CN117766110A - Medical image file processing system and method - Google Patents
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Abstract
The embodiment of the invention discloses a medical image file processing system and a medical image file processing method, wherein the medical image file processing system comprises the following steps: the system comprises an edge end and a platform end, wherein the edge end is connected with the platform end and is used for acquiring a medical image file, determining image association data corresponding to the medical image file, determining a target first application matched with the image association data, determining a callable computing resource value corresponding to the target first application, and transmitting the image association data to the platform end when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value; the platform end is used for receiving the image association data sent by the edge end, processing the image association data and obtaining a data analysis result corresponding to the image association data. The problem of among the prior art, medical institutions at all levels all need purchase medical application just can be to medical image file reasoning discernment, supplementary diagnosis treatment leads to increasing medical institutions 'cost input is solved, has realized the reduction to medical institutions' cost input, improves the utilization efficiency of using.
Description
Technical Field
The invention relates to the technical field of medical image file processing, in particular to a medical image file processing system and a medical image file processing method.
Background
Along with the rapid development of the AI technology, the increasing maturity of products and the perfection of a supervision system, the application of the medical image AI in medical scenes is more and more deep, and the medical image AI is gradually integrated into the daily workflow of doctors. In the actual clinical diagnosis process, the utilization rate of the medical image AI auxiliary diagnosis product by clinicians is very high, and particularly in the detection projects of lung nodule screening, children bone age growth and development examination, rib fracture examination and the like, which have more mature medical image AI auxiliary diagnosis products, most doctors indicate that the auxiliary development work by means of the medical image AI product is hoped.
Along with the increasing demand and application of medical AI, especially because of the gradual progress of grading diagnosis and treatment, under the circumstance that the demand of primary hospitals for AI is gradually increased, a plurality of pain points are highlighted in each link: the hardware resource investment of the hospital information department and the cost investment for data, equipment and network management are gradually increased; the clinic seeing amount of the primary hospital is relatively small, local AI application is purchased independently without enough budget, and the accessibility of the medical image AI application in the primary hospital is low; the medical community/medical conjunct undertaking mechanism is responsible for the consistency of the image quality of the subordinate mechanism, and uniform AI deployment and use are required.
Disclosure of Invention
The invention provides a medical image file processing system and a medical image file processing method, which are used for reducing the cost input of medical institutions and improving the utilization efficiency of applications.
According to an aspect of the present invention, there is provided a medical image file processing system including: an edge end and a platform end, wherein,
the edge end is connected with the platform end and is used for acquiring a medical image file, determining image association data corresponding to the medical image file, determining a target first application matched with the image association data, determining a callable computing resource value corresponding to the target first application, and transmitting the image association data to the platform end when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value;
the platform end is used for receiving the image association data sent by the edge end, processing the image association data and obtaining a data analysis result corresponding to the image association data.
According to another aspect of the present invention, there is provided a medical image file processing method applied to a medical image file processing system, the medical image file processing system including an edge end and a platform end, the edge end being connected to the platform end, wherein the medical image file processing method includes:
acquiring a medical image file through the edge end, determining image association data corresponding to the medical image file, determining a target first application matched with the image association data based on the image association data, determining a callable computing resource value corresponding to the target first application, and transmitting the image association data to the platform end when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value;
and receiving the image related data sent by the edge end through the platform end, and processing the image related data to obtain a data analysis result corresponding to the image related data.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor;
and a memory communicatively coupled to the at least one processor;
the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the medical image file processing method according to any embodiment of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the medical image file processing method according to any one of the embodiments of the present invention when executed.
According to the technical scheme, a medical image file is acquired through an edge terminal, image association data corresponding to the medical image file are determined, a target first application matched with the image association data is determined, a callable computing resource value corresponding to the target first application is determined, and when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value, the image association data are sent to a platform terminal; and receiving the image association data sent by the edge end through the platform end, and processing the image association data to obtain a data analysis result corresponding to the image association data. The problem of among the prior art, medical institutions at all levels all need purchase medical application just can be to medical image file reasoning discernment, supplementary diagnosis treatment leads to increasing medical institutions 'cost input is solved, has realized the reduction to medical institutions' cost input, improves the utilization efficiency of using.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of a medical image file processing system according to an embodiment of the present invention;
FIG. 2 is a flowchart of a medical image file processing method according to an embodiment of the present invention;
FIG. 3 is a flowchart of a medical image file processing method according to another embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 is a block diagram of a medical image file processing system according to an embodiment of the present invention, where the system includes: edge end 110 and platform end 120, edge end 110 being connected to platform end 120.
The edge 110 is configured to obtain a medical image file, determine image association data corresponding to the medical image file, determine a target first application matched with the image association data, determine a callable computing resource value corresponding to the target first application, and send the image association data to the platform 120 when the callable computing resource value corresponding to the target first application is less than a preset threshold.
The edge end can be a server deployed in a medical institution, and the medical institution deploying the edge end is usually a medium-sized and large-sized medical institution; the medical image file refers to an image file acquired by a medical image device, which may be a computed tomography (Computed Tomography, CT) device, a magnetic resonance imaging (Magne tic Resonance Imaging, MRI) device, an X-ray (X-ray) device, or the like. The image-related data refers to information data contained in the medical image file; the target first application refers to an AI application installed on the edge for processing a medical image file. The callable computing resource value refers to the size of the computing resource of the edge end that the target first application can call, and the callable computing resource includes, but is not limited to, GPU, CPU, etc., and the preset threshold refers to a preset threshold of the computing resource.
In the embodiment of the invention, the edge end can acquire the medical image file of the medical institution, and the edge end can establish communication with a medical image database of the medical institution, and actively acquire the medical image file of the medical institution based on the communication; the medical image file uploaded by the medical institution can be passively received by the edge end; after the medical image file is acquired, the edge end determines corresponding image association data according to the medical image file, and further determines a target first application suitable for processing the image association data.
It should be noted that, more computing resources are required to be occupied by the processing of the image associated data by the target first application, so that the callable computing resource value of the target first application can be determined first, and then the callable computing resource value is compared with a preset threshold, the preset threshold is usually set by a development tester based on experience, and when the callable computing resource value of the target first application is smaller than the preset threshold, that is, the callable computing resource of the target first application is insufficient to implement the processing of the image associated data, at this time, the image associated data can be sent to the platform end.
The platform end 120 is configured to receive the image related data sent by the edge end, and process the image related data to obtain a data analysis result corresponding to the image related data.
In this embodiment, the platform end may be understood as a server deployed away from the medical institution, and the data analysis result may be understood as a disease diagnosis result obtained after the image-related data is analyzed; compared with the edge end, the platform end has stronger data processing capability, and corresponding disease diagnosis results are obtained through analysis and processing of the image related data sent by the platform end to the edge end.
In one embodiment, the edge is further configured to: and when the callable computing resource value is larger than the preset threshold value, carrying out reasoning analysis on the image associated data through the target first application to obtain the data analysis result corresponding to the image associated data.
It can be understood that when the computing resources callable by the target first application in the edge end are enough to process the image associated data, the image associated data is analyzed by the target first application in a reasoning manner, so as to obtain a data analysis result corresponding to the image associated data, namely a disease diagnosis result.
On the basis of the above embodiment, the edge end includes: the image data analysis module is used for analyzing the medical image file to obtain the image associated data corresponding to the medical image file; the first application matching module is used for determining a target first application from a plurality of first applications according to the image association data; and the computing resource judging module is used for determining a callable computing resource value corresponding to the target first application, and sending the medical image file to the platform end when the callable computing resource value is smaller than the preset threshold value.
Wherein the image-associated data includes at least one of modality, examination site, image quality, and patient information; the first application refers to a plurality of medical AI applications installed at the edge.
Specifically, the image data analysis module analyzes the medical image file, such as analyzing and determining the mode, the position, the image quality, the patient information and the like of the medical image file. Further, the first application matching module selects a medical AI application matched with the image association data from a plurality of first applications as a target first application according to the image association data. For example, when the head CT image data is based on the image-related data, a first application for head CT diagnosis is searched out from the plurality of first applications accordingly as a target first application. And then, determining a callable computing resource value corresponding to the target first application through a computing resource judging module, and sending the medical image file to the platform end when the callable computing resource value is smaller than the preset threshold value.
On the basis of the above embodiment, the platform end includes: the second application matching module is used for receiving the image association data sent by the edge end and determining the target second application from the plurality of second applications according to the image association data; and the target second application is used for carrying out reasoning analysis on the image associated data to obtain the data analysis result corresponding to the image associated data.
In this embodiment, the second application refers to a medical AI application installed at the platform end, and the second application matching module determines, according to the image association data, a second application matched with the image association data, that is, a target second application suitable for processing the image association data. If the callable computing resources of the target first application on the edge end are insufficient for processing the image associated data, the image associated data can be sent to the platform end, and reasoning is performed on the image associated data through a proper target second application in the platform end, so that a medical diagnosis result is obtained.
In a preferred embodiment, the platform end further comprises: the image file receiving and analyzing module is used for receiving a target medical image file corresponding to a target medical institution, analyzing the target medical image file to obtain image data to be used, and sending the image data to be used as the medical image data to the second application matching module so as to determine a data analysis result corresponding to the image data to be used based on the second application matching module and the target second application.
Wherein the target medical facility is a medical facility that does not deploy a marginal end, such as some basic level medical facilities. The second matching application is used for matching a second application capable of processing the image data to be used, namely determining a target second application.
It will be appreciated that for some infrastructure medical institutions that do not deploy edge-based medical institutions, when there is a target medical image file that needs to be identified and analyzed by the medical institution, the target medical image file may be sent to the platform-based medical institution via the corresponding communication channel. The image file receiving and analyzing module at the platform end can receive the target medical image file and analyze the target medical image file to obtain image data to be used, namely, the mode, the examination part, the image quality, the patient information and the like. And then determining a target second application capable of processing the image data to be used by a second application matching module so as to process the image data to be used, and obtaining a corresponding medical diagnosis result. The advantages are that: even if the corresponding edge end is not deployed in the primary hospital, the identification processing of the medical image file can be realized, and the corresponding disease diagnosis result is obtained for the doctor to refer to, so that the cost of the primary medical institution is saved.
Optionally, the platform end further includes: and the archiving module is used for acquiring and storing the data analysis result corresponding to the image association data determined by the target first application and/or acquiring and storing the data analysis result corresponding to the image association data determined by the target second application.
In an actual application scenario, the archiving module may acquire a data analysis result of the target first application and the target second application, and store the data analysis result.
Optionally, the target first application is functionally identical to the target second application, the target first application including at least one of a lung nodule screening application, a child bone age growth and development inspection application, and a fracture inspection application.
Optionally, the platform end further includes: the access address generation module is used for generating an access address corresponding to the data analysis result; and the diagnosis result calling module is used for calling the data analysis result corresponding to the access address based on the access address when receiving the access request containing the access address.
Wherein, the access address can be understood as the corresponding access link of the data analysis result; an access request refers to a request to access the results of data analysis.
Specifically, after the platform end files the data analysis results, the access address generating module generates access addresses corresponding to the data analysis results, when a doctor needs to check the data analysis results, the access addresses can be input on the device through terminal equipment of the doctor, the terminal equipment of the doctor can generate an access request based on the input access addresses and send the access request to the diagnosis result calling module, and the diagnosis result calling module can call the data analysis results corresponding to the access addresses.
According to the technical scheme, a medical image file is acquired through an edge terminal, image association data corresponding to the medical image file are determined, a target first application matched with the image association data is determined, a callable computing resource value corresponding to the target first application is determined, and when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value, the image association data are sent to a platform terminal; and receiving the image association data sent by the edge end through the platform end, and processing the image association data to obtain a data analysis result corresponding to the image association data. The problem of among the prior art, medical institutions at all levels all need purchase medical application just can be to medical image file reasoning discernment, supplementary diagnosis treatment leads to increasing medical institutions 'cost input is solved, has realized the reduction to medical institutions' cost input, improves the utilization efficiency of using.
The embodiment meets the clinical application requirements of different hospitals of different grades and different doctors. The platform performs resource and information safety management in a centralized way, supports the access of all levels of hospital systems, is ready to use and does not need repeated construction.
FIG. 2 is a flowchart of a medical image file processing method according to an embodiment of the present invention; the embodiment is applicable to medical image file processing and determining a corresponding diagnosis result, and the method can be executed by a medical image file processing system, wherein the medical image file processing system comprises an edge end and a platform end, and the edge end is connected with the platform end. As shown in fig. 2, the method includes:
s210, acquiring a medical image file through the edge end, determining image association data corresponding to the medical image file, determining a target first application matched with the image association data based on the image association data, determining a callable computing resource value corresponding to the target first application, and transmitting the image association data to the platform end when the callable computing resource value corresponding to the target first application is smaller than a preset threshold.
The edge end can be a server deployed in a medical institution, the medical image file refers to an image file acquired by medical image equipment, and the medical image equipment can be computer tomography (Computed Tomograph y, CT) equipment, magnetic resonance imaging (Magnetic Resonance Imaging, MRI) equipment, X-ray (X-ray) equipment and the like; the image-related data refers to information data contained in the medical image file; the target first application refers to an application program installed at an edge end; the callable computing resource value refers to the size of computing resources of an edge end which can be called by the target first application, and the preset threshold value refers to a preset threshold value of the computing resources.
In this embodiment, the edge may acquire a medical image file of a medical institution, and after acquiring the medical image file, determine, according to image association data corresponding to the medical image file, a target first application matched with the image association data, that is, determine an application capable of processing the image file.
Because the processing of the image associated data needs to occupy more computing resources, the callable computing resource value in the target first application can be determined first, the callable computing resource value is compared with the preset threshold, and if the callable computing resource value corresponding to the target first application is smaller than the preset threshold, the fact that the callable computing resource of the target first application cannot realize the processing of the image associated data is indicated, so that the image associated data is sent to the platform end.
S220, receiving the image related data sent by the edge end through the platform end, and processing the image related data to obtain a data analysis result corresponding to the image related data.
On the basis of the embodiment, compared with the edge end, the platform end has higher data processing capability, and the data analysis result corresponding to the image association data is obtained through the analysis processing of the platform end on the image association data, and can be a disease diagnosis result.
On the basis of the above embodiment, the method further comprises: and when the callable computing resource value is larger than the preset threshold value through the edge end, carrying out reasoning analysis on the image associated data through the target first application to obtain the data analysis result corresponding to the image associated data.
It can be understood that when the computing resources which can be invoked by the target first application in the edge end are enough to process the image-related data, the image-related data is subjected to reasoning analysis by the target first application, so that a data analysis result corresponding to the image data, namely a disease diagnosis result, is obtained. Under the condition, the image related data does not need to be uploaded to the platform end, so that the data transmission efficiency is saved, and the diagnosis result efficiency is improved.
Fig. 3 is a flowchart of a medical image file processing method according to another embodiment of the present invention, where the present embodiment is a preferred embodiment of the foregoing embodiment, and a specific implementation manner of the present embodiment may be referred to a technical solution of the present embodiment. Wherein, the technical terms identical to or corresponding to the above embodiments are not repeated herein.
The medical image file processing method of the embodiment can be realized through an edge end and a platform end, wherein the edge end is a selectable item, and is suitable for medium and large medical institutions, and the edge end integrates an image file distinguishing and routing module (namely an application matching module). After the platform receives the original image data, the platform automatically matches the proper AI application according to the subscription content of the medical institution, and completes reasoning through computing resources of the edge end or the cloud end, and finally returns a reasoning result for the user to review. Subscription content may be understood as, among other things, some AI applications subscribed to or installed by a medical facility.
As shown in fig. 3, the method includes:
(1) And the edge end confirms that the image file stream is received.
(2) The edge end identifies the data such as the mode, the checking part, the image quality, the patient information and the like of the image file, and is matched with proper application. If no suitable application is matched, the flow is terminated.
(3) The edge side judges whether the AI application can be inferred at the edge side, i.e. whether the callable computing resources of the AI application are sufficient.
And (3.1) if the AI application can perform reasoning at the edge end, performing reasoning calculation at the edge end, and uploading a collection result to the platform end.
And (3.1) pushing to a platform end for processing if the edge end cannot make reasoning.
(4) And the platform end performs AI application reasoning.
(5) And the platform end finishes the reasoning calculation, and the result is archived and checked.
For some medical institutions without edge deployment, the specific flow is as follows:
(1) The platform end confirms that the image file stream is received.
(2) The platform end identifies the data such as the mode, the examination part, the image quality, the patient information and the like of the image file, and is matched with proper application. If no suitable application is matched, the flow is terminated.
(3) If the AI application is matched with the proper application, the platform end performs AI application reasoning.
(4) And the platform end finishes the reasoning calculation, and the result is archived and checked.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as medical image file processing methods.
In some embodiments, the medical image file processing method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the medical image file processing method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the medical image file processing method in any other suitable way (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A medical image file processing system, comprising: an edge end and a platform end, wherein,
the edge end is connected with the platform end and is used for acquiring a medical image file, determining image association data corresponding to the medical image file, determining a target first application matched with the image association data, determining a callable computing resource value corresponding to the target first application, and transmitting the image association data to the platform end when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value;
the platform end is used for receiving the image association data sent by the edge end, processing the image association data and obtaining a data analysis result corresponding to the image association data.
2. The system of claim 1, wherein the edge is further configured to perform inference analysis on the image-related data by the target first application to obtain the data analysis result corresponding to the image-related data when the callable computing resource value is greater than the preset threshold.
3. The system of claim 1, wherein the edge comprises: the system comprises an image data analysis module, a first application matching module, a computing resource judging module and a plurality of first applications, wherein,
the image data analysis module is used for analyzing the medical image file to obtain image related data corresponding to the medical image file, wherein the image related data comprises at least one of a mode, an examination part, image quality and patient information;
the first application matching module is used for determining a target first application from a plurality of first applications according to the image association data;
and the computing resource judging module is used for determining a callable computing resource value corresponding to the target first application, and sending the medical image file to the platform end when the callable computing resource value is smaller than the preset threshold value.
4. The system of claim 1, wherein the platform end comprises: a second application matching module and a plurality of second applications, wherein,
the second application matching module is used for receiving the image association data sent by the edge end and determining the target second application from a plurality of second applications according to the image association data;
and the target second application is used for carrying out reasoning analysis on the image associated data to obtain the data analysis result corresponding to the image associated data.
5. The system of claim 4, wherein the platform end further comprises: the image file receiving and analyzing module, wherein,
the image file receiving and analyzing module is used for receiving a target medical image file corresponding to a target medical institution, analyzing the target medical image file to obtain image data to be used, and sending the image data to be used as the medical image data to the second application matching module so as to determine a data analysis result corresponding to the image data to be used based on the second application matching module and the target second application;
the target medical institution is a medical institution not deploying the edge end.
6. The system of claim 4, wherein the platform end further comprises: an archiving module, wherein,
the archiving module is used for acquiring and storing the data analysis result corresponding to the image association data determined by the target first application and/or acquiring and storing the data analysis result corresponding to the image association data determined by the target second application.
7. The system of claim 4, wherein the target first application is functionally identical to the target second application, the target first application comprising at least one of a lung nodule screening application, a child bone age growth and development inspection application, and a fracture inspection application.
8. The system of claim 1, wherein the platform end further comprises: an access address generation module and a diagnosis result retrieval module, wherein,
the access address generation module is used for generating an access address corresponding to the data analysis result;
the diagnosis result calling module is used for calling the data analysis result corresponding to the access address based on the access address when the access request containing the access address is received.
9. The medical image file processing method is characterized by being applied to a medical image file processing system, wherein the medical image file processing system comprises an edge end and a platform end, the edge end is connected with the platform end, and the medical image file processing method comprises the following steps:
acquiring a medical image file through the edge end, determining image association data corresponding to the medical image file, determining a target first application matched with the image association data based on the image association data, determining a callable computing resource value corresponding to the target first application, and transmitting the image association data to the platform end when the callable computing resource value corresponding to the target first application is smaller than a preset threshold value;
and receiving the image related data sent by the edge end through the platform end, and processing the image related data to obtain a data analysis result corresponding to the image related data.
10. The method as recited in claim 9, further comprising:
and when the callable computing resource value is larger than the preset threshold value through the edge end, carrying out reasoning analysis on the image associated data through the target first application to obtain the data analysis result corresponding to the image associated data.
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