CN113053493A - Data processing platform - Google Patents
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- CN113053493A CN113053493A CN201911370982.2A CN201911370982A CN113053493A CN 113053493 A CN113053493 A CN 113053493A CN 201911370982 A CN201911370982 A CN 201911370982A CN 113053493 A CN113053493 A CN 113053493A
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- 238000012545 processing Methods 0.000 title claims abstract description 124
- 238000000034 method Methods 0.000 claims abstract description 45
- 238000004891 communication Methods 0.000 claims abstract description 16
- 238000001914 filtration Methods 0.000 claims description 17
- 230000008569 process Effects 0.000 claims description 15
- 238000007781 pre-processing Methods 0.000 claims description 10
- 238000000586 desensitisation Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000013500 data storage Methods 0.000 claims description 4
- 238000002604 ultrasonography Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 201000010099 disease Diseases 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 238000012549 training Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 1
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- 238000003745 diagnosis Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035935 pregnancy Effects 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G06F16/17—Details of further file system functions
- G06F16/172—Caching, prefetching or hoarding of files
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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Abstract
The invention provides a data processing platform, comprising: the user module is used for user registration and user identity authentication; a communication module at least used for acquiring data, wherein the data at least comprises medical image data, and the medical image data is obtained by an ultrasonic diagnostic device; the first processing module is used for processing the data according to a preset method to obtain the processed data; and the storage module is used for storing the data processed by the first processing module by adopting a preset distributed storage method.
Description
Technical Field
The invention relates to a data processing method, in particular to a data processing platform.
Background
Because most of the existing data processing and storage platforms only support media file storage, the DICOM format of the medical field is not supported, and the data processing and storage platforms are single-point storage, and data security and storage expansion are not guaranteed.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a data processing platform, wherein the data processing platform adopts a distributed storage method to store data, so that the expansibility and the fault tolerance of the data are improved, and the retrieval speed is improved. The embodiment of the invention adopts the technical scheme that:
the platform includes:
the user module is used for user registration and user identity authentication;
a communication module at least used for acquiring data, wherein the data at least comprises medical image data, and the medical image data is obtained by an ultrasonic diagnostic device;
the first processing module is used for processing the data according to a preset method to obtain the processed data;
and the storage module is used for storing the data processed by the first processing module by adopting a preset distributed storage method.
In some embodiments, the user module includes a registration unit, and the registration unit is configured to acquire user information, perform registration according to the user information, and divide a user into corresponding user types according to the user information, where the user types include at least a doctor and/or an algorithm engineer.
In some embodiments, the first processing module includes a stream processing engine unit, and the stream processing engine unit is configured to perform a preprocessing operation on the data acquired by the communication module, so as to obtain data meeting a preset storage standard.
In some embodiments, the preprocessing operation of the stream processing engine unit at least includes a format uniform conversion process and/or a redundant information merging process and/or a filtering process for data according to a preset data filtering rule.
In some embodiments, the storage module includes a storage unit, and the storage unit is configured to perform distributed storage on the data subjected to the preprocessing operation by the stream processing engine unit.
In some embodiments, the first processing module further includes a search engine unit, and the search engine unit is configured to search the data in the storage module according to a preset search method to obtain data that meets a preset search rule.
In some embodiments, the first processing module further includes a batch processing engine unit, the batch processing engine unit is configured to process the data searched by the search engine by using a preset workflow, the preset workflow at least includes filtering, rotating and/or stretching the data, and the communication module is further configured to provide the data processed by the batch processing engine unit to a user.
In some embodiments, the batch processing engine unit is further configured to perform desensitization processing on the data searched by the search engine unit, so as to obtain desensitized data.
In some embodiments, the storage module includes a hot spot data storage unit, the search engine unit is further configured to determine high-frequency hot spot data by using a preset high-frequency hot spot search method, and the hot spot data storage unit stores the high-frequency hot spot data determined by the search engine unit.
In some embodiments, the storage module further includes a metadata storage unit, and the stream processing engine unit is further configured to determine metadata by using a preset metadata determination method, and the metadata storage unit stores the metadata determined by the stream processing engine unit.
The embodiment of the invention has the advantages that: the invention utilizes the search engine unit in the first processing module to quickly search the required data according to the preset search method, thereby realizing the batch search, and utilizes the desensitization treatment of the batch processing engine unit to carry out the batch desensitization treatment on the data, thereby improving the data quality, and can carry out the batch treatment on the retrieved data, accelerating the processing speed, and utilizes the stream processing engine unit to carry out the pretreatment operation on the imported data, thereby realizing the uniform storage of the data, improving the data compatibility of the data processing platform, and simultaneously avoiding the problem of inconsistent data formats when exporting the data.
Drawings
Fig. 1 is a block diagram of a data processing platform 100 according to an embodiment of the present invention.
Fig. 2 is a block diagram of the first processing module 120 according to an embodiment of the invention.
Fig. 3 is a block diagram of the second processing module 130 according to an embodiment of the invention.
Fig. 4 is a block diagram of a data processing platform 400 according to an embodiment of the invention.
Detailed Description
The invention is further illustrated by the following specific figures and examples.
As shown in fig. 1, the data processing platform 100 may include a user module 110, a communication module 120, a first processing module 130, and a storage module 140, and the data processing platform 100 may be applied to a pacs system.
The user module 110 is used for user registration and for identity authentication.
In some embodiments, the user module 110 may include a registration unit, and the registration unit may be configured to obtain user information, perform registration according to the user information, and classify a user into a corresponding user type according to the user information, where the user type includes at least a doctor and/or an algorithm engineer.
In some embodiments, the platform 100 may assign different user permissions according to different user types, so as to provide different services to users, for example, when the user type is an algorithm engineer, the user permissions may be functions that enable retrieval, so as to acquire image data in the platform 100 for subsequent training, but not functions that enable import of data. For another example, when the user type is a doctor, the user authority may be that data can be imported but image data stored in the platform 100 cannot be acquired. It should be noted that, the definition of the user right in the present invention may be set according to the actual application, and the present invention is not limited specifically herein.
The communication module 120 may be at least used for acquiring data, which at least includes medical image data, which may be obtained by an ultrasound diagnostic apparatus.
In some embodiments, the medical image data may include ultrasound image data obtained by scanning a patient in real time by an ultrasound diagnostic apparatus, and may further include patient-related information, which may include at least basic information, clinical information, and the like of the patient. The basic information may include personal information such as patient name, age, sex, weight, height, pregnancy, etc. The clinical information may include historical ultrasound images, annotation information of the historical ultrasound images, historical diagnosis information, and the like, and the patient information may further include at least: historical examination part information and preset parameter preset values corresponding to the historical examination parts.
In some embodiments, the medical image data may also be passed through the communication module 120, for example, including importing patient-related information into the data processing platform 100 through an associated interface (e.g., an API interface).
The first processing module 130 may be configured to process data according to a preset method, so as to obtain the processed data.
In some embodiments, the data may be processed according to a preset method, for example, related data search, image processing, desensitization processing, and the like are performed on the data, so as to obtain data required by the user. In some embodiments, the first processing module 130 may include a stream processing engine unit 131, a search engine unit 132, and a batch processing engine unit 133. For the first processing module 130, reference may be made to related contents of fig. 2, which are not described herein again.
The storage module 140 may be configured to store the data processed by the first processing module by using a preset distributed storage method.
In some embodiments, the storage module 140 may include a storage unit 141, and the storage module 140 may further include a high frequency hot spot storage unit 142, a metadata storage unit 143, and the like according to different functions. The data acquired by the communication module 120 may be stored in the storage module 140 after being processed. The related contents of fig. 3 can be referred to for the storage module 140, and are not described herein again.
As shown in fig. 2, the first processing module 130 may include a stream processing engine unit 131, where the stream processing engine unit 131 is configured to perform a preprocessing operation on data (e.g., medical image data) acquired by the communication module 120, so as to obtain data meeting a preset storage standard.
In some embodiments, the preprocessing operation of the stream processing engine unit 131 includes at least a format uniform conversion process and/or a redundant information merging process and/or a filtering process for data according to a preset data filtering rule.
In some embodiments, the stream processing engine unit 131 may be used to store and process the files with the unified format into the DICOM format, for example, the files with various formats such as JPG, PNG, BMP, MP4, AVI, and DICOM may be converted into the DICOM file for storage, so as to be compatible with most image formats, and facilitate the downloading and subsequent processing of the files by the user.
In some embodiments, the stream processing engine unit 131 may also be used to perform merging processing of redundant information, for example, a same patient may use a same case, a plurality of medical image data in the patient may have a lot of identical data, if all the data of the patient are stored separately, a lot of identical data may be redundant, and the stream processing engine unit 131 may be used to merge the identical data in the same case of the patient and then perform storage processing, thereby saving storage space.
In some embodiments, the stream processing engine unit 131 may be further configured to perform filtering processing on data according to a preset data filtering rule, so as to obtain data meeting the data filtering rule. The user can define the data filtering rule according to the actual application requirement, so that the stream processing engine 131 is used for selecting and filtering according to the preset data to correspondingly filter the data, and the required data is obtained. As an alternative example, a user may use a script (e.g., python) to customize data filtering rules when using the data processing platform 100, for example, to filter desired data based on the clarity of the ultrasound image (e.g., resolution of the picture is less than 800x 600) or based on the age range of the patient (e.g., age range is 20-50 years).
By preprocessing the imported data in the data processing platform 100 by using the stream processing engine unit 131, the communication module 120 can be compatible with various data formats and various data sources, and store the imported data after performing format uniform conversion processing on the imported data by using the stream processing engine unit 131, so that the problem of inconsistent data formats when the data is exported through the communication module 120 is avoided, and the operation after exporting the data is reduced.
As shown in fig. 3, the storage module 140 may include a storage unit 141, and the storage unit 141 may be configured to perform distributed storage on data that is subjected to a preprocessing operation by the stream processing engine unit.
In some embodiments, the distributed storage method g (x) may employ formula (1) as follows:
G(x)=Save(Distributed(Encrypt(x))) （1）
wherein x is data to be stored; encrypt (x) is a preset encryption method, and encrypts data; the Distributed () is a preset Distributed method, divides data into a plurality of data blocks, and generates corresponding check codes and erasure codes; save () is a preset Save method, and stores the data block into the corresponding storage unit 141.
Specifically, the data may be encrypted by a preset encryption method (for example, by using the SHA-256 encryption algorithm), so as to ensure the data security in the data processing platform, and the storage module 140 may further include a controller, a scheduler, and a storage unit 141. The controller is responsible for receiving storage requests, all the storage requests are received by the component, and a plurality of storage units 141 can be horizontally deployed to achieve the purpose of load balancing, so that the storage throughput of the data processing platform is improved, and the controller can send the received requests to the scheduler. The scheduler is responsible for processing data from the controller, the scheduler cuts the data into blocks and sends the blocks to different storage units 141, the scheduler mainly realizes data segmentation and slice table recording, when a reading request is made, the scheduler can also read the data blocks according to the slice table and then merge the data blocks, and finally complete data is returned. The storage unit 141 is the last unit responsible for storage, and is responsible for storing only the received data block. The storage data is dispersed on a plurality of independent entity machines and can be horizontally expanded, a plurality of machines share the storage load and are mutually backed up, the storage consistency and high availability are realized, and the storage unavailability caused by single-point failure is prevented.
In some embodiments, the first processing module 130 further includes a search engine unit 132, where the search engine unit 132 is configured to search the data in the storage module 140 according to a preset search method, and obtain data that meets a preset search rule. For example, the user may quickly retrieve the required data according to the search field or search adjustment of the keywords, disease types, annotation types, data source conditions, etc. that meet the requirements of the data processing platform 100.
In some embodiments, the search engine unit 132 may be further configured to determine the high-frequency hotspot data by using a preset high-frequency hotspot searching method, where the high-frequency hotspot searching method f (x) may adopt formula (2):
F(x)=Search(x,HotCache(x)) （2）
wherein x is data to be searched; HotCache (x) is an LRU page replacement method; search (x, hotcache (x)) is a preset data hit method, if the data to be searched is hit in the high-frequency hot spot storage unit 142, the Search is finished, otherwise, the data to be searched is matched in the storage unit 141 by using the preset Search method.
Further, hotcache (x) may use the LRU page replacement method, which satisfies the following 3 characteristics: inserting data to be searched into the head of a linked list; whenever data to be searched is hit in the high-frequency hot spot storage unit 142 (i.e., the stored data is accessed), moving the data to be searched to the head of the linked list; when the linked list is full, the data at the tail of the linked list is discarded.
Further, Search (x, HotCache) uses a BFS breadth first algorithm to match with a cache hit algorithm, if stored data is accessed, direct Search is finished, otherwise, the stored data is matched with the data to be searched in a Search algorithm.
As an alternative example, the user may use the search engine unit 132 to perform the filtering in the metadata storage unit 143 according to the query information (e.g., the disease type, the data source, the patient age, etc.) input by the user, and then return the data from the storage unit 141 to the user, and the search engine unit 132 synchronizes the data frequently queried and accessed by the user (e.g., the user frequently accesses the carotid plaque disease picture) as the high-frequency hot data to the high-frequency hot storage unit 142, thereby speeding up the same type of search.
The first processing module 130 may include a batch processing engine unit 133, where the batch processing engine unit 133 may be configured to process the medical image data searched by the search engine unit 132 by using a preset workflow, where the preset workflow at least includes filtering, rotating and/or stretching the medical image data, and the communication module 120 is further configured to provide the data processed by the batch processing engine unit 133 to a user.
In some embodiments, the user may construct a required data processing workflow according to the actual application, for example, the user may filter data, reject images with low quality and low resolution, filter the data to remove noise of medical images, generally perform filtering using fourier transform, rotate the data, may acquire the data from different angles during entry, rotate all the data to the same angle at a later stage, stretch the data, have different sizes of different data, stretch all the data to the same size, each processing operation may be one of the workflows, the user may construct the required workflow by using the above processing operations, and input the workflow into the batch processing engine unit 133 after the construction is completed, the batch processing engine unit 133 processes the workflow constructed by the user, and finally stores the processed data or provides the processed data to the user through the communication module 120.
In some embodiments, the batch processing engine unit 133 may further be configured to perform desensitization processing on the data searched by the search engine unit, so as to obtain desensitized data.
In some embodiments, after acquiring the required data, the user (for example, the user type is an algorithm engineer) may perform desensitization processing on the data by using the batch processing engine unit 133, so as to clip the medical image data of the patient to only retain the critical image data, and remove the sensitive information and the confidential information of the patient, so that the quality of the data for training may be improved, thereby improving the quality of training. In some embodiments, after acquiring the required data, the user may directly acquire the required data after performing batch desensitization processing on the data by using the batch processing engine 133, thereby increasing the speed of data acquisition.
In some embodiments, the storage module 140 further includes a metadata storage unit 143, and the stream processing engine unit 131 is further configured to determine metadata by using a preset metadata determination method, and the metadata storage unit stores the metadata determined by the stream processing engine unit 131.
Further, the metadata refers to intermediate data and relay data, and is data describing data, and the metadata may be used to describe information of data attributes, and indicate storage location information of the data, history data information, resource search, file records, and the like, and may facilitate subsequent data search by a user. As an alternative example, the stream processing engine unit 131 may enter fields and values to be searched into a metadata document (e.g., age, disease type, entry time, etc. of a patient) as metadata.
As shown in fig. 4, which is a schematic diagram of a data processing platform 400 according to an embodiment of the present invention, the data processing platform 400 may be divided into a user layer, a service layer, and a storage layer. At the user level, the user types may be classified as doctors, algorithm engineers, or upload data devices, etc. At the business layer, an identity authentication module, an API module, a search engine, a stream processing engine, a batch processing engine and the like can be included. In the storage layer, a distributed object storage system, a metadata storage database, a hot spot data cache library and the like can be included. And then the searched and processed data is mounted on the user equipment through the network in a mounting mode for the user to use.
An embodiment of the present invention further provides a data processing system, including: the server is provided with the data processing platform as described above; an ultrasound diagnostic device capable of data interaction with the server.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to examples, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (10)
1. A data processing platform, said platform comprising:
the user module is used for user registration and user identity authentication;
a communication module at least used for acquiring data, wherein the data at least comprises medical image data, and the medical image data is obtained by an ultrasonic diagnostic device;
the first processing module is used for processing the data according to a preset method to obtain the processed data;
and the storage module is used for storing the data processed by the first processing module by adopting a preset distributed storage method.
2. The data processing platform of claim 1, wherein the user module comprises a registration unit, and the registration unit is configured to obtain user information, perform registration according to the user information, and divide a user into corresponding user types according to the user information, where the user types at least include doctors and/or algorithm engineers.
3. The data processing platform according to claim 1, wherein the first processing module comprises a stream processing engine unit, and the stream processing engine unit is configured to perform a preprocessing operation on the data acquired by the communication module to obtain data meeting a preset storage standard.
4. The data processing platform of claim 3, wherein the preprocessing operation of the stream processing engine unit at least comprises a format uniform conversion process and/or a redundant information merging process and/or a data filtering process according to a preset data filtering rule.
5. The data processing platform of claim 3, wherein the storage module comprises a storage unit configured to perform distributed storage on the data that has undergone the preprocessing operation by the stream processing engine unit.
6. The data processing platform of claim 1, wherein the first processing module further comprises a search engine unit, and the search engine unit is configured to search the data in the storage module according to a preset search method to obtain medical image data meeting a preset search rule.
7. The data processing platform of claim 6, wherein the first processing module further comprises a batch processing engine unit, the batch processing engine unit is configured to process the data searched by the search engine unit by using a preset workflow, the preset workflow at least includes filtering, rotating and/or stretching the data, and the communication module is further configured to provide the data processed by the batch processing engine unit to a user.
8. The data processing platform of claim 7, wherein the batch processing engine unit is further configured to perform desensitization processing on the data searched by the search engine unit to obtain desensitized data.
9. The data processing platform of claim 6, wherein the storage module comprises a hot spot data storage unit, the search engine unit is further configured to determine high-frequency hot spot data by using a preset high-frequency hot spot search method, and the hot spot data storage unit stores the high-frequency hot spot data determined by the search engine unit.
10. The data processing platform of claim 1, wherein the storage module further comprises a metadata storage unit, wherein the stream processing engine unit is further configured to determine metadata by using a preset metadata determination method, and wherein the metadata storage unit stores the metadata determined by the stream processing engine unit.
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