CN116415298A - Medical data desensitization method and system - Google Patents
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Abstract
The present application relates to a method and system for desensitizing medical data, wherein the method comprises: acquiring image data of a patient, preprocessing the image data, and storing the image data into a database; the method comprises the steps of carrying out structural analysis on file data under a data catalog to be desensitized based on a medical image desensitization model of an artificial intelligence technology to obtain metadata information of image content and metadata information of text content; according to the metadata information of the image content, positioning privacy features in the image content through a medical image desensitization model, and carrying out desensitization treatment on the privacy features; according to metadata information of text contents, text sensitive information in the text contents is positioned through a medical image desensitization model, and desensitization processing is carried out on the text sensitive information, so that the problem of how to carry out safety protection on the sensitive information in electronic medical data is solved, complete desensitization on images, texts, file names and file levels under a file directory is realized, and batch desensitization is supported.
Description
Technical Field
The present application relates to the field of computer technology, and in particular, to a method and system for desensitizing medical data.
Background
Along with the continuous development of big data and artificial intelligence, data sharing and data analysis make medical privacy more transparent, and the data demand of scientific research of being convenient for, but simultaneously, the personal privacy disclosure problem that causes also exposes gradually. In recent years, some expert and scholars research the privacy protection of medical information, divide the information into sensitive level information according to the severity of patient's illness, and achieve the purpose of privacy protection by limiting the frequency of occurrence of the sensitive level information, but some sensitive information still exists, how to safely protect the sensitive information in electronic medical data so as to reduce the risk of personal information data leakage is a problem which needs to be solved currently.
At present, no effective solution is proposed for the problem of how to secure the sensitive information in the electronic medical data in the related art.
Disclosure of Invention
The embodiment of the application provides a medical data desensitizing method and a medical data desensitizing system, which at least solve the problem of how to safely protect sensitive information in electronic medical data in the related technology.
In a first aspect, embodiments of the present application provide a method of desensitizing medical data, the method comprising:
acquiring image data of a patient, preprocessing the image data, and storing the image data into a database;
through a medical image desensitization model based on an artificial intelligence technology, carrying out structural analysis on file data under a data catalog to be desensitized to obtain metadata information of image content and metadata information of text content;
positioning privacy features in the image content through the medical image desensitization model according to the metadata information of the image content, and carrying out desensitization processing on the privacy features;
and positioning text sensitive information in the text content through the medical image desensitization model according to the metadata information of the text content, and carrying out desensitization processing on the text sensitive information.
In some embodiments, through a medical image desensitization model based on artificial intelligence technology, performing structural analysis on file data under a data catalog to be desensitized, and obtaining metadata information of image content includes:
extracting image features of image content in file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology, and carrying out structural processing on the image features to obtain metadata information of the image content, wherein the image features comprise position features, coordinate features and direction features.
In some embodiments, through a medical image desensitization model based on artificial intelligence technology, performing structural analysis on file data under a data catalog to be desensitized, and obtaining metadata information of text content includes:
extracting text information of text content in file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology, and carrying out structural processing on the text information to obtain metadata information of the text content, wherein the text information comprises name information, number information and birthday information.
In some of these embodiments, locating privacy features in the image content by the medical image desensitization model and desensitizing the privacy features comprises:
and positioning privacy features in the image content through the medical image desensitization model, hiding the privacy features by adopting a drawing function based on an image processing library, and storing desensitized file data into a database.
In some embodiments, locating text-sensitive information in text content by the medical image desensitization model and desensitizing the text-sensitive information includes:
and positioning text sensitive information in the text content through the medical image desensitization model, removing the text sensitive information by adopting a hash function, and storing the desensitized file data into a database.
In some of these embodiments, the method further comprises:
and developing a cross-platform system for the medical image desensitization model based on the artificial intelligence technology through an Electron programming framework, wherein the platform system comprises a Windows system, a MacOS system and a Linux system.
In some of these embodiments, the method further comprises:
developing the interactive interface of the medical image desensitization model based on the artificial intelligence technology through a preset front-end programming language, wherein the preset front-end programming language comprises a JavaScript programming language, an HTML5 programming language and a CSS programming language.
In some of these embodiments, the artificial intelligence technology based medical image desensitization model is an offline deployed lightweight model.
In some of these embodiments, acquiring image data of a patient, preprocessing the image data and storing the image data in a database includes:
and acquiring image data of the patient, performing data cleaning, data labeling and data grouping on the image data, and storing the image data into a database.
In a second aspect, embodiments of the present application provide a medical data desensitizing system, the system including a data acquisition module, a data extraction module, and a desensitizing processing module;
the data acquisition module is used for acquiring image data of a patient, preprocessing the image data and storing the preprocessed image data into a database;
the data extraction module is used for carrying out structural analysis on file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology to obtain metadata information of image content and metadata information of text content;
the desensitization processing module is used for positioning privacy features in the image content through the medical image desensitization model according to the metadata information of the image content and carrying out desensitization processing on the privacy features; and positioning text sensitive information in the text content through the medical image desensitization model according to the metadata information of the text content, and carrying out desensitization processing on the text sensitive information.
Compared with the related art, the medical data desensitizing method and system provided by the embodiment of the application at least solve the problem in the related art, wherein the method is characterized in that the image data of a patient is acquired, preprocessed and stored in a database; the method comprises the steps of carrying out structural analysis on file data under a data catalog to be desensitized based on a medical image desensitization model of an artificial intelligence technology to obtain metadata information of image content and metadata information of text content; according to the metadata information of the image content, positioning privacy features in the image content through a medical image desensitization model, and carrying out desensitization treatment on the privacy features; according to metadata information of text contents, text sensitive information in the text contents is positioned through a medical image desensitization model, and desensitization processing is carried out on the text sensitive information, so that the problem of how to safely protect the sensitive information in electronic medical data is solved, complete desensitization on images, texts, file names and file levels under the directory based on the file directory is realized, and batch desensitization is supported.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow chart of steps of a medical data desensitization method according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of desensitizing medical data in a real world scenario according to an embodiment of the present application;
FIG. 3 is a schematic illustration of a medical image in a post-desensitization catalog according to an embodiment of the present application;
FIG. 4 is a schematic illustration of medical text in a post-desensitized catalog according to an embodiment of the present application;
FIG. 5 is a block diagram of a medical data desensitization system according to an embodiment of the present application;
fig. 6 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application.
Reference numerals: 51. a data acquisition module; 52. a data extraction module; 53. and a desensitizing treatment module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described and illustrated below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden on the person of ordinary skill in the art based on the embodiments provided herein, are intended to be within the scope of the present application.
It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is possible for those of ordinary skill in the art to apply the present application to other similar situations according to these drawings without inventive effort. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the embodiments described herein can be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar terms herein do not denote a limitation of quantity, but rather denote the singular or plural. The terms "comprising," "including," "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "connected," "coupled," and the like in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as used herein refers to two or more. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., "a and/or B" may mean: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.
An embodiment of the present application provides a method for desensitizing medical data, and fig. 1 is a flowchart of steps of the method for desensitizing medical data provided according to an embodiment of the present application, as shown in fig. 1, where the method specifically includes the following steps:
step S102, obtaining image data of a patient, preprocessing the image data and storing the image data into a database;
in step S102, specifically, image data of the patient is acquired, and the image data is subjected to data cleaning, data labeling and data grouping and then stored in a database.
Step S102 is preferably mainly provided by the dermatology department of the beijing synergetic hospital in terms of data acquisition. Patient image data is collected retrospectively: and obtaining more than 3000 dermatological image pictures, 1000 clinical general pictures, 100 medical record shooting pictures, 100 ultrasonic pictures, 100 txt, doc and other format files, and 500 file catalogues. The Beijing co-ordination hospital dermatology team uses a desensitizing tool to hide the patient's name and groups the dermatology image pictures.
And after the data is acquired, carrying out data cleaning, labeling and grouping structuring treatment, encrypting and warehousing, and controlling authority.
The criteria for data cleansing included the inclusion and exclusion criteria, the inclusion criteria being as follows:
1) The picture or the file name is provided with patient information needing desensitization;
2) The picture size, PPI, color depth and format need to meet the requirements of table 1.
TABLE 1
| Picture type | Picture resolution | Picture PPI | Depth of color of picture | Picture format |
| Skin mirror | 1280 x 1024 and above | 1000PPI and above | 8-bit RGB and above | jpg/png |
| Clinical general | 2160 x 1080 or above | 72PPI and above | 8-bit RGB and above | jpg/png |
| Ultrasonic wave | 1024 x 576 and above | 120PPI and above | 8-bit RGB and above | jpg/png |
| Medical record | 2160 x 1080 or above | 72PPI and above | 8-bit RGB and above | jpg/png |
The exclusion criteria were as follows:
1) No sensitive information of the patient is seen on the picture or the file name;
2) A situation that cannot be recognized as a picture of the patient;
3) And other pictures which do not accord with the actual application scene.
Step S104, carrying out structural analysis on file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology to obtain metadata information of image content and metadata information of text content;
before step S104, the method further includes step S103:
through an Electron programming framework, a medical image desensitization model based on an artificial intelligence technology is developed in a cross-platform system, wherein the platform system comprises a Windows system, a MacOS system and a Linux system.
Developing an interactive interface of a medical image desensitization model based on an artificial intelligence technology through a preset front-end programming language, wherein the preset front-end programming language comprises a JavaScript programming language, an HTML5 programming language and a CSS programming language.
It should be noted that:
1) An Electron framework is employed to enable cross-operating system platform (Windows, macOS, linux) execution. The biggest problem of desktop end application is the compatibility of operating systems, different operating systems need to package different installation packages, and components required by the systems are correctly installed and registered to the systems through the installation packages, so that normal operation and use can be realized.
Such installation is inconvenient and is subject to compatibility problems in view of the actual use scenario in the department. In order to be convenient to use, safe and smooth to operate, an Electron framework is used for constructing a desktop-level application system of a high-performance and safe cross-operating system platform, and one-key operation is not required to be installed under Windows, macOS and Linux operating systems. The sandbox mechanism provided by the Electron is utilized, the problem that the running variables of different operating systems are dependent and compatible is solved, and meanwhile, the starting process sandboxed can further improve the running performance, efficiency, compatibility and safety of interfaces and interactions.
2) Interaction and interface design was performed through JavaScript, HTML and CSS. HTML5 and CSS are used as the most basic interface and layout design language, so that the dependency on the operating system platform can be eliminated, and the operation is efficient and universal. The interface content is divided into a system content presentation introduction part and a main function operation interaction part 2. The main functions include AI model loading, intelligent analysis, image and text desensitization and desensitization processing data reporting.
3) And (5) performing offline deployment application on the medical image desensitization model (AI model). Through the accumulation of long-term medical skin image artificial intelligence practices, AI models have been able to read, analyze, extract, and identify pixel-level image content information features in images for different skin image types. Since AI models are typically deployed on servers, the network environment via a wide area network or local area network utilizes TLS/SSL network protocols to interact with model deployment servers for data requests and model computation. Firstly, converting a model so as to meet the operation time requirement under the server-free and network-free environment; and secondly, model quantization compression is carried out on the premise of ensuring low recognition rate and throughput rate, so that the occupation consumption of resources such as CPU/GPU/memory and the like of a desktop computer in an offline environment is reduced, and the running and calculating efficiency is improved. Finally, the models are encrypted, packed and packaged, on one hand, a plurality of models are integrated together to form a model calculation module, and on the other hand, processing logic is invoked before and after alignment to enhance expansibility to cope with different use scenes.
Step S104 specifically:
extracting image features of image content in file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology, and carrying out structural processing on the image features to obtain metadata information of the image content, wherein the image features comprise position features, coordinate features and direction features.
And secondly, extracting text information of text content in file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology, and carrying out structural processing on the text information to obtain metadata information of the text content, wherein the text information comprises name information, number information and birthday information.
In step S104, preferably, fig. 2 is a flow chart of a medical data desensitizing method in a practical scenario according to an embodiment of the present application, and as shown in fig. 2, the desensitizing method mainly performs sensitive information batch processing on clinical gross images, skin mirror images, ultrasound images, medical records images, txt format files and other files.
And carrying out intelligent analysis processing on all files below the selected data directory to be desensitized, wherein the intelligent analysis processing is mainly divided into 3 parts. Firstly, loading an AI model by a system, and carrying out offline deployment processing such as packing, compression, encryption and the like on the AI model due to supporting an offline network-free scene; secondly, scanning files below the selected data directory to be desensitized, and inputting each file into an AI model for real-time analysis in the scanning process. The image under the desensitization data directory is used as unstructured data, and after analysis, part of image characteristics (such as position, coordinates, direction and the like) are converted into structured metadata information and stored in a memory. And taking the text under the data directory to be desensitized as unstructured data, adopting a text rule desensitization algorithm to carry out semantic analysis and feature extraction on text information such as names, IDs, birthdays and the like, converting the text information into structured metadata information, and storing the structured metadata information in a memory. The analysis result of each file is compressed and stored in the computer memory in the analysis process, so that the processing efficiency is improved;
step S106, positioning privacy features in the image content through a medical image desensitization model according to metadata information of the image content, and carrying out desensitization treatment on the privacy features;
in step S106, the privacy features in the image content are located through the medical image desensitization model, the privacy features are hidden by adopting a rendering function based on the image processing library, and the desensitized file data is stored in the database.
Step S106 is preferably based on the intelligent analysis result of step S104, the image is desensitized by combining the metadata information, firstly, the system reads the metadata information, and the structural construction of the image information is completed; secondly, using the structured metadata information to locate image privacy features (e.g., site-face, coordinate-eye); thirdly, extracting privacy characteristic information for processing, and finishing information hiding processing by using an image processing library drawing function; and finally, storing the desensitized image. Fig. 3 is a schematic illustration of medical images in a post-desensitization catalog according to an embodiment of the present application.
And S108, positioning text sensitive information in the text content through a medical image desensitization model according to metadata information of the text content, and carrying out desensitization processing on the text sensitive information.
In step S108, the text sensitive information in the text content is located through the medical image desensitization model, the text sensitive information is removed by adopting a hash function, and the desensitized file data is stored in the database.
Step S108 preferably reads feature analysis information based on the metadata information on the basis of the intelligent analysis of step S104 and the image desensitization of step S106, and locates the feature analysis information to the semantic packet array subscript; and finally, removing the text sensitive information by utilizing a hash function, and then storing the text sensitive information. Fig. 4 is a schematic illustration of medical text in a post-desensitization catalog according to an embodiment of the present application.
Through the steps S102 to S108 in the embodiment of the application, based on artificial intelligence and cross-platform technology, the sensitive information processing of clinical general images, skin mirror images, ultrasonic images, medical record shooting images, medical record txt and other format files with wider application range and larger number for dermatologists is successfully completed, and complete desensitization of images, texts, file names and file levels under the catalogue is realized starting from the catalogue of the files. And the batch desensitization is supported, and compared with the traditional manual operation, the efficiency is obviously improved. The method solves the problem of how to carry out safety protection on the sensitive information in the electronic medical data.
It should be noted that the steps illustrated in the above-described flow or flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.
The embodiment of the application provides a medical data desensitizing system, and fig. 5 is a structural block diagram of the medical data desensitizing system according to the embodiment of the application, and as shown in fig. 5, the system comprises a data acquisition module 51, a data extraction module 52 and a desensitizing processing module 53;
the data acquisition module 51 is configured to acquire image data of a patient, pre-process the image data, and store the image data in a database;
the data extraction module 52 is configured to perform structural analysis on file data under the data to be desensitized directory through a medical image desensitization model based on an artificial intelligence technology, so as to obtain metadata information of image content and metadata information of text content;
the desensitization processing module 53 is configured to locate privacy features in the image content through a medical image desensitization model according to metadata information of the image content, and perform desensitization processing on the privacy features; and positioning text sensitive information in the text content through a medical image desensitization model according to the metadata information of the text content, and carrying out desensitization processing on the text sensitive information.
Through the data acquisition module 51, the data extraction module 52 and the desensitization processing module 53 in the embodiment of the application, the problem of how to carry out safety protection on sensitive information in electronic medical data is solved, complete desensitization on images, texts, file names and file levels under the directory based on the file directory is realized, and batch desensitization is supported.
The above-described respective modules may be functional modules or program modules, and may be implemented by software or hardware. For modules implemented in hardware, the various modules described above may be located in the same processor; or the above modules may be located in different processors in any combination.
The present embodiment also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
It should be noted that, specific examples in this embodiment may refer to examples described in the foregoing embodiments and alternative implementations, and this embodiment is not repeated herein.
In addition, in combination with the medical data desensitizing method in the above embodiments, the embodiments of the present application may provide a storage medium to be implemented. The storage medium has a computer program stored thereon; the computer program, when executed by a processor, implements a medical data desensitization method of any of the above embodiments.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of desensitizing medical data. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
In one embodiment, fig. 6 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, and as shown in fig. 6, an electronic device is provided, which may be a server, and an internal structure diagram thereof may be as shown in fig. 6. The electronic device includes a processor, a network interface, an internal memory, and a non-volatile memory connected by an internal bus, where the non-volatile memory stores an operating system, computer programs, and a database. The processor is for providing computing and control capabilities, the network interface is for communicating with an external terminal via a network connection, the internal memory is for providing an environment for the operation of an operating system and a computer program which when executed by the processor implements a medical data desensitizing method, and the database is for storing data.
It will be appreciated by those skilled in the art that the structure shown in fig. 6 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the electronic device to which the present application is applied, and that a particular electronic device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be understood by those skilled in the art that the technical features of the above-described embodiments may be combined in any manner, and for brevity, all of the possible combinations of the technical features of the above-described embodiments are not described, however, they should be considered as being within the scope of the description provided herein, as long as there is no contradiction between the combinations of the technical features.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A method of desensitizing medical data, the method comprising:
acquiring image data of a patient, preprocessing the image data, and storing the image data into a database;
through a medical image desensitization model based on an artificial intelligence technology, carrying out structural analysis on file data under a data catalog to be desensitized to obtain metadata information of image content and metadata information of text content;
positioning privacy features in the image content through the medical image desensitization model according to the metadata information of the image content, and carrying out desensitization processing on the privacy features;
and positioning text sensitive information in the text content through the medical image desensitization model according to the metadata information of the text content, and carrying out desensitization processing on the text sensitive information.
2. The method of claim 1, wherein the step of performing structural analysis on the file data in the data directory to be desensitized by using a medical image desensitization model based on an artificial intelligence technology to obtain metadata information of image contents comprises:
extracting image features of image content in file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology, and carrying out structural processing on the image features to obtain metadata information of the image content, wherein the image features comprise position features, coordinate features and direction features.
3. The method of claim 1, wherein the step of performing structural analysis on the file data in the data directory to be desensitized by using a medical image desensitization model based on an artificial intelligence technology to obtain metadata information of text content comprises:
extracting text information of text content in file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology, and carrying out structural processing on the text information to obtain metadata information of the text content, wherein the text information comprises name information, number information and birthday information.
4. The method of claim 1, wherein locating privacy features in image content by the medical image desensitization model and desensitizing the privacy features comprises:
and positioning privacy features in the image content through the medical image desensitization model, hiding the privacy features by adopting a drawing function based on an image processing library, and storing desensitized file data into a database.
5. The method of claim 1, wherein locating text-sensitive information in text content by the medical image desensitization model and desensitizing the text-sensitive information comprises:
and positioning text sensitive information in the text content through the medical image desensitization model, removing the text sensitive information by adopting a hash function, and storing the desensitized file data into a database.
6. The method according to claim 1, wherein the method further comprises:
and developing a cross-platform system for the medical image desensitization model based on the artificial intelligence technology through an Electron programming framework, wherein the platform system comprises a Windows system, a MacOS system and a Linux system.
7. The method according to claim 1, wherein the method further comprises:
developing the interactive interface of the medical image desensitization model based on the artificial intelligence technology through a preset front-end programming language, wherein the preset front-end programming language comprises a JavaScript programming language, an HTML5 programming language and a CSS programming language.
8. The method of claim 1, wherein the artificial intelligence technology based medical image desensitization model is an offline deployed lightweight model.
9. The method of claim 1, wherein acquiring image data of the patient, preprocessing the image data and storing the image data in a database comprises:
and acquiring image data of the patient, performing data cleaning, data labeling and data grouping on the image data, and storing the image data into a database.
10. A medical data desensitization system, which is characterized by comprising a data acquisition module, a data extraction module and a desensitization processing module;
the data acquisition module is used for acquiring image data of a patient, preprocessing the image data and storing the preprocessed image data into a database;
the data extraction module is used for carrying out structural analysis on file data under a data catalog to be desensitized through a medical image desensitization model based on an artificial intelligence technology to obtain metadata information of image content and metadata information of text content;
the desensitization processing module is used for positioning privacy features in the image content through the medical image desensitization model according to the metadata information of the image content and carrying out desensitization processing on the privacy features; and positioning text sensitive information in the text content through the medical image desensitization model according to the metadata information of the text content, and carrying out desensitization processing on the text sensitive information.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117150565A (en) * | 2023-10-31 | 2023-12-01 | 山东网安安全技术有限公司 | Medical data desensitization storage method and device, electronic equipment and storage medium |
| CN117675870A (en) * | 2024-01-31 | 2024-03-08 | 中国医学科学院北京协和医院 | Electronic medical record distributed sharing method and device based on blockchain |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117150565A (en) * | 2023-10-31 | 2023-12-01 | 山东网安安全技术有限公司 | Medical data desensitization storage method and device, electronic equipment and storage medium |
| CN117150565B (en) * | 2023-10-31 | 2024-03-01 | 山东网安安全技术有限公司 | Medical data desensitization storage method and device, electronic equipment and storage medium |
| CN117675870A (en) * | 2024-01-31 | 2024-03-08 | 中国医学科学院北京协和医院 | Electronic medical record distributed sharing method and device based on blockchain |
| CN117675870B (en) * | 2024-01-31 | 2024-04-19 | 中国医学科学院北京协和医院 | Electronic medical record distributed sharing method and device based on blockchain |
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