Method and apparatus for detecting cardiac ultrasound data, ultrasound device and storage medium

Abstract

This application discloses a method, apparatus, ultrasound device, and storage medium for detecting cardiac ultrasound data. The method includes: acquiring cardiac ultrasound data to be detected; extracting image features from the cardiac ultrasound data and determining the target section type corresponding to the cardiac ultrasound data based on the image features; when the target section type is a parasternal left ventricular long-axis section, determining the target section image for display from the cardiac ultrasound data; determining the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target section image, and associating the diameter data with the target section image for display. By determining the section type of the cardiac ultrasound data, and when the section type is a parasternal left ventricular long-axis section, directly extracting the target section image for display from the cardiac ultrasound data, this application ensures effective subsequent measurement of the left ventricular outflow channel, obtaining data on the left ventricular outflow channel, and improving measurement accuracy.

Description

Technical Field

[0001] This application relates to the field of image processing, and in particular to a method, apparatus, ultrasound equipment, and storage medium for detecting cardiac ultrasound data. Background Technology

[0002] Echocardiography data refers to data obtained by using shortwave ranging to measure the periodic activity of structures such as the heart walls, ventricles, and valves through the chest wall and soft tissues. During the acquisition of echocardiography data, various cross-sections are used, such as the apical three-chamber view, the apical five-chamber view, and the parasternal left ventricular long-axis view. In current techniques, when measuring the diameter of the left ventricular outflow tract using echocardiography data, manual selection is usually required, which leads to significant errors in the final diameter measurement. Summary of the Invention

[0003] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, this application provides a method, apparatus, ultrasound equipment and storage medium for detecting cardiac ultrasound data.

[0004] According to one aspect of the embodiments of this application, a method for detecting cardiac ultrasound data is provided, comprising:

[0005] Acquire the cardiac ultrasound data to be tested;

[0006] Extract image features from the cardiac ultrasound data, and determine the target section type corresponding to the cardiac ultrasound data based on the image features;

[0007] In the case where the target section type is a parasternal left ventricular long-axis section, the target section image for display is determined from the cardiac ultrasound data;

[0008] The diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis is determined from the target cross-sectional image, and the diameter data is displayed in association with the target cross-sectional image.

[0009] Furthermore, acquiring the cardiac ultrasound data to be detected includes:

[0010] Acquire ultrasound probe images captured by the ultrasound probe;

[0011] The ultrasonic probe image is analyzed to determine the current status information of the ultrasonic probe;

[0012] When the current state information matches the target state information, the cardiac ultrasound data is acquired based on the current state information.

[0013] Furthermore, the method also includes:

[0014] The current status information of the ultrasound probe is displayed, and a prompt message is generated based on the current status information. The prompt message is used to guide the user to control the ultrasound probe to acquire the cardiac ultrasound data.

[0015] Furthermore, the step of extracting image features from the cardiac ultrasound data and determining the image type corresponding to the cardiac ultrasound data based on the image features includes:

[0016] The cardiac ultrasound data is detected to obtain image features from the cardiac ultrasound data;

[0017] Based on the correspondence between preset image features and section types, the target section type corresponding to the image features is determined. The target section type includes: parasternal left ventricular long axis section, apical three-chamber section, and apical five-chamber section.

[0018] Furthermore, determining the target cross-sectional image for display from the cardiac ultrasound data includes:

[0019] Determine the number of image frames included in the cardiac ultrasound data;

[0020] The target cross-sectional image for display is selected from the cardiac ultrasound data based on the number of image frames.

[0021] Furthermore, the step of selecting the target cross-sectional image for display from the cardiac ultrasound data based on the image frame number includes:

[0022] When the number of image frames is 1, the cardiac ultrasound data is determined as the target cross-sectional image;

[0023] or,

[0024] When the number of image frames is greater than 1, each frame of the cardiac ultrasound data is detected to obtain the angle of the aortic opening angle in each frame, and the image with the largest aortic opening angle is determined as the target section image.

[0025] Furthermore, determining the diameter data of the left ventricular outflow passage along the parasternal left ventricular long axis from the target cross-sectional image includes:

[0026] Identify the location information of the left ventricular outflow channel in the target cross-sectional image;

[0027] Based on the location information, extract the cross-sectional data of the left ventricular long axis beside the sternum, and calculate the diameter of the left ventricular outflow channel based on the cross-sectional data.

[0028] According to another aspect of the embodiments of this application, a device for detecting cardiac ultrasound data is also provided, comprising:

[0029] The acquisition module is used to acquire the cardiac ultrasound data to be tested;

[0030] An extraction module is used to extract image features from the cardiac ultrasound data and determine the target section type corresponding to the cardiac ultrasound data based on the image features;

[0031] The determination module is used to determine the target section image for display from the echocardiography data when the target section type is a parasternal left ventricular long-axis section.

[0032] The display module is used to determine the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target cross-sectional image, and to associate the diameter data with the target cross-sectional image for display.

[0033] According to another aspect of the embodiments of this application, an ultrasound device is also provided, including a main unit and at least one ultrasound probe interface, the ultrasound probe interface being used to connect an ultrasound probe to the main unit, the main unit being used for...

[0034] Acquire the cardiac ultrasound data to be tested;

[0035] Extract image features from the cardiac ultrasound data, and determine the target section type corresponding to the cardiac ultrasound data based on the image features;

[0036] In the case where the target section type is a parasternal left ventricular long-axis section, the target section image for display is determined from the cardiac ultrasound data;

[0037] The diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis is determined from the target cross-sectional image, and the diameter data is displayed in association with the target cross-sectional image.

[0038] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium storing computer instructions for causing a computer to perform the above-described method for detecting cardiac ultrasound data.

[0039] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the steps in the above-described method.

[0040] Compared with the prior art, the above-mentioned technical solution provided in this application has the following advantages: This application determines the section type of cardiac ultrasound data by extracting image features from cardiac ultrasound data, and when the section type is the parasternal left ventricular long axis section, the target section image for display is directly extracted from the cardiac ultrasound data, which can ensure that the left ventricular outflow channel is effectively measured and the data of the left ventricular outflow channel is obtained, thus improving the measurement accuracy. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0042] 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, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart illustrating a method for detecting cardiac ultrasound data provided in this application embodiment;

[0044] Figure 2 This is a schematic diagram of the aortic valve opening angle provided in the embodiments of this application;

[0045] Figure 3 This is a schematic diagram of the target cross-sectional image provided for the embodiments of this application;

[0046] Figure 4 A flowchart illustrating a method for detecting cardiac ultrasound data, provided as another embodiment of this application;

[0047] Figure 5 A block diagram of a cardiac ultrasound data detection device provided in an embodiment of this application;

[0048] Figure 6 This is a schematic diagram of the structure of an ultrasonic device provided in an embodiment of this application. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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 some embodiments of this application, not all embodiments. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation of this application. 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.

[0050] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another similar entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0051] This application provides a method, apparatus, ultrasound device, and storage medium for detecting cardiac ultrasound data. The method provided by this invention can be applied to any ultrasound device as needed, such as a server, terminal, or other ultrasound device. No specific limitation is made here, and for ease of description, it will be referred to as an ultrasound device.

[0052] According to one aspect of the embodiments of this application, a method embodiment for detecting cardiac ultrasound data is provided. Figure 1 A flowchart of a method for detecting cardiac ultrasound data provided in an embodiment of this application is shown below. Figure 1 As shown, the method includes:

[0053] Step S11: Obtain the cardiac ultrasound data to be tested.

[0054] The method provided in this application embodiment can be applied to a control terminal. The control terminal sends an acquisition command to the ultrasound probe, which controls the ultrasound probe to acquire at least one cross-sectional image of the target object's heart. After executing the acquisition command, the ultrasound probe transmits the acquired at least one cross-sectional image to the control terminal. The control terminal combines the at least one cross-sectional image to obtain cardiac ultrasound data. The control terminal can be an ultrasound device, including a cart-type or portable ultrasound device.

[0055] In this embodiment of the application, step S11, acquiring the cardiac ultrasound data to be detected, specifically includes the following steps A1-A3:

[0056] Step A1: Acquire the ultrasound probe image acquired by the ultrasound probe.

[0057] In this embodiment of the application, after the control terminal sends a collection command to the ultrasonic probe, it will display the ultrasonic probe image during the ultrasonic probe's collection process.

[0058] Step A2: Analyze the ultrasound probe image to determine the current status information of the ultrasound probe.

[0059] In this embodiment, a recognition model can be used to extract the features of the heart chambers in the ultrasound probe image. Then, each chamber is located and segmented to obtain the chamber parameters, including chamber size, chamber area, etc. It should be noted that the chamber parameters and the section type can reflect the current position information and / or current orientation information of the ultrasound probe, thereby determining the current position information and / or current orientation information as the current state information.

[0060] Step A3: When the current state information is consistent with the target state information, acquire cardiac ultrasound data based on the current state information.

[0061] In this embodiment, the target state information includes target position information and target direction information, where the target position and target direction are the standard positions and directions of the ultrasonic probe during data acquisition. Then, the current position information and current direction information in the current state information are compared with the target position information and target direction information in the target state information to determine whether the current state information matches the target state information.

[0062] In this embodiment, if the current location information and the target location information are consistent, and the current direction information and the target direction information are consistent, then the current state information and the target state information are determined to be consistent. The ultrasound probe is controlled to continue the acquisition operation to obtain at least one frame of cross-sectional image. Then, the control terminal generates cardiac ultrasound data based on the obtained at least one frame of cross-sectional image.

[0063] After obtaining the current status information of the ultrasound probe, this embodiment displays the current status information and generates prompts based on it to guide the user in controlling the ultrasound probe to acquire cardiac ultrasound data. The prompts can be in the form of text, images, animations, or voice messages to guide the user on the next steps for using the ultrasound probe.

[0064] Step S12: Extract image features from the cardiac ultrasound data and determine the target section type corresponding to the cardiac ultrasound data based on the image features.

[0065] In this embodiment of the application, step S12, extracting image features from the cardiac ultrasound data and determining the image type corresponding to the cardiac ultrasound data based on the image features, includes:

[0066] Echocardiography data is examined to obtain image features. Based on the pre-defined correspondence between image features and section types, the target section type corresponding to the image features is determined. The target section types include: parasternal left ventricular long-axis section, apical three-chamber section, and apical five-chamber section.

[0067] In this embodiment of the application, the detection process may be as follows: inputting cardiac ultrasound data into a pre-trained detection model so that the detection model extracts the image features of the cardiac ultrasound data and determines the target section type of the cardiac ultrasound data based on the image features. The target section type includes: parasternal left ventricular long axis section, apical three-chamber section, and apical five-chamber section.

[0068] In this embodiment, the detection model can be a classification model established using artificial intelligence methods / traditional methods. This model can extract features from the input echocardiogram data and identify whether the cross-section in the echocardiogram data is a parasternal left ventricular long-axis cross-section, an apical three-chamber cross-section, an apical five-chamber cross-section, or others. The detection model can be, but is not limited to, Support Vector Machine (SVM), Extra-Limited Learning Machine (ELM), VGG, ResNet, etc.

[0069] In this embodiment, the training method for the detection model is as follows: A sample image set is obtained, including sample images of various different types of cross-sections; annotation information corresponding to the sample images is obtained, whereby the annotation information is used to annotate the cross-sectional features in the sample images and the cross-sectional types corresponding to the cross-sectional features. The cross-sectional types include: parasternal left ventricular long-axis cross-section, apical three-chamber cross-section, and apical five-chamber cross-section; the sample image set and annotation information are input to a preset neural network model, so that the initial neural network model learns the correlation between the cross-sectional features and cross-sectional types in the sample images of the sample image set, ultimately obtaining the detection model.

[0070] Step S13: When the target section type is the parasternal left ventricular long axis section, determine the target section image to be displayed from the echocardiogram data.

[0071] In this embodiment of the application, step S13, determining the target cross-sectional image for display from the cardiac ultrasound data, includes the following steps B1-B2:

[0072] Step B1: Determine the number of image frames included in the cardiac ultrasound data.

[0073] In this embodiment, the target section type indicates that the echocardiogram data belongs to the parasternal left ventricular long-axis section, meaning the echocardiogram data can be directly displayed. In this case, to improve the image display effect, it is necessary to obtain the best image from the echocardiogram data for display. Therefore, it is necessary to determine the number of image frames included in the echocardiogram data.

[0074] Step B2: Select the target cross-sectional image for display from the cardiac ultrasound data based on the image frame number.

[0075] In this embodiment, step B2, selecting the target cross-sectional image for display from the cardiac ultrasound data based on the number of image frames, includes: when the number of image frames is 1, determining the cardiac ultrasound data as the target cross-sectional image. It should be noted that, since there is only one frame in the cardiac ultrasound data, this single frame is determined as the target cross-sectional image.

[0076] In this embodiment of the application, step B2, selecting the target section image for display from the cardiac ultrasound data according to the number of image frames, further includes: when the number of image frames is greater than 1, detecting each frame of the cardiac ultrasound data, obtaining the angle of the aortic opening angle in each frame, and determining the image with the largest aortic opening angle as the target section image.

[0077] In this embodiment, the detection process for cardiac ultrasound data is as follows: If the cardiac ultrasound data includes multiple frames, a first recognition model can be established using artificial intelligence methods, level set segmentation, Unet, DeepLab, FCN, and other segmentation algorithms. This first recognition model is then used to detect and analyze the parasternal left ventricular long-axis section data to obtain the target section image with the best display effect. Specifically, in this embodiment, each frame is input into the first recognition model, which can directly output the aortic valve opening angle size (e.g., ...) in each frame. Figure 2 By calculating the aortic valve opening angle in each frame of the image and sorting them, the frame with the largest aortic valve opening angle is the target cross-sectional image.

[0078] In this embodiment, the training method for the first recognition model is as follows: A sample image is acquired, including the aortic opening angle; simultaneously, annotation information of the sample image is acquired, the annotation information being used to annotate the features of the aortic opening angle and the angle of the aortic opening angle. The sample image and its corresponding annotation information are input into a preset neural network model, so that the preset neural network model learns the features of the aortic opening angle and the correspondence between the features and the angle, ultimately obtaining the first recognition model.

[0079] In this embodiment of the application, the angle of the aortic opening angle is identified by the first recognition model, and the angle with the largest angle is determined as the target section image. The purpose is to facilitate the subsequent effective measurement of the left ventricular outflow channel based on the target section image, and at the same time ensure the accuracy of the subsequent measurement data.

[0080] Step S14: Determine the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target cross-sectional image, and display the diameter data in association with the target cross-sectional image.

[0081] In this embodiment of the application, step S14, determining the diameter data of the left ventricular outflow channel of the target detection object, includes the following steps C1-C2:

[0082] Step C1: Identify the location information of the left ventricular outflow channel in the target cross-sectional image.

[0083] Step C2: Extract cross-sectional data of the left ventricular long axis near the sternum based on location information, and calculate the diameter of the left ventricular outflow channel based on the cross-sectional data.

[0084] In this embodiment, a second recognition model is established based on artificial intelligence algorithms (e.g., OTSU method, level set segmentation, Unet, DeepLab, FCN, etc.). This second recognition model extracts parasternal left ventricular long-axis section data from the target section image. Simultaneously, the second recognition model can also calculate the diameter of the left ventricular outflow tract based on the parasternal left ventricular long-axis section data, and then associate and display the diameter data with the target section image (e.g., ...). Figure 3 (As shown).

[0085] As an example, the cross-sectional area of ​​the left ventricular outflow tract (LVOT CSA) is calculated using the following formula:

[0086] LVOT CSA = (LVOT D)2 × k (LVOT D is the diameter of the left ventricular outflow tract in the parasternal long axis section of the left ventricle, and k is a constant).

[0087] This application embodiment determines the section type of cardiac ultrasound data by extracting image features from the cardiac ultrasound data. When the section type is a parasternal left ventricular long axis section, the target section image for display is directly extracted from the cardiac ultrasound data, which can ensure that the left ventricular outflow channel can be effectively measured and the data of the left ventricular outflow channel can be obtained, thus improving the measurement accuracy.

[0088] Figure 4 A flowchart of a method for detecting cardiac ultrasound data provided in an embodiment of this application is shown below. Figure 4 As shown, the method also includes:

[0089] Step S21, acquire sample images, wherein the sample images include: cross-sectional images of the thoracic cavity of different objects acquired by the ultrasound probe;

[0090] Step S22: Obtain the annotation information corresponding to the sample image, wherein the annotation information is used to annotate the image feature samples in the sample image and the cross section type corresponding to the image feature samples;

[0091] Step S23: Input the sample image and annotation information into the preset neural network model so that the neural network model learns the correspondence between image feature samples and cross-section types to obtain the detection model.

[0092] Figure 5 This is a block diagram of a cardiac ultrasound data detection device provided in an embodiment of this application. This device can be implemented as part or all of an ultrasound device through software, hardware, or a combination of both. Figure 5 As shown, the device includes:

[0093] Acquisition module 51 is used to acquire the cardiac ultrasound data to be detected;

[0094] Extraction module 52 is used to extract image features from cardiac ultrasound data and determine the target section type corresponding to the cardiac ultrasound data based on the image features;

[0095] The determination module 53 is used to determine the target section image for display from the echocardiogram data when the target section type is the parasternal left ventricular long axis section;

[0096] Display module 54 is used to determine the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target section image, and to associate the diameter data with the target section image for display.

[0097] In this embodiment of the application, the acquisition module 51 is used to acquire ultrasound probe images collected by the ultrasound probe; analyze the ultrasound probe images to determine the current status information of the ultrasound probe; and acquire cardiac ultrasound data based on the current status information when the current status information is consistent with the target status information.

[0098] In this embodiment of the application, the cardiac ultrasound data detection device further includes: a display module, used to display the current status information of the ultrasound probe and generate prompt information based on the current status information, the prompt information being used to guide the user to control the ultrasound probe to acquire cardiac ultrasound data.

[0099] In this embodiment of the application, the extraction module 52 is used to detect cardiac ultrasound data and obtain image features in the cardiac ultrasound data; based on the correspondence between preset image features and section types, the target section type corresponding to the image features is determined, wherein the target section type includes: parasternal left ventricular long axis section, apical three-chamber section and apical five-chamber section.

[0100] In this embodiment of the application, the determining module 53 includes:

[0101] The detection submodule is used to determine the number of image frames included in the cardiac ultrasound data;

[0102] The selection submodule is used to select the target cross-sectional image for display from the cardiac ultrasound data based on the image frame number.

[0103] In this embodiment of the application, a selection submodule is used to determine the cardiac ultrasound data as the target cross-sectional image when the number of image frames is 1;

[0104] or,

[0105] In this embodiment of the application, a selection submodule is used to detect each frame of the cardiac ultrasound data when the number of image frames is greater than 1, obtain the angle of the aortic opening angle in each frame, and determine the image with the largest aortic opening angle as the target cross-sectional image.

[0106] In this embodiment, the display module is used to identify the position information of the left ventricular outflow channel in the target cross-sectional image; extract cross-sectional data of the parasternal left ventricular long axis based on the position information, and calculate the diameter of the left ventricular outflow channel based on the cross-sectional data.

[0107] This application embodiment also provides an ultrasonic device, including a main unit and at least one ultrasonic probe interface. The ultrasonic probe interface is used to connect an ultrasonic probe to the main unit, and the main unit is used for...

[0108] Acquire the cardiac ultrasound data to be tested;

[0109] Extract image features from cardiac ultrasound data and determine the target section type corresponding to the cardiac ultrasound data based on the image features;

[0110] When the target section type is a parasternal left ventricular long-axis section, the target section image for display is determined from the echocardiography data;

[0111] Determine the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target section image, and display the diameter data in association with the target section image.

[0112] This application also provides an ultrasonic device, such as... Figure 6 As shown, the ultrasound device may include: a processor 1501, a communication interface 1502, a memory 1503, and a communication bus 1504, wherein the processor 1501, the communication interface 1502, and the memory 1503 communicate with each other through the communication bus 1504.

[0113] Memory 1503 is used to store computer programs;

[0114] When the processor 1501 executes the computer program stored in the memory 1503, it implements the steps of the above embodiments.

[0115] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0116] The communication interface is used for communication between the aforementioned terminal and other devices.

[0117] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0118] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0119] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform the cardiac ultrasound data identification method described in any of the above embodiments.

[0120] In another embodiment provided in this application, a computer-readable storage medium is also provided, the computer-readable storage medium storing computer instructions for causing a computer to perform the above-described method for detecting cardiac ultrasound data.

[0121] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive).

[0122] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

[0123] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for detecting cardiac ultrasound data, characterized in that, include: Acquire the cardiac ultrasound data to be tested; Extract image features from the cardiac ultrasound data, and determine the target section type corresponding to the cardiac ultrasound data based on the image features; In the case where the target section type is a parasternal left ventricular long-axis section, the target section image for display is determined from the cardiac ultrasound data; Determine the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target cross-sectional image, and display the diameter data in association with the target cross-sectional image; The step of determining the target section image for display from the cardiac ultrasound data includes: determining the number of image frames included in the cardiac ultrasound data; selecting the target section image for display from the cardiac ultrasound data according to the number of image frames; wherein, the step of selecting the target section image for display from the cardiac ultrasound data according to the number of image frames includes: when the number of image frames is 1, determining the cardiac ultrasound data as the target section image; or, when the number of image frames is greater than 1, detecting each frame of the cardiac ultrasound data, obtaining the angle of the aortic opening angle in each frame, and determining the image with the largest aortic opening angle as the target section image.

2. The method according to claim 1, characterized in that, The acquisition of the cardiac ultrasound data to be detected includes: Acquire ultrasound probe images captured by the ultrasound probe; The ultrasonic probe image is analyzed to determine the current status information of the ultrasonic probe; When the current state information matches the target state information, the cardiac ultrasound data is acquired based on the current state information.

3. The method of claim 2, wherein, The method further includes: The current status information of the ultrasound probe is displayed, and a prompt message is generated based on the current status information. The prompt message is used to guide the user to control the ultrasound probe to acquire the cardiac ultrasound data.

4. The method of claim 1, wherein, The step of extracting image features from the echocardiogram data and determining the target section type corresponding to the echocardiogram data based on the image features includes: The cardiac ultrasound data is detected to obtain image features from the cardiac ultrasound data; Based on the correspondence between preset image features and section types, the target section type corresponding to the image features is determined. The target section type includes: parasternal left ventricular long axis section, apical three-chamber section, and apical five-chamber section.

5. The method of claim 1, wherein, The data used to determine the diameter of the left ventricular outflow pathway along the parasternal left ventricular long axis from the target cross-sectional image includes: Identify the location information of the left ventricular outflow channel in the target cross-sectional image; Based on the location information, the cross-sectional data of the left ventricular long axis beside the sternum is extracted, and the diameter of the left ventricular outflow channel is calculated based on the cross-sectional data.

6. An apparatus for detecting cardiac ultrasound data, characterized by include: The acquisition module is used to acquire the cardiac ultrasound data to be tested; An extraction module is used to extract image features from the cardiac ultrasound data and determine the target section type corresponding to the cardiac ultrasound data based on the image features; The determination module is used to determine the target section image for display from the echocardiography data when the target section type is a parasternal left ventricular long-axis section. The display module is used to determine the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target section image, and associate the diameter data with the target section image for display. Determining the target section image for display from the echocardiogram data includes: determining the number of image frames included in the echocardiogram data; selecting the target section image for display from the echocardiogram data according to the number of image frames; wherein, selecting the target section image for display from the echocardiogram data according to the number of image frames includes: when the number of image frames is 1, determining the echocardiogram data as the target section image; or, when the number of image frames is greater than 1, detecting each frame of the echocardiogram data, obtaining the angle of the aortic opening angle in each frame, and determining the image with the largest aortic opening angle as the target section image.

7. An ultrasound apparatus, characterized by It includes a main unit and at least one ultrasound probe interface, the ultrasound probe interface being used to connect an ultrasound probe to the main unit, the main unit being used for, Acquire the cardiac ultrasound data to be tested; Extract image features from the cardiac ultrasound data, and determine the target section type corresponding to the cardiac ultrasound data based on the image features; In the case where the target section type is a parasternal left ventricular long-axis section, the target section image for display is determined from the cardiac ultrasound data; The diameter data of the left ventricular outflow passage along the parasternal left ventricular long axis is determined from the target section image, and the diameter data is associated with the target section image for display. The determination of the target section image for display from the echocardiogram data includes: determining the number of image frames included in the echocardiogram data; selecting the target section image for display from the echocardiogram data according to the number of image frames; wherein, selecting the target section image for display from the echocardiogram data according to the number of image frames includes: when the number of image frames is 1, determining the echocardiogram data as the target section image; or, when the number of image frames is greater than 1, detecting each frame of the echocardiogram data to obtain the angle of the aortic opening angle in each frame, and determining the image with the largest aortic opening angle as the target section image.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method for detecting cardiac ultrasound data according to any one of claims 1-5.

Images