A method for assessing cardiac contractile function, an ultrasound device and a storage medium

Abstract

A method for evaluating cardiac systolic function, an ultrasonic device and a storage medium are applied to the technical field of ultrasonography. The method for evaluating cardiac systolic function comprises the following steps: acquiring an ultrasonic image sequence of a target heart; performing first processing on the ultrasonic image sequence to obtain a first type of ultrasonic index, and performing second processing to obtain a second type of ultrasonic index; the first processing comprises common processing and first branch processing, and the second processing comprises common processing and second branch processing; performing common processing on the ultrasonic image sequence to obtain a plurality of target myocardial sampling points, performing first branch processing on the target myocardial sampling points of different ultrasonic images to obtain the first type of ultrasonic index, and performing second branch processing to obtain the second type of ultrasonic index; and displaying the first type of ultrasonic index and the second type of ultrasonic index. Since the common processing is provided, the first type of ultrasonic index and the second type of ultrasonic index related to the cardiac systolic function can be output at one time based on an overall calculation process, and the operation process is simplified.

Description

Technical Field

[0001] This application relates to the field of ultrasound technology, specifically to a method for assessing cardiac contractile function, an ultrasound device, and a storage medium. Background Technology

[0002] The heart, as one of the most vital organs in the human body, has a contractile function that is a key indicator of cardiac hemodynamics, and it holds significant clinical value for the diagnosis, disease monitoring, treatment evaluation, and prognosis of many cardiovascular diseases. Ultrasound, as a non-invasive, safe, and convenient examination method, can be used to assess cardiac contractile function.

[0003] Current technical solutions typically involve first acquiring ultrasound images of the heart through an ultrasound examination, then calculating ultrasound indicators that can be used to assess the heart's contractile function based on these images, and finally, the physician assessing the heart's contractile function using these ultrasound indicators. Several ultrasound indicators can be used to assess the heart's contractile function.

[0004] However, acquiring multiple ultrasound parameters requires sequentially activating different ultrasound measurement functions to process the ultrasound images differently, making the process relatively cumbersome. Therefore, new technical solutions are needed. Summary of the Invention

[0005] The main technical problem addressed in this application is that obtaining multiple ultrasound parameters related to cardiac contractile function is relatively complicated.

[0006] According to the first aspect, one embodiment provides a method for assessing cardiac systolic function, comprising:

[0007] Acquire an ultrasound image sequence of the target heart, the ultrasound image sequence comprising multiple ultrasound images, the ultrasound images being able to reflect the tissue structure of the target heart;

[0008] The ultrasound image sequence is first processed to obtain a first type of ultrasound index related to the contractile function of the target heart, and then processed to obtain a second type of ultrasound index related to the contractile function of the target heart. The first type of ultrasound index is related to the strain parameters and / or displacement parameters of the myocardial tissue of the target heart, and the second type of ultrasound index is related to the ventricular volume parameters and / or area parameters of the target heart, and / or to the atrial volume parameters and / or area parameters of the target heart.

[0009] The first processing includes a common processing and a first branch processing, and the second processing includes the common processing and a second branch processing. The common processing is performed on the ultrasound image sequence to obtain multiple target myocardial sampling points. Based on the target myocardial sampling points in different ultrasound images in the ultrasound image sequence, the first branch processing is performed to obtain the first type of ultrasound index, and the second branch processing is performed to obtain the second type of ultrasound index.

[0010] The first type of ultrasound index and the second type of ultrasound index are displayed.

[0011] In some embodiments, the common processing of the ultrasound image sequence yields multiple target myocardial sampling points, including:

[0012] Based on the ultrasound image sequence, the target myocardial tissue of the target heart is determined, and the target myocardial tissue is sampled to obtain the multiple target myocardial sampling points.

[0013] or,

[0014] In response to the user's sampling operation of the target myocardial tissue of the target heart in the ultrasound image sequence, the corresponding plurality of target myocardial sampling points are obtained.

[0015] In some embodiments, multiple target myocardial sampling points are located within the outline of the target myocardial tissue.

[0016] In some embodiments, the target myocardial tissue is sampled to obtain the plurality of target myocardial sampling points, including:

[0017] Determine the contour of the target myocardial tissue;

[0018] The contour of the target myocardial tissue is sampled to obtain the multiple target myocardial sampling points.

[0019] In some embodiments, point sampling of the contour of the target myocardial tissue includes:

[0020] Equally spaced point sampling is performed based on the contour of the target myocardial tissue, so that the spacing between each target myocardial sampling point is consistent.

[0021] And / or,

[0022] Based on the degree of contraction of the target myocardial tissue, point sampling is performed on its corresponding contour, so that the target myocardial tissue with a greater degree of contraction has a smaller spacing between the target myocardial sampling points on its corresponding contour, and the target myocardial tissue with a smaller degree of contraction has a larger spacing between the target myocardial sampling points on its corresponding contour.

[0023] In some embodiments, point sampling is performed on the contour corresponding to the target myocardial tissue based on the degree of contraction, including:

[0024] Determine the slope corresponding to the contour of the target myocardial tissue, and perform point sampling based on the slope corresponding to the contour of the target myocardial tissue, so that the spacing between the target myocardial sampling points corresponding to the contour with a larger slope is smaller, and the spacing between the target myocardial sampling points corresponding to the contour with a smaller slope is larger.

[0025] In some embodiments, the first type of ultrasound index is obtained by performing the first branch processing based on the target myocardial sampling points of different ultrasound images in the ultrasound image sequence, and the second type of ultrasound index is obtained by performing the second branch processing, including:

[0026] Determine the location of each of the target myocardial sampling points in each ultrasound image within the ultrasound image sequence;

[0027] The first type of ultrasound index is calculated based on the positional changes of the target myocardial sampling point in different ultrasound images in the ultrasound image sequence.

[0028] The target myocardial tissue contour is obtained by connecting the target myocardial sampling points in different ultrasound images in the ultrasound image sequence. The second type of ultrasound index is calculated based on the positional changes of the target myocardial tissue contour in different ultrasound images.

[0029] In some embodiments:

[0030] Calculating the first type of ultrasound index includes:

[0031] Calculate the distance between the target myocardial sampling points corresponding to the first type of ultrasound index in different ultrasound images, and calculate the strain parameters and / or displacement parameters of the target myocardial tissue based on the distance between the target myocardial sampling points corresponding to the first type of ultrasound index in different ultrasound images to obtain the first type of ultrasound index;

[0032] And / or,

[0033] The calculation of the second type of ultrasound index includes:

[0034] Calculate the area and / or volume corresponding to the contour of the target myocardial tissue in different ultrasound images that correspond to the second type of ultrasound index. Based on the area and / or volume parameters corresponding to the contour of the target myocardial tissue in different ultrasound images, calculate the second type of ultrasound index.

[0035] In some embodiments, the first type of ultrasound parameters includes at least one of global longitudinal strain, mitral annular displacement, and tricuspid annular displacement, and the second type of ultrasound parameters includes at least one of ejection fraction and area change rate.

[0036] In some embodiments:

[0037] When calculating the overall longitudinal strain, the sum of the distances between the target myocardial sampling points corresponding to the overall longitudinal strain in different ultrasound images is calculated, and the overall longitudinal strain is obtained based on the sum of the distances calculated in different ultrasound images.

[0038] And / or,

[0039] When calculating the ejection fraction, the volume corresponding to the target myocardial tissue contour in different ultrasound images corresponding to the ejection fraction is calculated, and the ejection fraction is obtained based on the volume calculated from the different ultrasound images.

[0040] And / or,

[0041] When calculating the area change rate, the area corresponding to the target myocardial tissue contour corresponding to the area change rate in different ultrasound images is calculated, and the area change rate is obtained based on the area calculated from the different ultrasound images.

[0042] and / or,

[0043] When calculating the mitral annulus displacement, the distance between the target myocardial sampling points corresponding to the mitral annulus displacement in different ultrasound images is calculated. Based on the distances calculated corresponding to the mitral annulus displacement in different ultrasound images, the mitral annulus displacement is obtained.

[0044] and / or,

[0045] When calculating the tricuspid annular displacement, the distance between the target myocardial sampling points corresponding to the tricuspid annular displacement in different ultrasound images is calculated. Based on the distances calculated corresponding to the tricuspid annular displacement in different ultrasound images, the tricuspid annular displacement is obtained.

[0046] In some embodiments, the first type of ultrasound indicators and the second type of ultrasound indicators are shown, including:

[0047] Identify the chambers of the target heart in the ultrasound image sequence, the chambers including at least one of the left atrium, right atrium, left ventricle, and right ventricle;

[0048] For each identified chamber, display its corresponding first type of ultrasound index and / or second type of ultrasound index.

[0049] According to the second aspect, one embodiment provides a method for assessing cardiac systolic function, comprising:

[0050] Acquire an ultrasound image sequence of the target heart, the ultrasound image sequence comprising multiple ultrasound images, the ultrasound images being able to reflect the tissue structure of the target heart;

[0051] Based on the ultrasound image sequence, multiple ultrasound indicators related to the contractile function of the target heart are calculated simultaneously. The multiple ultrasound indicators include a first type of ultrasound indicator and a second type of ultrasound indicator. The first type of ultrasound indicator is related to the strain parameters and / or displacement parameters of the myocardial tissue of the target heart, and the second type of ultrasound indicator is related to the ventricular volume parameters and / or area parameters of the target heart, and / or to the atrial volume parameters and / or area parameters of the target heart.

[0052] The multiple ultrasound indicators are displayed.

[0053] In some embodiments, multiple ultrasound parameters related to the target heart's systolic function are simultaneously calculated based on the ultrasound image sequence, including:

[0054] In the first time period, the first type of ultrasound index is calculated based on the first processing model: the target myocardial tissue of the target heart is determined based on the ultrasound image sequence, and the first type of ultrasound index is calculated based on the positional changes of the target myocardial tissue in different ultrasound images in the ultrasound image sequence.

[0055] In the second time period, the second type of ultrasound index is calculated based on the second processing model: the target myocardial tissue contour of the target heart is determined based on the ultrasound image sequence, and the second type of ultrasound index is calculated based on the positional change of the target myocardial tissue contour in different ultrasound images in the ultrasound image sequence.

[0056] Wherein, the first time period and the second time period are the same, or the first time period and the second time period share a common period of time;

[0057] or,

[0058] The first type of ultrasound index and the second type of ultrasound index are calculated based on the third processing model: the ultrasound image sequence is processed in the first way to obtain the first type of ultrasound index related to the target heart and systolic function, and processed in the second way to obtain the second type of ultrasound index related to the target heart and systolic function; wherein, the first processing includes common processing and first branch processing, and the second processing includes the common processing and second branch processing; the common processing is performed on the ultrasound image sequence to obtain multiple target myocardial sampling points, and the first branch processing is performed on the target myocardial sampling points in different ultrasound images in the ultrasound image sequence to obtain the first type of ultrasound index, and the second branch processing is performed to obtain the second type of ultrasound index.

[0059] According to a third aspect, one embodiment provides a method for assessing cardiac systolic function, comprising:

[0060] Acquire an ultrasound image sequence of the target heart, the ultrasound image sequence comprising multiple ultrasound images, the ultrasound images being able to reflect the tissue structure of the target heart;

[0061] Calculate multiple ultrasound indicators related to the contractile function of the target heart based on the ultrasound image sequence;

[0062] The multiple ultrasound indicators are displayed.

[0063] According to a fourth aspect, one embodiment provides an ultrasonic device, characterized in that it comprises:

[0064] An ultrasonic probe is used to emit ultrasonic waves toward a region of interest and to receive the echoes of the ultrasonic waves.

[0065] A transmitting and receiving control circuit is used to control the ultrasonic probe to transmit ultrasonic waves toward the region of interest and to receive the echoes of the ultrasonic waves.

[0066] A processor for executing computer programs and / or instructions to implement the methods described in the first, second, or third aspect.

[0067] According to a fifth aspect, one embodiment provides a computer-readable storage medium storing a program that can be executed by a processor to implement the methods described in the first, second, or third aspects.

[0068] According to the cardiac contractile function assessment method, ultrasound equipment, and storage medium of the above embodiments, multiple target myocardial sampling points are obtained by common processing of ultrasound image sequences. Based on these multiple target myocardial sampling points, strain and / or displacement parameters, as well as volume and / or area parameters of myocardial tissue, can be calculated. A first branch processing is performed on the target myocardial sampling points in different ultrasound images within the ultrasound image sequence to obtain a first type of ultrasound index related to the strain and / or displacement parameters of myocardial tissue. A second branch processing is then performed to obtain a second type of ultrasound index related to the volume and / or area parameters of myocardial tissue. Since the calculation process for both the first and second type of ultrasound indices involves a common processing step, subsequent different processing steps can be performed based on this common processing to obtain the first and second type of ultrasound indices respectively. This allows for the generation of both the first and second type of ultrasound indices based on a single overall calculation process, enabling the simultaneous output of both types of ultrasound indices related to cardiac contractile function, thus simplifying the operation process. Attached Figure Description

[0069] Figure 1 This is a schematic diagram of the structure of an ultrasonic device according to one embodiment;

[0070] Figure 2 This is a schematic diagram of the structure of an ultrasound index calculation model according to one embodiment;

[0071] Figure 3 This is an ultrasonic schematic diagram illustrating the calculation of overall longitudinal strain according to one embodiment.

[0072] Figure 4 This is a schematic diagram of ultrasound used to calculate the displacement of the mitral valve annulus in one embodiment.

[0073] Figure 5 This is an ultrasound diagram illustrating the calculation of ejection fraction in one embodiment.

[0074] Figure 6 This is a flowchart illustrating one embodiment of a method for assessing cardiac systolic function.

[0075] Figure 7 This is a flowchart illustrating another embodiment of a method for assessing cardiac systolic function. Detailed Implementation

[0076] The present application will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by related similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of the present application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to the present application are not shown or described in the specification. This is to avoid obscuring the core parts of the present application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; the relevant operations can be fully understood based on the description in the specification and general technical knowledge in the art.

[0077] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0078] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0079] Current technical solutions typically use multiple ultrasound parameters related to systolic function, including global longitudinal strain, mitral annular displacement and / or tricuspid annular displacement, ejection fraction and / or area change rate. However, a single ultrasound measurement function can only output a portion of these parameters. For example, the first measurement function outputs global longitudinal strain and mitral annular displacement and / or tricuspid annular displacement, while the second outputs ejection fraction and / or area change rate. This is because the calculation processes for different ultrasound parameters differ. For instance, global longitudinal strain primarily calculates the strain parameter of myocardial tissue, while mitral annular displacement and / or tricuspid annular displacement primarily calculate the displacement parameter of myocardial tissue. Similarly, ejection fraction primarily calculates the volume parameter of the ventricle, and area change rate primarily calculates the area parameter of the ventricle. Therefore, different ultrasound measurement functions are usually activated to calculate different ultrasound parameters separately, making the overall acquisition process relatively cumbersome.

[0080] In some embodiments of this application, when calculating multiple ultrasound indicators, the calculation process for each indicator follows a single, identical procedure. Subsequent processing is then performed based on this same procedure to obtain different ultrasound indicators. This allows multiple ultrasound indicators to be obtained from a single overall calculation process, enabling the simultaneous output of multiple ultrasound indicators related to cardiac contractile function, thus simplifying the operation. Specifically, the identical procedure may involve acquiring multiple target myocardial sampling points. Based on these multiple target myocardial sampling points, strain and / or displacement parameters, as well as volume and / or area parameters of the myocardial tissue, can be calculated.

[0081] Some embodiments provide an ultrasonic device; please refer to [the relevant documentation]. Figure 1 The ultrasonic device includes an ultrasonic probe 10, a transmission and reception control circuit, a processor 20, a human-computer interaction device 70, and a memory 80, which will be described in detail below.

[0082] An ultrasound probe 10 is used to emit ultrasound waves toward a region of interest within a target tissue and to receive the echoes of the ultrasound waves, thereby obtaining an ultrasound echo signal. The ultrasound probe 10 includes a transducer (not shown) composed of multiple array elements arranged in an array. Each array element is used to emit ultrasound waves according to an excitation electrical signal, or to convert received ultrasound waves into electrical signals. Therefore, each array element can be used to achieve the mutual conversion between electrical pulse signals and ultrasound waves, thereby enabling the emission of ultrasound waves toward the biological tissue being scanned, and it can also be used to receive the echoes of ultrasound waves reflected back from the tissue.

[0083] The transmitting and receiving control circuit is used to control the ultrasonic probe 10 to transmit ultrasonic waves and receive the echoes of ultrasonic waves, and to obtain ultrasonic echo signals. The transmitting and receiving control circuit may include a transmitting circuit 30 and a receiving circuit 40. The transmitting circuit 30 is used to excite the ultrasonic probe 10 to transmit ultrasonic waves toward the scanned object according to the control of the processor 20. The receiving circuit 40 is used to receive the echoes of ultrasonic waves returned from the scanned object through the ultrasonic probe 10 to obtain ultrasonic echo signals, and can also process the ultrasonic echo signals.

[0084] The human-computer interaction device 70 is used for human-computer interaction, such as outputting visual information and receiving user input. It can receive user input using a keyboard, operation buttons, mouse, trackball, touchpad, or a touchscreen integrated with the display; it can output visual information using a display, touchscreen display, screen, or touchscreen display.

[0085] The memory 80 is used to store various types of data.

[0086] Please refer to Figure 1 The ultrasound equipment may also include a beamforming module 50 and an IQ demodulation module 60.

[0087] The beamforming module 50 is signal-connected to the receiving circuit 40 and is used to perform beamforming processing on the echo signal, including delay and weighted summation. Because the distance from the ultrasonic receiving point in the tested tissue to the receiving array elements varies, the channel data of the same receiving point output by different receiving array elements has delay differences, requiring delay processing to align the phases. Weighted summation of the different channel data of the same receiving point is then performed to obtain the beamformed ultrasonic image data. The ultrasonic image data output by the beamforming module 50 is also called radio frequency (RF) data. The beamforming module 50 outputs the RF data to the IQ demodulation module 60. In some embodiments, the beamforming module 50 may also output the RF data to the memory 80 for caching or storage, or directly output the RF data to the processor 20 for image processing.

[0088] The beamforming module 50 can perform the above functions using hardware, firmware, or software. The beamforming module 50 can be integrated into the processor 20 or set up separately; this application does not impose any limitations on this.

[0089] The IQ demodulation module 60 removes the signal carrier through IQ demodulation, extracts the tissue structure information contained in the signal, and filters to remove noise. The signal obtained at this time is called the baseband signal (IQ data pair). The IQ demodulation module 60 outputs the IQ data pair to the processor 20 for image processing. In some embodiments, the IQ demodulation module 60 also outputs the IQ data pair to the memory 80 for buffering or storage, so that the processor 20 can read the data from the memory 80 for subsequent image processing.

[0090] The IQ demodulation module 60 can also perform the above functions in hardware, firmware, or software. Similarly, the IQ demodulation module 60 can be integrated into the processor 20 or set up separately; this application does not impose any limitations on this.

[0091] The processor 20 is configured to process input data according to specific logic instructions. It is a central controller circuit (CPU), one or more microprocessors, a graphics controller circuit (GPU), or any other electronic component. It can control peripheral electronic components according to input instructions or predetermined instructions, or perform data reading and / or saving on the memory 80. It can also process input data by executing programs in the memory 80. For example, it can perform one or more processing operations on the acquired ultrasound data according to one or more operating modes. The processing operations include, but are not limited to, adjusting or limiting the form of ultrasound waves emitted by the ultrasound probe 10, generating various image frames for display on the display of the human-machine interface device 70, or adjusting or limiting the content and form displayed on the display, or adjusting one or more image display settings displayed on the display (e.g., ultrasound images, interface components, locating regions of interest).

[0092] When an ultrasonic echo signal is received, the acquired ultrasonic data can be processed in real time by the processor 20 during the scan, or it can be temporarily stored in the memory 80 and processed in a near real-time manner during online or offline operation.

[0093] In this embodiment, the processor 20 controls the operation of the transmitting circuit 30 and the receiving circuit 40, for example, controlling the transmitting circuit 30 and the receiving circuit 40 to operate alternately or simultaneously. The processor 20 can also determine a suitable operating mode according to the user's selection or the program settings, form a transmission sequence corresponding to the current operating mode, and send the transmission sequence to the transmitting circuit 30 so that the transmitting circuit 30 can use the appropriate transmission sequence to control the ultrasonic probe 10 to emit ultrasonic waves.

[0094] In some embodiments, the processor 20 controls the ultrasound probe to emit ultrasound waves toward the target tissue and receive the echoes of the ultrasound waves through the transmit and receive control circuit according to the transmit and receive parameters, thereby obtaining ultrasound echo signals, and processes the ultrasound echo signals according to the imaging parameters to obtain an ultrasound cross-sectional image of the target tissue.

[0095] In some embodiments, the transmit and receive parameters include parameters for the transmit sequence and parameters for the receive sequence. The transmit sequence parameters include the number of array elements used for transmitting and ultrasonic wave transmission parameters (e.g., pulse amplitude, transmit voltage, transmit frequency, number of waves emitted, transmit interval, transmit angle, transmit waveform, transmit aperture, linear density, dot density, and / or focal position, etc.). The receive sequence is used to control the reception of some or all of the ultrasonic waves from the multiple array elements after they have passed through the tissue. The receive sequence parameters include the number of array elements used for receiving and the echo reception parameters (e.g., reception angle, depth, etc.). The ultrasonic wave parameters in the transmit sequence and the echo parameters in the receive sequence may differ depending on the intended use of the ultrasonic echo or the image generated by the ultrasonic echo.

[0096] In some embodiments, the imaging parameters include parameters for signal processing and image processing of the ultrasonic echo signal received by the ultrasonic probe 10 by the processor 20. Signal processing refers to one or more steps of processing the ultrasonic echo signal / channel echo data in the signal domain, such as analog-to-digital conversion, signal demodulation, amplification, filtering, downsampling, and / or beamforming. Image processing refers to one or more steps of processing the signal-processed ultrasonic image data in the image domain, such as modulus extraction, logarithmic compression, grayscale transformation, and / or other unlisted image processing. Furthermore, image processing can also be image algorithm processing of the generated ultrasonic image.

[0097] The above is an explanation of ultrasound equipment. The following is a detailed explanation of the process of assessing cardiac systolic function based on ultrasound equipment.

[0098] Processor 20 acquires ultrasound image sequences of the target heart.

[0099] In some embodiments, the processor 20 can read the stored ultrasound image sequence from the memory 80, or it can acquire the data in real time based on the ultrasound probe. For example, the processor controls the ultrasound probe to emit ultrasound waves toward the target heart and receives the echo of the ultrasound waves to obtain the corresponding ultrasound echo signal. The ultrasound echo signal is then processed to obtain the ultrasound image sequence of the target heart.

[0100] In some embodiments, the ultrasound image sequence includes multiple ultrasound images, and the ultrasound image sequence includes at least multiple ultrasound images corresponding to a complete cardiac cycle, so that the ultrasound image sequence can reflect the changes of the target heart during at least one complete cardiac cycle, facilitating the analysis of relevant ultrasound parameters of the target heart based on the ultrasound image sequence. In some embodiments, the complete cardiac cycle can be determined based on various existing methods, such as determining the complete cardiac cycle based on the periodicity of the ECG signal, which will not be elaborated here.

[0101] In some embodiments, the ultrasound image sequence may include multiple frames of ultrasound images corresponding to multiple complete cardiac cycles. The section types of the multiple frames of ultrasound images corresponding to each complete cardiac cycle may be the same or different. For example, multiple frames of ultrasound images corresponding to a complete cardiac cycle may be acquired in the apical two-chamber view (A2C), the apical four-chamber view (A4C), and the apical three-chamber view (A3C), or multiple frames of ultrasound images corresponding to a complete cardiac cycle may be acquired in the apical four-chamber view (A4C).

[0102] In some embodiments, when multiple frames of ultrasound images corresponding to multiple complete cardiac cycles are available, ultrasound parameters can be calculated based on multiple complete cardiac cycles, or the optimal cardiac cycle can be selected for ultrasound parameter calculation. This can be done manually by the user or automatically. For example, the chambers in each frame of the ultrasound image within the cardiac cycle can be segmented using traditional or artificial intelligence methods, and the area of ​​the chambers can be calculated. Then, the cardiac cycle corresponding to the largest or smallest area can be selected as the optimal cardiac cycle. Alternatively, the ultrasound image sequence can be directly input into existing convolutional neural networks or deep learning networks, and the optimal cardiac cycle in the ultrasound image sequence can be directly output.

[0103] In some embodiments, ultrasound images can reflect the tissue structure of the target heart, thereby enabling the calculation of relevant ultrasound parameters based on the ultrasound images. For example, in B (brightness) mode, the ultrasound probe can be controlled to perform ultrasound imaging on one or more slice types of the target heart, and an ultrasound image sequence corresponding to one or more slice types can be obtained.

[0104] After acquiring the ultrasound image sequence, the processor 20 calculates multiple ultrasound parameters related to the target heart and its contractile function based on the ultrasound image sequence.

[0105] In some embodiments, multiple ultrasound parameters related to systolic function include one or more of GLS (global longitudinal strain), EF (ejection fraction), FAC (rate of change of area), MAPSE (mitral annular displacement), and TAPSE (tricuspid annular displacement).

[0106] In some embodiments, when calculating multiple ultrasound parameters related to the target heart's systolic function, the left ventricular ejection fraction (EF) and left ventricular gross suture length (GLS) can be calculated based on multiple frames of ultrasound images corresponding to a complete cardiac cycle from an apical two-chamber view; the left ventricular GLS can be calculated based on multiple frames of ultrasound images corresponding to a complete cardiac cycle from an apical three-chamber view; and MAPSE, TAPSE, right ventricular femoral artery occlusion (FAC), right ventricular GLS, left ventricular GLS, and left ventricular EF can be calculated based on multiple frames of ultrasound images corresponding to a complete cardiac cycle from an apical four-chamber view. These ultrasound parameters can be calculated based on a single section type or by combining multiple section types; details will not be elaborated further here.

[0107] In some embodiments, based on different calculation processes for different ultrasound indicators, the aforementioned multiple ultrasound indicators can be divided into a first category of ultrasound indicators and a second category of ultrasound indicators. The first category of ultrasound indicators is related to the strain parameters and / or displacement parameters of the myocardial tissue of the target heart, including global longitudinal strain, mitral annular displacement, and tricuspid annular displacement. The second category of ultrasound indicators is related to the ventricular volume parameters and / or area parameters of the target heart, and / or to the atrial volume parameters and / or area parameters of the target heart, including ejection fraction and rate of change of area.

[0108] In some embodiments, the processor performs a first processing on the ultrasound image sequence to obtain at least one of a first type of ultrasound index, and performs a second processing to obtain at least one of a second type of ultrasound index.

[0109] Please refer to Figure 2 In some embodiments, the first process includes a common process 111 and a first branch process 112, and the second process includes a common process 111 and a second branch process 113.

[0110] In this embodiment, a common processing step 111 is performed on the ultrasound image sequence to obtain multiple target myocardial sampling points of the target heart. In some embodiments, the common processing step 111 can be an automated process. For example, it can involve first determining the target myocardial tissue of the target heart based on the ultrasound image sequence, and then performing sampling processing on the target myocardial tissue to obtain multiple target myocardial sampling points. For instance, the first ultrasound image can be determined from multiple ultrasound images corresponding to a complete cardiac cycle, and then the target myocardial tissue can be determined based on the first ultrasound image. In some embodiments, different ultrasound indices can be calculated from multiple ultrasound images of different section types; therefore, the target myocardial tissue can correspond to the section type, thereby calculating matching ultrasound indices. In some embodiments, the target myocardial tissue can be the myocardial tissue corresponding to the ventricle and / or atrium, thereby calculating different corresponding ultrasound indices based on different myocardial tissues of the ventricle and / or atrium.

[0111] In some embodiments, the target myocardial sampling points are located within the contour of the target myocardial tissue, i.e., the envelope of the target myocardial tissue. In some embodiments, during the above sampling process, the contour of the target myocardial tissue is first determined, and then point sampling is performed on the contour of the target myocardial tissue to obtain multiple target myocardial sampling points. The target myocardial tissue can be segmented using existing segmentation methods, such as deep learning segmentation networks, region-based segmentation algorithms, or machine learning-based segmentation methods, to extract the boundaries of the myocardial tissue and thus determine the contour of the target myocardial tissue. For example, all chambers can be segmented in the first frame of the ultrasound image, and then the contour of the target myocardial tissue can be determined based on the segmentation results; this will not be elaborated further here.

[0112] In some embodiments, when performing the above-mentioned point sampling, point sampling can be performed at equal intervals based on the contour of the target myocardial tissue, ensuring consistent spacing between each target myocardial sampling point, thereby facilitating rapid point sampling. In some embodiments, point sampling can also be performed based on the degree of contraction of the target myocardial tissue corresponding to its contour. This results in smaller spacing between target myocardial sampling points corresponding to a target myocardial tissue with greater contraction, and larger spacing between target myocardial sampling points corresponding to a target myocardial tissue with less contraction. This ensures that the density of sampling points matches the degree of contraction of the target myocardial tissue, thereby improving the effectiveness of point sampling and the accuracy of subsequently calculated ultrasound parameters.

[0113] In some embodiments, the degree of contraction of the target myocardial tissue can be determined based on the slope corresponding to the contour of the target myocardial tissue. For example, the slope corresponding to the contour of the target myocardial tissue can be determined first, and point sampling can be performed based on the slope of the contour of the target myocardial tissue. This results in contours with larger slopes having smaller spacing between the target myocardial tissue sampling points, and contours with smaller slopes having larger spacing between the target myocardial tissue sampling points. For example, the slope is calculated every preset length of contour, and then the target myocardial tissue corresponding to the preset length of contour is sampled at equal intervals matching the slope.

[0114] In some embodiments, the shared processing 111 can also be a manual process. For example, the processor responds to the user's sampling operation on the target myocardial tissue in the first frame of the ultrasound image and acquires multiple corresponding target myocardial sampling points. For instance, the user performs a touch operation on the outline of the target myocardial tissue, and then acquires the corresponding target myocardial sampling points based on the position corresponding to the touch operation. In some embodiments, the shared processing can also be a combination of manual and automatic processing, which will not be elaborated here.

[0115] Based on the target myocardial sampling points in different ultrasound images in the ultrasound image sequence, the first branch processing is performed to obtain at least one ultrasound index in the first category of ultrasound indices, and the second branch processing is performed to obtain at least one ultrasound index in the second category of ultrasound indices.

[0116] In some embodiments, during the first branch processing 112, the target myocardial sampling points are tracked using existing tracking technologies. First, the position of each target myocardial sampling point in each ultrasound image sequence is determined. Then, based on the positional changes of the target myocardial sampling points in different ultrasound images within the sequence, a first type of ultrasound index is calculated, such as at least one of overall longitudinal strain, mitral annular displacement, and tricuspid annular displacement. The existing tracking technologies can be speckle tracking or artificial intelligence-based tracking technologies, which will not be elaborated further here.

[0117] In some embodiments, when calculating the first type of ultrasound index, the distance between the target myocardial sampling points corresponding to the first type of ultrasound index in different ultrasound images is calculated. Based on the distance between the target myocardial sampling points corresponding to the first type of ultrasound index in different ultrasound images, the strain parameters and / or displacement parameters of the target myocardial tissue are calculated to obtain the first type of ultrasound index.

[0118] In some embodiments, when calculating the overall longitudinal strain, the sum of distances between target myocardial sampling points corresponding to the overall longitudinal strain in different ultrasound images is calculated, and the overall longitudinal strain is obtained based on the sum of distances calculated from different ultrasound images. For example... Figure 3 Multiple target myocardial sampling points corresponding to the ventricle are... Figure 3The black dots represent the length of the myocardial tissue corresponding to each ventricle. By calculating the distance between each target myocardial sampling point, the length of the myocardial tissue is obtained. The overall longitudinal strain is then calculated by determining the variation in the length of the myocardial tissue across different ultrasound images, i.e., calculating the strain parameters of the corresponding myocardial tissue. For example, the overall longitudinal strain primarily calculates the change in the length of the corresponding myocardial tissue between end-systole and end-diastole.

[0119] In some embodiments, when calculating the mitral annular displacement, the distance between target myocardial sampling points corresponding to the mitral annular displacement in different ultrasound images is calculated. Based on the distances calculated corresponding to the mitral annular displacement in different ultrasound images, the mitral annular displacement is obtained. For example... Figure 4 The mitral valve annulus and the apex of the heart correspond to multiple target myocardial sampling points in the myocardial tissue. Figure 4 The black dots represent the distance between the mitral valve annulus and the apex of the heart, calculated by determining the distance between the target myocardial sampling points corresponding to the mitral valve annulus and the apex of the heart, respectively. This involves calculating the displacement parameters of the corresponding myocardial tissue. For example, mitral valve annulus displacement primarily involves calculating the change in distance from the corresponding tissue of the mitral valve annulus (e.g., the lateral wall of the mitral valve annulus) to the apex tissue between end-systole and end-diastole.

[0120] In some embodiments, when calculating the tricuspid annular displacement, the distance between target myocardial sampling points corresponding to the tricuspid annular displacement in different ultrasound images is calculated. Based on the distances calculated corresponding to the tricuspid annular displacement in different ultrasound images, the displacement parameters of the corresponding myocardial tissue are calculated to obtain the tricuspid annular displacement. For example, the tricuspid annular displacement mainly calculates the change in the distance from the tissue corresponding to the tricuspid annular annular annular annular annular annular annular annular annular to the apex tissue between end-systole and end-diastole.

[0121] In some embodiments, during the second branch processing 113, the target myocardial sampling points are tracked based on existing tracking technology. First, the position of each target myocardial sampling point in each ultrasound image sequence is determined. Then, the target myocardial sampling points in different ultrasound images in the ultrasound image sequence are connected to obtain the target myocardial tissue contour. Based on the positional changes of the target myocardial tissue contour in different ultrasound images, a second type of ultrasound index is calculated, such as at least one of ejection fraction and area change rate.

[0122] In some embodiments, when calculating the second type of ultrasound index, the area and / or volume corresponding to the target myocardial tissue contour in different ultrasound images corresponding to the second type of ultrasound index are calculated, and the second type of ultrasound index is calculated based on the area parameters and / or volume parameters corresponding to the target myocardial tissue contour in different ultrasound images.

[0123] In some embodiments, when calculating the ejection fraction, the volume corresponding to the target myocardial tissue contour in different ultrasound images corresponding to the ejection fraction is calculated, and the ejection fraction is obtained based on the volume calculated from the different ultrasound images. For example... Figure 5 The outline of the myocardial tissue corresponding to the ventricle is... Figure 5 The black lines in the diagram are formed by connecting multiple target myocardial sampling points. The volume corresponding to the myocardial tissue contour is calculated, i.e., the volume parameter corresponding to the myocardial tissue contour is calculated to obtain the ejection fraction. For example, the ejection fraction mainly calculates the change in the volume of the corresponding myocardial tissue contour between end-systole and end-diastole.

[0124] In some embodiments, when calculating the area change rate, the area corresponding to the target myocardial tissue contour in different ultrasound images corresponding to the area change rate is calculated, that is, the area parameter corresponding to the myocardial tissue contour is calculated, and then the area change rate is obtained based on the area calculated from different ultrasound images. For example, the area change rate mainly calculates the change in the area of ​​the corresponding myocardial tissue contour between the end of cardiac systole and the end of cardiac diastole.

[0125] In some embodiments, the step of tracking the target myocardial sampling points based on existing tracking technology and first determining the position of each target myocardial sampling point in each ultrasound image in the ultrasound image sequence can be a step shared by the first branch processing and the second branch processing, or a step included in both the first branch processing and the second branch processing.

[0126] In the above embodiments, multiple ultrasound indicators can be calculated at once based on a single ultrasound indicator calculation model. For example, the first type of ultrasound indicator and the second type of ultrasound indicator can be calculated based on the third processing model 11. The third processing model 11 includes a common processing 111 and a first branch processing 112 of the first processing, and a common processing 111 and a second branch processing 113 of the second processing.

[0127] In some embodiments, when calculating the above-mentioned multiple ultrasound indicators, the corresponding ultrasound indicators can also be calculated separately based on different multiple ultrasound indicator calculation models, which will be explained separately below.

[0128] In some embodiments, the processor can calculate the corresponding ultrasound indicators using multiple calculation models based on different calculation processes for multiple ultrasound indicators. For example, based on a first processing model, it can calculate one or more of the following from ultrasound image sequences: overall longitudinal strain, mitral annular displacement, and tricuspid annular displacement. These indicators are mainly related to the strain and / or displacement parameters of myocardial tissue. Alternatively, based on a second processing model, it can calculate one or both of the following from ultrasound image sequences: ejection fraction and rate of change of area. These indicators are mainly related to the area and / or volume parameters of the myocardial tissue contour.

[0129] In some embodiments, a first type of ultrasound index is calculated based on a first processing model during a first time period. This involves first determining the target myocardial tissue of the target heart based on an ultrasound image sequence, and then calculating the first type of ultrasound index based on the positional changes of the target myocardial tissue in different ultrasound images within the sequence. For example, this might involve calculating one or more of the following: global longitudinal strain, mitral annular displacement, and tricuspid annular displacement. For instance, the first ultrasound image is determined from multiple frames corresponding to a complete cardiac cycle. The target myocardial tissue of the target heart is then determined based on this first frame. The target myocardial tissue is then tracked using existing tracking technology to obtain its position in other ultrasound images within the multiple frames corresponding to the complete cardiac cycle. Finally, the corresponding ultrasound index is calculated based on the positional changes of the target myocardial tissue. Specifically, global longitudinal strain primarily calculates the change in the length of the corresponding myocardial tissue between end-systole and end-diastole; mitral annular displacement primarily calculates the change in the distance from the corresponding mitral annular tissue to the apex between end-systole and end-diastole; and tricuspid annular displacement primarily calculates the change in the distance from the corresponding tricuspid annular tissue to the apex between end-systole and end-diastole. In some embodiments, one or more of the mitral annular displacement and tricuspid annular displacement can also be calculated based on the first processing model.

[0130] In some embodiments, a second type of ultrasound index is calculated based on a second processing model during a second time period. First, the target myocardial tissue contour of the target heart is determined based on the ultrasound image sequence. Then, based on the positional changes of the target myocardial tissue contour in different ultrasound images within the sequence, the second type of ultrasound index is calculated, such as calculating one or both of ejection fraction and area change rate. For example, from multiple ultrasound images corresponding to a complete cardiac cycle, the first ultrasound image is determined, and the target myocardial tissue contour of the target heart is determined based on the first ultrasound image. Then, the target myocardial tissue contour is tracked using existing tracking techniques to obtain the position of the target myocardial tissue contour in other ultrasound images corresponding to the complete cardiac cycle. Finally, the corresponding ultrasound index is calculated based on the positional changes of the target myocardial tissue contour. The target myocardial tissue contour can be determined using existing segmentation methods, which will not be elaborated further here. Based on the myocardial tissue contour, its corresponding area parameters and / or volume parameters can be calculated. The ejection fraction mainly calculates the change in volume of the corresponding myocardial tissue contour between end-systole and end-diastole, and the area change rate mainly calculates the change in area of ​​the corresponding myocardial tissue contour between end-systole and end-diastole. In some embodiments, one or more of the overall longitudinal strain, ejection fraction, and area change rate can also be calculated based on the second calculation model.

[0131] In the above embodiments, the first time period and the second time period are the same, or the first time period and the second time period share a common period of time. That is, the first processing model and the second processing model do not calculate the ultrasound indicators sequentially, but simultaneously. Therefore, with a single operation by the user, the first processing model and the second processing model can calculate the first type of ultrasound indicators and the second type of ultrasound indicators simultaneously, without the user needing to activate the first processing model and the second processing model separately.

[0132] After calculating the first type of ultrasound index and the second type of ultrasound index, the processor 20 controls the human-computer interaction device 70 to display the first type of ultrasound index and the second type of ultrasound index.

[0133] In some embodiments, the display controls the display of at least one of the first type of ultrasound parameters and at least one of the second type of ultrasound parameters. In some embodiments, all of the calculated first type of ultrasound parameters and all of the calculated second type of ultrasound parameters are displayed. For example, global longitudinal strain, mitral annular displacement, and ejection fraction may be displayed; for example, global longitudinal strain, tricuspid annular displacement, and ejection fraction may be displayed; for example, global longitudinal strain, mitral annular displacement, and area change rate may be displayed; for example, global longitudinal strain, tricuspid annular displacement, and area change rate may be displayed.

[0134] In some embodiments, the processor can also identify the chambers of the target heart in the ultrasound image sequence, including at least one of the left atrium, right atrium, left ventricle, and right ventricle, and then display the corresponding first-type ultrasound indices and / or second-type ultrasound indices for each identified chamber. For example, displaying MAPSE, TAPSE, FAC of the right ventricle, GLS of the right ventricle, GLS of the left ventricle, and EF of the left ventricle.

[0135] The above is an explanation of using ultrasound equipment to assess cardiac contractile function.

[0136] Some embodiments provide a method for assessing cardiac contractile function, which can be applied to the aforementioned ultrasound equipment. Please refer to... Figure 6 Methods for assessing cardiac systolic function may include the following steps:

[0137] Step 100: Acquire an ultrasound image sequence of the target heart. The ultrasound image sequence includes multiple ultrasound images that reflect the tissue structure of the target heart.

[0138] Step 110: Perform a first processing on the ultrasound image sequence to obtain the first type of ultrasound index.

[0139] Step 120: Perform a second processing on the ultrasound image sequence to obtain the second type of ultrasound index.

[0140] The first processing includes common processing and first branch processing, and the second processing includes common processing and second branch processing. The common processing of the ultrasound image sequence yields multiple target myocardial sampling points. Based on the target myocardial sampling points of different ultrasound images in the ultrasound image sequence, the first branch processing yields a first type of ultrasound index, and the second branch processing yields a second type of ultrasound index.

[0141] Step 130: Display the first type of ultrasound indicators and the second type of ultrasound indicators.

[0142] Some embodiments provide a method for assessing cardiac contractile function, which can be applied to the aforementioned ultrasound equipment. Please refer to... Figure 7 Methods for assessing cardiac systolic function may include the following steps.

[0143] Step 200: Acquire an ultrasound image sequence of the target heart. The ultrasound image sequence includes multiple ultrasound images that reflect the tissue structure of the target heart.

[0144] Step 210: Calculate multiple ultrasound parameters simultaneously based on the ultrasound image sequence. These multiple ultrasound parameters include first-type ultrasound parameters and second-type ultrasound parameters.

[0145] Step 220: Display multiple ultrasound parameters.

[0146] Some embodiments provide a computer-readable storage medium storing a program that can be executed by a processor to implement the above-described cardiac contractile function assessment method.

[0147] Those skilled in the art will understand that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in a server, another computer, disk, optical disk, flash drive, or external hard drive, etc., and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be achieved.

[0148] The above examples illustrate this application only to aid understanding and are not intended to limit its scope. Those skilled in the art to which this application pertains can make various simple deductions, modifications, or substitutions based on the ideas presented.

Claims

1. A method for assessing cardiac contractile function, characterized in that, include: Acquire an ultrasound image sequence of the target heart, the ultrasound image sequence comprising multiple ultrasound images, the ultrasound images being able to reflect the tissue structure of the target heart; The ultrasound image sequence is first processed to obtain a first type of ultrasound index related to the contractile function of the target heart, and then processed to obtain a second type of ultrasound index related to the contractile function of the target heart. The first type of ultrasound index is related to the strain parameters and / or displacement parameters of the myocardial tissue of the target heart, and the second type of ultrasound index is related to the ventricular volume parameters and / or area parameters of the target heart, and / or to the atrial volume parameters and / or area parameters of the target heart. The first process includes a common process and a first branch process, and the second process includes the common process and the second branch process. The common processing of the ultrasound image sequence yields multiple target myocardial sampling points. Based on the target myocardial sampling points of different ultrasound images in the ultrasound image sequence, the first branch processing is performed to obtain the first type of ultrasound index, and the second branch processing is performed to obtain the second type of ultrasound index. The first type of ultrasound index and the second type of ultrasound index are displayed.

2. The method for assessing cardiac contractile function as described in claim 1, characterized in that, The shared processing of the ultrasound image sequence yields multiple target myocardial sampling points, including: Based on the ultrasound image sequence, the target myocardial tissue of the target heart is determined, and the target myocardial tissue is sampled to obtain the multiple target myocardial sampling points. or, In response to the user's sampling operation of the target myocardial tissue of the target heart in the ultrasound image sequence, the corresponding plurality of target myocardial sampling points are obtained.

3. The method for assessing cardiac contractile function as described in claim 2, characterized in that, Multiple target myocardial sampling points are located within the outline of the target myocardial tissue.

4. The method for assessing cardiac contractile function as described in claim 2, characterized in that, The target myocardial tissue is sampled to obtain the multiple target myocardial sampling points, including: Determine the contour of the target myocardial tissue; The contour of the target myocardial tissue is sampled to obtain the multiple target myocardial sampling points.

5. The method for assessing cardiac contractile function as described in claim 4, characterized in that, Point sampling of the contour of the target myocardial tissue includes: Equally spaced point sampling is performed based on the contour of the target myocardial tissue, so that the spacing between each target myocardial sampling point is consistent. And / or, Based on the degree of contraction of the target myocardial tissue, point sampling is performed on its corresponding contour, so that the target myocardial tissue with a greater degree of contraction has a smaller spacing between the target myocardial sampling points on its corresponding contour, and the target myocardial tissue with a smaller degree of contraction has a larger spacing between the target myocardial sampling points on its corresponding contour.

6. The method for assessing cardiac contractile function as described in claim 5, characterized in that, Based on the degree of contraction of the target myocardial tissue, point sampling is performed on its corresponding contour, including: Determine the slope corresponding to the contour of the target myocardial tissue, and perform point sampling based on the slope corresponding to the contour of the target myocardial tissue, so that the spacing between the target myocardial sampling points corresponding to the contour with a larger slope is smaller, and the spacing between the target myocardial sampling points corresponding to the contour with a smaller slope is larger.

7. The method for assessing cardiac systolic function as described in claim 1, characterized in that, Based on the target myocardial sampling points in different ultrasound images within the ultrasound image sequence, the first branch processing is performed to obtain the first type of ultrasound index, and the second branch processing is performed to obtain the second type of ultrasound index, including: Determine the location of each of the target myocardial sampling points in each ultrasound image within the ultrasound image sequence; The first type of ultrasound index is calculated based on the positional changes of the target myocardial sampling point in different ultrasound images in the ultrasound image sequence. The target myocardial tissue contour is obtained by connecting the target myocardial sampling points in different ultrasound images in the ultrasound image sequence. The second type of ultrasound index is calculated based on the positional changes of the target myocardial tissue contour in different ultrasound images.

8. The method for assessing cardiac systolic function as described in claim 7, characterized in that: Calculating the first type of ultrasound index includes: Calculate the distance between the target myocardial sampling points corresponding to the first type of ultrasound index in different ultrasound images, and calculate the strain parameters and / or displacement parameters of the target myocardial tissue based on the distance between the target myocardial sampling points corresponding to the first type of ultrasound index in different ultrasound images to obtain the first type of ultrasound index; And / or, The calculation of the second type of ultrasound index includes: Calculate the area and / or volume corresponding to the contour of the target myocardial tissue in different ultrasound images that correspond to the second type of ultrasound index. Based on the area and / or volume parameters corresponding to the contour of the target myocardial tissue in different ultrasound images, calculate the second type of ultrasound index.

9. The method for assessing cardiac contractile function as described in claim 1, characterized in that, The first type of ultrasound indicators includes at least one of overall longitudinal strain, mitral annular displacement, and tricuspid annular displacement, and the second type of ultrasound indicators includes at least one of ejection fraction and area change rate.

10. The method for assessing cardiac systolic function as described in claim 9, characterized in that: When calculating the overall longitudinal strain, the sum of the distances between the target myocardial sampling points corresponding to the overall longitudinal strain in different ultrasound images is calculated, and the overall longitudinal strain is obtained based on the sum of the distances calculated in different ultrasound images. And / or, When calculating the ejection fraction, the volume corresponding to the target myocardial tissue contour in different ultrasound images corresponding to the ejection fraction is calculated, and the ejection fraction is obtained based on the volume calculated from the different ultrasound images. And / or, When calculating the area change rate, the area corresponding to the target myocardial tissue contour corresponding to the area change rate in different ultrasound images is calculated, and the area change rate is obtained based on the area calculated from the different ultrasound images. and / or, When calculating the mitral annulus displacement, the distance between the target myocardial sampling points corresponding to the mitral annulus displacement in different ultrasound images is calculated. Based on the distances calculated corresponding to the mitral annulus displacement in different ultrasound images, the mitral annulus displacement is obtained. and / or, When calculating the tricuspid annular displacement, the distance between the target myocardial sampling points corresponding to the tricuspid annular displacement in different ultrasound images is calculated. Based on the distances calculated corresponding to the tricuspid annular displacement in different ultrasound images, the tricuspid annular displacement is obtained.

11. The method for assessing cardiac systolic function as described in claim 1, characterized in that, Displaying the first type of ultrasound indicators and the second type of ultrasound indicators, including: Identify the chambers of the target heart in the ultrasound image sequence, the chambers including at least one of the left atrium, right atrium, left ventricle, and right ventricle; For each identified chamber, display its corresponding first type of ultrasound index and / or second type of ultrasound index.

12. A method for assessing cardiac systolic function, characterized in that, include: Acquire an ultrasound image sequence of the target heart, the ultrasound image sequence comprising multiple ultrasound images, the ultrasound images being able to reflect the tissue structure of the target heart; Based on the ultrasound image sequence, multiple ultrasound indicators related to the contractile function of the target heart are calculated simultaneously. The multiple ultrasound indicators include a first type of ultrasound indicator and a second type of ultrasound indicator. The first type of ultrasound indicator is related to the strain parameters and / or displacement parameters of the myocardial tissue of the target heart, and the second type of ultrasound indicator is related to the ventricular volume parameters and / or area parameters of the target heart, and / or to the atrial volume parameters and / or area parameters of the target heart. The multiple ultrasound indicators are displayed.

13. The method for assessing cardiac systolic function as described in claim 12, characterized in that, Based on the ultrasound image sequence, multiple ultrasound parameters related to the target heart and its systolic function are calculated simultaneously, including: In the first time period, the first type of ultrasound index is calculated based on the first processing model: the target myocardial tissue of the target heart is determined based on the ultrasound image sequence, and the first type of ultrasound index is calculated based on the positional changes of the target myocardial tissue in different ultrasound images in the ultrasound image sequence. In the second time period, the second type of ultrasound index is calculated based on the second processing model: the target myocardial tissue contour of the target heart is determined based on the ultrasound image sequence, and the second type of ultrasound index is calculated based on the positional change of the target myocardial tissue contour in different ultrasound images in the ultrasound image sequence. Wherein, the first time period and the second time period are the same, or the first time period and the second time period share a common period of time; or, The first type of ultrasound index and the second type of ultrasound index are calculated based on the third processing model: the ultrasound image sequence is processed in the first way to obtain the first type of ultrasound index related to the target heart and systolic function, and processed in the second way to obtain the second type of ultrasound index related to the target heart and systolic function; wherein, the first processing includes common processing and first branch processing, and the second processing includes the common processing and second branch processing; the common processing is performed on the ultrasound image sequence to obtain multiple target myocardial sampling points, and the first branch processing is performed on the target myocardial sampling points in different ultrasound images in the ultrasound image sequence to obtain the first type of ultrasound index, and the second branch processing is performed to obtain the second type of ultrasound index.

14. A method for assessing cardiac contractile function, characterized in that, include: Acquire an ultrasound image sequence of the target heart, the ultrasound image sequence comprising multiple ultrasound images, the ultrasound images being able to reflect the tissue structure of the target heart; Calculate multiple ultrasound indicators related to the contractile function of the target heart based on the ultrasound image sequence; The multiple ultrasound indicators are displayed.

15. An ultrasonic device, characterized in that, include: An ultrasonic probe is used to emit ultrasonic waves toward a region of interest and to receive the echoes of the ultrasonic waves. A transmitting and receiving control circuit is used to control the ultrasonic probe to transmit ultrasonic waves toward the region of interest and to receive the echoes of the ultrasonic waves. A processor for executing computer programs and / or instructions to implement the method as described in any one of claims 1-14.

16. A computer-readable storage medium, characterized in that, The medium stores a program that can be executed by a processor to implement the method as described in any one of claims 1-14.

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