Heart evaluation parameter determination method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a method and device for determining evaluation parameters of a heart, equipment and a storage medium. The method comprises the following steps: acquiring a Doppler ultrasonic spectrum image of the heart; determining each cardiac cycle based on the Doppler ultrasound spectrum image; and determining the evaluation parameters for evaluating the cardiac function based on each cardiac cycle and the Doppler ultrasonic spectrum image, so that the evaluation parameters can be automatically identified based on the image, the detection efficiency can be improved, and the accuracy of the determined evaluation parameters can be improved.

Description

Technical Field

[0001] The present application belongs to the field of medical technology, and in particular, relates to a method, device, equipment and storage medium for determining evaluation parameters of a heart. Background Art

[0002] In conventional cardiac ultrasound examinations, doctors can use tissue Doppler imaging methods to print out the velocity spectra of the mitral valve annulus septum, mitral valve annulus lateral wall, and tricuspid valve annulus lateral wall of the patient on the apical four-chamber heart section as needed. On these spectra, doctors can obtain the following parameters by manual direct measurement: early diastolic velocity e', late diastolic velocity a', systolic velocity S', isovolumic relaxation time IVRT (Isovolumic Relaxation Time), isovolumic contraction time IVCT (Isovolumic Contraction Time) and ejection time ET (Ejection Time). In actual examinations, this method that completely relies on manual measurement by doctors requires doctors to use measurement tools to measure points and time periods many times, which will lead to problems such as long cardiac ultrasound examinations and low efficiency. At the same time, due to the unclear boundaries and small intervals of IVCT, IVRT, and ET, large deviations are likely to occur when clinicians are inexperienced and operate in a careful manner, resulting in increased measurement errors. Summary of the invention

[0003] To solve the above technical problems, the embodiments of the present application provide a method, device, equipment and storage medium for determining evaluation parameters of the heart, which can automatically identify evaluation parameters based on images, improve detection efficiency, and improve the accuracy of determined evaluation parameters.

[0004] In a first aspect, an embodiment of the present application provides a method for determining a cardiac assessment parameter, comprising:

[0005] Acquire Doppler ultrasound spectrum images of the heart;

[0006] Determine each cardiac cycle based on the Doppler ultrasound spectrum image;

[0007] An evaluation parameter for evaluating the heart function is determined based on each cardiac cycle and the Doppler ultrasound spectrum image.

[0008] In some embodiments, determining each cardiac cycle based on the Doppler ultrasound spectrum image includes:

[0009] Segmenting the Doppler ultrasound spectrum image based on the abscissa in the Doppler ultrasound spectrum image to obtain a first Doppler ultrasound spectrum image above the abscissa;

[0010] Determine each minimum value position in the spectrum based on the first Doppler ultrasound spectrum image;

[0011] Individual cardiac cycles are determined based on the minimum positions.

[0012] In some embodiments, determining each minimum position in the spectrum based on the first Doppler ultrasound spectrum image includes:

[0013] Binarizing the first Doppler ultrasound spectrum image;

[0014] Accumulating pixel values ​​on the ordinate in the first Doppler ultrasound spectrum image after the binarization process and performing smoothing process to obtain a processed first Doppler ultrasound spectrum image;

[0015] The minimum position in the spectrum is determined based on the processed first Doppler ultrasound spectrum image.

[0016] In some embodiments, determining the evaluation parameters for evaluating the cardiac function based on each cardiac cycle and the Doppler ultrasound spectrum image comprises:

[0017] Dividing the first Doppler ultrasound spectrum image into a plurality of first sub-images based on each cardiac cycle;

[0018] The first sub-image is input into a first key point detection model to obtain the target key point position in the contraction period of each cardiac cycle.

[0019] In some embodiments, the target key point positions of the systolic period include: the peak position of the systolic movement velocity, the starting position and the ending position of the ejection period, and the evaluation parameters for evaluating the cardiac function determined based on each cardiac cycle and the Doppler ultrasound spectrum image also include:

[0020] Mapping the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase in each cardiac cycle back to the Doppler ultrasound spectrum image to obtain a third Doppler ultrasound spectrum image;

[0021] Based on the peak position of the systolic motion velocity corresponding to each cardiac cycle, the second Doppler ultrasound spectrum image under the horizontal coordinate in the Doppler ultrasound spectrum image is divided into periods to obtain a second sub-image corresponding to each cardiac cycle;

[0022] The second sub-image corresponding to each cardiac cycle is input into the second key point detection model to obtain the target key point position of the diastolic period in the second sub-image corresponding to each cardiac cycle.

[0023] In some embodiments, the target key point position of the diastolic period includes: the peak position and the starting position of the early diastolic motion velocity, the peak position and the ending position of the late diastolic motion velocity, and the evaluation parameters for evaluating the cardiac function determined based on each cardiac cycle and the Doppler ultrasound spectrum image also include:

[0024] Mapping the peak position and starting position of the early diastolic motion velocity and the peak position and ending position of the late diastolic motion velocity corresponding to each cardiac cycle back to the third Doppler ultrasound spectrum image to obtain a target Doppler ultrasound spectrum image;

[0025] The cardiac function evaluation parameters are obtained based on the target Doppler ultrasound spectrum image.

[0026] In some embodiments, the cardiac function evaluation parameters include: one or more of: systolic tissue motion velocity peak S', early diastolic tissue motion velocity peak e', late diastolic tissue motion velocity peak a', isovolumetric contraction time, ejection time and isovolumetric relaxation time. The cardiac function evaluation parameters obtained based on the target Doppler ultrasound spectrum image include:

[0027] Determine the velocity corresponding to the peak position of the systolic motion velocity in the target Doppler ultrasound spectrum image as the systolic tissue motion velocity peak value S', and / or;

[0028] Determine the velocity corresponding to the peak position of the early diastolic motion velocity in the target Doppler ultrasound spectrum image as the peak velocity e' of the early diastolic tissue motion velocity, and / or;

[0029] Determine the velocity corresponding to the peak position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image as the peak velocity a' of the late diastolic tissue motion velocity, and / or;

[0030] Determine the time between the end position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image and the start position of the ejection phase adjacent to the right as the isovolumetric contraction time, and / or;

[0031] Determining the time between the starting position and the ending position of the ejection period in the target Doppler ultrasound spectrum image as the ejection time; and / or,

[0032] The time between the end position of the ejection phase in the target Doppler ultrasound spectrum image and the start position of the adjacent early diastolic motion velocity on the right is determined as the isovolumetric relaxation time.

[0033] In some embodiments, the method further comprises:

[0034] Obtain an average value of the peak value S' of the systolic tissue movement velocity in each cardiac cycle, or determine the peak value S' of the systolic tissue movement velocity in one cardiac cycle based on the first selection instruction to obtain a target peak value S' of the systolic tissue movement velocity;

[0035] Obtaining an average of the peak values ​​of the early diastolic tissue motion velocity e' in each cardiac cycle, or determining the peak value of the early diastolic tissue motion velocity e' in one cardiac cycle based on the second selection instruction, to obtain a target peak value of the early diastolic tissue motion velocity e';

[0036] Obtaining an average value of the peak value a' of the late diastolic tissue motion velocity in each cardiac cycle, or determining the peak value a' of the late diastolic tissue motion velocity in one cardiac cycle based on the third selection instruction, to obtain a target peak value a' of the late diastolic tissue motion velocity;

[0037] Calculate the average value of each isovolumetric contraction time in each cardiac cycle, or determine the isovolumetric contraction time of one cardiac cycle based on the fourth selection instruction to obtain a target isovolumetric contraction time;

[0038] Calculate the average value of each ejection time in each cardiac cycle, or determine the ejection time of one cardiac cycle based on the fifth selection instruction to obtain a target ejection time;

[0039] The target isovolumetric expansion time is obtained by obtaining an average value of each isovolumetric relaxation time in each cardiac cycle, or determining the isovolumetric relaxation time of a cardiac cycle based on the sixth selection instruction.

[0040] In a second aspect, an embodiment of the present application provides a device for determining a cardiac evaluation parameter, comprising:

[0041] An acquisition module, used for acquiring a Doppler ultrasound spectrum image of the heart;

[0042] A first determination module, configured to determine each cardiac cycle based on the Doppler ultrasound spectrum image;

[0043] The second determination module is used to determine the evaluation parameters for evaluating the heart function based on each cardiac cycle and the Doppler ultrasound spectrum image.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described methods when executing the computer program.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any of the methods described above is implemented.

[0046] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the electronic device to execute any of the methods described above.

[0047] An embodiment of the present application provides a method for determining evaluation parameters of the heart, which obtains a Doppler ultrasound spectrum image of the heart; determines each cardiac cycle based on the Doppler ultrasound spectrum image; and determines evaluation parameters for evaluating the heart function based on each cardiac cycle and the Doppler ultrasound spectrum image. The method can automatically identify evaluation parameters based on images, improve detection efficiency, and improve the accuracy of determined evaluation parameters.

[0048] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 A schematic diagram of an implementation flow of a method for determining cardiac evaluation parameters provided in an embodiment of the present application;

[0051] Figure 2 A schematic diagram of the structure of a first key point detection model provided in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of displaying a measurement result provided in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of an implementation flow of a method for determining cardiac evaluation parameters provided in an embodiment of the present application;

[0054] Figure 5 A schematic diagram of a process for obtaining a sub-graph provided in an embodiment of the present application;

[0055] Figure 6 A schematic diagram of a peak position and a start and end position provided in an embodiment of the present application;

[0056] Figure 7 A schematic diagram of a process for obtaining a sub-graph provided in an embodiment of the present application;

[0057] Figure 8A schematic diagram of a sub-graph key point provided in an embodiment of the present application;

[0058] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0059] In the drawings, the same reference numerals are used for the same components, and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0060] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0061] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0062] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0063] As used in the specification of this application and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrases "if it is determined" or "if it is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce detected" or "in response to detecting" depending on the context.

[0064] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0065] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways.

[0066] Based on the technical problems of the related technologies, the embodiments of the present application provide a method for determining the evaluation parameters of the heart, which can be applied to electronic devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA), electrosurgery hosts, etc. The embodiments of the present application do not impose any restrictions on the specific types of electronic devices.

[0067] Based on the above embodiments, the present application provides a method for determining cardiac evaluation parameters. Figure 1 A schematic diagram of an implementation flow of a method for determining cardiac evaluation parameters provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, including:

[0068] Step S101, obtaining a Doppler ultrasound spectrum image of the heart.

[0069] In the embodiment of the present application, the Doppler ultrasound spectrum image is an image obtained by means of a technical means such as an ultrasound cardiogram. In an ultrasound cardiogram, the Doppler effect can be used to measure information such as the blood flow velocity and myocardial movement velocity in the heart, and the velocity information is displayed in the form of a spectrum. The abscissa of the Doppler ultrasound spectrum image represents the sampling time, and the ordinate represents the movement velocity (such as the blood flow velocity or myocardial movement velocity).

[0070] In the embodiment of the present application, an ultrasonic probe can be used to emit ultrasonic waves, and when the ultrasonic waves encounter the blood flow or myocardial tissue moving in the heart, reflection will occur. After receiving the reflected waves, the device calculates the velocity information based on the Doppler frequency shift principle, and then generates a Doppler ultrasonic spectrum image.

[0071] Step S102: determining each cardiac cycle based on the Doppler ultrasound spectrum image.

[0072] In the embodiment of the present application, the cardiac cycle refers to a mechanical activity cycle consisting of one contraction and relaxation of the heart, which includes stages such as atrial contraction, ventricular contraction and ventricular diastole.

[0073] In the embodiment of the present application, the cardiac cycle can be determined by using image recognition technology based on the Doppler ultrasound spectrum image.

[0074] Step S103: determining evaluation parameters for evaluating the cardiac function based on each cardiac cycle and the Doppler ultrasound spectrum image.

[0075] In the embodiment of the present application, the evaluation parameters can reflect the indicators of the working state of the heart. The evaluation parameters can measure the contractile function, diastolic function and overall pumping function of the heart from different angles. The evaluation parameters may include: one or more of the peak systolic tissue movement velocity S', the peak diastolic tissue movement velocity e', the peak diastolic tissue movement velocity a', the isovolumetric contraction time, the ejection time and the isovolumetric relaxation time.

[0076] In the embodiment of the present application, a neural network model can be combined based on each cardiac cycle and the Doppler ultrasound spectrum image to identify key points in the Doppler ultrasound spectrum image, and corresponding evaluation parameters are calculated based on the key points.

[0077] The method provided in the embodiment of the present application acquires a Doppler ultrasound spectrum image of the heart; determines each cardiac cycle based on the Doppler ultrasound spectrum image; and determines evaluation parameters for evaluating the heart function based on each cardiac cycle and the Doppler ultrasound spectrum image. The method can automatically identify evaluation parameters based on the image, improve detection efficiency, and improve the accuracy of the determined evaluation parameters.

[0078] In some embodiments, step S102 may be implemented by the following steps:

[0079] Step S1021 : segmenting the Doppler ultrasound spectrum image based on the abscissa in the Doppler ultrasound spectrum image to obtain a first Doppler ultrasound spectrum image above the abscissa.

[0080] In the embodiment of the present application, in a complete cardiac examination record, the Doppler ultrasound spectrum image may contain multiple cardiac cycles and some other information that may interfere with the analysis. By segmenting based on the horizontal axis, the purpose is to extract the first Doppler ultrasound spectrum image above the horizontal axis. When segmenting, the image below the horizontal axis, i.e., the second Doppler ultrasound spectrum image, can also be obtained.

[0081] Step S1022: determining positions of each minimum value in the spectrum based on the first Doppler ultrasound spectrum image.

[0082] In an embodiment of the present application, in the velocity change curve related to cardiac activity (such as blood flow velocity or myocardial movement velocity) displayed by the Doppler ultrasound spectrum image, the minimum position refers to the position on the horizontal axis (time axis) of the point where the velocity value reaches the local minimum.

[0083] In an embodiment of the present application, the first Doppler ultrasound spectrum image can be binarized; the pixel values ​​on the vertical axis of the first Doppler ultrasound spectrum image after the binarization are accumulated and smoothed to obtain a processed first Doppler ultrasound spectrum image; and the minimum value position in the spectrum is determined based on the processed first Doppler ultrasound spectrum image.

[0084] In an embodiment of the present application, binarization of the first Doppler ultrasound spectrum image can convert the pixel values ​​in the first Doppler ultrasound spectrum image into only two values ​​(usually 0 and 1) according to a certain threshold value, thereby highlighting the main feature contours, such as distinguishing the part representing the heart activity speed information from the background part. Accumulating the pixel values ​​on the ordinate of the first Doppler ultrasound spectrum image after binarization can enhance the feature performance of the image in the longitudinal direction. If a certain position has similar features at multiple time points (ordinate direction), the feature will be more obvious after accumulation. Smoothing can be performed by a moving average method. Smoothing can reduce the noise in the image, make the feature curve smoother, and facilitate accurate finding of the minimum value position. Because the original image may have some small fluctuations due to factors such as device signal interference, smoothing can remove these interferences.

[0085] In an embodiment of the present application, image recognition technology can be used to find the position of the point where the speed value reaches the local minimum on the time axis (horizontal axis), thereby obtaining the minimum position. When performing image recognition, adjacent pixel values ​​can be compared to determine the minimum position.

[0086] Step S1023, determining each cardiac cycle based on the minimum position.

[0087] In the embodiment of the present application, since the cardiac cycle is a continuous process, there is a certain periodicity in the Doppler ultrasound spectrum image. The minimum position corresponds to the key node in the cardiac activity cycle, and the part between two adjacent minimum values ​​has a high probability of containing a complete cardiac cycle. The cardiac cycle can be divided by looping through each minimum position.

[0088] The method provided in the embodiment of the present application can determine the cardiac cycle through Doppler ultrasound spectrum images, can get rid of the dependence on electrocardiograms, and does not require doctors to attach electrocardiogram electrodes to patients before each examination, which saves time and cost and is more in line with doctors' habits.

[0089] In some embodiments, step S103 may include:

[0090] Step S1031 : dividing the first Doppler ultrasound spectrum image into a plurality of first sub-images based on each cardiac cycle.

[0091] In the embodiment of the present application, the first sub-image is a small portion of the image divided by the cardiac cycle, and each first sub-image corresponds to a complete cardiac cycle.

[0092] Step S1032: input the first sub-image into a first key point detection model to obtain the target key point position of the contraction period in each cardiac cycle.

[0093] In the embodiment of the present application, the target key point position of the systolic period is used to describe the movement speed characteristics of the heart during the systolic period, and the target key point position of the systolic period includes the peak position of the movement speed during the systolic period, the starting position and the ending position of the ejection period. The peak position refers to the position on the Doppler ultrasound spectrum image when the heart movement speed during the systolic period reaches the maximum value; the starting position is the starting position of the movement speed change at the beginning of the ejection period; and the ending position is the ending position of the movement speed change at the end of the ejection period.

[0094] In an embodiment of the present application, a first key point detection model can be pre-trained to identify and locate key points or areas in the input first sub-image. The model may be constructed based on a machine learning algorithm (such as a support vector machine) or a deep learning algorithm (such as a convolutional neural network) and trained with a large amount of labeled data to learn how to accurately find key feature points related to systolic motion speed from the input sub-image.

[0095] In the embodiment of the present application, Figure 2 A schematic diagram of the structure of a first key point detection model provided in an embodiment of the present application is shown in FIG. Figure 2 As shown in the figure, the network structure of the first key point detection model adopts two parts: encoding layer and decoding layer. The encoding layer uses EfficientNetV2-S as the backbone network to extract the features of the first sub-image; the decoding layer uses UperNet fine-tuning to detect key points; according to the pre-marked peak position and starting and ending positions, a key point heat map is generated for model training; the AdamW optimizer is used for model training, and the loss function uses the local heat map loss; after the model training converges, the model with the best performance on the test set is selected as the first key point detection model. When applied, the first sub-image is input into the first key point detection model, processed by the encoding layer, and then by the decoding layer, and the corresponding detection results are output through the peak point convolution layer, the starting point convolution layer and the ending point convolution layer.

[0096] The method provided in the embodiment of the present application divides the first Doppler ultrasound spectrum image into multiple first sub-images based on each cardiac cycle; the first sub-images are input into a first key point detection model to obtain the target key point position of the contraction period in each cardiac cycle.

[0097] In some embodiments, step S103 may further include:

[0098] Step S1033, mapping the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase in each cardiac cycle back to the Doppler ultrasound spectrum image.

[0099] In an embodiment of the present application, the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase can be re-labeled or associated with the original Doppler ultrasound spectrum image according to their corresponding relationship on the time axis (horizontal axis), so that the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase in each cardiac cycle can be mapped back to the Doppler ultrasound spectrum image, and the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase in each cardiac cycle can be mapped back to the Doppler ultrasound spectrum image, and a third Doppler ultrasound spectrum image can be obtained.

[0100] Step S1034 , dividing the second Doppler ultrasound spectrum image under the abscissa in the Doppler ultrasound spectrum image into periods based on the peak positions of the systolic motion velocities corresponding to each cardiac cycle, to obtain second sub-images corresponding to each cardiac cycle.

[0101] In the embodiment of the present application, the second Doppler ultrasound spectrum image is the image below the horizontal axis.

[0102] In the embodiment of the present application, the second Doppler ultrasound spectrum image may be divided based on the peak position of the systolic motion velocity corresponding to each cardiac cycle to obtain a small portion of the image. Each second sub-image corresponds to a cardiac cycle.

[0103] Step S1035: input the second sub-image corresponding to each cardiac cycle into the second key point detection model to obtain the target key point position of the diastolic period in the second sub-image corresponding to each cardiac cycle.

[0104] In the embodiment of the present application, the second key point detection model is a pre-trained model, and its function is to identify and locate the target key point position of the diastolic period in the input second sub-graph. The target key point position of the diastolic period can be: the peak position and starting position of the early diastolic motion velocity, and the peak position and ending position of the late diastolic motion velocity.

[0105] In the embodiment of the present application, before outputting the second sub-image to the second key point detection model, the second sub-image may be pre-processed, and the pre-processing may include: denoising, standardization, etc., to ensure the quality of the input data.

[0106] In an embodiment of the present application, the second key point detection model may be constructed based on a machine learning algorithm (such as a support vector machine) or a deep learning algorithm (such as a convolutional neural network), and is trained through a large amount of labeled data to learn how to accurately find key feature points related to systolic motion speed from an input sub-graph. The structure of the second key point detection module and the first key point detection model may be the same or may be the same. When the structure is the same, when the second key point detection model is trained, the input of the second key point detection model is a sample sub-graph, and the output is the target key point position of the diastolic period, while the input of the first key point detection model is a sample sub-graph, and the output is the target key point position of the systolic period.

[0107] In the embodiment of the present application, in the cardiac cycle of the heart, early diastole refers to the stage when the blood in the atrium quickly fills the ventricle after the ventricle begins to relax. The peak position of the early diastole motion velocity is the corresponding point in the Doppler ultrasound spectrum image when the motion velocity of the myocardium or related tissues (such as the mitral valve ring, etc.) reaches the maximum value at this stage. The starting position is the position on the time axis of the point where the early diastole motion velocity begins to change significantly (usually starting to rise from a lower speed).

[0108] In the embodiment of the present application, the late diastole is the stage when the atrial contraction squeezes the remaining blood further into the ventricle. The peak position of the movement velocity in the late diastole is the corresponding point on the time axis of the Doppler ultrasound spectrum image when the movement velocity of the myocardium or related tissue reaches the maximum value in this stage. The end position is the position on the time axis of the point where the movement velocity in the late diastole ends changing (usually gradually decreasing from a higher speed to a relatively stable state).

[0109] In some embodiments, step S103 further includes:

[0110] Step S1036, mapping the peak position of the systolic velocity, the starting position and ending position of the ejection phase, the peak position and starting position of the early diastolic velocity, and the peak position and ending position of the late diastolic velocity corresponding to each cardiac cycle back to the Doppler ultrasound spectrum image to obtain a target Doppler ultrasound spectrum image.

[0111] In the embodiment of the present application, the target Doppler ultrasound spectrum image is a new image obtained by mapping key information such as the peak position of the systolic motion velocity, the starting position and ending position of the ejection phase, the peak position and starting position of the early diastolic motion velocity, and the peak position and ending position of the late diastolic motion velocity corresponding to each cardiac cycle back to the original Doppler ultrasound spectrum image.

[0112] Step S1037: obtaining cardiac function evaluation parameters based on the target Doppler ultrasound spectrum image.

[0113] In an embodiment of the present application, the evaluation parameters of cardiac function may include: the evaluation parameters of cardiac function include: one or more of the peak systolic tissue movement velocity S', the peak early diastolic tissue movement velocity e', the peak late diastolic tissue movement velocity a', the isovolumetric contraction time, the ejection time and the isovolumetric relaxation time.

[0114] In an embodiment of the present application, the speed corresponding to the peak position of the systolic motion velocity in the target Doppler ultrasound spectrum image is determined as the systolic tissue motion velocity peak S', and / or; the speed corresponding to the peak position of the early diastolic motion velocity in the target Doppler ultrasound spectrum image is determined as the early diastolic tissue motion velocity peak e', and / or; the speed corresponding to the peak position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image is determined as the late diastolic tissue motion velocity peak a', and / or; the time between the end position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image to the start position of the adjacent ejection period on the right is determined as the isovolumetric contraction time, and / or; the time between the start position and the end position of the ejection period in the target Doppler ultrasound spectrum image is determined as the ejection time; and / or, the time between the end position of the ejection period in the target Doppler ultrasound spectrum image to the start position of the adjacent early diastolic motion velocity on the right is determined as the isovolumetric relaxation time.

[0115] In the embodiment of the present application, the doctor can select one set of results as the final parameter as needed.

[0116] In some embodiments, the average value of the systolic tissue movement velocity peak S' in each cardiac cycle can be calculated, or the systolic tissue movement velocity peak S' in a cardiac cycle can be determined based on the first selection instruction to obtain a target systolic tissue movement velocity peak S'; the average value of the early diastolic tissue movement velocity peak e' in each cardiac cycle can be calculated, or the early diastolic tissue movement velocity peak e' in a cardiac cycle can be determined based on the second selection instruction to obtain a target early diastolic tissue movement velocity peak e'; the average value of the late diastolic tissue movement velocity peak a' in each cardiac cycle can be calculated, or the early diastolic tissue movement velocity peak a' can be determined based on the third selection instruction The peak value a' of the tissue movement velocity in the late diastole of a cardiac cycle is obtained to obtain the target peak value a' of the tissue movement velocity in the late diastole; the average value of each isovolumetric contraction time in each cardiac cycle is obtained, or, based on the fourth selection instruction, the isovolumetric contraction time of a cardiac cycle is determined to obtain the target isovolumetric contraction time; the average value of each ejection time in each cardiac cycle is obtained, or, based on the fifth selection instruction, the ejection time of a cardiac cycle is determined to obtain the target ejection time; the average value of each isovolumetric relaxation time in each cardiac cycle is obtained, or, based on the sixth selection instruction, the isovolumetric relaxation time of a cardiac cycle is determined to obtain the target isovolumetric expansion time.

[0117] In the embodiment of the present application, the user can determine the target systolic tissue motion velocity peak S' by inputting the specified cardiac cycle number or the systolic tissue motion velocity peak S'. The user can obtain the target early diastolic tissue motion velocity peak e' by inputting the specified cardiac cycle number or the early diastolic tissue motion velocity peak a', the user can obtain the target late diastolic tissue motion velocity peak a' by inputting the specified cardiac cycle number or the late diastolic tissue motion velocity peak a', the user can obtain the target isovolumetric contraction time by inputting the specified cardiac cycle number or the systolic time, the user can obtain the target ejection time by inputting the specified cardiac cycle number or the ejection time, and the user can obtain the target isovolumetric expansion time by inputting the specified cardiac cycle number or the isovolumetric relaxation time.

[0118] In the embodiment of the present application, the measured evaluation parameters can be displayed on the Doppler ultrasound spectrum image. Figure 3 A schematic diagram of displaying a measurement result provided in an embodiment of the present application is shown as follows: Figure 3 As shown, the systolic tissue movement velocity peak S', the early diastolic tissue movement velocity peak e', the late diastolic tissue movement velocity peak a', IVCT, ET, IVRT, etc. can be displayed in the image.

[0119] The method provided in the embodiment of the present application can automatically complete the measurement without the doctor manually clicking the peak position and time interval range, which greatly improves the doctor's examination efficiency and the objectivity of the measurement results. At the same time, compared with manual measurement, which usually only gives the measurement results of one cycle, this method can give the measurement results of all cycles in the figure, making the final measurement value more reasonable.

[0120] Based on the above embodiments, the present application further provides a method for determining cardiac evaluation parameters. Figure 4 A schematic diagram of an implementation flow of a method for determining cardiac evaluation parameters provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, including:

[0121] Step S401, obtaining a Doppler spectrum diagram of the tissue.

[0122] Step S402, cropping the image into two parts, an upper part and a lower part.

[0123] In the embodiment of the present application, Figure 5 A schematic diagram of a process for obtaining a sub-graph provided in an embodiment of the present application, such as Figure 5 As shown in the figure, the spectrum diagram is cut into two parts, upper and lower parts, according to the position of the coordinate axis.

[0124] Step S403, binarize the upper part, obtain the change curve, and find out the period.

[0125] In the embodiment of the present application, the upper half is binarized, the pixel values ​​on the vertical axis are accumulated and smoothed, and a rough curve of the Doppler ultrasound spectrum image on the time coordinate is obtained. The periodic variation of the curve reflects the periodic variation of the spectrum, and the positions of the various minimum values ​​of the curve are found.

[0126] Step S404, obtaining a subgraph including the S' peak.

[0127] The image can be cut into multiple sub-images based on the minimum position as the boundary, each sub-image is a different cardiac cycle and contains the S' peak, and the more complete sub-image is retained.

[0128] Step S405: detect key points of each sub-image, obtain the peak position, start and end positions, and map them back to the original image.

[0129] In the embodiment of the present application, Figure 6 A schematic diagram of a peak position and a start and end position provided in an embodiment of the present application, such as Figure 6As shown in the figure, each sub-image has a corresponding peak position, start and end position. The sub-images processed offline in advance can be used to train the key point detection model. According to the trained model, the positions of each key point in each sub-image can be obtained. By mapping back to the original image, the peak position, start position and end position of the S' peak on each cardiac cycle in the original image can be obtained.

[0130] Step S406, the lower part finds the period according to the S' peak.

[0131] In the embodiment of the present application, Figure 7 A schematic diagram of a process for obtaining a sub-graph provided in an embodiment of the present application, such as Figure 7 As shown, there is an e' and an a' peak between every two S'. According to the positions of the S' peaks of each period obtained above, the lower half of the image is divided into periods.

[0132] Step S407, obtaining a sub-graph including the e' peak and the a' peak.

[0133] In the embodiment of the present application, the sub-graphs including the e' peak and the a' peak of each period are cropped, and the relatively complete ones are retained.

[0134] Step S408: Detect key points of each sub-image, obtain the peak position start and end positions, and map them back to the original image.

[0135] In the embodiment of the present application, the processed sub-image is used to train the key point detection model, and there are four key points, namely, the peak position of e', the peak position of a', the starting position of e' peak and the ending position of a' peak. Figure 8 A schematic diagram of a sub-graph key point provided in an embodiment of the present application, such as Figure 8 As shown, the model structure and training process are the same as before.

[0136] Step S409, obtaining all peak positions, and obtaining each IVCT, IVRT and ET according to the sequence relationship of each start and end position.

[0137] In the embodiment of the present application, all peak positions in the original image and the starting and ending positions of each peak can be obtained, and all the obtained points are sorted in chronological order. The interval from the ending position of the a' peak to the starting position of the adjacent S' peak on the right is the isovolumetric contraction time IVCT, the duration of a single S' peak (the interval between the starting position and the ending position) is the ejection time ET, and the interval from the ending position of the S' peak to the starting position of the adjacent e' peak on the right is the isovolumetric expansion time IVRT. Thus, by traversing all the starting and ending positions obtained in chronological order, all IVCT, ET and IVRT in the figure can be obtained. The doctor can select one set of results according to the needs, or choose to retain all the results and take the average.

[0138] The method provided in the embodiment of the present application utilizes image features to extract the cardiac cycle in the spectrum diagram according to the peak position. In each cycle, a deep learning key point detection method is used to find the position of each peak value and the start and end positions of each time interval. After post-processing, the peak value and time interval of each cycle are obtained. The doctor can choose to retain the results of all cycles and take the average based on experience, or select the result of one of the cycles as the final result.

[0139] Compared with the traditional heart examination method, the measurement method proposed in the present invention is a fully automatic technical process. It can automatically complete the measurement without the doctor manually clicking the peak position and time interval range, which greatly improves the doctor's examination efficiency and the objectivity of the measurement results. At the same time, compared with manual measurement, which usually only gives the measurement results of one cycle, this method can give the measurement results of all cycles in the figure, making the final measurement value more reasonable.

[0140] Compared with the current method of partially confirming the cardiac cycle based on the electrocardiogram to assist in automatic Doppler ultrasound measurement, the method proposed in the present invention gets rid of the dependence on the electrocardiogram, and does not require doctors to attach electrocardiogram electrodes to patients before each examination, which saves time and cost and is more in line with doctors' habits.

[0141] Based on the foregoing embodiments, the present application provides a device for determining evaluation parameters of heart control. The modules and units included in the modules of the device for determining evaluation parameters of heart control can be implemented by a processor in a computer device; of course, they can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc. The control device includes:

[0142] An acquisition module, used for acquiring a Doppler ultrasound spectrum image of the heart;

[0143] A first determination module, configured to determine each cardiac cycle based on the Doppler ultrasound spectrum image;

[0144] The second determination module is used to determine the evaluation parameters for evaluating the heart function based on each cardiac cycle and the Doppler ultrasound spectrum image.

[0145] In some embodiments, the first determining module includes:

[0146] a segmentation unit, configured to segment the Doppler ultrasound spectrum image based on the abscissa in the Doppler ultrasound spectrum image to obtain a first Doppler ultrasound spectrum image above the abscissa;

[0147] A first determining unit, configured to determine each minimum value position in the spectrum based on the first Doppler ultrasound spectrum image;

[0148] The second determining unit is used to determine each cardiac cycle based on the minimum position.

[0149] In some embodiments, the first determining unit includes:

[0150] A binarization processing subunit, used for binarizing the first Doppler ultrasound spectrum image;

[0151] A processing subunit, used for accumulating and smoothing the pixel values ​​on the ordinate in the first Doppler ultrasound spectrum image after the binarization process to obtain the processed first Doppler ultrasound spectrum image;

[0152] The determination subunit is used to determine the minimum value position in the spectrum based on the processed first Doppler ultrasound spectrum image.

[0153] In some embodiments, the second determining module includes:

[0154] A first dividing unit, configured to divide the first Doppler ultrasound spectrum image into a plurality of first sub-images based on each cardiac cycle;

[0155] The third determination unit is used to input the first sub-image into a first key point detection model to obtain the target key point position in the contraction period of each cardiac cycle.

[0156] In some embodiments, the target key point positions of the systolic period include: the peak position of the systolic movement speed, the starting position and the ending position of the ejection period, and the second determination module includes:

[0157] A first mapping unit is used to map the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase in each cardiac cycle back to the Doppler ultrasound spectrum image;

[0158] A second division unit is used to divide the second Doppler ultrasound spectrum image under the horizontal coordinate in the Doppler ultrasound spectrum image into periods based on the peak position of the systolic motion velocity corresponding to each cardiac cycle, so as to obtain a second sub-image corresponding to each cardiac cycle;

[0159] The fourth determination unit is used to input the second sub-image corresponding to each cardiac cycle into the second key point detection model to obtain the target key point position of the diastolic period in the second sub-image corresponding to each cardiac cycle.

[0160] In some embodiments, the position of the target key point in the diastolic period includes: the peak position and the starting position of the early diastolic motion velocity, the peak position and the ending position of the late diastolic motion velocity, and the second determination module further includes:

[0161] A second mapping unit is used to map the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase, the peak position and the starting position of the early diastolic motion velocity, and the peak position and the ending position of the late diastolic motion velocity corresponding to each cardiac cycle back to the Doppler ultrasound spectrum image to obtain a target Doppler ultrasound spectrum image;

[0162] A fifth determining unit is configured to obtain a cardiac function evaluation parameter based on the target Doppler ultrasound spectrum image.

[0163] In some embodiments, the cardiac function evaluation parameters include: one or more of: systolic tissue motion velocity peak S', early diastolic tissue motion velocity peak e', late diastolic tissue motion velocity peak a', isovolumetric contraction time, ejection time and isovolumetric relaxation time. The cardiac function evaluation parameters obtained based on the target Doppler ultrasound spectrum image include:

[0164] Determining the velocity corresponding to the peak position of the systolic motion velocity in the target Doppler ultrasound spectrum image as the systolic tissue motion velocity peak value, and / or;

[0165] Determining the velocity corresponding to the peak position of the early diastolic motion velocity in the target Doppler ultrasound spectrum image as the peak velocity of the early diastolic tissue motion, and / or;

[0166] Determining the velocity corresponding to the peak position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image as the peak velocity of the late diastolic tissue motion, and / or;

[0167] Determine the time between the end position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image and the start position of the ejection phase adjacent to the right as the isovolumetric contraction time, and / or;

[0168] Determine the time between the start position and the end position of the ejection period in the target Doppler ultrasound spectrum image as the ejection time; and / or,

[0169] The time between the end position of the ejection phase in the target Doppler ultrasound spectrum image and the start position of the adjacent early diastolic motion velocity on the right is determined as the isovolumetric relaxation time.

[0170] In some embodiments, the determination of the cardiac assessment parameter is also used to:

[0171] Obtain an average value of the peak value S' of the systolic tissue movement velocity in each cardiac cycle, or determine the peak value S' of the systolic tissue movement velocity in one cardiac cycle based on the first selection instruction to obtain a target peak value S' of the systolic tissue movement velocity;

[0172] Obtaining an average of the peak values ​​of the early diastolic tissue motion velocity e' in each cardiac cycle, or determining the peak value of the early diastolic tissue motion velocity e' in one cardiac cycle based on the second selection instruction, to obtain a target peak value of the early diastolic tissue motion velocity e';

[0173] Obtaining an average value of the peak value a' of the late diastolic tissue motion velocity in each cardiac cycle, or determining the peak value a' of the late diastolic tissue motion velocity in one cardiac cycle based on the third selection instruction, to obtain a target peak value a' of the late diastolic tissue motion velocity;

[0174] Calculate the average value of each isovolumetric contraction time in each cardiac cycle, or determine the isovolumetric contraction time of one cardiac cycle based on the fourth selection instruction to obtain a target isovolumetric contraction time;

[0175] Calculate the average value of each ejection time in each cardiac cycle, or determine the ejection time of one cardiac cycle based on the fifth selection instruction to obtain a target ejection time;

[0176] The target isovolumetric expansion time is obtained by obtaining an average value of each isovolumetric relaxation time in each cardiac cycle, or determining the isovolumetric relaxation time of a cardiac cycle based on the sixth selection instruction.

[0177] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Fig. 9 As shown, the electronic device 3 of this embodiment may include: at least one processor 30 ( Fig. 9 Only one processor 30 is shown in the figure), a memory 31, and a computer program 32 stored in the memory 31 and executable on at least one processor 30. When the processor 30 executes the computer program 32, the steps in any of the above-mentioned method embodiments are implemented; or, when the processor 30 executes the computer program 32, the functions of the modules / units in the above-mentioned system embodiments are implemented.

[0178] Exemplarily, the computer program 32 may be divided into one or more modules / units, one or more modules / units are stored in the memory 31, and are executed by the processor 30 to complete the present application. One or more modules / units may be a series of computer program 32 instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the electronic device 3.

[0179] An embodiment of the present application provides an electrosurgical system, including: an electrosurgical host and at least one electrosurgical instrument.

[0180] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program 32. When the computer program 32 is executed by the processor 30, the steps in the above-mentioned method embodiments can be implemented.

[0181] An embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0182] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. According to this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program 32, and the computer program 32 can be stored in a computer-readable storage medium, and the computer program 32 can implement the steps of the above-mentioned various method embodiments when executed by the processor 30. Among them, the computer program 32 includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the terminal, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0183] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0184] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0185] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0186] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0187] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for determining cardiac evaluation parameters, characterized in that: include: Acquire Doppler ultrasound spectrum images of the heart; Determine each cardiac cycle based on the Doppler ultrasound spectrum image; An evaluation parameter for evaluating the heart function is determined based on each cardiac cycle and the Doppler ultrasound spectrum image.

2. The method according to claim 1, characterized in that Determining each cardiac cycle based on the Doppler ultrasound spectrum image includes: Segmenting the Doppler ultrasound spectrum image based on the abscissa in the Doppler ultrasound spectrum image to obtain a first Doppler ultrasound spectrum image above the abscissa; Determine each minimum value position in the spectrum based on the first Doppler ultrasound spectrum image; Individual cardiac cycles are determined based on the minimum positions.

3. The method according to claim 2, characterized in that The determining of each minimum value position in the spectrum based on the first Doppler ultrasound spectrum image comprises: Binarizing the first Doppler ultrasound spectrum image; Accumulating pixel values ​​on the ordinate in the first Doppler ultrasound spectrum image after the binarization process and performing smoothing process to obtain a processed first Doppler ultrasound spectrum image; The minimum position in the spectrum is determined based on the processed first Doppler ultrasound spectrum image.

4. The method according to claim 2, characterized in that: The step of determining the evaluation parameters for evaluating the cardiac function based on each cardiac cycle and the Doppler ultrasound spectrum image comprises: Dividing the first Doppler ultrasound spectrum image into a plurality of first sub-images based on each cardiac cycle; The first sub-image is input into a first key point detection model to obtain the target key point position in the contraction period of each cardiac cycle.

5. The method according to claim 4, characterized in that The target key point positions of the systolic period include: the peak position of the systolic movement velocity, the starting position and the ending position of the ejection period, and the evaluation parameters for evaluating the cardiac function determined based on each cardiac cycle and the Doppler ultrasound spectrum image also include: Mapping the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase in each cardiac cycle back to the Doppler ultrasound spectrum image; Based on the peak position of the systolic motion velocity corresponding to each cardiac cycle, the second Doppler ultrasound spectrum image under the horizontal coordinate in the Doppler ultrasound spectrum image is divided into periods to obtain a second sub-image corresponding to each cardiac cycle; The second sub-image corresponding to each cardiac cycle is input into the second key point detection model to obtain the target key point position of the diastolic period in the second sub-image corresponding to each cardiac cycle.

6. The method according to claim 5, characterized in that The target key point positions of the diastolic period include: the peak position and the starting position of the early diastolic motion velocity, the peak position and the ending position of the late diastolic motion velocity, and the evaluation parameters for evaluating the cardiac function determined based on each cardiac cycle and the Doppler ultrasound spectrum image also include: Mapping the peak position of the systolic motion velocity, the starting position and the ending position of the ejection phase, the peak position and the starting position of the early diastolic motion velocity, and the peak position and the ending position of the late diastolic motion velocity corresponding to each cardiac cycle back to the Doppler ultrasound spectrum image to obtain a target Doppler ultrasound spectrum image; The cardiac function evaluation parameters are obtained based on the target Doppler ultrasound spectrum image.

7. The method according to claim 6, characterized in that The cardiac function evaluation parameters include: one or more of: systolic tissue motion velocity peak S', early diastolic tissue motion velocity peak e', late diastolic tissue motion velocity peak a', isovolumetric contraction time, ejection time and isovolumetric relaxation time. The cardiac function evaluation parameters obtained based on the target Doppler ultrasound spectrum image include: Determine the velocity corresponding to the peak position of the systolic motion velocity in the target Doppler ultrasound spectrum image as the systolic tissue motion velocity peak value S', and / or; Determine the velocity corresponding to the peak position of the early diastolic motion velocity in the target Doppler ultrasound spectrum image as the peak velocity e' of the early diastolic tissue motion velocity, and / or; Determine the velocity corresponding to the peak position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image as the peak velocity a' of the late diastolic tissue motion velocity, and / or; Determine the time between the end position of the late diastolic motion velocity in the target Doppler ultrasound spectrum image and the start position of the ejection phase adjacent to the right as the isovolumetric contraction time, and / or; Determine the time between the start position and the end position of the ejection period in the target Doppler ultrasound spectrum image as the ejection time; and / or, The time between the end position of the ejection phase in the target Doppler ultrasound spectrum image and the start position of the adjacent early diastolic motion velocity on the right is determined as the isovolumetric relaxation time.

8. The method according to claim 7, characterized in that The method further comprises: Obtain an average value of the peak value S' of the systolic tissue movement velocity in each cardiac cycle, or determine the peak value S' of the systolic tissue movement velocity in one cardiac cycle based on the first selection instruction to obtain a target peak value S' of the systolic tissue movement velocity; Obtaining an average of the peak values ​​of the early diastolic tissue motion velocity e' in each cardiac cycle, or determining the peak value of the early diastolic tissue motion velocity e' in one cardiac cycle based on the second selection instruction, to obtain a target peak value of the early diastolic tissue motion velocity e'; Obtaining an average value of the peak value a' of the late diastolic tissue motion velocity in each cardiac cycle, or determining the peak value a' of the late diastolic tissue motion velocity in one cardiac cycle based on the third selection instruction, to obtain a target peak value a' of the late diastolic tissue motion velocity; Calculate the average value of each isovolumetric contraction time in each cardiac cycle, or determine the isovolumetric contraction time of one cardiac cycle based on the fourth selection instruction to obtain a target isovolumetric contraction time; Calculate the average value of each ejection time in each cardiac cycle, or determine the ejection time of one cardiac cycle based on the fifth selection instruction to obtain a target ejection time; The target isovolumetric expansion time is obtained by obtaining an average value of each isovolumetric relaxation time in each cardiac cycle, or determining the isovolumetric relaxation time of a cardiac cycle based on the sixth selection instruction.

9. A device for determining cardiac evaluation parameters, characterized in that: include: An acquisition module, used for acquiring a Doppler ultrasound spectrum image of the heart; A first determination module, configured to determine each cardiac cycle based on the Doppler ultrasound spectrum image; The second determination module is used to determine the evaluation parameters for evaluating the heart function based on each cardiac cycle and the Doppler ultrasound spectrum image.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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