Parameter item management method, ultrasonic device, storage medium and computer program product

Abstract

The application discloses a parameter item management method, an ultrasonic device, a computer readable storage medium and a computer program product. The method comprises the following steps: receiving an examination request, and obtaining information of a target ultrasonic probe and a target examination item corresponding to the examination request; determining an operation frequently-used position in a screen and a target frequently-used parameter item corresponding to the target ultrasonic probe and the target examination item; wherein the target frequently-used parameter item is a parameter item with an operation frequency greater than a first preset value in parameter items corresponding to the target ultrasonic probe and the target examination item; the operation frequently-used position is a target display position selected for operation on the parameter item, and the selected frequency is greater than a second preset value; and the target frequently-used parameter item is adjusted to the operation frequently-used position for display. The application realizes automatic adjustment of the position of the parameter item, and improves the examination efficiency.

Description

Technical Field

[0001] This application relates to the field of ultrasound technology, and more specifically, to a parameter management method, an ultrasound device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] Ultrasound imaging technology is widely used in disease screening and diagnosis due to its advantages such as low cost, real-time imaging, and no radiation. During ultrasound examinations, the ultrasound touchscreen serves as the main interface for users to operate and view examination results. Its display includes parameter items arranged in various interfaces such as probe diagnostic items, imaging mode parameters, measurement menus, body landmarks menus, annotation menus, and reports. The rational layout of these parameter items is crucial for users to efficiently complete the examination.

[0003] However, the default factory parameter layout of ultrasound equipment often fails to meet the personalized needs of different examination items and users. Although some ultrasound equipment allows users to manually drag and drop parameter positions for personalized layout, this requires users to spend extra time and effort to adjust, increasing workload and reducing examination efficiency.

[0004] Therefore, how to automatically adjust the position of parameter items according to the inspection requirements of different inspection items and the user's operating habits, thereby improving inspection efficiency, is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this application is to provide a parameter item management method, an ultrasound device, a computer-readable storage medium, and a computer program product that automatically adjust the position of parameter items according to the inspection needs of different inspection items and the user's operating habits, thereby improving inspection efficiency.

[0006] To achieve the above objectives, this application provides a parameter item management method applied to ultrasonic equipment, the method comprising:

[0007] Receive an examination request and obtain information about the target ultrasound probe and the target examination item corresponding to the examination request;

[0008] Determine the frequently used operation positions on the screen and the frequently used target parameter items corresponding to the target ultrasound probe and the target examination item; wherein, the frequently used target parameter items are the parameter items whose operation frequency is greater than a first preset value among the parameter items corresponding to the target ultrasound probe and the target examination item; the frequently used operation position is the target display position selected when operating on the parameter item, and the selection frequency is greater than a second preset value;

[0009] Adjust the commonly used target parameters to the commonly used operation positions for display.

[0010] Before receiving the inspection request, the process also includes:

[0011] Collect operation data for each parameter item on the screen; wherein, in the operation data, each parameter item is respectively bound to the corresponding examination item and ultrasound probe.

[0012] After collecting the operation data of each parameter item on the screen, the process further includes:

[0013] Based on the operation data of each parameter item on the screen collected within a preset time period, determine the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item;

[0014] The frequently used operation positions on the screen are determined based on the operation data of each parameter item within a preset time period.

[0015] The step of determining frequently used operation locations on the screen based on the operation data of each parameter item within a preset time period includes:

[0016] Based on the operation data of each parameter item within a preset time period, determine the operation data of the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item within the preset time period;

[0017] Determine the commonly used operation positions on the screen based on the operation data of the commonly used target parameter items.

[0018] The step of determining the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item based on the operation data of each parameter item collected on the screen within a preset time period includes:

[0019] The operation data of each parameter item on the screen collected within a preset time period, as well as the information of the target ultrasound probe and the target examination item, are input into the first deep learning model. The first deep learning model then outputs the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item.

[0020] The operation data includes the timestamp of the operation, the operation type, and the operation location, wherein the operation type includes at least click and / or drag;

[0021] If the operation type is drag, the corresponding operation position is the target display position of the drag parameter item.

[0022] The operation type also includes adjusting parameter levels.

[0023] After adjusting the commonly used target parameter items to the commonly used operation position for display, the method further includes:

[0024] The system acquires the case data of the target examination case corresponding to the examination request, inputs the case data of the target examination case into the trained second deep learning model, outputs the predicted level information of the parameter items with levels corresponding to the target ultrasound probe and the target examination item through the trained second deep learning model, and adjusts the parameter level of the displayed parameter items with levels according to the predicted level information.

[0025] This also includes:

[0026] Collect and examine case data;

[0027] A training dataset is constructed based on case data and corresponding operational data of cases examined within a preset time period;

[0028] A second deep learning model is trained using the training dataset. The trained second deep learning model is used to predict the parameter level of parameter items with level based on the case data of the target examination case.

[0029] The determination of commonly used operation locations on the screen and the commonly used target parameter items corresponding to the target ultrasound probe and the target examination item includes:

[0030] Determine a preset number of frequently used operation positions, and sort the preset number of frequently used operation positions in descending order of their selection frequency to obtain the sorting result of the frequently used operation positions;

[0031] A preset number of commonly used target parameters corresponding to the target ultrasound probe and the target examination item are determined, as well as a sorting result of the preset number of commonly used target parameters; wherein, the preset number of commonly used target parameters in the sorting result are sorted from highest to lowest operation frequency;

[0032] Accordingly, the commonly used target parameters are adjusted to be displayed in the commonly used operation positions, including:

[0033] Based on the sorting position of each target common parameter item in the sorting result of the target common parameter items, the common operation positions with the same sorting position in the sorting result of the common operation positions are determined as the common operation positions corresponding to each target common parameter item;

[0034] Adjust each of the commonly used target parameters to its corresponding commonly used position for display.

[0035] The determination of commonly used operation locations on the screen and the commonly used target parameter items corresponding to the target ultrasound probe and the target examination item includes:

[0036] Obtain the account information of the target account that initiated the inspection request;

[0037] Determine the frequently used operation locations corresponding to the account information; wherein, the frequently used operation locations are determined based on target operation data within a preset time period, and the target operation data is the operation data of the parameter items corresponding to the account information;

[0038] The target commonly used parameter items corresponding to the account information, the target ultrasound probe, and the target examination item are determined; wherein, the target commonly used parameter items are determined based on the operation data of the parameter items corresponding to the target ultrasound probe and the target examination item in the target operation data.

[0039] To achieve the above objectives, this application provides a parameter management device for use in ultrasonic equipment, the device comprising:

[0040] The first determining module is used to receive an examination request and obtain information about the target ultrasound probe and the target examination item corresponding to the examination request;

[0041] The second determining module is used to determine the frequently used operation positions on the screen and the frequently used target parameter items corresponding to the target ultrasound probe and the target examination item; wherein, the frequently used target parameter items are the parameter items whose operation frequency is greater than a first preset value among the parameter items corresponding to the target ultrasound probe and the target examination item; the frequently used operation position is the target display position selected for operating the parameter item, and the selection frequency is greater than a second preset value;

[0042] The first adjustment module is used to adjust the target commonly used parameter items to the commonly used operation position for display.

[0043] To achieve the above objectives, this application provides an ultrasonic device, comprising:

[0044] Memory, used to store computer programs;

[0045] A processor for implementing the steps of the parameter item management method described above when executing the computer program.

[0046] To achieve the above objectives, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the parameter item management method described above.

[0047] To achieve the above objectives, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the parameter item management method described above.

[0048] The parameter management method provided in this application acquires information about the target ultrasound probe and target examination item corresponding to the ultrasound device when it receives an examination request. Based on the analysis of historical operation data of the parameter items corresponding to the target ultrasound probe and target examination item, it can accurately identify frequently used parameter items with an operation frequency higher than a first preset value. These frequently used parameter items are determined according to the user's usage frequency during actual operation, reflecting the user's operating habits and preferences in a specific examination scenario. Simultaneously, it also identifies frequently used operation positions on the screen with an operation frequency higher than a second preset value. These positions are frequently selected by the user during operation, ensuring that the display of parameter items better matches the user's operating habits. By automatically adjusting the target frequently used parameter items to their frequently used operation positions, users can more quickly find and use these frequently used parameter items during examinations, reducing the time spent searching for and adjusting parameter items during the examination process, thereby significantly improving operational efficiency. This automated parameter layout adjustment mechanism not only better adapts to the specific needs of different examination items but also automatically optimizes the display logic of parameter items according to the user's operating habits, making the operation of the ultrasound device more convenient and efficient, and greatly improving the user's operating experience. This application also discloses a parameter management device, an ultrasonic device, a computer-readable storage medium, and a computer program product, which can achieve the same technical effects as described above.

[0049] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this application. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. The drawings are used to provide a further understanding of this disclosure and constitute a part of the specification. They are used together with the following detailed description to explain this disclosure, but do not constitute a limitation of this disclosure. In the drawings:

[0051] Figure 1 This is a flowchart illustrating a parameter item management method according to an exemplary embodiment;

[0052] Figure 2 This is a flowchart illustrating another parameter item management method according to an exemplary embodiment;

[0053] Figure 3 A flowchart illustrating yet another parameter item management method according to an exemplary embodiment;

[0054] Figure 4 This is a structural diagram illustrating a parameter item management device according to an exemplary embodiment;

[0055] Figure 5 This is a structural diagram of an ultrasonic device according to an exemplary embodiment. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Furthermore, in the embodiments of this application, "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0057] This application discloses a parameter item management method that automatically adjusts the position of parameter items according to the inspection requirements of different inspection items and the user's operating habits, thereby improving inspection efficiency.

[0058] See Figure 1 A flowchart illustrating a parameter item management method according to an exemplary embodiment, such as... Figure 1 As shown, it includes:

[0059] S101: Receive an inspection request and obtain information about the target ultrasound probe and the target inspection item corresponding to the inspection request;

[0060] An ultrasound probe is a component of an ultrasound examination device. Different types of probes are suitable for different examination sites and needs. An ultrasound device can be equipped with multiple ultrasound probes. Users can select different probes depending on the examination item. For example, ultrasound probes can include linear array probes, convex array probes, and phased array probes. Linear array probes are mainly used for superficial examinations, and their corresponding examination items can include the thyroid gland, breast, muscles and bones, and blood vessels. Convex array probes are suitable for examinations of the abdomen, kidneys, urinary system, and early, mid, and late pregnancy in obstetrics. Phased array probes are suitable for examinations of the heart, etc. Each examination item has multiple adjustable parameters, such as gain, depth, and frequency. These parameters affect image quality and examination results. It should be noted that these operable or adjustable parameters are interface parameters displayed on the screen. For desktop ultrasound devices, these are usually displayed on the touchscreen. As a feasible implementation, before receiving an examination request, the device further includes: acquiring the operation data of each parameter item on the screen; wherein, in the operation data, each parameter item is respectively bound to the corresponding examination item and ultrasound probe.

[0061] During ultrasound examinations (including the current examination and previous historical examinations), the system monitors in real-time the doctor's actions on different types of ultrasound probes and parameters of different examination items. The system captures the doctor's actions through an event monitoring mechanism. The action data includes timestamps, action types, and action locations. Timestamps record the specific time the action occurred. Action types can include clicking and dragging. Clicking is typically used to select or activate a parameter, and can include clicking using input tools like a mouse or touchscreens. Dragging is used to change the position of a parameter, moving it to a more convenient location on the screen. The action location records the specific location where the action occurred. For clicking, the location is usually the exact coordinates of the point on the screen where the doctor clicked; for dragging, the location is more specific. When a doctor needs to move a parameter from one location to another, a dragging action is performed. The starting point of a dragging action is the initial position of the parameter, and the ending point is the target position where the parameter is placed. For dragging actions, the system records not all intermediate positions during the dragging process, but only the endpoint, i.e., the final target display position where the parameter is placed. This target display location reflects the specific position the doctor wants the parameters to be displayed, representing the most convenient location chosen by the doctor after careful consideration. Subsequently, the system binds this operational data to the type of ultrasound probe currently used and the examination procedure, ensuring that subsequent analysis can differentiate operating habits under different probes and examination procedures.

[0062] For example, suppose a doctor frequently adjusts the gain and depth parameters during a thyroid examination. The system records this operational data and links it to the "thyroid examination" test and the high-frequency probe used. This allows the system to accurately understand the doctor's preferences for gain and depth parameters during the thyroid examination.

[0063] By collecting and binding operational data, the system can comprehensively record doctors' operating habits in different examination scenarios, providing a data foundation for subsequent personalized parameter settings. This process not only improves data accuracy but also provides necessary correlation information for subsequent automated adjustments.

[0064] In step S101, the user selects the target ultrasound probe and the target examination item for this ultrasound examination. When the ultrasound equipment receives the examination request, it obtains the information of the target ultrasound probe and the target examination item selected by the user.

[0065] An examination request can be initiated by the user by clicking a specific button on the ultrasound device, or it can be considered initiated after the user completes the registration of patient information. The user can then select the type or model of the ultrasound probe and the diagnostic item (i.e., the examination item) on the ultrasound device's screen, allowing the ultrasound device to obtain information about the target ultrasound probe and the target examination item.

[0066] S102: Determine the frequently used operation positions on the screen and the frequently used target parameter items corresponding to the target ultrasound probe and the target examination item; wherein, the frequently used target parameter items are the parameter items whose operation frequency is greater than a first preset value among the parameter items corresponding to the target ultrasound probe and the target examination item; the frequently used operation position is the target display position selected for operating the parameter item, and the selection frequency is greater than a second preset value;

[0067] In this step, frequently used operation positions on the screen and the target frequently used parameter items corresponding to the target ultrasound probe and target examination items are identified. Based on the operation data of the parameter items corresponding to the target ultrasound probe and target examination items, the operation frequency of the parameter items is analyzed. If the operation frequency of a certain parameter item is greater than a first preset value, then that parameter item is identified as a target frequently used parameter item.

[0068] Frequently used operation locations refer to the target display positions that users frequently select during operation. Specifically, the determination of frequently used operation locations is based on user actions on parameter items, including dragging and clicking. First, if a parameter item is never dragged during use but is frequently clicked, it indicates that the parameter item is frequently used by the user at its current position. In this case, the current position of the parameter item is considered a frequently used operation location. For example, if a doctor consistently clicks a parameter item at a certain target display position during daily operations, this indicates that the target display position is the user's habitual operation location. Second, if a user frequently drags a parameter item to a certain target display position, and that target position is frequently clicked, then that target display position is also considered a frequently used operation location. This is because frequent dragging and clicking behavior indicates that the user tends to place the parameter item at that target display position for operation, thereby improving the convenience and efficiency of the operation. For example, during various examinations, if a doctor frequently moves different parameter items to a certain target display position on the touchscreen (e.g., the upper left corner) and frequently clicks the parameter item at that target display position after moving it, then that target display position is the user's habitual operation location. In other words, frequently used operation locations are determined by statistically analyzing the frequency with which a particular location is dragged and clicked. When a location is selected for an operation (including dragging and / or clicking) and its selection frequency exceeds a second preset value, that location is identified as a frequently used operation location. Therefore, identifying frequently used operation locations allows us to pinpoint the locations that doctors are most accustomed to and use most frequently during operations.

[0069] As a feasible implementation method, after collecting the operation data of each parameter item in the screen, the method further includes: determining the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item based on the operation data of each parameter item collected in the screen within a preset time period; and determining the commonly used operation positions in the screen based on the operation data of each parameter item within the preset time period.

[0070] In practice, a time range, or preset time period, is set for statistical analysis of operational data, such as one day, one week, or one month. Within this preset time period, operational data for different examination items corresponding to different types of ultrasound probes is collected, and the frequency of operation for each parameter is analyzed. If the frequency of operation for a certain parameter exceeds a first preset value, that parameter is identified as a frequently used parameter. The frequently used parameters are determined for each type of ultrasound probe and examination item separately. For example, statistical analysis might reveal that doctors frequently adjust depth and Doppler parameters during fetal examinations. If the frequency of operation for these parameters exceeds a first preset value, then depth and Doppler parameters are identified as frequently used parameters. Therefore, by analyzing the operational data for each parameter, the frequently used parameters for examination items corresponding to different types of ultrasound probes can be determined, thus allowing the identification of the target frequently used parameters for the target ultrasound probe and the target examination item.

[0071] As a feasible implementation method, determining the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item based on the operation data of each parameter item in the screen collected within a preset time period includes: inputting the operation data of each parameter item in the screen collected within a preset time period and the information of the target ultrasound probe and the target examination item into a first deep learning model, and outputting the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item through the first deep learning model.

[0072] In practice, operational data of different types of ultrasound probes and corresponding examination items collected within a preset time period, along with information about the target ultrasound probe and the target examination item, are input into a pre-trained first deep learning model. This model's task is to analyze this operational data to identify which parameters are frequently used by doctors in specific examination items. Through the analysis and processing of the first deep learning model, it outputs the target commonly used parameters corresponding to the target ultrasound probe and the target examination item. These commonly used parameters are determined based on information such as the frequency of operation reflected in the operational data, reflecting the doctor's preferences and usage habits for certain parameters when using the target ultrasound probe to perform the target examination item. Using a deep learning model, commonly used parameters can be automatically learned and identified from a large amount of operational data without the need for manually setting complex rules, thus improving the accuracy and efficiency of identification.

[0073] At the same time, the operation data of each parameter item within the preset time period is analyzed to determine the commonly used operation positions on the screen. By determining the commonly used operation positions, the positions that doctors are most accustomed to and use most frequently during the operation can be identified.

[0074] In a preferred embodiment, determining the frequently used operation location on the screen based on the operation data of each parameter item within a preset time period includes: determining the operation data of the target frequently used parameter items corresponding to the target ultrasound probe and the target examination item within the preset time period based on the operation data of each parameter item within the preset time period; and determining the frequently used operation location on the screen based on the operation data of the target frequently used parameter items.

[0075] In practice, the operation data of the target ultrasound probe and the target examination item corresponding to the target commonly used parameter items are determined from the operation data of each parameter item within a preset time period. The operation data of the target ultrasound probe and the target examination item corresponding to the target commonly used parameter items are analyzed separately to determine the commonly used operation positions on the screen, so that the determined commonly used operation positions are more in line with the doctor's actual operating habits for the target ultrasound probe and the target examination item.

[0076] It should be noted that this embodiment does not limit the timing of analyzing operational data. Operational data collected within a preset time period can be analyzed and stored before receiving an examination request to determine commonly used operation locations on the screen and commonly used parameters for different examination items corresponding to different types of ultrasound probes. When an examination request is received, the pre-determined commonly used operation locations and the target commonly used parameters corresponding to the target ultrasound probe and the target examination item can be directly invoked. Alternatively, after receiving an examination request, the pre-collected operational data within a preset time period can be used to determine the commonly used operation locations on the screen, and the pre-collected operational data corresponding to the target ultrasound probe and the target examination item within the preset time period can be used to determine the target commonly used parameters corresponding to the target ultrasound probe and the target examination item.

[0077] In a preferred embodiment, determining the frequently used operation locations on the screen and the frequently used target parameter items corresponding to the target ultrasound probe and the target examination item includes: obtaining account information of the target account that initiated the examination request; determining the frequently used operation locations corresponding to the account information; wherein the frequently used operation locations are determined based on target operation data within a preset time period, and the target operation data is the operation data of the parameter items corresponding to the account information; determining the frequently used target parameter items corresponding to the account information, the target ultrasound probe, and the target examination item; wherein the frequently used target parameter items are determined based on the operation data of the parameter items corresponding to the target ultrasound probe and the target examination item in the target operation data.

[0078] In practice, when an account logs in, firstly, the account information, including the account's identifier, is retrieved from the login information. Secondly, when an inspection request is received, the target account that initiated the request is identified. Based on the target account's account information, the database is used to filter the target account's operation data within a preset time period, i.e., the target operation data. By analyzing the target operation data, the frequently used operation locations and frequently used parameter items corresponding to the target account are determined.

[0079] It should be noted that this embodiment does not limit the timing of analyzing the target operation data. Before receiving an inspection request, the target operation data can be pre-analyzed to determine commonly used operation locations on the screen and commonly used parameters for different inspection items corresponding to different types of ultrasound probes, and stored. When an inspection request is received, the pre-determined commonly used operation locations and the target ultrasound probe and target inspection item's corresponding commonly used parameters can be directly invoked. Alternatively, after receiving an inspection request, the pre-collected target operation data can be used to determine the commonly used operation locations on the screen, and the operation data corresponding to the target ultrasound probe and target inspection item can be invoked from the pre-collected target operation data to determine the target account, target ultrasound probe, and target inspection item's corresponding commonly used parameters.

[0080] When analyzing target data, the frequency of use for each parameter item is statistically analyzed to determine which parameters are frequently used by users, i.e., commonly used parameters. Simultaneously, by analyzing user dragging and clicking behavior on parameter items, the preferred operation positions of users are determined, i.e., frequently used target operation positions. The process of determining frequently used target parameters and operation positions has been previously explained and will not be repeated here.

[0081] As can be seen, through the above implementation method, the commonly used parameter items and frequently used operation locations of different users can be bound to the user's account information. When it is detected that a user has logged into the target account and initiated an examination request, the target account, target ultrasound probe and target examination item corresponding to the target commonly used parameter items are automatically adjusted to the frequently used operation locations corresponding to the target account for display. This realizes targeted parameter item adjustments for different users, improves the flexibility of parameter item adjustments, and further enhances the user experience.

[0082] S103: Adjust the commonly used target parameter items to the commonly used operation position for display.

[0083] In this step, frequently used parameters are automatically rearranged and displayed in their most frequently accessed positions. By automatically adjusting the parameter layout, frequently used parameters can be quickly placed in the doctor's most comfortable location based on the specific needs of the current examination request. This not only reduces the doctor's operational steps but also improves examination efficiency and user experience.

[0084] For example, suppose the doctor selects a low-frequency probe and the fetus as the examination item. Previous statistical analysis shows that the commonly used parameters in fetal examinations are depth and Doppler parameters, and these parameters are typically located in the upper left and upper right corners of the touchscreen. Therefore, automatically adjusting the depth and Doppler parameters to these positions facilitates the doctor's examination.

[0085] The parameter item management method provided in this application acquires information about the target ultrasound probe and target examination item corresponding to the examination request. Based on the analysis of historical operation data of the parameter items corresponding to the target ultrasound probe and target examination item, it can accurately identify frequently used parameter items with an operation frequency higher than a first preset value. These frequently used parameter items are determined according to the user's usage frequency during actual operation, reflecting the user's operating habits and preferences in a specific examination scenario. Simultaneously, it also identifies frequently used operation positions on the screen with an operation frequency higher than a second preset value. These positions are frequently selected by the user during operation, ensuring that the display of parameter items better matches the user's operating habits. By automatically adjusting the target frequently used parameter items to the frequently used operation positions, users can find and use these frequently used parameter items more quickly during examinations, reducing the time spent searching for and adjusting parameter items during the examination process, thereby significantly improving operational efficiency. This automated parameter layout adjustment mechanism not only better adapts to the specific needs of different examination items but also automatically optimizes the display logic of parameter items according to the user's operating habits, making the operation of ultrasound equipment more convenient and efficient, and greatly improving the user's operating experience.

[0086] This application discloses a parameter item management method. Compared with the previous embodiment, this embodiment further explains and optimizes the technical solution. Specifically:

[0087] See Figure 2 A flowchart illustrating another parameter item management method according to an exemplary embodiment, such as... Figure 2 As shown, it includes:

[0088] S201: Receive an inspection request and obtain information about the target ultrasound probe and the target inspection item corresponding to the inspection request;

[0089] S202: Determine a preset number of frequently used operation positions, and sort the preset number of frequently used operation positions in descending order of their selection frequency to obtain the sorting result of the frequently used operation positions;

[0090] In this step, based on the operation data of each parameter item within a preset time period, the frequency with which the doctor moves the parameter item to different display positions is statistically analyzed. Frequency is used to describe the number of times the doctor moves a particular parameter item to a particular position. Based on the selection frequency, a preset number (e.g., 5 or 10) of commonly used positions on the screen are determined; these positions are the display positions most frequently selected by the doctor during the operation. Then, these commonly used positions are sorted from highest to lowest selection frequency to obtain the commonly used position ranking result.

[0091] S203: Determine a preset number of commonly used target parameter items corresponding to the target ultrasound probe and the target examination item, and a sorting result of the preset number of commonly used target parameter items; wherein, the preset number of commonly used target parameter items in the sorting result are sorted from largest to smallest according to the operation frequency;

[0092] In this step, based on the operation data corresponding to the target ultrasound probe and target examination items within a preset time period, the operation frequency of each parameter item is calculated. Operation frequency refers to the number of times the doctor adjusts a certain parameter item. Based on the operation frequency, a preset number (e.g., 5 or 10) of commonly used target parameters corresponding to the target ultrasound probe and target examination items are determined, along with the ranking of these commonly used target parameters according to their operation frequency from high to low.

[0093] It should be noted that this embodiment does not limit the timing of analyzing operational data, determining the sorting results of commonly used positions, and determining the sorting results of commonly used target parameters. Before receiving an inspection request, operational data collected within a preset time period can be analyzed in advance to determine the commonly used operational positions on the screen and their sorting results, as well as the commonly used parameter items and their sorting results for different types of ultrasound probes corresponding to different inspection items. This information is then stored. When an inspection request is received, the pre-determined commonly used operational positions and their sorting results, as well as the commonly used target parameters and their sorting results for the target ultrasound probe and the target inspection item, are directly invoked. Alternatively, after receiving an inspection request, the pre-collected operational data within a preset time period can be used to determine the commonly used operational positions on the screen and their sorting results, and the pre-collected operational data for the target ultrasound probe and the target inspection item within the preset time period can be used to determine the commonly used target parameters and their sorting results for the target ultrasound probe and the target inspection item.

[0094] S204: Based on the sorting position of each target common parameter item in the sorting result of the target common parameter items, determine the common operation positions with the same sorting position in the sorting result of the common operation positions as the common operation positions corresponding to each target common parameter item;

[0095] In this step, based on the ranking of each frequently used target parameter in the ranking results, the commonly used positions for operations with the same ranking position in the commonly used positions ranking results are found. For example, if depth is the first-ranked parameter in the ranking results, then the first-ranked commonly used operation position in the commonly used positions ranking results is assigned to the depth parameter. This process ensures that each frequently used target parameter is adjusted to the position that doctors are most familiar with and use most frequently, thereby optimizing the parameter layout of the touchscreen.

[0096] S205: Adjust each of the commonly used target parameters to the corresponding commonly used operation position for display.

[0097] In this step, based on the correspondence established in the previous step, each commonly used parameter item is adjusted to its corresponding frequently used position for display. For example, if the depth parameter item is assigned to the upper left corner of the touchscreen, it is automatically adjusted to that position. This process reduces the time doctors spend searching for and adjusting parameters during examinations, improving operational efficiency and user experience.

[0098] Therefore, this embodiment provides a clear basis for optimizing the layout of parameter items by sorting commonly used operation locations and commonly used parameter items separately. When an examination request for a target case is received, the system can quickly identify the target ultrasound probe, target examination item, and target commonly used parameter items corresponding to that case, and adjust them to their corresponding commonly used operation locations based on the sorting results of the target commonly used parameter items. This process not only reduces the time doctors spend searching for and adjusting parameters during the examination, but also optimizes the parameter layout of the touchscreen, enabling doctors to access and operate the most frequently used parameter items more quickly. Ultimately, by automatically adjusting the position of parameter items, the system improves operational efficiency and enhances the user experience.

[0099] This application discloses a parameter item management method. Compared with the first embodiment, this embodiment further explains and optimizes the technical solution. Specifically:

[0100] See Figure 3 A flowchart illustrating another parameter item management method according to an exemplary embodiment, such as... Figure 3 As shown, it includes:

[0101] S301: Receive an inspection request and obtain information about the target ultrasound probe and the target inspection item corresponding to the inspection request;

[0102] S302: Determine the frequently used operation positions on the screen and the frequently used target parameter items corresponding to the target ultrasound probe and the target examination item; wherein, the frequently used target parameter items are the parameter items whose operation frequency is greater than a first preset value among the parameter items corresponding to the target ultrasound probe and the target examination item; the frequently used operation position is the target display position selected for operating the parameter item, and the selection frequency is greater than a second preset value;

[0103] S303: Adjust the target commonly used parameter item to the commonly used operation position for display;

[0104] S304: Obtain the case data of the target examination case corresponding to the examination request, input the case data of the target examination case into the trained second deep learning model, output the predicted level information of the parameter items with level corresponding to the target ultrasound probe and the target examination item through the trained second deep learning model, and adjust the parameter level of the displayed parameter items with level according to the predicted level information.

[0105] As a feasible implementation method, this embodiment further includes: collecting case data of the examined cases; constructing a training dataset based on the case data of the examined cases and the corresponding operation data within a preset time period; training a second deep learning model using the training dataset, wherein the trained second deep learning model is used to predict the parameter level of the parameter item with level based on the case data of the target examined case.

[0106] In practice, the collected operational data includes timestamps, operation types, and operation locations. Operation types include clicking, dragging, and adjusting parameter levels. That is, the collected operational data also includes actions involving adjusting parameter levels for parameters with specific settings. For example, a doctor might adjust the values ​​of parameters such as gain, depth, and frequency based on the specific examination. By collecting data on parameter level adjustments, the system can more comprehensively record the doctor's operational habits during the examination. This includes not only adjusting the position of parameter items but also adjusting parameter values, thus providing richer data support for subsequent deep learning and personalized layout.

[0107] The system collects case data from examination patients, including detailed information such as the patient's pathological characteristics and examination sites. Combining this data with corresponding operational data collected within a preset time period, the system constructs a training dataset. This dataset contains doctors' operational habits and parameter adjustment behaviors in different cases. Using this training dataset, the system trains a second deep learning model. This model learns the doctors' parameter adjustment patterns in different cases, providing support for subsequent parameter level prediction.

[0108] In step S304, the case data of the target examination case corresponding to the examination request is acquired, and this data is input into the previously trained second deep learning model. Based on the previously learned parameter adjustment patterns of doctors in different cases, this model outputs predicted parameter levels for the target ultrasound probe and the corresponding parameter items for the target examination. The system automatically adjusts the displayed parameter levels based on this predicted level information, making the parameter settings more consistent with the doctor's operating habits and the examination needs of the current case, further improving examination efficiency and diagnostic accuracy.

[0109] For example, when a doctor performs a fetal ultrasound examination, the system first acquires the patient's medical records. This data may include basic patient information (such as age and gestational age), medical history (such as whether there was a high-risk pregnancy), and previous ultrasound examination results (such as fetal growth, heart rate, etc.). The acquired medical records data is then input into a previously trained second deep learning model. This model has been trained using a large amount of historical medical data and the doctor's operating habits, enabling it to identify the parameter settings that doctors typically choose in similar situations. The model analyzes and outputs predicted parameter settings corresponding to the target ultrasound probe (e.g., a low-frequency probe) and the target examination item (fetal ultrasound). For example, the model might predict that in this type of examination, the gain should be set to 70%, the depth to 15 cm, and the frequency to 3.5 MHz. These predicted settings are based on the model's learning from historical data and reflect the doctor's commonly used settings in similar cases. Based on the output predicted settings, the system automatically adjusts the parameters displayed on the ultrasound equipment. For example, the gain is automatically adjusted to 70%, the depth to 15 cm, and the frequency to 3.5 MHz. In this way, when doctors conduct examinations, the equipment has already preset the parameter settings most suitable for the current case, and doctors only need to make necessary fine adjustments or confirmations.

[0110] As can be seen, this embodiment intelligently predicts and adjusts the parameter settings of the ultrasound equipment through a deep learning model, making it more in line with the doctor's operating habits and the needs of the current case. This not only improves the efficiency and accuracy of ultrasound examinations, but also provides doctors with a better operating experience.

[0111] The following describes a parameter item management device provided in an embodiment of this application. The parameter item management device described below and the parameter item management method described above can be referred to each other.

[0112] See Figure 4 A structural diagram of a parameter item management device according to an exemplary embodiment is shown, such as... Figure 4 As shown, it includes:

[0113] The first determining module 100 is used to receive an inspection request and obtain information about the target ultrasound probe and the target inspection item corresponding to the inspection request.

[0114] The second determining module 200 is used to determine the commonly used operation positions on the screen and the commonly used target parameter items corresponding to the target ultrasound probe and the target examination item; wherein, the commonly used target parameter items are the parameter items whose operation frequency is greater than a first preset value among the parameter items corresponding to the target ultrasound probe and the target examination item; the commonly used operation position is the target display position selected for operating the parameter item, and the selection frequency is greater than a second preset value;

[0115] The first adjustment module 300 is used to adjust the target commonly used parameter items to the commonly used operation position for display.

[0116] The parameter management device provided in this application, when the ultrasound equipment receives an examination request, acquires information about the target ultrasound probe and the target examination item corresponding to the examination request. Based on the analysis of historical operation data of the parameter items corresponding to the target ultrasound probe and the target examination item, it can accurately identify frequently used parameter items with an operation frequency higher than a first preset value. These frequently used parameter items are determined according to the frequency of use of parameter items by the user in actual operation, reflecting the user's operating habits and preferences in a specific examination scenario. At the same time, it also determines the frequently used operation positions on the screen with an operation frequency higher than a second preset value. These positions are the display positions frequently selected by the user during operation, ensuring that the display of parameter items is more in line with the user's operating habits. By automatically adjusting the target frequently used parameter items to the frequently used operation positions for display, the user can find and use these frequently used parameter items more quickly during the examination, reducing the time spent searching for and adjusting parameter items during the examination, thereby significantly improving operating efficiency. This automated parameter layout adjustment mechanism can not only better adapt to the specific needs of different examination items, but also automatically optimize the display logic of parameter items according to the user's operating habits, making the operation of the ultrasound equipment more convenient and efficient, and greatly improving the user's operating experience.

[0117] Based on the above embodiments, as a preferred embodiment, it further includes:

[0118] The first acquisition module is used to acquire operation data of each parameter item on the screen before receiving the inspection request and / or during the real-time inspection process; wherein, in the operation data, each parameter item is respectively bound to the corresponding inspection item and ultrasound probe.

[0119] Based on the above embodiments, as a preferred embodiment, it further includes:

[0120] The third determination module is used to determine the target ultrasound probe and the target examination item corresponding to the target common parameter items based on the operation data of each parameter item collected on the screen within a preset time period.

[0121] The fourth determination module is used to determine the frequently used operation positions on the screen based on the operation data of each parameter item within a preset time period.

[0122] Based on the above embodiments, as a preferred implementation, the fourth determining module includes:

[0123] The first determining unit is used to determine the operation data of the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item within the preset time period based on the operation data of each parameter item within the preset time period.

[0124] The second determining unit is used to determine the commonly used operation positions on the screen based on the operation data of the commonly used target parameter items.

[0125] Based on the above embodiments, as a preferred implementation, the third determining module is specifically used to: input the operation data of each parameter item in the screen collected within a preset time period, as well as the information of the target ultrasound probe and the target examination item, into the first deep learning model, and output the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item through the first deep learning model.

[0126] Based on the above embodiments, as a preferred implementation, the operation data includes the timestamp of the operation behavior, the operation type, and the operation location. The operation type includes at least clicking and / or dragging. If the operation type is dragging, the corresponding operation location is the target display location of the dragged parameter item.

[0127] Based on the above embodiments, as a preferred implementation, the operation type also includes adjusting parameter levels.

[0128] Based on the above embodiments, as a preferred embodiment, it further includes:

[0129] The second adjustment module is used to acquire the case data of the target examination case corresponding to the examination request, input the case data of the target examination case into the trained second deep learning model, output the predicted level information of the parameter items with level corresponding to the target ultrasound probe and the target examination item through the trained second deep learning model, and adjust the parameter level of the displayed parameter items with level according to the predicted level information.

[0130] Based on the above embodiments, as a preferred embodiment, it further includes:

[0131] The second data acquisition module is used to collect case data from examined cases;

[0132] The module is used to build a training dataset based on case data and corresponding operational data of cases examined within a preset time period.

[0133] The training module is used to train a second deep learning model using the training dataset. The trained second deep learning model is used to predict the parameter level of parameter items with levels based on the case data of the target examination case.

[0134] Based on the above embodiments, as a preferred implementation, the second determining module 200 is specifically used for: determining a preset number of commonly used operation positions, and sorting the preset number of commonly used operation positions in descending order of selected frequency to obtain a sorting result of commonly used operation positions; determining a preset number of commonly used target parameter items corresponding to the target ultrasound probe and the target examination item, and a sorting result of the commonly used target parameter items; wherein, in the sorting result of the commonly used target parameter items, the preset number of commonly used target parameter items are sorted in descending order of operation frequency;

[0135] Accordingly, the first adjustment module 300 is specifically used to: determine the common operation positions with the same sorting position in the common operation position sorting result as the common operation positions corresponding to each of the target common parameter items, based on the sorting position of each of the target common parameter items in the sorting result of the target common parameter items; and adjust each of the target common parameter items to the corresponding common operation position for display.

[0136] Based on the above embodiments, as a preferred implementation, the second determining module 200 is specifically used for: obtaining account information of the target account that initiated the inspection request; determining the commonly used operation location corresponding to the account information; wherein, the commonly used operation location is determined based on target operation data within a preset time period, and the target operation data is the operation data of the parameter item corresponding to the account information; determining the target commonly used parameter item corresponding to the account information, the target ultrasound probe, and the target inspection item; wherein, the target commonly used parameter item is determined based on the operation data of the parameter item corresponding to the target ultrasound probe and the target inspection item in the target operation data.

[0137] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0138] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiments of this application, the embodiments of this application also provide an ultrasonic device. Figure 5This is a structural diagram illustrating an ultrasonic device according to an exemplary embodiment, such as... Figure 5 As shown, the ultrasound equipment includes:

[0139] Communication interface 1 enables information exchange with other devices, such as network devices;

[0140] Processor 2 is connected to communication interface 1 to enable information interaction with other devices and, when running a computer program, executes the parameter management methods provided by one or more of the above-mentioned technical solutions. The computer program is stored in memory 3.

[0141] Of course, in practical applications, the various components of the ultrasonic equipment are coupled together through bus system 4. It can be understood that bus system 4 is used to achieve communication and connection between these components. In addition to the data bus, bus system 4 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 5 The general will label all buses as Bus System 4.

[0142] The memory 3 in this embodiment is used to store various types of data to support the operation of the ultrasound device. Examples of such data include any computer program used to operate the ultrasound device.

[0143] It is understood that memory 3 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 3 described in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0144] The methods disclosed in the embodiments of this application can be applied to processor 2, or implemented by processor 2. Processor 2 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 2 or by instructions in the form of software. The processor 2 may be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 2 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory 3. Processor 2 reads the program in memory 3 and completes the steps of the aforementioned method in combination with its hardware.

[0145] When processor 2 executes the program, it implements the corresponding processes in the various methods of the embodiments of this application. For the sake of brevity, these will not be described in detail here.

[0146] In an exemplary embodiment, this application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, such as a memory 3 that stores a computer program, which can be executed by a processor 2 to complete the steps described in the aforementioned method. The computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM.

[0147] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0148] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an ultrasound device (which may be a personal computer, server, network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0149] In an exemplary embodiment, this application also provides a computer program product, including a computer program executed by a processor 2 to perform the steps described in the aforementioned method.

[0150] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A parameter item management method, characterized in that, Applied to ultrasonic equipment, the method includes: Receive an examination request and obtain information about the target ultrasound probe and the target examination item corresponding to the examination request; Determine the frequently used operation positions on the screen and the frequently used target parameter items corresponding to the target ultrasound probe and the target examination item; wherein, the frequently used target parameter items are the parameter items whose operation frequency is greater than a first preset value among the parameter items corresponding to the target ultrasound probe and the target examination item; the frequently used operation position is the target display position selected when operating on the parameter item, and the selection frequency is greater than a second preset value; Adjust the commonly used target parameters to the commonly used operation positions for display.

2. The parameter item management method according to claim 1, characterized in that, Before receiving an inspection request, the following is also included: Collect operation data for each parameter item on the screen; wherein, in the operation data, each parameter item is respectively bound to the corresponding examination item and ultrasound probe.

3. The parameter item management method according to claim 2, characterized in that, After collecting the operation data of each parameter item on the screen, the method further includes: Based on the operation data of each parameter item on the screen collected within a preset time period, determine the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item; The frequently used operation positions on the screen are determined based on the operation data of each parameter item within a preset time period.

4. The parameter item management method according to claim 3, characterized in that, The step of determining frequently used operation locations on the screen based on the operation data of each parameter item within a preset time period includes: Based on the operation data of each parameter item within a preset time period, determine the operation data of the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item within the preset time period; Determine the commonly used operation positions on the screen based on the operation data of the commonly used target parameter items.

5. The parameter item management method according to claim 3, characterized in that, The step of determining the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item based on the operation data of each parameter item collected on the screen within a preset time period includes: The operation data of each parameter item on the screen collected within a preset time period, as well as the information of the target ultrasound probe and the target examination item, are input into the first deep learning model. The first deep learning model then outputs the target commonly used parameter items corresponding to the target ultrasound probe and the target examination item.

6. The parameter item management method according to claim 2, characterized in that, The operation data includes the timestamp of the operation, the operation type, and the operation location, and the operation type includes at least click and / or drag; If the operation type is drag, the corresponding operation position is the target display position of the drag parameter item.

7. The parameter item management method according to claim 6, characterized in that, The operation type also includes adjusting parameter settings.

8. The parameter item management method according to claim 7, characterized in that, After adjusting the commonly used target parameter items to the commonly used operation position for display, the method further includes: The system acquires the case data of the target examination case corresponding to the examination request, inputs the case data of the target examination case into the trained second deep learning model, outputs the predicted level information of the parameter items with levels corresponding to the target ultrasound probe and the target examination item through the trained second deep learning model, and adjusts the parameter level of the displayed parameter items with levels according to the predicted level information.

9. The parameter item management method according to claim 8, characterized in that, Also includes: Collect and examine case data; A training dataset is constructed based on case data and corresponding operational data of cases examined within a preset time period; A second deep learning model is trained using the training dataset. The trained second deep learning model is used to predict the parameter level of parameter items with level based on the case data of the target examination case.

10. The parameter item management method according to claim 1, characterized in that, The process of determining commonly used operation locations on the screen and the commonly used target parameter items corresponding to the target ultrasound probe and the target examination item includes: Determine a preset number of frequently used operation positions, and sort the preset number of frequently used operation positions in descending order of their selection frequency to obtain the sorting result of the frequently used operation positions; A preset number of commonly used target parameters corresponding to the target ultrasound probe and the target examination item are determined, as well as a sorting result of the preset number of commonly used target parameters; wherein, the preset number of commonly used target parameters in the sorting result are sorted from highest to lowest operation frequency; Accordingly, the commonly used target parameters are adjusted to be displayed in the commonly used operation positions, including: Based on the sorting position of each target common parameter item in the sorting result of the target common parameter items, the common operation positions with the same sorting position in the sorting result of the common operation positions are determined as the common operation positions corresponding to each target common parameter item; Adjust each of the commonly used target parameters to its corresponding commonly used position for display.

11. The parameter management method according to claim 1, characterized in that, The process of determining commonly used operation locations on the screen and the commonly used target parameter items corresponding to the target ultrasound probe and the target examination item includes: Obtain the account information of the target account that initiated the inspection request; Determine the frequently used operation locations corresponding to the account information; wherein, the frequently used operation locations are determined based on target operation data within a preset time period, and the target operation data is the operation data of the parameter items corresponding to the account information; The target commonly used parameter items corresponding to the account information, the target ultrasound probe, and the target examination item are determined; wherein, the target commonly used parameter items are determined based on the operation data of the parameter items corresponding to the target ultrasound probe and the target examination item in the target operation data.

12. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for implementing the steps of the parameter item management method as described in any one of claims 1 to 11 when executing the computer program.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the steps of the parameter item management method as described in any one of claims 1 to 11.

14. A computer program product, characterized in that, It includes a computer program that, when executed, implements the steps of the parameter item management method as described in any one of claims 1 to 11.

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