Medical image distributed management method, system, equipment and medium

Abstract

The invention provides a medical image distributed management method, system, device and medium, and belongs to the technical field of data management, the method comprises the following steps: a local storage module collects and processes an original medical image, encrypts the processed medical image to obtain an encrypted file, and stores the encrypted file; uploading the encrypted file to a cloud storage module, and triggering a block chain network module at the same time to store the encrypted file; a user performs identity authentication through the access control module and authorizes a data access request; and after the data access request is authorized, the smart contract judges the permission, and after the smart contract judges the permission, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until a target encrypted file is obtained. And the encrypted file is uploaded to the cloud storage module, data storage is realized by means of mass cloud storage, and the data security is greatly enhanced by means of the tamper-proof characteristic of the block chain technology.

Description

Technical Field

[0001] The present invention belongs to the technical field of data management, and in particular relates to a medical image distributed management method, system, device and medium. Background Art

[0002] The trend of integration between the medical industry and information technology Under the current wave of digitalization, information technology and the medical industry are intertwined with each other at an unprecedented level. On the one hand, various cutting-edge information technologies are booming, and emerging technologies such as big data, cloud computing, and blockchain are constantly innovating the mode of data processing and information flow; on the other hand, the medical industry continues to rely more on information technology to meet the growing needs of precision diagnosis, telemedicine and other diversified needs. The deep integration of the two has become the core driving force for the advanced development of modern medical services, giving rise to a series of information technology reforms aimed at optimizing medical processes and improving service quality.

[0003] The informatization of medical imaging is crucial in the grand blueprint of medical informatization, and the field of medical imaging undoubtedly occupies a pivotal and key position. With the rapid development of medical examination technology, advanced examination methods such as CT with high-resolution imaging capabilities and MRI that can accurately present soft tissue details have been widely popularized in clinical practice. While these examination equipment provide high-definition and accurate imaging basis for disease diagnosis, they also generate massive amounts of medical imaging data at an unprecedented speed. These imaging data not only carry intuitive information about the patient's physical condition, but are also the cornerstone of subsequent diagnosis, treatment plan formulation and even medical research. Its importance is self-evident.

[0004] Currently, medical imaging data is stored, transmitted and managed using PACS (Picture Archiving and Communication Systems). However, the existing PACS system faces many challenges: Large data volume: Medical imaging data is huge and complex. Traditional NAS, DAS, and SAN storage models are costly and difficult to expand.

[0005] Insufficient security: Data is vulnerable to attacks during transmission, resulting in information leakage or tampering.

[0006] To this end, the present invention provides a medical image distributed management method, system, device and medium. Summary of the invention

[0007] The present invention provides a medical image distributed management method, system, device and medium, so as to at least solve the problems of large data volume and insufficient security faced by the PACS system in the prior art.

[0008] In a first aspect, an embodiment of the present application provides a medical image distributed management method, the distributed management method comprising: Step S1: The local storage module collects and processes the original medical images, encrypts the processed medical images to obtain encrypted files, and stores the encrypted files; Step S2: Upload the encrypted file to the cloud storage module, and trigger the blockchain network module to store the encrypted file; Step S3: The user performs identity authentication through the access control module and authorizes the data access request; Step S4: After the data access request is authorized, the smart contract determines the authority. After the smart contract determines the authority, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until the target encrypted file is obtained.

[0009] Furthermore, the local storage module uses a lightweight storage node to store encrypted files whose access frequency exceeds a preset value within 3 months, wherein the lightweight storage node is a NAS device; The cloud storage module adopts a distributed architecture, stores encrypted files in pieces on several nodes, and allocates encrypted file locations through a consistent hashing algorithm. The distributed architecture is FastDFS.

[0010] Furthermore, the cloud storage module performs standardization processing on the encrypted files, extracts feature values, and stores and transmits the results back.

[0011] Furthermore, the encrypted files are standardized, and encrypted files of different formats are converted into a unified format; Extract feature values ​​from encrypted files, automatically identify lesion areas in encrypted files, and generate structured reports for the identified lesion areas; The encrypted files are stored and transmitted back, and the generated structured reports are associated with the original medical images.

[0012] Furthermore, processing data evidence includes: Generate a unique hash value for the encrypted file through a hash algorithm; The generated hash value and related operation logs are packaged into a transaction and stored on the blockchain. The related operation logs include: timestamp, operator, and operation type; After the evidence transaction is stored in the blockchain, it is verified through the blockchain's consensus mechanism.

[0013] Furthermore, the smart contract defines the access rights to the encrypted file, wherein the access rights include accessing the encrypted file and modifying the encrypted file; When a user initiates a request to obtain an encrypted file, the smart contract is called to perform logical judgment and verify the user's access rights; If the access permission is verified, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until the target encrypted file is obtained, which is then decrypted and sent to the user.

[0014] Furthermore, the method also includes: connecting to the hospital's information system through the GNUHealth module to obtain original medical images.

[0015] In a second aspect, the embodiments of the present application further provide a distributed management system applied to the medical image distributed management method as described in the above aspects, the distributed management system comprising: A local storage module is used to collect and process original medical images, encrypt the processed medical images to obtain encrypted files, and store the encrypted files; A cloud storage module, used to record the characteristic values ​​of encrypted files using blockchain and store the encrypted files; The blockchain network module is used to process data evidence and execute smart contracts. Data evidence is used to record hash values ​​and operation logs, and smart contracts are used to control permissions. The access control module is used to authenticate identities through blockchain and dynamically authorize data access requests.

[0016] In a third aspect, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the medical image distributed management method as described in the above aspects are implemented.

[0017] In a fourth aspect, a storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the medical image distributed management method as described in the above aspects are implemented.

[0018] It can be seen from the above technical solutions that the present invention has the following advantages: In the medical image distributed management method provided in this application, the local storage module is responsible for collecting and preliminarily processing the original medical images, and uploading the encrypted files to the cloud storage module. With the massive and easy-to-expand characteristics of cloud storage, it can cope with the problem of huge and continuously growing amounts of medical image data, breaking the bottleneck of high cost and limited expansion of traditional NAS, DAS, and SAN storage models.

[0019] With the help of the tamper-proof characteristics of blockchain technology, data security is greatly enhanced; compared with traditional centralized servers, the distributed architecture can significantly reduce hardware investment and maintenance costs; it supports medical image files in multiple formats and is easy to integrate with other existing systems; the entire process of each image material from generation to use is fully recorded to facilitate subsequent review and supervision.

[0020] The combination of local and cloud storage makes the data storage architecture more reasonable. Local storage serves as a front-end buffer to ensure the fast reading and writing of daily high-frequency data; cloud storage serves as a back-end support, taking on the tasks of long-term archiving and large-scale data backup. The two work together to meet the current massive storage needs of medical imaging data and ensure that the process of medical informatization will not be hindered by storage problems.

[0021] The processed medical images are encrypted during the local storage stage to ensure that the data exists in ciphertext form from the source. Even if the local device is physically invaded or attacked by malware, the attacker will not be able to decipher the medical image content without the decryption key, effectively preventing the risk of data leakage and safeguarding the security of medical data.

[0022] When data is uploaded to cloud storage, the blockchain network module is triggered to store the data. The decentralized and tamper-proof characteristics of blockchain are used to record reliable ledger information for each data operation. No matter whether it is uploading, accessing or modifying key nodes, there are clear and tamper-proof records. Once a data security problem occurs, it can be quickly traced back and the source of the problem can be accurately located, providing a solid security shield for the entire life cycle management of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0024] Figure 1 The figure is a flowchart of a distributed management method for medical images. DETAILED DESCRIPTION

[0025] Various embodiments of the present disclosure will be described more fully in the following detailed description of the medical image distributed management method, system, device and medium. The present disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, but rather the present disclosure should be understood to cover all adjustments, equivalents and / or alternatives that fall within the spirit and scope of the various embodiments of the present disclosure.

[0026] Hereinafter, the terms "include" or "may include" used in various embodiments of the present disclosure indicate the presence of disclosed functions, operations, or elements, and do not limit the addition of one or more functions, operations, or elements. In addition, as used in various embodiments of the present disclosure, the terms "include", "have", and their cognates are intended only to indicate specific features, numbers, steps, operations, elements, components, or a combination of the foregoing, and should not be understood as first excluding the presence of one or more other features, numbers, steps, operations, elements, components, or a combination of the foregoing or the possibility of adding one or more features, numbers, steps, operations, elements, components, or a combination of the foregoing.

[0027] The expressions (such as "first", "second", etc.) used in the various embodiments of the present disclosure may modify the various constituent elements in the various embodiments, but may not limit the corresponding constituent elements. For example, the above expressions do not limit the order and / or importance of the elements. The above expressions are only used for the purpose of distinguishing one element from other elements. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, without departing from the scope of the various embodiments of the present disclosure, the first element may be referred to as the second element, and similarly, the second element may also be referred to as the first element.

[0028] The term “user” used in various embodiments of the present disclosure may indicate a person who uses an electronic device, and may be a monitoring person, a test person, or an operator.

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The embodiments of the present application provide a medical image distributed management method, system, device and medium to solve the technical problems of large data volume and insufficient security faced by the current PACS system.

[0031] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0032] Figure 1 This is a flow chart of a medical image distributed management method provided in an embodiment of the present application. Figure 1 As shown, a medical image distributed management method provided in an embodiment of the present application specifically includes the following steps: Step S1: The local storage module collects and processes the original medical image, encrypts the processed medical image, obtains an encrypted file, and stores the encrypted file. It should be noted that the encrypted file is the medical image obtained after encryption.

[0033] Step S2: Upload the encrypted file to the cloud storage module and trigger the blockchain network module to store the encrypted file.

[0034] The cloud storage module performs standardization processing on encrypted files, extracts feature values, and stores and transmits the results back.

[0035] Standardize the encrypted files and convert encrypted files of different formats into a unified format.

[0036] The encrypted file extracted from the local storage module is converted into a unified DICOM format using a DICOM conversion tool, and the converted encrypted file is uploaded to the cloud storage module through the API interface of the cloud storage module. It should be noted that the DICOM file contains a file header, a data set, and image data.

[0037] The file header is the prefix part of the DICOM file, which contains basic information of the file, such as file format and transfer syntax (encoding method). The main function of the file header is to help the parser identify the format and content of the file.

[0038] The data set is the core part of the DICOM file, which contains the actual data of the medical image and related metadata. Metadata is the key information that describes the medical image, including: Patient information: name, gender, age, patient ID; Imaging equipment information: equipment manufacturer, equipment model, scanning parameters; Image properties: image size, pixel pitch, bit depth, image sequence; Clinical information: examination date, examination type, diagnostic report.

[0039] Image data is the actual image content stored in a DICOM file, usually represented in the form of a two-dimensional or three-dimensional matrix. The pixel data can be a grayscale image (such as X-ray, CT), a color image (such as ultrasound), or more complex multidimensional data (such as MRI sequences).

[0040] DICOM is an international standard that ensures seamless exchange and sharing of medical imaging data between different storage devices. This standardization allows files generated by imaging devices (such as CT, MRI, and ultrasound) to be used in different storage terminals.

[0041] Taking the DICOM file of CT images as an example, its file structure is as follows: File header: Contains file format and encoding information.

[0042] Metadata: Patient name: ###; Patient ID: 123456; Examination date: 2025-03-06; Device model: GECTScanner; Image size: 512×512 pixels; Pixel pitch: 0.5mm×0.5mm.

[0043] Image data: a 512×512 grayscale image matrix, each pixel value represents the CT value.

[0044] The encrypted file is subjected to feature value extraction, the lesion area in the encrypted file is automatically identified, and a structured report is generated for the identified lesion area.

[0045] By extracting texture features and shape features of medical images, the identification and quantitative analysis of lesion areas can be achieved. For example, the Radiomics tool is used to extract omics features from DICOM images. The DICOMSR (Structure Report) standard is used to generate structured reports, which supports associating text and data with key images to form reports with both pictures and text. The Bi-LSTM+CRF model is used to extract text feature labels, and mapping rules are designed to generate structured reports.

[0046] The encrypted files are stored and transmitted back, and the generated structured reports are associated with the original medical images.

[0047] The structured report is stored in the cloud storage module and associated with the original medical image through metadata. In this embodiment, the metadata (patient ID, examination date) in the DICOM file is used as the association key. The association key is used for data retrieval and management to ensure the integrity and traceability of the medical image.

[0048] The local storage module uses a lightweight storage node to store encrypted files whose access frequency exceeds a preset value within 3 months, wherein the lightweight storage node is a NAS device.

[0049] The cloud storage module adopts a distributed architecture, stores encrypted files in pieces on several nodes, and allocates encrypted file locations through a consistent hashing algorithm. The distributed architecture is FastDFS.

[0050] The local storage module serves as a cache layer, and the cloud storage module serves as a permanent storage repository. When obtaining a target encrypted file, the target encrypted file in the local storage module is accessed first. If the local storage module has been cleared, the cloud storage module is accessed to obtain the encrypted file from the cloud storage module.

[0051] Reduce FastDFS access latency by caching encrypted files with access frequencies exceeding a preset value in Redis. Use the LRU (least recently used) algorithm to cache encrypted files with access frequencies exceeding a preset value in Redis. Set a cache expiration time (24 hours) and automatically reload from FastDFS after a timeout. Deploy a Redis cluster to support cross-node data synchronization and failover.

[0052] The local storage module is responsible for collecting and preliminarily processing original medical images, and uploading the encrypted files to the cloud storage module. With the massive and easy-to-expand features of cloud storage, it can cope with the problem of huge and continuously growing amounts of medical imaging data, breaking the bottleneck of high costs and limited expansion of traditional NAS, DAS, and SAN storage models.

[0053] The combination of local and cloud storage makes the data storage architecture more reasonable. Local storage serves as a front-end buffer to ensure the fast reading and writing of daily high-frequency data; cloud storage serves as a back-end support, taking on the tasks of long-term archiving and large-scale data backup. The two work together to meet the current massive storage needs of medical imaging data and ensure that the process of medical informatization will not be hindered by storage problems.

[0054] The processed medical images are encrypted during the local storage stage to ensure that the data exists in ciphertext form from the source. Even if the local device is physically invaded or attacked by malware, the attacker will not be able to decipher the medical image content without the decryption key, effectively preventing the risk of data leakage and safeguarding the security of medical data.

[0055] It should be noted that processing data evidence refers to using blockchain technology to store and verify data to ensure that the data cannot be tampered with, is traceable and authentic.

[0056] When data is uploaded to cloud storage, the blockchain network module is triggered to store the data. The decentralized and tamper-proof characteristics of blockchain are used to record reliable ledger information for each data operation. No matter whether it is uploading, accessing or modifying key nodes, there are clear and tamper-proof records. Once a data security problem occurs, it can be quickly traced back and the source of the problem can be accurately located, providing a solid security shield for the entire life cycle management of data.

[0057] Step S3: The user authenticates the identity through the access control module and authorizes the data access request. The user access control module uses blockchain to authenticate the identity and strictly verify the legitimacy of each visitor's identity, preventing illegal users from using fake identities to access medical imaging data, ensuring that only authorized medical staff, scientific researchers or patients themselves (under the conditions that meet the regulations) can access the relevant images, and further strengthen privacy protection from the access entrance.

[0058] Processing data evidence includes: Step S31: Generate a unique hash value from the encrypted file through a hash algorithm; the hash value is the digital fingerprint of the data and can uniquely identify the content of the data. Once the data is tampered with, the hash value will change, so that the integrity of the data can be detected.

[0059] Step S32: Package the generated hash value and related operation logs into a transaction and store them on the blockchain, where the related operation logs include: timestamp, operator, and operation type; each block contains the hash value of the previous block. This chain structure ensures that the data cannot be tampered with.

[0060] Step S33: After the evidence transaction is stored in the blockchain, it is verified through the consensus mechanism of the blockchain. Once the verification is passed, the evidence of the data is recognized as valid. The decentralized nature of the blockchain makes data storage more secure, and any node can verify the authenticity of the data. Due to the immutable and traceable characteristics of the blockchain, the evidence data can be quickly retrieved and verified. Through the records on the blockchain, the source and flow path of the data can be traced to ensure the authenticity and integrity of the data.

[0061] It should be noted that the smart contract defines the access rights to encrypted files, where the access rights include accessing encrypted files and modifying encrypted files.

[0062] When a user initiates a request to obtain an encrypted file, the smart contract is called to perform logical judgment and verify the user's access rights.

[0063] If the access permission is verified, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until the target encrypted file is obtained, which is then decrypted and sent to the user.

[0064] Step S4: After the data access request is authorized, the smart contract determines the authority. After the smart contract determines the authority, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until the target encrypted file is obtained.

[0065] The method further includes: connecting to the hospital's information system through the GNUHealth module to obtain original medical images.

[0066] To further ensure the reliability of data transmission, the TLS / SSL protocol is used to protect the transmission of encrypted files between the client and the cloud. Asymmetric encryption (RSA) is used to authenticate and digitally sign users to protect the content of encrypted files. The private key is held by the authorized owner. A complete user identity authentication mechanism is established based on the blockchain, including doctors, researchers, and patients, to ensure that only authorized people can view specific information. User information is stored on the chain, and based on the RBAC model, role permissions (such as read / write / share) are defined through smart contracts. For example, "Radiology & Deputy Chief Physician" can access CT raw data. The client calls the on-chain API to verify the user's digital signature, ensure the authenticity of the identity, and read the permission list.

[0067] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, storage and other aspects of medical images involved in the technical solution disclosed in this application comply with the provisions of relevant laws and regulations, are used for legal purposes and do not violate public order and good morals, and necessary measures are taken to prevent the illegal use of medical images to maintain medical image security, network security and national security.

[0068] The present invention also provides a medical image distributed management system, which includes: a local storage module, a cloud storage module, a blockchain network module and an access control module.

[0069] The local storage module is used to collect and process original medical images, encrypt the processed medical images to obtain encrypted files, and store the encrypted files; it should be noted that the encrypted files are the medical images obtained after encryption processing.

[0070] The cloud storage module is used to record the characteristic values ​​of encrypted files using blockchain and store encrypted files.

[0071] The blockchain network module is used to process data evidence and execute smart contracts, where data evidence is used to record hash values ​​and operation logs, and smart contracts are used to control permissions.

[0072] The access control module is used to perform identity authentication through blockchain and dynamically authorize data access requests.

[0073] The medical image distributed management method provided in the embodiment of the present application can be applied to electronic devices. Those skilled in the art will appreciate that the electronic device structure involved in the embodiment of the present invention does not constitute a limitation on the electronic device, and the electronic device may include more or less components than shown, or combine certain components, or arrange different components. In an embodiment of the present invention, the electronic device includes but is not limited to a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples, and are not intended to limit the implementation of the embodiments of the present application described and / or required herein.

[0074] The electronic device may include a processor, an external memory interface, an internal memory, a universal serial bus (USB) interface, a charging management module, a power management module, a battery, a wireless communication module, an audio module, a speaker, a microphone, a sensor module, buttons, a camera, a display, and a SIM card interface, etc.

[0075] The above-mentioned electronic device implements the local storage module of the medical image distributed management method of the present application to collect and process the original medical images, encrypt the processed medical images to obtain encrypted files, and store the encrypted files; upload the encrypted files to the cloud storage module, and trigger the blockchain network module at the same time to store the encrypted files; the user performs identity authentication through the access control module and authorizes the data access request; after the data access request is authorized, the smart contract determines the authority, and after the smart contract determines the authority, the encrypted files stored in the local storage module and the cloud storage module are accessed in turn until the target encrypted file is obtained. The local storage module is responsible for collecting and preliminarily processing the original medical images, and uploading the encrypted files to the cloud storage module. With the massive and easy-to-expand characteristics of cloud storage, it can cope with the problem of huge and continuously growing medical image data, breaking the bottleneck of high cost and limited expansion of traditional NAS, DAS, and SAN storage modes. With the help of the tamper-proof characteristics of blockchain technology, data security is greatly enhanced; compared with traditional centralized servers, the distributed architecture can significantly reduce hardware investment and maintenance costs; it supports medical image files in multiple formats and is easy to integrate with other existing systems; the entire process of each image material from generation to use is fully recorded to facilitate subsequent review and supervision.

[0076] The storage medium provided in the present application stores a program product that can implement a medical image distributed management method and system.

[0077] The distributed management method of medical images includes: a local storage module collects and processes original medical images, encrypts the processed medical images to obtain encrypted files, and stores the encrypted files; the encrypted files are uploaded to a cloud storage module, and a blockchain network module is triggered at the same time to store the encrypted files; the user performs identity authentication through an access control module and authorizes a data access request; after the data access request is authorized, the smart contract determines the authority, and after the smart contract determines the authority, the encrypted files stored in the local storage module and the cloud storage module are accessed in turn until the target encrypted file is obtained.

[0078] The combination of local and cloud storage makes the data storage architecture more reasonable. Local storage serves as a front-end buffer to ensure the fast reading and writing of daily high-frequency data; cloud storage serves as a back-end support, taking on the tasks of long-term archiving and large-scale data backup. The two work together to meet the current massive storage needs of medical imaging data and ensure that the process of medical informatization will not be hindered by storage problems.

[0079] The processed medical images are encrypted during the local storage stage to ensure that the data exists in ciphertext form from the source. Even if the local device is physically invaded or attacked by malware, the attacker will not be able to decipher the medical image content without the decryption key, effectively preventing the risk of data leakage and safeguarding the security of medical data.

[0080] When data is uploaded to cloud storage, the blockchain network module is triggered to store the data. The decentralized and tamper-proof characteristics of blockchain are used to record reliable ledger information for each data operation. No matter whether it is uploading, accessing or modifying key nodes, there are clear and tamper-proof records. Once a data security problem occurs, it can be quickly traced back and the source of the problem can be accurately located, providing a solid security shield for the entire life cycle management of data.

[0081] In some possible implementations, the medical image distributed management method disclosed herein can be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps described in the above "Exemplary Method" section of this specification according to various exemplary implementations of the present disclosure.

[0082] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0083] For those skilled in the art, designing different forms of control circuits according to the teachings of the present invention does not require creative work. These changes, modifications, substitutions and variations of the embodiments without departing from the principles and spirit of the present invention still fall within the scope of protection of the present invention.

Claims

1. A medical image distributed management method, characterized in that: The distributed management method comprises: Step S1: The local storage module collects and processes the original medical images, encrypts the processed medical images to obtain encrypted files, and stores the encrypted files; Step S2: Upload the encrypted file to the cloud storage module, and trigger the blockchain network module to store the encrypted file; Step S3: The user performs identity authentication through the access control module and authorizes the data access request; Step S4: After the data access request is authorized, the smart contract determines the authority. After the smart contract determines the authority, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until the target encrypted file is obtained.

2. The medical image distributed management method according to claim 1, characterized in that: The local storage module uses lightweight storage nodes to store encrypted files whose access frequency exceeds the preset value within 3 months. The lightweight storage nodes are NAS devices. The cloud storage module adopts a distributed architecture, stores encrypted files in pieces on several nodes, and allocates encrypted file locations through a consistent hashing algorithm. The distributed architecture is FastDFS.

3. The medical image distributed management method according to claim 2, characterized in that: The cloud storage module performs standardization processing on encrypted files, extracts feature values, and stores and transmits the results back.

4. The medical image distributed management method according to claim 3, characterized in that: Standardize the encrypted files and convert the encrypted files of different formats into a unified format; Extract feature values ​​from encrypted files, automatically identify lesion areas in encrypted files, and generate structured reports for the identified lesion areas; The encrypted files are stored and transmitted back, and the generated structured reports are associated with the original medical images.

5. The medical image distributed management method according to claim 4, characterized in that: Processing data evidence includes: Generate a unique hash value for the encrypted file through a hash algorithm; The generated hash value and related operation logs are packaged into a transaction and stored on the blockchain. The related operation logs include: timestamp, operator, and operation type; After the evidence transaction is stored in the blockchain, it is verified through the blockchain's consensus mechanism.

6. The medical image distributed management method according to claim 5, characterized in that: Smart contracts define the access rights to encrypted files, including accessing and modifying encrypted files. When a user initiates a request to obtain an encrypted file, the smart contract is called to perform logical judgment and verify the user's access rights; If the access permission is verified, the encrypted files stored in the local storage module and the cloud storage module are accessed in sequence until the target encrypted file is obtained, which is then decrypted and sent to the user.

7. The medical image distributed management method according to claim 6, characterized in that: The method further includes: connecting to the hospital's information system through the GNUHealth module to obtain original medical images.

8. A distributed management system applied to the medical image distributed management method according to any one of claims 1 to 7, characterized in that: The distributed management system comprises: A local storage module is used to collect and process original medical images, encrypt the processed medical images to obtain encrypted files, and store the encrypted files; A cloud storage module, used to record the characteristic values ​​of encrypted files using blockchain and store the encrypted files; The blockchain network module is used to process data evidence and execute smart contracts. Data evidence is used to record hash values ​​and operation logs, and smart contracts are used to control permissions. The access control module is used to authenticate identities through blockchain and dynamically authorize data access requests.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the medical image distributed management method as described in any one of claims 1-7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the medical image distributed management method as described in any one of claims 1 to 7 are implemented.

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