An ultrasonic parameter monitoring method and device, computer equipment and storage medium

Abstract

The application relates to the technical field of parameter monitoring, and discloses an ultrasonic parameter monitoring method and device, computer equipment and a storage medium, the method comprising the following steps: extracting ultrasonic parameters, classifying the ultrasonic parameters, and obtaining a classified parameter structure; generating a parameter tree according to a node hierarchical manner of the classified parameter structure; comparing parameter nodes stored in the parameter tree with previously backed-up parameter nodes to obtain a comparison result; and automatically monitoring changes in the ultrasonic parameters according to the comparison result. The application extracts and classifies ultrasonic parameters, generates a parameter tree according to a node hierarchical manner of the classified parameter structure, stores parameter nodes by using the parameter tree, and monitors the influence of changes in upper-layer parameters on changes in lower-layer parameters by using the hierarchical relationship of the parameter tree itself. Changes in the ultrasonic parameters are automatically monitored by comparing the parameter nodes stored in the parameter tree with the previously backed-up parameter nodes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of parameter monitoring, and in particular to an ultrasonic parameter monitoring method and device, computer equipment and a storage medium. BACKGROUND

[0002] At present, medical ultrasonic imaging is widely used in radiology, cardiothoracic surgery, gynecology and obstetrics, etc. The ultrasonic imaging device transmits ultrasonic waves, and the ultrasonic waves pass through the human body surface. In the ultrasonic imaging process, the ultrasonic system generates a large number of parameters, and doctors or related staff can use the ultrasonic parameters to calculate relevant indicators, and the related staff can also call the parameters for analysis, etc.

[0003] In the prior art, the related staff usually manually sorts the ultrasonic parameters, combs the linkage range of parameter transformation, and monitors the parameter changes. However, this method depends on high professional talents and consumes a large amount of human and time costs. SUMMARY

[0004] Therefore, the present application provides an ultrasonic parameter monitoring method and device, computer equipment and a storage medium to solve the problem of manual monitoring of parameter changes in the prior art, which consumes a large amount of human and time costs.

[0005] In a first aspect, the present application provides an ultrasonic parameter monitoring method, which comprises:

[0006] extracting ultrasonic parameters and classifying the ultrasonic parameters to obtain a classified parameter structure;

[0007] generating a parameter tree from the classified parameter structure according to a node hierarchical manner;

[0008] comparing the parameter nodes stored in the parameter tree with the pre-backup parameter nodes to obtain a comparison result;

[0009] automatically monitoring the changes of the ultrasonic parameters according to the comparison result.

[0010] The present application classifies the extracted ultrasonic parameters, generates a parameter tree from the classified ultrasonic parameters according to a node hierarchical manner, stores the parameter nodes by using the parameter tree, and monitors the influence of the changes of the upper layer parameters on the changes of the lower layer parameters by using the hierarchical structure of the parameter tree itself. By comparing the parameter nodes stored in the parameter tree with the pre-backup parameter nodes, the changes of the ultrasonic parameters are automatically monitored according to the comparison result, instead of manual monitoring, which reduces the dependence on high professional talents and saves human and time costs.

[0011] In an optional embodiment, classifying the ultrasonic parameters to obtain a classified parameter structure comprises:

[0012] The ultrasonic parameters are classified according to the ultrasonic imaging modes to obtain first-layer ultrasonic parameters;

[0013] The ultrasonic parameters are classified according to the parameter action ranges to obtain second-layer ultrasonic parameters;

[0014] The ultrasonic parameters are classified according to the parameter specific related businesses to obtain third-layer ultrasonic parameters;

[0015] The three-layer ultrasonic parameters are determined as the classified ultrasonic parameters.

[0016] The present application classifies the ultrasonic parameters according to the ultrasonic mode imaging mode, the parameter action range and the parameter specific related business respectively, combines the first-layer ultrasonic parameters, the second-layer ultrasonic parameters and the third-layer ultrasonic parameters, and completes the classification of the ultrasonic parameters, so as to facilitate the analysis of the ultrasonic parameters.

[0017] In an optional embodiment, the classified parameter structure is used to generate a parameter tree in a node hierarchical manner, including:

[0018] The three-layer ultrasonic parameters are connected in series to generate a parameter tree corresponding to each ultrasonic imaging mode;

[0019] It is judged whether the linkage parameter exists in the branch node corresponding to the three-layer ultrasonic parameters;

[0020] If the linkage parameter does not exist in the branch node corresponding to the three-layer ultrasonic parameters, the corresponding branch node is newly added in the three-layer ultrasonic parameters.

[0021] The present application generates a parameter tree corresponding to each ultrasonic imaging mode by connecting the three-layer ultrasonic parameters in series, and newly adds the corresponding branch node in the three-layer ultrasonic parameters when the linkage parameter does not exist in the branch node corresponding to the three-layer ultrasonic parameters, so as to establish a complete parameter tree, thereby facilitating the monitoring of the parameter nodes stored on the parameter tree.

[0022] In an optional embodiment, before the parameter nodes stored in the parameter tree are compared with the parameter nodes backed up in advance, the method further includes:

[0023] The linkage path of the linkage parameter is preset by using the comparison table;

[0024] The linkage path corresponding to the linkage parameter is determined by traversing the comparison table.

[0025] The present application presets the linkage path of the linkage parameter by using the comparison table, and determines the linkage path corresponding to the linkage parameter by traversing the comparison table, so as to facilitate the comparison of the parameter nodes.

[0026] In an optional implementation, determining a linkage path corresponding to a linkage parameter includes:

[0027] Use smoke script to adjust parameters randomly;

[0028] If the triggered linkage path does not exist in the comparison table, the linkage path will be inserted into the comparison table, and the comparison table will be used to count the triggers. After the comparison table is trained and perfected to reach a stable state, useless records in the comparison table will be removed to obtain the specific path of parameter linkage.

[0029] The present invention utilizes a smoke script to perform random parameter adjustment. The smoke script automatically adjusts the parameters randomly without manual intervention, thereby improving the efficiency of parameter adjustment. When a triggered linkage path does not exist in a comparison table, the linkage path is inserted into the comparison table to obtain a completed linkage path. After the comparison table training reaches a stable state, useless records in the comparison table are removed to prevent useless records from interfering with the specific path for determining parameter linkage.

[0030] In an optional embodiment, automatically monitoring changes in ultrasound parameters based on the comparison results includes:

[0031] If the comparison results are consistent, it is determined that the ultrasound parameters have not changed;

[0032] If the comparison result is inconsistent, it is determined that the ultrasound parameters have changed.

[0033] The present invention determines whether the ultrasonic parameters have changed by comparing the current parameters with the backup parameters, so as to monitor the ultrasonic parameters when the ultrasonic parameters have changed.

[0034] In an optional embodiment, after determining that the ultrasound parameter has changed, the method further includes:

[0035] Automatically monitor changes in ultrasonic parameters, obtain monitoring results, and update backup parameters based on the monitoring results.

[0036] The present invention updates the backup parameters according to the monitoring results of the automatically monitored ultrasonic parameter changes, so that when the parameters are compared again, the data source is the latest backup parameters, thereby improving the accuracy of the parameter comparison results.

[0037] In a second aspect, the present invention provides an ultrasonic parameter monitoring device, the device comprising:

[0038] A classification module is used to extract ultrasound parameters, classify the ultrasound parameters, and obtain a classified parameter structure;

[0039] A generation module is used to generate a parameter tree according to the node layering method of the classified parameter structure;

[0040] The comparing module is configured to compare the parameter node stored in the parameter tree with the pre-stored parameter node to obtain a comparison result.

[0041] The monitoring module is configured to automatically monitor the change of the ultrasonic parameter according to the comparison result.

[0042] In a third aspect, the present application provides a computer device, comprising a memory and a processor, the memory and the processor are connected with each other in communication, the memory stores computer instructions, and the processor executes the computer instructions to perform the ultrasonic parameter monitoring method of the first aspect or any of the corresponding embodiments.

[0043] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make a computer execute the ultrasonic parameter monitoring method of the first aspect or any of the corresponding embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0045] Figure 1 is a flowchart of the ultrasonic parameter monitoring method according to an embodiment of the present application;

[0046] Figure 2 is a flowchart of another ultrasonic parameter monitoring method according to an embodiment of the present application;

[0047] Figure 3 is a structural block diagram of the ultrasonic parameter monitoring device according to an embodiment of the present application;

[0048] Figure 4 is a hardware structure diagram of the computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme of the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0050] In the related art, the parameters of an ultrasonic system are issued to an FPGA (Field Programmable Gate Array) so as to facilitate the FPGA to configure ultrasonic signals and the like according to the parameters, and meanwhile, the user can adjust the parameters, which need to involve parameter variation and linkage calculation, issuing, storage and the like, and the process is very cumbersome, error-prone, and some detail errors are difficult to be found.

[0051] According to the embodiment of the present application, an ultrasonic parameter monitoring method is provided, and it should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.

[0052] In the present embodiment, an ultrasonic parameter monitoring method is provided, which can be used in a mobile terminal, Figure 1 is a flowchart of the ultrasonic parameter monitoring method according to the embodiment of the present application, as Figure 1 shown, the flow includes the following steps:

[0053] Step S101, extracting ultrasonic parameters and classifying the ultrasonic parameters to obtain a classified parameter structure.

[0054] In the embodiment of the present application, a worker performs ultrasonic detection through an ultrasonic detector and other ultrasonic detection equipment, and a large amount of ultrasonic parameters are generated in the human-computer interaction process. The ultrasonic parameters generated by the ultrasonic detection equipment in the ultrasonic detection process are extracted. The ultrasonic parameters include detection parameters related to an ultrasonic probe and parameters common to an ultrasonic system, and the like. The ultrasonic parameters are classified to obtain a classified parameter structure, so as to facilitate analysis of the ultrasonic parameters.

[0055] Step S102, generating a parameter tree according to a node hierarchical manner based on the classified parameter structure.

[0056] In the embodiment of the present application, the classified parameter structure is taken as a branch node, and a parameter tree is generated according to a node hierarchical manner. Specifically, the parameter tree refers to a structure formed by parameters according to a logical structure in a data analysis process, and the tree structure of the parameter tree is determined according to the logical relationship between the parameters. The classified parameter structure is taken as a branch node, and a parameter tree corresponding to the ultrasonic parameters is established.

[0057] Since the parameter tree has a hierarchical structure, the parameter tree can monitor the influence of upper parameter changes on lower parameter changes, and realize monitoring of parameter linkage. The parameter tree can perform correctness verification of parameter linkage, compare parameter linkage input, output and process parameters, conveniently and quickly locate error points, and report error paths, so as to locate error nodes and improve debugging efficiency. At the same time, the introduction of the parameter tree can generate a parameter linkage sequence table for the linkage process, and compare and verify the parameter linkage table obtained by the traditional manual grooming of the linkage range, so that the parameter linkage range and the manually groomed linkage range complement each other and verify each other, thereby reducing the probability of errors.

[0058] In step S103, the parameter nodes stored in the parameter tree are compared with the pre-backup parameter nodes to obtain a comparison result.

[0059] In the embodiment of the application, the parameter nodes stored in the parameter tree and the pre-backup parameter nodes are compared to monitor the parameter changes. The parameter nodes stored in the parameter tree and the pre-backup parameter nodes are used as the data sources for comparison to obtain a comparison result.

[0060] In step S104, the change of the ultrasonic parameters is automatically monitored according to the comparison result.

[0061] In the embodiment of the application, the change of the ultrasonic parameters is monitored according to the comparison result of the parameter nodes stored in the parameter tree and the pre-backup parameter nodes, so as to automatically monitor the change of the ultrasonic parameters for parameter calculation, issuance and storage.

[0062] The ultrasonic parameter monitoring method provided in the embodiment divides and classifies the extracted ultrasonic parameters, generates a parameter tree in a node hierarchical manner according to the classified ultrasonic parameters, stores the parameter nodes by using the parameter tree, monitors the influence of upper parameter changes on lower parameter changes by using the hierarchical structure of the parameter tree, compares the parameter nodes stored in the parameter tree with the pre-backup parameter nodes, and automatically monitors the change of the ultrasonic parameters according to the comparison result, thereby replacing manual monitoring, reducing the dependence on high professional personnel, and saving labor cost and time cost.

[0063] In the embodiment, an ultrasonic parameter monitoring method is provided, which can be used for the mobile terminal described above, Figure 2 The flowchart of the ultrasonic parameter monitoring method according to the embodiment of the application is shown in FIG. 2, which includes the following steps: Figure 2

[0064] In step S201, the ultrasonic parameters are extracted, and the ultrasonic parameters are divided and classified to obtain a classified parameter structure.

[0065] ​Specifically, in the above step S201, the ultrasound parameters are divided and classified, and the classified parameter structure includes:

[0066] Step S2011: Classify the ultrasound parameters according to the ultrasound imaging mode to obtain the first layer of ultrasound parameters.

[0067] Step S2012: Classify the ultrasound parameters according to their scope of application to obtain the second layer of ultrasound parameters.

[0068] Step S2013: Classify the ultrasound parameters according to the specific services related to the parameters to obtain the third layer of ultrasound parameters.

[0069] In step S2014, the three-layer ultrasound parameters consisting of the first-layer ultrasound parameters, the second-layer ultrasound parameters, and the third-layer ultrasound parameters are determined as the classified ultrasound parameters.

[0070] In the embodiment of the present invention, the ultrasound parameters are divided and classified into three structures.

[0071] The first layer is categorized by ultrasound imaging mode, including B-mode, C-mode, PW mode, CW mode, and M-mode. B-mode uses brightness to display echo strength. Scanning in B-mode produces a grayscale image, or black-and-white B-frame image, that reflects the body's tissue structure. Scanning in C-mode produces a C-frame image that reflects blood flow distribution within the body. PW mode uses pulsed Doppler mode to transmit and receive pulse signals to obtain blood flow information. CW mode utilizes continuous Doppler technology for examinations. M-mode records on a fixed sampling line, observing changes in tissues and organs over time.

[0072] The second layer is classified according to the scope of parameter application, which is divided into front-end parameters and back-end parameters. The front-end parameters are related to FPGA and involve imaging, while the back-end parameters are related to image algorithms and involve image post-processing.

[0073] The third layer categorizes parameters by their specific business relevance. Front-end parameters are categorized as transmit-related, beamforming, extraction, timing, signal processing, and upload. Back-end parameters are mostly generated offline, requiring only parameter reading based on rules. Some parameters requiring simple calculations are categorized as either direct reading or calculation generation.

[0074] Specifically, the emission correlation is a parameter generated in the initial stage of ultrasonic imaging, usually a parameter generated by the ultrasonic probe (or ultrasonic transducer) converting electrical energy into ultrasonic energy emission. The beamforming is a parameter generated in the process of beamforming when the ultrasonic probe receives the reflected return signal after the ultrasonic emission encounters different tissue interfaces. The extraction is a parameter generated in the process of removing noise, enhancing signals and other processing of the emitted wave. The timing is a parameter generated when the round-trip time of ultrasonic waves is calculated in the ultrasonic imaging process. The signal processing is a parameter generated in the process of data processing of ultrasonic waves and ultrasonic imaging. The uploading is to upload the parameters to the cloud or the ultrasonic system.

[0075] The ultrasonic parameters are classified and categorized mainly based on the ultrasonic system scheme document. The form of the ultrasonic system scheme document is parsed through a preset script to automatically generate the identification of the meaning of each layer of parameters, so as to facilitate the subsequent binding of the parameters.

[0076] The ultrasonic parameters are classified and categorized by ultrasonic mode imaging mode, parameter range, and specific related business, and the classified first layer ultrasonic parameters, second layer ultrasonic parameters, and third layer ultrasonic parameters are combined to complete the classification of the ultrasonic parameters, so as to facilitate the analysis of the ultrasonic parameters.

[0077] Step S202, generating a parameter tree according to the node hierarchical structure of the classified parameters.

[0078] Specifically, the above step S202 includes:

[0079] Step S2021, concatenating the three layers of ultrasonic parameters to generate a parameter tree corresponding to each ultrasonic imaging mode.

[0080] Step S2022, determining whether the linkage parameter exists in the branch node corresponding to the three layers of ultrasonic parameters.

[0081] Step S2023, if the linkage parameter does not exist in the branch node corresponding to the three layers of ultrasonic parameters, a corresponding branch node is added in the three layers of ultrasonic parameters.

[0082] In the embodiment of the present application, the three layers of ultrasonic parameters classified above are concatenated by coding in the initial stage. Since ultrasonic has different imaging modes, the parameters are classified according to the ultrasonic imaging mode to generate a parameter tree corresponding to each ultrasonic imaging mode. In the process of human-computer interaction parameter linkage, a plurality of nodes of the parameter tree of each ultrasonic imaging mode are passed through. For each ultrasonic imaging mode parameter tree, these passed nodes constitute a sub-parameter tree. For human-computer interaction parameters, the above sub-parameter tree is combined to construct a parameter tree.

[0083] Each linkage parameter has a corresponding trigger condition for the entire parameter model, that is, the trigger for the parameter after user operation is the change of the gear adjusted by the user, and the change of the gear adjusted by the user is reflected in the three-layer ultrasonic parameter model, so it is necessary to determine whether the linkage parameter has the three-layer ultrasonic parameter, if not, it proves that the three-layer ultrasonic parameter is indeed, and node insertion is needed to perfect the three-layer ultrasonic parameter.

[0084] Firstly, it is judged whether the linkage parameter has the branch node corresponding to the three-layer ultrasonic parameter, if the linkage parameter has the branch node corresponding to the three-layer ultrasonic parameter in the pre-existing branch node, the branch node is skipped, if the pre-existing branch node of the parameter tree does not have the branch node corresponding to the three-layer ultrasonic parameter, the corresponding branch node is added in the three-layer ultrasonic parameter, and the parameter tree is updated.

[0085] By connecting the three-layer ultrasonic parameters in series, the parameter tree corresponding to each ultrasonic imaging mode is generated, and when the linkage parameter does not have the branch node corresponding to the three-layer ultrasonic parameter, the corresponding branch node is added in the three-layer ultrasonic parameter to establish a complete parameter tree, so that the parameter nodes stored on the parameter tree are monitored.

[0086] In step S203, the linkage path of the linkage parameter is preset by using the comparison table.

[0087] In step S204, the linkage path corresponding to the linkage parameter is determined by traversing the comparison table.

[0088] In the embodiment of the application, in the human-computer interaction process, the linkage path of the linkage parameter is preset by using the comparison table, so that the data is analyzed. By traversing the comparison table, the linkage path corresponding to the linkage parameter can be determined in combination with the parameter linkage total interface.

[0089] The comparison table can be generated in the human-computer interaction process, and each time the human-computer interaction process can add a node, the added node needs to be stored and the comparison table needs to be updated. The comparison table can also be pre-configured.

[0090] The linkage path of the linkage parameter is preset by using the comparison table, and the linkage path corresponding to the linkage parameter is determined by traversing the comparison table, so that the parameter nodes are compared.

[0091] Specifically, the above step S204 includes:

[0092] In step S2041, the parameter is randomly adjusted by using the smoke script.

[0093] In step S2042, if the triggered linkage path does not exist in the comparison table, the linkage path is inserted into the comparison table, and the comparison table is used for trigger counting, after the comparison table is trained and perfected to reach a stable state, the useless records in the comparison table are removed, and the specific path of the parameter linkage is obtained.

[0094] In the embodiment of the present application, the smoke script is a smoke test script, and the smoke script can be used to automatically adjust the parameters randomly without human intervention, so as to realize automatic parameter adjustment. If the triggered linkage path does not exist in the comparison table, the linkage path is inserted into the comparison table, and the comparison table is triggered for counting, so as to compare the parameter nodes. After the comparison table is trained and perfected and reaches a stable state, the useless records in the comparison table are deleted, so as to avoid the interference of the useless records on the specific path of the determined parameter linkage.

[0095] The human-computer interaction operation process is recorded, and the operations are randomly shuffled and combined, the script is used to replace the human operation, and the complete path node is determined in advance, which is the path node of the combined parameter tree of each human-computer interaction.

[0096] When the parameters on the path are compared, the parameters on the path may not change, but the parameters on the path may affect the change of other parameters, so comparison according to the path can avoid the situation that the parameter change cannot be monitored.

[0097] The smoke script is used to automatically adjust the parameters randomly without human intervention, so as to improve the efficiency of parameter adjustment. When the triggered linkage path does not exist in the comparison table, the linkage path is inserted into the comparison table, so as to obtain the completed linkage path. After the comparison table training reaches a stable state, the useless records in the comparison table are deleted, so as to avoid the interference of the useless records on the specific path of the determined parameter linkage.

[0098] In step S205, the parameter nodes stored in the parameter tree are compared with the pre-backup parameter nodes, and a comparison result is obtained.

[0099] For details, please refer to Figure 1 The step S103 of the embodiment shown in the figure will not be described here.

[0100] In step S206, the change of the ultrasonic parameter is automatically monitored according to the comparison result.

[0101] Specifically, the step S206 includes:

[0102] In step S2061, if the comparison result is consistent, it is determined that the ultrasonic parameter does not change.

[0103] In step S2062, if the comparison result is inconsistent, it is determined that the ultrasonic parameter changes.

[0104] In an embodiment of the present invention, parameter changes are monitored by comparing parameters. The current parameter and the backup parameter are used as the data source for comparison, and the trigger parameter node at the source is compared. This layered parameter comparison improves efficiency. If the comparison result of the current parameter and the backup parameter is consistent, it is determined that the ultrasound parameter has not changed. If the comparison result of the current parameter and the backup parameter is inconsistent, it is determined that the ultrasound parameter has changed, thereby achieving monitoring of ultrasound parameter changes.

[0105] By comparing the current parameters with the backup parameters, it is determined whether the ultrasound parameters have changed, so that the ultrasound parameters can be monitored when they change.

[0106] Step S2063: automatically monitor changes in ultrasonic parameters, obtain monitoring results, and update backup parameters according to the monitoring results.

[0107] In an embodiment of the present invention, changes in ultrasonic parameters are automatically monitored to obtain monitoring results. When ultrasonic parameters change, corresponding parameter linkage is triggered, and backup parameters are updated according to the monitoring results, so that the latest data source is used when comparing parameters to achieve the purpose of monitoring parameter changes.

[0108] The ultrasonic parameter monitoring method provided in this embodiment updates the backup parameters based on the monitoring results of the automatically monitored ultrasonic parameter changes so that when the parameters are compared again, the data source is the latest backup parameters, thereby improving the accuracy of the parameter comparison results.

[0109] This embodiment also provides an ultrasonic parameter monitoring device for implementing the above-mentioned embodiments and preferred embodiments. Details already described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0110] This embodiment provides an ultrasonic parameter monitoring device, such as Figure 3 As shown, including:

[0111] The classification module 301 is used to extract ultrasound parameters, classify the ultrasound parameters, and obtain a classified parameter structure.

[0112] The generating module 302 is used to generate a parameter tree by arranging the classified parameter structure in a node-layered manner.

[0113] The comparison module 303 is configured to compare the parameter nodes stored in the parameter tree with the pre-backed-up parameter nodes to obtain a comparison result.

[0114] The monitoring module 304 is configured to automatically monitor changes in the ultrasound parameters based on the comparison results.

[0115] In some optional embodiments, the categorizing module 301 comprises:

[0116] a first categorizing unit configured to categorize the ultrasound parameters according to the ultrasound imaging modes to obtain first-level ultrasound parameters.

[0117] a second categorizing unit configured to categorize the ultrasound parameters according to the parameter action ranges to obtain second-level ultrasound parameters.

[0118] a third categorizing unit configured to categorize the ultrasound parameters according to the parameter specific related businesses to obtain third-level ultrasound parameters.

[0119] a first determining unit configured to determine the three-level ultrasound parameters composed of the first-level ultrasound parameters, the second-level ultrasound parameters and the third-level ultrasound parameters as the categorized ultrasound parameters.

[0120] In some optional embodiments, the generating module 302 comprises:

[0121] a generating unit configured to concatenate the three-level ultrasound parameters to generate a parameter tree corresponding to each ultrasound imaging mode.

[0122] a judging unit configured to judge whether the linkage parameter exists in a branch node corresponding to the three-level ultrasound parameters.

[0123] an adding unit configured to add the branch node corresponding to the three-level ultrasound parameters in the three-level ultrasound parameters if the linkage parameter does not exist in the branch node corresponding to the three-level ultrasound parameters.

[0124] In some optional embodiments, the apparatus further comprises:

[0125] a presetting module configured to preset the linkage path of the linkage parameter by using the comparison table.

[0126] a traversing module configured to traverse the comparison table to determine the linkage path corresponding to the linkage parameter.

[0127] In some optional embodiments, the traversing module comprises:

[0128] a parameter adjusting unit configured to adjust the parameters randomly by using the smoke script.

[0129] an inserting unit configured to insert the linkage path into the comparison table if the triggered linkage path does not exist in the comparison table, and perform trigger counting by using the comparison table, and delete the useless records in the comparison table after the comparison table is trained and perfected to reach a stable state to obtain the specific path of the parameter linkage.

[0130] In some optional embodiments, the monitoring module 304 comprises:

[0131] The second determining unit is configured to determine that the ultrasound parameters have not changed if the comparison result is consistent.

[0132] The third determining unit is configured to determine that the ultrasound parameter has changed if the comparison result is inconsistent.

[0133] In some optional embodiments, the device further comprises:

[0134] The update module is used to automatically monitor changes in ultrasonic parameters, obtain monitoring results, and update backup parameters based on the monitoring results.

[0135] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0136] The ultrasonic parameter monitoring device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0137] The embodiment of the present invention also provides a computer device having the above Figure 3 The ultrasonic parameter monitoring device shown.

[0138] See also Figure 4 , Figure 4 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 4 A processor 10 is taken as an example.

[0139] The processor 10 can be a central processor, a network processor, or a combination thereof. The processor 10 can further include a hardware chip. The hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device can be a complex programmable logic device, a field programmable logic device, a general array logic, or any combination thereof.

[0140] The memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods illustrated in the above embodiments.

[0141] The memory 20 can include a program storage area and a data storage area. The program storage area can store an operating system and application programs required by at least one function. The data storage area can store data created according to the use of the computer device, etc. In addition, the memory 20 can include a high-speed random access memory, and can further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some optional embodiments, the memory 20 can optionally include a memory disposed remotely with respect to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0142] The memory 20 can include a volatile memory, such as a random access memory, and can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid state disk. The memory 20 can further include a combination of the above types of memories.

[0143] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 can be connected through a bus or other means, Figure 4 For example, the connection through the bus is taken as an example.

[0144] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, etc. The output device 40 can include a display device, etc.

[0145] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0146] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. An ultrasonic parameter monitoring method, characterized by, The method comprises: extracting the ultrasonic parameters and classifying the ultrasonic parameters to obtain a classified parameter structure; generating a parameter tree according to a node hierarchical manner of the classified parameter structure; comparing the parameter nodes stored in the parameter tree with the parameter nodes backed up in advance to obtain a comparison result; automatically monitoring the change of the ultrasonic parameters according to the comparison result; the classification of the ultrasonic parameters to obtain the classified parameter structure comprises: classifying the ultrasonic parameters according to ultrasonic imaging modes to obtain first-level ultrasonic parameters; classifying the ultrasonic parameters according to parameter action ranges to obtain second-level ultrasonic parameters; classifying the ultrasonic parameters according to specific related businesses to obtain third-level ultrasonic parameters; the three-level ultrasonic parameters composed of the first-level ultrasonic parameters, the second-level ultrasonic parameters and the third-level ultrasonic parameters are determined as the classified ultrasonic parameters; the generation of the parameter tree according to the node hierarchical manner of the classified parameter structure comprises: concatenating the three-level ultrasonic parameters to generate a parameter tree corresponding to each ultrasonic imaging mode; judging whether a linkage parameter exists in a branch node corresponding to the three-level ultrasonic parameters; if the linkage parameter does not exist in the branch node corresponding to the three-level ultrasonic parameters, a corresponding branch node is added in the three-level ultrasonic parameters.

2. The method of claim 1, wherein, Before the comparison of the parameter nodes stored in the parameter tree with the parameter nodes backed up in advance, the method further comprises: presetting a linkage path of a linkage parameter by using a comparison table; traversing the comparison table to determine the linkage path corresponding to the linkage parameter.

3. The method of claim 2, wherein, The determination of the linkage path corresponding to the linkage parameter comprises: randomly adjusting the parameter by using a smoke script; if the triggered linkage path does not exist in the comparison table, the linkage path is inserted into the comparison table, and the comparison table is used for trigger counting; after the comparison table is trained and improved to a stable state, useless records in the comparison table are deleted to obtain a specific path of parameter linkage.

4. The method of claim 1, wherein, The automatic monitoring of the change of the ultrasonic parameters according to the comparison result comprises: if the comparison result is consistent, it is determined that the ultrasonic parameters do not change; if the comparison result is inconsistent, it is determined that the ultrasonic parameters change.

5. The method of claim 4, wherein, After it is determined that the ultrasonic parameters change, the method further comprises: automatically monitoring the change of the ultrasonic parameters to obtain a monitoring result, and updating the backup parameters according to the monitoring result.

6. An ultrasound parameter monitoring device, characterized by The device comprises: a classification module configured to extract the ultrasonic parameters and classify the ultrasonic parameters to obtain a classified parameter structure; a generation module configured to generate a parameter tree according to a node hierarchical manner of the classified parameter structure; a comparison module configured to compare the parameter nodes stored in the parameter tree with the parameter nodes backed up in advance to obtain a comparison result; a monitoring module configured to automatically monitor the change of the ultrasonic parameters according to the comparison result. The categorizing module is specifically configured to: categorize the ultrasonic parameters according to ultrasonic imaging modes to obtain first-layer ultrasonic parameters; categorize the ultrasonic parameters according to parameter action ranges to obtain second-layer ultrasonic parameters; categorize the ultrasonic parameters according to parameter specific related businesses to obtain third-layer ultrasonic parameters; and determine the three-layer ultrasonic parameters composed of the first-layer ultrasonic parameters, the second-layer ultrasonic parameters and the third-layer ultrasonic parameters as the categorized ultrasonic parameters. The generating module is specifically configured to: concatenate the three-layer ultrasonic parameters to generate a parameter tree corresponding to each ultrasonic imaging mode; determine whether a linkage parameter exists in a branch node corresponding to the three-layer ultrasonic parameters; and if the linkage parameter does not exist in the branch node corresponding to the three-layer ultrasonic parameters, add a corresponding branch node in the three-layer ultrasonic parameters.

7. A computer device, comprising: Comprise: A memory and a processor, which are in communication connection with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the ultrasonic parameter monitoring method in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute the ultrasonic parameter monitoring method in any one of claims 1 to 5.

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