) of the medical image data management system (100) by the average or minimum values ​​of threshold resolutions selected by two or more doctors, for each type of photographing device (e.g., X-ray photographing equipment, DSLR camera, smartphone, etc.) or each type of photographing target object (e.g., face, torso, teeth, etc.).

[0066] In steps S120 and S130, the photographing device (410) simultaneously captures medical image data and transmits the original image to the medical image data management system (100).

[0067] That is, in step S130, the image data receiving unit (130) of the medical image data management system (100) can receive medical image data captured by at least one photographing device (410). In particular, in step S130, the image data receiving unit (130) can receive the medical image data in real time by communicating with the photographing devices (410) in a wired / wireless communication manner.

[0068] In step S140, the medical image data management system (100) stores the original image of the medical image data. At this time, in step S140, the medical image data management system (100) may store the original image in an internal storage device (i.e., original image management DB (110)) or in a cloud storage device (200) connected to a communication network.

[0069] In steps S150 and S160, the medical image data management system (100) stores verification information for monitoring forgery / alteration of the original image in the blockchain server (300). At this time, the verification information may be generated by the control unit (170) by encrypting a portion of the image identification code of the corresponding medical image data, or may be a hash code received together with the image data receiving unit (130) when receiving the medical image data.

[0070] That is, in step S150, the medical image data management system (100) transmits the verification information to the blockchain server (300) via wired / wireless communication, and in step S160, the blockchain server (300) stores the verification information.

[0071] In step S170, the medical image data management system (100) generates a correction image with a reduced capacity of the medical image data. For example, in step S170, the correction image generation unit (140) of the medical image data management system (100) can generate a correction image with a reduced data capacity by down-converting the resolution of the original image based on preset image correction information in order to optimize and store the medical image data.

[0072] An example of the processing process of the correction image generation unit (140) for this purpose is illustrated in FIGS. 5 and 6.

[0073] FIG. 5 illustrates a process of generating a correction image (170a) according to a first embodiment of step S170, in which a correction image is generated based on a first resolution change reference value preset for each photographing device (e.g., X-ray photographing equipment, DSLR camera, smartphone, etc.).

[0074] Referring to FIG. 5, the correction image generation unit (140) first derives information about the photographing device in step S171a. That is, in step S171a, the correction image generation unit (140) can derive a device type code from the image identification code of the original image, which is the target of correction image generation. Then, in step S172a, the correction image generation unit (140) derives image correction information. To this end, in step S172a, the correction image generation unit (140) can match the photographing device information derived in step S171a with the image correction information for each photographing device set in step S110, and derive image correction information of the photographing device corresponding to the derived device type code. That is, in step S172a, the correction image generation unit (140) can derive a first resolution change reference value (e.g., a resolution threshold at which no difference in quality can be perceived with the naked eye) for reducing the capacity of the target original image. Finally, in step S173a, the correction image generation unit (140) corrects the original image using the image correction information derived above. That is, in step S173a, the correction image generation unit (140) downconverts the resolution of the original image to generate a correction image.

[0075] According to FIG. 5, it can be seen that the correction image generation unit (140) can reduce the capacity of the medical image data by down-converting the resolution of the medical image data based on the first resolution change reference value preset for each photographing device through the correction image generation process (170a).

[0076] FIG. 6 illustrates a process of generating a correction image (170b) according to a second embodiment of step S170, in which a correction image is generated based on a second resolution change reference value preset for each target object to be photographed (e.g., face, torso, teeth, etc.).

[0077] Referring to FIG. 6, the correction image generation unit (140) first searches for an object from the original image of the received medical image data in step S171b, recognizes the object, and automatically classifies the recognized object in step S172b. Then, in step S173b, the correction image generation unit (140) derives image correction information. To this end, in step S173b, the correction image generation unit (140) can derive image correction information corresponding to the automatically classified object by matching the classification type of the object automatically classified in step S172b with the image correction information for each object to be photographed set in step S110. That is, in step S173b, the correction image generation unit (140) can derive a second resolution change reference value (e.g., a resolution threshold at which no quality difference is perceptible with the naked eye) for reducing the capacity of the target original image. Finally, in step S174b, the correction image generation unit (140) corrects the original image using the image correction information derived above. That is, in step S174b, the correction image generation unit (140) downconverts the resolution of the original image to generate a correction image.

[0078] According to FIG. 6, it can be seen that the correction image generation unit (140) can reduce the capacity of the medical image data by down-converting the resolution of the medical image data based on the second resolution change reference value preset for each object to be photographed through the correction image generation process (170b).

[0079] To this end, the correction image generation unit (140) can reduce the capacity of the original image by storing a preset correction algorithm and performing steps S171b to S174b based on the correction algorithm.

[0080] In step S180, the medical image data management system (100) transmits the corrected image generated in step S170 to the in-hospital storage device (420), and in step S190, the in-hospital storage device (420) stores the corrected image.

[0081] In this way, medical image data that is stored separately in the original image management DB (110) or cloud storage device (200) and the in-hospital storage device (420) in an optimized state according to its utilization can be accessed by the in-hospital terminal device (430) or specialized diagnostic equipment (500) and used according to its intended purpose. Examples of this processing process are illustrated in FIGS. 7 and 8.

[0082] FIG. 7 is a diagram illustrating an example of a hospital terminal device (430) utilizing medical data stored in a hospital storage device (420) or a cloud storage device (200). Referring to FIG. 7, first, in step S205, the hospital terminal device (430) requests a correction image from the hospital storage device (420). At this time, the hospital terminal device (430) may input the patient code of the patient to be treated or examined and transmit it together when requesting the correction image.

[0083] Then, in steps S210 and S215, the hospital storage device (420) searches for medical image data (i.e., corrected image) stored therein using the patient code as a keyword, and then transmits the corrected image corresponding to the patient code to the hospital terminal device (430).

[0084] In step S220, the hospital terminal device (430) stores the correction image detected from the hospital storage device (420) in its internal memory or displays it on the screen. At this time, since the capacity of the correction image has been reduced through step S170, in step S205, the load on the hospital system (400) resources can be reduced in all processes for searching, transmitting, loading, and displaying the requested correction data, and the requested medical image data can be displayed on the hospital terminal device (430) at a high speed.

[0085] Meanwhile, when there is a request from medical staff who need the original image of specific medical image data for research or artificial intelligence learning, etc., the terminal device (430) within the hospital can access the medical image data management system (100) and request the original image, and the processing process is exemplified in steps S225 to S275.

[0086] That is, in step S225, the hospital terminal device (430) requests the original image from the medical image data management system (100). At this time, the hospital terminal device (430) may also transmit the image identification code of the original image required for research or artificial intelligence learning.

[0087] Then, in steps S230 and S235, the medical image data management system (100) searches for medical image data (i.e., original images) stored in the cloud storage device (200) using the image identification code as a keyword, and then detects the original image corresponding to the image identification code and transmits it to the hospital terminal device (430). At this time, the medical image data management system (100) and the hospital terminal device (430) are connected via a communication network, so that in step S235, the download time of the original image can be determined according to the communication quality or speed. In addition, since the original image has a relatively large capacity compared to the corrected image, the download time may take longer than the transmission time of the corrected image loaded via the internal network.

[0088] In steps S240 to S250, it is determined whether the original image has been forged / altered based on information stored in the blockchain server (300).

[0089] That is, in step S240, the hospital terminal device (430) that received the original image requests the blockchain server (300) to verify the original image, and in steps S245 and S250, the blockchain server (300) verifies whether the original image has been forged or altered and then transmits the result.

[0090] In step S255, the hospital terminal device (430) that received the verification result for the original image determines whether forgery / alteration has occurred.

[0091] If the determination result of step S255 indicates that there is no forgery / alteration in the original image, then in step S260, the hospital terminal device (430) stores the original image in the internal memory or displays it on the screen. That is, the hospital terminal device (430) verifies whether the original image stored in the cloud storage device (200) has been forged / alterated, and only displays the results for which integrity has been verified.

[0092] Meanwhile, if it is determined in step S255 that the original image has been forged / altered, the hospital terminal device (430) transmits forgery / alteration information to the medical image data management system (100) in step S265, and outputs a forgery / alteration notification message in step S270.

[0093] In step S275, the medical image data management system (100) that received the forgery / alteration information deletes the forged / alterated original image. Alternatively, the medical image data management system (100) that received the forgery / alteration information may notify the administrator, thereby allowing the administrator to restore the data.

[0094] FIG. 8 is a drawing illustrating an example of a specialized diagnostic device (500) utilizing medical data stored in a cloud storage device (200). It exemplifies a processing procedure in which medical staff or researchers who require original images of specific medical image data for research or artificial intelligence learning, etc., access a medical image data management system (100) using specialized diagnostic equipment (500) and then request and receive the original images.

[0095] Referring to FIG. 8, first, in step S305, the specialized diagnostic equipment (500) requests an original image from the medical image data management system (100). At this time, the specialized diagnostic equipment (500) may input a separate keyword to request an original image required for research or artificial intelligence learning.

[0096] Then, in steps S310 and S315, the medical image data management system (100) searches for medical image data (i.e., original images) stored in the cloud storage device (200) using the above keywords, and then transmits the searched images to the specialized diagnostic equipment (500). At this time, the medical image data management system (100) and the specialized diagnostic equipment (500) are connected via a communication network, so that in step S315, the download time of the searched images can be determined according to the communication quality or speed.

[0097] In steps S320 to S330, it is determined whether the image received by the specialized diagnostic equipment (500) has been forged / modified based on the information stored in the blockchain server (300).

[0098] That is, in step S320, the specialized diagnostic equipment (500) that received the searched image requests the blockchain server (300) to verify the searched image, and in steps S325 and S330, the blockchain server (300) verifies whether the searched image has been forged or altered and then transmits the result.

[0099] In step S335, the specialized diagnostic equipment (500) that received the verification result for the searched image determines whether forgery / alteration occurred.

[0100] If the result of the judgment in step S335 indicates that there is no forgery / alteration in the searched image, then in step S340, the specialized diagnostic equipment (500) stores the searched image in the internal memory or displays it on the screen. That is, the specialized diagnostic equipment (500) verifies whether the original image stored in the cloud storage device (200) has been forged / alterated, and only displays the results for which integrity has been verified.

[0101] Meanwhile, if it is determined in step S335 that the original image has been forged / altered, the specialized diagnostic equipment (500) transmits forgery / alteration information to the medical image data management system (100) in step S345, and outputs a forgery / alteration notification message in step S350.

[0102] In step S355, the medical image data management system (100) that received the forgery / alteration information deletes the forged / alteration original image. Alternatively, the medical image data management system (100) that received the forgery / alteration information may notify the administrator, thereby allowing the administrator to restore the data.

[0103] In this way, the medical image data management system and method of the present invention correct medical image data received from any photographing device according to a predetermined standard, and then separate and store the original image and the corrected image in an optimized state according to their usability, thereby enabling more efficient construction of a medical treatment environment and a research environment in the field of medical technology.

[0104] In addition, the present invention has a feature that enables efficient use of computer resources within a hospital by performing correction to down-convert the capacity of medical image data and then transmitting the corrected image to a storage device within a hospital, thereby saving storage space within the storage device within the hospital.

[0105] In addition, the present invention has the feature of enabling a doctor to quickly process data for searching and loading necessary image data by referring to the corrected image stored in a storage device within a hospital when diagnosing a patient or checking the patient's symptoms, thereby enabling an efficient treatment environment to be established.

[0106] In addition, the present invention has a feature that enables effective management of a large amount of original images at low cost by storing high-resolution original images of the medical image data in a cloud storage device and providing information corresponding to a request from an expert in a specific field who requires the original images.

[0107] In addition, the present invention has a feature that enables the safe management of the original image by storing verification information for verifying whether the original image of medical image data stored in a cloud storage device has been falsified or altered in a blockchain server.

[0108] Although the embodiments of the present invention have been described above, the scope of the present invention is not limited thereto, and the present invention includes all changes and modifications that can be easily modified by a person having ordinary skill in the art to which the present invention pertains from the embodiments and are recognized as equivalent.

[0109] [Explanation of symbols]

[0110] 10: Communications Network 100: Medical Image Data Management System

[0111] 110: Original image management DB 120: User I / F

[0112] 130: Image data receiving unit 140: Correction image generating unit

[0113] 150: Correction image transmission unit 160: Blockchain server I / F

[0114] 170: Control unit 200: Cloud storage device

[0115] 300: Blockchain server 400: Hospital system

[0116] 410: Camera 420: Hospital storage device

[0117] 430: Hospital terminal device 500: Professional diagnostic device

Claims

1. An image data receiving unit that receives medical image data captured by at least one photographing device; An original image storage unit that stores the original image of the above medical image data; A correction image generation unit that generates a correction image by reducing the capacity of the above medical image data; and Including a correction image transmission unit that transmits the above correction image to a storage device within a designated hospital, The above correction image generation unit Pre-save the second resolution change reference value set in advance for each target object, After analyzing the original image of the medical image data received above and automatically recognizing the target object, A medical image data management system characterized in that the capacity of the medical image data is reduced by down-converting the resolution of the medical image data based on a second resolution change reference value corresponding to the automatically recognized object.

2. A medical image data management system characterized in that, in the first paragraph, the image data receiving unit provides a communication interface with the photographing devices and receives the medical image data in real time from the photographing devices via wired / wireless communication.

3. A medical image data management system, characterized in that the original image storage unit in the first paragraph is implemented as a cloud storage device.

4. In paragraph 1, A blockchain server interface unit that provides a communication interface with an external blockchain server via wired / wireless communication; and A medical image data management system further comprising a control unit that controls the blockchain server interface unit to store verification information for monitoring forgery / alteration of the original image in the blockchain server.

5. A method for managing medical image data using a medical image data management system that receives and manages medical image data from a remote location, The above medical image data management system includes an image correction information storage step for storing image correction information for optimizing and storing the above medical image data; The above medical image data management system comprises an image data receiving step for receiving medical image data captured by at least one photographing device; The above medical image data management system comprises an original image storage step for storing the original image of the above medical image data; The above medical image data management system generates a correction image by reducing the capacity of the medical image data; The above medical image data management system, a correction image transmission step in which the correction image is transmitted to a storage device within a designated hospital; and The above-mentioned hospital storage device includes a correction image storage step for storing the correction image, The above image correction information storage step is Save the second resolution change reference value preset for each target object, The above correction image generation step is, An object recognition step for automatically recognizing an object to be photographed by analyzing the original image of the medical image data received in the above image data receiving step; A medical image data management method characterized in that the capacity of the medical image data is reduced by down-converting the resolution of the medical image data based on a second resolution change reference value corresponding to the automatically recognized object.

6. In the fifth paragraph, the image data receiving step, A medical image data management method characterized by receiving the medical image data in real time by communicating with the above photographing devices via wired / wireless communication.

7. In paragraph 5, the original image storage step is: A medical image data management method characterized by storing the original image in a cloud storage device connected to the medical image data management system through a communication network.

8. In paragraph 5, The above medical image data management system includes a verification information generation step for generating verification information to monitor forgery / alteration of the original image; and A medical image data management method characterized in that the medical image data management system further includes a verification information storage step of communicating with an external blockchain server via wired / wireless communication to store the verification information in the blockchain server.

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