Method for determining a cardiac hemodynamic parameter and electronic device

Abstract

The present disclosure provides a method for determining a cardiac hemodynamic parameter and an electronic device. The accuracy of the cardiac hemodynamic parameter is improved. The method comprises: extracting a cardiac tissue signal and a contrast microbubble signal in a current frame of cardiac ultrasound image to obtain a cardiac tissue image and a contrast microbubble image, and identifying an endocardial region in the cardiac tissue image; obtaining the identification position of each target contrast microbubble in the current frame of cardiac ultrasound image based on the pixel value of each pixel point in the endocardial region and the pixel value of the neighborhood pixel points of each pixel point in the contrast microbubble image; obtaining the target position of the target contrast microbubble in the current frame of cardiac ultrasound image through the identification position of the target contrast microbubble for any target contrast microbubble; obtaining the instantaneous velocity of the target contrast microbubble based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the last frame of cardiac ultrasound image; and obtaining the viscosity blood flow friction by using the instantaneous velocity of each target contrast microbubble.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ultrasonic imaging, in particular to a method for determining cardiac hemodynamic parameters and an electronic device. BACKGROUND

[0002] The functional state of cardiac blood flow circulation directly affects the structure, function and metabolism of the heart, and has important influence on the occurrence, development, efficacy and prognosis of heart disease. Therefore, effective observation and analysis of the hemodynamic state of the heart is crucial for screening of heart disease.

[0003] At present, the ultrasonic techniques for studying cardiac hemodynamic parameters mainly include Doppler imaging technology, speckle tracking imaging technology, acoustic contrast imaging technology and four-dimensional quantitative analysis technology, etc. However, the Doppler imaging technology has angle dependence of the angle between the ultrasonic beam and the blood flow direction, and usually can only estimate the velocity component of the blood flow along the beam direction, with large deviation in blood flow velocity estimation; the acoustic contrast imaging technology can only dynamically display the blood flow perfusion, and cannot present more flow field change information; the speckle tracking imaging technology is easily affected by heart rate, and the repeatability needs to be further improved. Therefore, the accuracy of the determined hemodynamic parameters is low. SUMMARY

[0004] In an exemplary embodiment of the present disclosure, a method for determining cardiac hemodynamic parameters and an electronic device are provided to improve the accuracy of cardiac hemodynamic parameters.

[0005] A first aspect of the present disclosure provides a method for determining cardiac hemodynamic parameters, the method comprising:

[0006] In response to a cardiac hemodynamic parameter determination instruction sent by a user, a current frame of cardiac ultrasound image corresponding to the cardiac hemodynamic parameter determination instruction is acquired;

[0007] A cardiac tissue signal is extracted from the current frame of cardiac ultrasound image to obtain a cardiac tissue image, and a contrast microbubble signal is extracted from the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size;

[0008] The endocardial region of the cardiac tissue image is identified by using a preset algorithm to obtain the position of the endocardial region;

[0009] Based on the pixel values of each pixel point in the endocardial region of the contrast microbubble image and the pixel values of the neighborhood pixel points of the each pixel point, the identification position of each target contrast microbubble in the current frame of cardiac ultrasound image is obtained;

[0010] For any one target contrast microbubble, a target position of the target contrast microbubble in the current frame of the cardiac ultrasound image is obtained through an identified position of the target contrast microbubble in the current frame of the cardiac ultrasound image; and

[0011] Based on the target position of the target contrast microbubble in the current frame of the cardiac ultrasound image and the target position of the target contrast microbubble in the previous frame of the cardiac ultrasound image, an instantaneous velocity of the target contrast microbubble is obtained.

[0012] The viscosity blood flow friction wss corresponding to the current frame of the cardiac ultrasound image is obtained by using the instantaneous velocities of the target contrast microbubbles.

[0013] In the embodiment, the cardiac tissue image and the contrast microbubble image are obtained by extracting the cardiac tissue signal and the contrast microbubble signal in the current frame of the cardiac ultrasound image, then the position of the endocardial region is determined based on the cardiac tissue image, the identified position of each target contrast microbubble in the current frame of the cardiac ultrasound image is obtained based on the pixel value of each pixel point in the endocardial region and the pixel value of the neighborhood pixel points of the pixel point, and the instantaneous velocity of each target contrast microbubble is obtained to determine the viscosity blood flow friction corresponding to the current frame of the cardiac ultrasound image. Since the physical characteristics of the contrast microbubble are similar to those of the red blood cell, the contrast microbubble can be used as a tracer of the red blood cell, so that the complex fluid state of a single / multiple blood cells in the heart can be captured in real time, and the change of the blood flow hemodynamic parameter can be evaluated in more detail. Thus, the accuracy of the determined blood flow hemodynamic parameter is improved.

[0014] In one embodiment, the extraction of the cardiac tissue signal in the current frame of the cardiac ultrasound image to obtain the cardiac tissue image comprises:

[0015] The linear signal in the echo signal corresponding to the current frame of the cardiac ultrasound image is extracted to obtain the cardiac tissue image.

[0016] The extraction of the contrast microbubble signal in the current frame of the cardiac ultrasound image to obtain the contrast microbubble image comprises:

[0017] The non-linear signal in the echo signal corresponding to the current frame of the cardiac ultrasound image is extracted to obtain the contrast microbubble image.

[0018] In the embodiment, the cardiac tissue image is obtained by extracting the linear signal and the contrast microbubble image is obtained by extracting the non-linear signal, so that the cardiac tissue signal and the contrast microbubble signal are separated, and the accuracy of the determined cardiac blood flow hemodynamic parameter is ensured.

[0019] In one embodiment, the method further comprises, before obtaining the identification position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of the neighborhood pixels of the each pixel, obtaining the identification position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of the neighborhood pixels of the each pixel.

[0020] The method further comprises, before obtaining the identification position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of the neighborhood pixels of the each pixel, obtaining the identification position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of the neighborhood pixels of the each pixel.

[0021] In this embodiment, the contrast microbubble image is filtered to make the characteristics of the contrast microbubble more obvious, and the accuracy of the determined cardiac hemodynamic parameters is further improved.

[0022] In one embodiment, the method further comprises, before obtaining the identification position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of the neighborhood pixels of the each pixel, obtaining the identification position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of the neighborhood pixels of the each pixel.

[0023] For any one pixel in the contrast microbubble image endocardium region, based on the pixel value of the pixel and the pixel value of each other pixel in the specified neighborhood of the pixel, the pixel difference value of the pixel and each other pixel is obtained; and,

[0024] The other pixel with the maximum pixel difference value is determined as the intermediate pixel, and the energy value of the intermediate pixel is obtained based on the pixel mean value of each pixel in the specified neighborhood of the intermediate pixel.

[0025] The energy values of the intermediate pixels corresponding to each pixel in the endocardium region are used to sort the intermediate pixels in descending order, and the first specified number of intermediate pixels are determined as the center points of each target contrast microbubble.

[0026] Each target contrast microbubble is obtained by taking each center point as the center and a specified length as the radius, and the position of the center point of each target contrast microbubble is determined as the identification position of the target contrast microbubble.

[0027] In this embodiment, the target contrast microbubble and the identification position of the target contrast microbubble are determined based on the pixel value of each pixel in the contrast microbubble image endocardium region and the pixel value of each other pixel in the specified neighborhood of the each pixel. The accuracy of the determined identification position of the target contrast microbubble is ensured.

[0028] In one embodiment, the target position of the target contrast microbubble in the current frame of the cardiac ultrasound image is obtained based on the identified position of the target contrast microbubble, comprising:

[0029] A position range of the target contrast microbubble is obtained based on the identified position of the target contrast microbubble.

[0030] For any one position in the position range, a confidence degree of the position is obtained based on pixel values of each pixel point in a specified neighborhood of the position in the current frame of the cardiac ultrasound image and pixel values of each pixel point in a specified neighborhood of the position in the previous frame of the cardiac ultrasound image.

[0031] The position with the highest confidence degree in the position range is determined as the target position of the target contrast microbubble.

[0032] In the embodiment, the position range of the target contrast microbubble is obtained based on the identified position of the target contrast microbubble, and the position with the highest confidence degree in the position range is determined as the target position of the target contrast microbubble, so that the determined target position of the target contrast microbubble is more accurate.

[0033] In one embodiment, the confidence degree of the position is obtained based on the pixel values of each pixel point in the specified neighborhood of the position in the current frame of the cardiac ultrasound image and the pixel values of each pixel point in the specified neighborhood of the position in the previous frame of the cardiac ultrasound image, comprising:

[0034] A first intermediate confidence degree is obtained by multiplying the pixel value of the pixel point at the position in the current frame of the cardiac ultrasound image and the pixel value of the pixel point at the position in the previous frame of the cardiac ultrasound image; and

[0035] For any one pixel point in the specified neighborhood of the position in the current frame of the cardiac ultrasound image, a second intermediate confidence degree of the pixel point is obtained by multiplying the pixel value of the pixel point in the current frame of the cardiac ultrasound image and the pixel value of the pixel point in the previous frame of the cardiac ultrasound image; and

[0036] The second intermediate confidence degrees of each pixel point in the specified neighborhood are added to obtain a third intermediate confidence degree.

[0037] The third intermediate confidence degree and the first intermediate confidence degree are added to obtain the confidence degree of the position.

[0038] In one embodiment, the instantaneous velocity of the target contrast microbubble is obtained based on the target position of the target contrast microbubble in the current frame of the cardiac ultrasound image and the target position of the target contrast microbubble in the previous frame of the cardiac ultrasound image, comprising:

[0039] obtaining a displacement of the target contrast microbubble according to the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the last frame of cardiac ultrasound image;

[0040] obtaining an instantaneous velocity of the target contrast microbubble by dividing the displacement of the target contrast microbubble by a target time, wherein the target time is a time interval between the current frame of cardiac ultrasound image and the last frame of cardiac ultrasound image.

[0041] In one embodiment, the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image is obtained by using the instantaneous velocity of each target contrast microbubble.

[0042] obtaining a parameter value according to the instantaneous velocity of each target contrast microbubble and the displacement of each target contrast microbubble;

[0043] multiplying the parameter value by a preset fluid viscosity to obtain the wss.

[0044] The second aspect of the present disclosure provides an electronic device, comprising a processor and a memory connected through a bus;

[0045] The memory stores a computer program, and the processor is configured to execute the following operations based on the computer program:

[0046] In response to a user-sent cardiac hemodynamic parameter determination instruction, a current frame of cardiac ultrasound image corresponding to the cardiac hemodynamic parameter determination instruction is obtained;

[0047] extracting a cardiac tissue signal in the current frame of cardiac ultrasound image to obtain a cardiac tissue image, and extracting a contrast microbubble signal in the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size;

[0048] using a preset algorithm to identify an endocardial region of the cardiac tissue image to obtain a position of the endocardial region;

[0049] obtaining an identified position of each target contrast microbubble in the current frame of cardiac ultrasound image based on a pixel value of each pixel point in the endocardial region of the contrast microbubble image and a pixel value of a neighborhood pixel point of the pixel point;

[0050] For any one target contrast microbubble, a target position of the target contrast microbubble in the current frame of cardiac ultrasound image is obtained through the identified position of the target contrast microbubble in the current frame of cardiac ultrasound image; and

[0051] obtaining a velocity of each target contrast microbubble based on the target position of the target contrast microbubble in the current frame of the cardiac ultrasound image and the target position of the target contrast microbubble in a previous frame of the cardiac ultrasound image;

[0052] obtaining a viscous blood flow friction wss corresponding to the current frame of the cardiac ultrasound image by using the velocity of each target contrast microbubble.

[0053] In one embodiment, the processor performing the extracting of the cardiac tissue signal in the current frame of the cardiac ultrasound image to obtain a cardiac tissue image is specifically configured to:

[0054] extracting a linear signal in an echo signal corresponding to the current frame of the cardiac ultrasound image to obtain the cardiac tissue image;

[0055] the processor performing the extracting of the contrast microbubble signal in the current frame of the cardiac ultrasound image to obtain a contrast microbubble image is specifically configured to:

[0056] extracting a nonlinear signal in an echo signal corresponding to the current frame of the cardiac ultrasound image to obtain the contrast microbubble image.

[0057] In one embodiment, the processor is further configured to:

[0058] performing clutter filtering on the contrast microbubble image based on pixel values of each pixel point in an intima region of the contrast microbubble image and pixel values of neighborhood pixel points of the each pixel point to obtain a filtered contrast microbubble image, and determining the filtered contrast microbubble image as the contrast microbubble image before obtaining the identified position of each target contrast microbubble in the current frame of the cardiac ultrasound image.

[0059] In one embodiment, the processor performing the obtaining of the identified position of each target contrast microbubble in the current frame of the cardiac ultrasound image based on the pixel values of each pixel point in the intima region of the contrast microbubble image and the pixel values of the neighborhood pixel points of the each pixel point is specifically configured to:

[0060] for any one pixel point in the intima region of the contrast microbubble image, obtaining pixel difference values of the pixel point and each other pixel point in a designated neighborhood of the pixel point based on a pixel value of the pixel point and pixel values of the each other pixel point; and,

[0061] determining a middle pixel point as the other pixel point with the largest pixel difference value, and obtaining an energy value of the middle pixel point based on a pixel mean value of each pixel point in a designated neighborhood of the middle pixel point;

[0062] Sort the intermediate pixel points in the endocardial region in descending order according to the energy values of the intermediate pixel points corresponding to the pixels in the endocardial region, and determine the first specified number of intermediate pixel points as the center points of the target contrast microbubbles, respectively.

[0063] Obtain the target contrast microbubbles by taking each center point as a center and a specified length as a radius, and determine the position of the center point of each target contrast microbubble as the recognition position of the target contrast microbubble.

[0064] In one embodiment, the processor performs the obtaining of the target position of the target contrast microbubble in the current frame of the cardiac ultrasound image through the recognition position of the target contrast microbubble in the current frame of the cardiac ultrasound image, and is specifically configured to:

[0065] Obtain a position range of the target contrast microbubble based on the recognition position of the target contrast microbubble.

[0066] For any position in the position range, obtain a confidence degree of the position based on the pixel values of the pixels in a specified neighborhood of the position in the current frame of the cardiac ultrasound image and the pixel values of the pixels in a specified neighborhood of the position in a previous frame of the cardiac ultrasound image.

[0067] Determine the position with the highest confidence degree in the position range as the target position of the target contrast microbubble.

[0068] In one embodiment, the processor performs the obtaining of the confidence degree of the position based on the pixel values of the pixels in a specified neighborhood of the position in the current frame of the cardiac ultrasound image and the pixel values of the pixels in a specified neighborhood of the position in a previous frame of the cardiac ultrasound image, and is specifically configured to:

[0069] Multiply the pixel value of the pixel at the position in the current frame of the cardiac ultrasound image by the pixel value of the pixel at the position in the previous frame of the cardiac ultrasound image to obtain a first intermediate confidence degree; and

[0070] For any pixel in a specified neighborhood of the position in the current frame of the cardiac ultrasound image, multiply the pixel value of the pixel in the current frame of the cardiac ultrasound image by the pixel value of the pixel in a previous frame of the cardiac ultrasound image to obtain a second intermediate confidence degree of the pixel; and

[0071] Add the second intermediate confidence degrees of the pixels in the specified neighborhood to obtain a third intermediate confidence degree.

[0072] Add the third intermediate confidence degree and the first intermediate confidence degree to obtain the confidence degree of the position.

[0073] In one embodiment, the processor performs the obtaining the instantaneous velocity of the target contrast microbubble based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the previous frame of cardiac ultrasound image, and is specifically configured to:

[0074] obtaining the displacement of the target contrast microbubble according to the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the previous frame of cardiac ultrasound image;

[0075] dividing the displacement of the target contrast microbubble by a target time to obtain the instantaneous velocity of the target contrast microbubble, wherein the target time is a time interval between the current frame of cardiac ultrasound image and the previous frame of cardiac ultrasound image.

[0076] In one embodiment, the processor performs the obtaining the wss corresponding to the current frame of cardiac ultrasound image by using the instantaneous velocity of each target contrast microbubble, and is specifically configured to:

[0077] obtaining a parameter value according to the instantaneous velocity of each target contrast microbubble and the displacement of each target contrast microbubble;

[0078] multiplying the parameter value by a preset fluid viscosity to obtain the wss.

[0079] According to a third aspect provided by the embodiments of the present disclosure, a computer storage medium is provided, which stores a computer program for executing the method according to the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0080] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor.

[0081] Figure 1 is one of the application scenarios according to an embodiment of the present disclosure;

[0082] Figure 2 is one of the flowcharts of the method for determining cardiac hemodynamic parameters according to an embodiment of the present disclosure;

[0083] Figure 3 is a schematic diagram of the reconstruction matrix according to an embodiment of the present disclosure;

[0084] Figure 4 a schematic diagram of a range of singular values of a range of ultrasound signals according to an embodiment of the present disclosure;

[0085] Figure 5 a schematic diagram of a process of identifying a position of a target contrast microbubble in a current frame of cardiac ultrasound images according to an embodiment of the present disclosure;

[0086] Figure 6 a schematic diagram of a pixel of a contrast microbubble image according to an embodiment of the present disclosure;

[0087] Figure 7 a schematic diagram of a process of determining a target position of a target contrast microbubble in a current frame of cardiac ultrasound images according to an embodiment of the present disclosure;

[0088] Figure 8 a schematic diagram of a process of determining a viscosity blood flow friction according to an embodiment of the present disclosure;

[0089] Figure 9 a schematic diagram of a process of determining a cardiac hemodynamic parameter according to an embodiment of the present disclosure;

[0090] Figure 10 a device for determining a cardiac hemodynamic parameter according to an embodiment of the present disclosure;

[0091] Figure 11 a schematic diagram of a structure of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0092] In order to make the purposes, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present disclosure.

[0093] In the embodiments of the present disclosure, the term “and / or” describes an association relationship of associated objects, which means that there can be three relationships, for example, A and / or B can mean that there are three cases of A alone, A and B together, and B alone. The character “ / ” generally means that the associated objects before and after it are in an “or” relationship.

[0094] The application scenarios described in this disclosure are for the purpose of more clearly illustrating the technical solutions of this disclosure and do not constitute a limitation on the technical solutions provided in this disclosure. Those skilled in the art will understand that with the emergence of new application scenarios, the technical solutions provided in this disclosure are also applicable to similar technical problems. In the description of this disclosure, unless otherwise stated, "multiple" means two or more.

[0095] In existing technologies, ultrasound techniques for studying cardiac hemodynamic parameters mainly include Doppler imaging, speckle tracking imaging, acoustic contrast imaging, and four-dimensional quantitative analysis. However, Doppler imaging is subject to angular dependence of the angle between the ultrasound beam and the blood flow direction, and it can usually only estimate the velocity component of blood flow along the beam direction, resulting in significant errors in blood flow velocity estimation. Acoustic contrast imaging can only dynamically display blood perfusion and cannot present more information on flow field changes. Speckle tracking imaging is easily affected by heart rate, and its repeatability needs further improvement. Therefore, the accuracy of the determined hemodynamic parameters is relatively low.

[0096] Therefore, this disclosure provides a method for determining cardiac hemodynamic parameters. The method involves extracting cardiac tissue signals and contrast microbubble signals from the current frame of an echocardiogram to obtain cardiac tissue and contrast microbubble images. Then, the location of the endocardial region is determined based on the cardiac tissue image. Based on the pixel values ​​of each pixel in the central endocardial region of the contrast microbubble image and the pixel values ​​of its neighboring pixels, the identification position of each target contrast microbubble in the current frame of the echocardiogram is obtained. This allows for the determination of the instantaneous velocity of each target contrast microbubble, thereby determining the viscous blood flow friction force (wss) corresponding to the current frame of the echocardiogram. Since the physical properties of contrast microbubbles are similar to those of red blood cells, they can be used as tracers for red blood cells. Therefore, this embodiment can capture the complex fluid state of single / multiple blood cells within the heart in real time, allowing for a more detailed assessment of changes in hemodynamic parameters. This improves the accuracy of the determined hemodynamic parameters. The solution of this disclosure will now be described in detail with reference to the accompanying drawings.

[0097] like Figure 1 The diagram illustrates an application scenario for determining cardiac hemodynamic parameters, including an ultrasound device 110 and a memory 120. This application scenario uses an ultrasound device as an example.

[0098] In a possible application scenario, the ultrasound device 110 acquires a current frame of cardiac ultrasound image corresponding to a cardiac hemodynamic parameter determination instruction sent by a user in response to the cardiac hemodynamic parameter determination instruction; then the ultrasound device 110 extracts a cardiac tissue signal in the current frame of cardiac ultrasound image to obtain a cardiac tissue image, and extracts a contrast microbubble signal in the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size; and identifies an endocardial region of the cardiac tissue image by using a preset algorithm to obtain a position of the endocardial region; the ultrasound device 110 obtains the identification position of each target contrast microbubble in the current frame of cardiac ultrasound image based on the pixel value of each pixel point in the endocardial region of the contrast microbubble image and the pixel value of the neighborhood pixel points of the pixel point; then for any one target contrast microbubble, the ultrasound device 110 obtains the target position of the target contrast microbubble in the current frame of cardiac ultrasound image through the identification position of the target contrast microbubble in the current frame of cardiac ultrasound image; and the ultrasound device 110 obtains the instantaneous velocity of the target contrast microbubble based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in a previous frame of cardiac ultrasound image; and obtains the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image by using the instantaneous velocities of the target contrast microbubbles, and sends the wss to the memory 120 for storage.

[0099] In the description of the present application, only a single ultrasound device 110 and a single memory 120 are described in detail, but those skilled in the art should understand that the ultrasound device 110 and the memory 120 shown are intended to represent the operation of the ultrasound device 110 and the memory 120 involved in the technical solution of the present application. Rather than implying a limitation on the number, type or location of the ultrasound device 110 and the memory 120. It should be noted that if additional modules are added to the illustrated environment or individual modules are removed therefrom, the underlying concept of the example embodiments of the present application will not change.

[0100] It should be noted that the method for determining cardiac hemodynamic parameters proposed in the present application is not only applicable to the application scenario shown Figure 1 but also to any device for determining cardiac hemodynamic parameters.

[0101] The method for determining cardiac hemodynamic parameters of the example embodiments of the present application will be described below in conjunction with the above-described application scenario and with reference to the accompanying drawings. It should be noted that the above-described application scenario is only shown to facilitate understanding of the method and principles of the present application, and the embodiments of the present application are not limited in this respect.

[0102] As Figure 2As shown, a flowchart of a method for determining a cardiac hemodynamic parameter according to the present disclosure can include the following steps:

[0103] Step 201: In response to a cardiac hemodynamic parameter determination instruction sent by a user, a current frame of cardiac ultrasound image corresponding to the cardiac hemodynamic parameter determination instruction is acquired;

[0104] Step 202: A cardiac tissue signal is extracted from the current frame of cardiac ultrasound image to obtain a cardiac tissue image, and a contrast microbubble signal is extracted from the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size;

[0105] In one embodiment, the cardiac tissue image is obtained by the following method:

[0106] The linear signal in the echo signal corresponding to the current frame of cardiac ultrasound image is extracted to obtain the cardiac tissue image.

[0107] It should be noted that the method of extracting the linear signal in this embodiment can be set according to actual conditions, and this embodiment does not limit the method of extracting the linear signal.

[0108] In one embodiment, the contrast microbubble image is obtained by the following method:

[0109] The nonlinear signal in the echo signal corresponding to the current frame of cardiac ultrasound image is extracted to obtain the contrast microbubble image.

[0110] For example, a positive pulse is transmitted once, and a negative pulse is transmitted once. The signals of the two echoes are added. The cardiac tissue signal will be cancelled out, and the contrast microbubble signal will remain due to its nonlinear characteristics. Thus, the extraction of the nonlinear signal is completed.

[0111] It should be noted that the method of extracting the contrast microbubble signal in this embodiment can be set according to actual conditions, and this embodiment does not limit the method of extracting the contrast microbubble signal.

[0112] Step 203: The endocardial region of the cardiac tissue image is identified by using a preset algorithm to obtain the position of the endocardial region;

[0113] Since the cardiac tissue image and the microbubble contrast image have the same size, the position of the endocardial region in the cardiac tissue image is the same as that in the microbubble contrast image.

[0114] The preset algorithm in this embodiment can be an edge detection algorithm, an image segmentation algorithm, a region growing algorithm, and a segmentation algorithm based on a convolutional neural network, etc. The preset algorithm in this embodiment can be set according to actual conditions, and the preset algorithm is not limited herein.

[0115] Due to the interference of hardware noise such as cardiac tissue movement and acoustic voltage characteristics, the cardiac tissue part and the contrast microbubble part of the echo signal cannot be effectively split, resulting in that the contrast microbubble information contains cardiac tissue and noise interference and other clutter information. It is necessary to more carefully distinguish the components of the ultrasonic echo signal to make the contrast microbubble characteristics more prominent, and less affected by non-blood flow motion parameters such as probe jitter and respiratory motion. In order to further improve the accuracy of the determined cardiac blood flow parameters, in an embodiment, before step 204 is performed, the contrast microbubble image is filtered to obtain a filtered contrast microbubble image, and the filtered contrast microbubble image is determined as the contrast microbubble image.

[0116] The clutter filtering method can include a singular value decomposition-based clutter filtering method, an RPCA (Robust Principal Component Analysis) method, or a GoDec algorithm (godecomposition, matrix decomposition algorithm).

[0117] Next, the singular value decomposition method and the GoDec algorithm are briefly introduced:

[0118] The singular value decomposition method: for any one ultrasonic signal in the contrast microbubble image, the ultrasonic signal is reconstructed into a Casorati matrix, where the reconstruction method is as shown in Figure 3 , where D x is the position of the scanning line in the ultrasonic signal, D z is the physical depth of the ultrasonic signal, and D t is the transmission time of the ultrasonic signal. The reconstructed Casorati matrix is singular value decomposed to obtain the singular value corresponding to the ultrasonic signal.

[0119] The singular value represents the size of the ultrasonic signal energy, and the ultrasonic signal with a small order has a large singular value, as shown in Figure 4 , the cardiac tissue signal is concentrated in the low-order singular value range, and the noise signal is concentrated in the high-order singular value range. Therefore, a suitable threshold can be designed to extract the contrast microbubble signal. The threshold in this embodiment can be set according to actual conditions, and the threshold is not limited herein.

[0120] GoDec algorithm: for any one of the contrast microbubble images of the ultrasound signal, the ultrasound signal D is regarded as the combination of low-rank matrix L, sparse matrix S and noise matrix N. Wherein L represents the heart tissue signal, S represents the contrast microbubble signal, N represents the noise signal, that is, as shown in formula (1):

[0121] D=L+S+N, rank(L)≤r, card(S)≤k …… (1);

[0122] Wherein, r is a preset low-rank parameter, and k is a preset sparse parameter.

[0123] The initialization matrix is set as shown in formula (2):

[0124]

[0125] Wherein, med(D i ) represents the median of the ith row of matrix D, and I 1×n represents a 1*n unit vector.

[0126] The low-rank parameter r and the sparse parameter k are set to iteratively decompose the ultrasound signal D, and the problem can be converted into the following subproblem, as shown in formula (3):

[0127]

[0128] Then L1, S1, L2, S2… can be obtained by formula (2) and formula (3) and solved alternately.

[0129] When the number of cycles is sufficient, or the condition is met, the following iterative loop process is executed:

[0130] step1: t=t+1;

[0131] step2: Wherein, q is a preset power index;

[0132] step3: A2=Y1;

[0133] Step 4: QR decomposition:

[0134] Step 5: judge whether it is less than r, if yes, let After that, return to execute step1, if not, execute step6;

[0135] Step 6:

[0136] Step 7: matrix sampling projection, St =P Ω (DL t ), where Ω represents the non-zero subset of the first k largest elements of DL.

[0137] Where A1 and A2 represent random matrices A1∈R constructed according to a given rank r. n×r A2∈R m×r And n is the preset number of columns in matrix D, and m is the preset number of rows in matrix D.

[0138] It should be noted that the singular value algorithm and GoDec algorithm described above in this embodiment are only for illustrative purposes and do not limit the clutter filtering method in this embodiment. The clutter filtering method in this embodiment can be set according to the actual situation.

[0139] Step 204: Based on the pixel values ​​of each pixel in the central endothelial region of the angiography microbubble image and the pixel values ​​of the neighboring pixels of each pixel, obtain the identification position of each target angiography microbubble in the current frame of cardiac ultrasound image;

[0140] like Figure 5 The diagram illustrates the process for obtaining the identification location of each target contrast microbubble in the current frame of echocardiography, including the following steps:

[0141] Step 501: For any pixel in the central inner membrane region of the contrast microbubble image, based on the pixel value of the pixel and the pixel values ​​of other pixels in the specified neighborhood of the pixel, obtain the pixel difference between the pixel and each of the other pixels.

[0142] In one embodiment, step 501 may be implemented as follows: for any other pixel in the specified neighborhood of the pixel, subtract the pixel value of the pixel from the pixel value of the other pixel to obtain the pixel difference between the pixel and the other pixel.

[0143] In this embodiment, the designated neighborhood is the eight-neighborhood of the pixel.

[0144] Step 502: Determine the other pixels with the largest pixel difference as the intermediate pixel, and obtain the energy value of the intermediate pixel based on the average pixel value of each pixel in the specified neighborhood of the intermediate pixel.

[0145] For example, such as Figure 6 If pixel 11 is the middle pixel of pixel 6, then the average value of the pixel values ​​of pixels 6, 7, 8, 10, 12, 14, 15 and 16 is determined as the energy value of pixel 11.

[0146] Step 503: Sort the intermediate pixels in descending order using the energy values ​​of the intermediate pixels corresponding to each pixel in the endocardial region, and determine the first specified number of intermediate pixels as the center point of each target angiography microbubble.

[0147] Step 504: Using each center point as the center and a specified length as the radius, obtain each target contrast microbubble, and determine the position of the center point of each target contrast microbubble as the identification position of the target contrast microbubble.

[0148] It should be noted that the specified length in this embodiment can be set according to the actual situation, and this embodiment does not limit the specified length.

[0149] Step 205: For any target angiography microbubble, obtain the target position of the target angiography microbubble in the current frame of the echocardiogram image by identifying the target angiography microbubble in the current frame of the echocardiogram image.

[0150] like Figure 7 The diagram illustrates a flowchart for determining the target location of the target angiography microbubble in the current frame of echocardiography, including the following steps:

[0151] Step 701: Based on the identified location of the target contrast microbubble, obtain the location range of the target contrast microbubble;

[0152] The position range includes the position range of the horizontal coordinate and the position range of the vertical coordinate.

[0153] In one embodiment, step 701 may be implemented as follows: adding the abscissa of the identified location to a first specified value to obtain the maximum position range of the abscissa, and subtracting the abscissa of the identified location from a second specified value to obtain the minimum position range of the abscissa. Based on the minimum and maximum position ranges of the abscissa, the position range of the abscissa is obtained.

[0154] The vertical coordinate of the identified location is added to a third specified value to obtain the maximum position range of the vertical coordinate. The vertical coordinate of the identified location is then subtracted from a fourth specified value to obtain the minimum position range of the vertical coordinate. Based on the minimum and maximum position ranges of the vertical coordinate, the position of the vertical coordinate is determined.

[0155] Step 702: For any location within the specified location range, based on the pixel values ​​of each pixel in a specified neighborhood of the location in the current frame of the echocardiogram image and the pixel values ​​of each pixel in a specified neighborhood of the location in the previous frame of the echocardiogram image, obtain the confidence level of the location.

[0156] In one embodiment, step 702 can be implemented as: multiplying the pixel value of the pixel point at the position in the current frame of cardiac ultrasound image with the pixel value of the pixel point at the position in the last frame of cardiac ultrasound image to obtain a first intermediate confidence; and for any one pixel point in a specified neighborhood of the position in the current frame of cardiac ultrasound image, multiplying the pixel value of the pixel point in the current frame of cardiac ultrasound image with the pixel value of the pixel point in the last frame of cardiac ultrasound image to obtain a second intermediate confidence of the pixel point; and adding the second intermediate confidences of the pixel points in the specified neighborhood to obtain a third intermediate confidence; and adding the third intermediate confidence with the first intermediate confidence to obtain the confidence of the position.

[0157] Step 703: determining the position with the highest confidence in the position range as the target position of the target contrast microbubble.

[0158] It should be noted that: if there are multiple positions with the highest confidence, any one of the positions with the highest confidence can be determined as the target position.

[0159] Step 206: obtaining the instantaneous velocity of the target contrast microbubble based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the last frame of cardiac ultrasound image.

[0160] In one embodiment, step 206 can be specifically implemented as:

[0161] First, obtaining the displacement of the target contrast microbubble according to the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the last frame of cardiac ultrasound image; wherein the displacement of the target contrast microbubble can be obtained by formula (4):

[0162]

[0163] wherein d is the displacement of the target contrast microbubble, x1 is the horizontal coordinate of the target position of the target contrast microbubble in the current frame of cardiac ultrasound image, y1 is the vertical coordinate of the target position of the target contrast microbubble in the current frame of cardiac ultrasound image, x2 is the horizontal coordinate of the target position of the target contrast microbubble in the last frame of cardiac ultrasound image, and y2 is the vertical coordinate of the target position of the target contrast microbubble in the last frame of cardiac ultrasound image.

[0164] Then, the displacement of the target contrast microbubble is divided by a target time to obtain a transient velocity of the target contrast microbubble, wherein the target time is a time interval between the current frame of cardiac ultrasound image and the last frame of cardiac ultrasound image. Wherein, the transient velocity of the target contrast microbubble can be obtained by formula (5):

[0165]

[0166] Wherein, v is the transient velocity of the target contrast microbubble, d is the displacement of the target contrast microbubble, and t is the target time.

[0167] Step 207: using the transient velocity of each target contrast microbubble, obtaining the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image.

[0168] As shown in the flowchart for determining the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image, comprising the following steps: Figure 8

[0169] Step 801: according to the transient velocity of each target contrast microbubble and the displacement of each target contrast microbubble, obtaining a parameter value;

[0170] Wherein, the transient velocity of each target contrast microbubble and the displacement of each target contrast microbubble are substituted into formula (6) to form a system of equations, and the values of a, b and c are solved.

[0171] v = ad + bd + c …… (6); 2

[0172] Wherein, v is the transient velocity of the target contrast microbubble, and d is the displacement of the target contrast microbubble.

[0173] Step 802: multiplying the parameter value by the preset fluid viscosity to obtain the wss. Wherein, the wss can be obtained by formula (7):

[0174] wss = μ × b …… (7);

[0175] Wherein, μ is the preset fluid viscosity, and b is the parameter value.

[0176] In order to further understand the technical scheme of the present disclosure, the following will be described in detail in combination with Figure 9 may include the following steps:

[0177] Step 901: in response to the cardiac hemodynamic parameter determination instruction sent by the user, obtaining the current frame of cardiac ultrasound image corresponding to the cardiac hemodynamic parameter determination instruction;

[0178] ​​Step 902: extracting a cardiac tissue signal in the current frame of the cardiac ultrasound image to obtain a cardiac tissue image, and extracting a contrast microbubble signal in the current frame of the cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size;

[0179] Step 903: identifying an endocardial region in the cardiac tissue image by using a preset algorithm to obtain a position of the endocardial region;

[0180] Step 904: filtering out clutter in the contrast microbubble image to obtain a filtered contrast microbubble image, and determining the filtered contrast microbubble image as the contrast microbubble image;

[0181] Step 905: for any one pixel point in the endocardial region of the contrast microbubble image, based on a pixel value of the pixel point and pixel values of each other pixel point in a designated neighborhood of the pixel point, obtaining a pixel difference value between the pixel point and each other pixel point;

[0182] Step 906: determining a pixel point with the largest pixel difference value as an intermediate pixel point, and based on a pixel mean value of each pixel point in a designated neighborhood of the intermediate pixel point, obtaining an energy value of the intermediate pixel point;

[0183] Step 907: sorting each intermediate pixel point in the endocardial region in descending order of the energy value of the intermediate pixel point corresponding to the pixel point, and determining a first designated number of intermediate pixel points as center points of target contrast microbubbles;

[0184] Step 908: obtaining each target contrast microbubble by taking each center point as a center and a designated length as a radius, and determining a position of the center point of each target contrast microbubble as a recognition position of the target contrast microbubble;

[0185] Step 909: for any one target contrast microbubble, based on the recognition position of the target contrast microbubble, obtaining a position range of the target contrast microbubble;

[0186] Step 910: for any one position in the position range, based on a pixel value of each pixel point in a designated neighborhood of the position in the current frame of the cardiac ultrasound image and a pixel value of each pixel point in a designated neighborhood of the position in a previous frame of the cardiac ultrasound image, obtaining a confidence degree of the position;

[0187] Step 911: determining a position with the highest confidence degree in the position range as a target position of the target contrast microbubble;

[0188] Step 912: obtaining the instantaneous velocity of each target contrast microbubble based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the last frame of cardiac ultrasound image;

[0189] Step 913: obtaining the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image by using the instantaneous velocity of each target contrast microbubble.

[0190] Based on the same disclosure concept, the method for determining the cardiac hemodynamic parameter as described above can also be implemented by a device for determining the cardiac hemodynamic parameter. The device for determining the cardiac hemodynamic parameter has similar effects to the method described above, and will not be described here.

[0191] Figure 10 The structure diagram of the device for determining the cardiac hemodynamic parameter according to an embodiment of the present disclosure.

[0192] As shown in Figure 10 The device for determining the cardiac hemodynamic parameter 1000 of the present disclosure can include an acquisition module 1010, an extraction module 1020, an endocardial region identification module 1030, a microbubble identification position determination module 1040, a microbubble target position determination module 1050, a microbubble instantaneous velocity determination module 1060, and a blood flow parameter determination module 1070.

[0193] The acquisition module 1010 is configured to acquire a current frame of cardiac ultrasound image corresponding to a cardiac hemodynamic parameter determination instruction sent by a user in response to the cardiac hemodynamic parameter determination instruction;

[0194] The extraction module 1020 is configured to extract a cardiac tissue signal in the current frame of cardiac ultrasound image to obtain a cardiac tissue image, and extract a contrast microbubble signal in the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size;

[0195] The endocardial region identification module 1030 is configured to identify the endocardial region of the cardiac tissue image by using a preset algorithm to obtain the position of the endocardial region;

[0196] The microbubble identification position determination module 1040 is configured to obtain the identification position of each target contrast microbubble in the current frame of cardiac ultrasound image based on the pixel value of each pixel point in the endocardial region of the contrast microbubble image and the pixel value of the neighborhood pixel points of the each pixel point;

[0197] The microbubble target position determination module 1050 is configured to obtain a target position of any one target contrast microbubble in the current frame of cardiac ultrasound image according to a recognized position of the target contrast microbubble in the current frame of cardiac ultrasound image; and

[0198] The microbubble instantaneous velocity determination module 1060 is configured to obtain an instantaneous velocity of the target contrast microbubble according to the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the previous frame of cardiac ultrasound image.

[0199] The blood flow parameter determination module 1070 is configured to obtain a viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image by using the instantaneous velocities of the target contrast microbubbles.

[0200] In an embodiment, the extraction module 1020 is configured to perform the extraction of the cardiac tissue signal in the current frame of cardiac ultrasound image to obtain a cardiac tissue image, and specifically configured to:

[0201] extract a linear signal in the echo signal corresponding to the current frame of cardiac ultrasound image to obtain the cardiac tissue image.

[0202] The extraction module 1020 is configured to perform the extraction of the contrast microbubble signal in the current frame of cardiac ultrasound image to obtain a contrast microbubble image, and specifically configured to:

[0203] extract a non-linear signal in the echo signal corresponding to the current frame of cardiac ultrasound image to obtain the contrast microbubble image.

[0204] In an embodiment, the device further comprises:

[0205] The clutter filtering module 1080 is configured to perform clutter filtering on the contrast microbubble image to obtain a filtered contrast microbubble image before the determination of the recognized position of each target contrast microbubble in the current frame of cardiac ultrasound image based on pixel values of each pixel point in the endometrial region of the contrast microbubble image and pixel values of neighborhood pixel points of the pixel point, and determine the filtered contrast microbubble image as the contrast microbubble image.

[0206] In an embodiment, the microbubble recognized position determination module 1040 is specifically configured to:

[0207] for any one pixel point in the endometrial region of the contrast microbubble image, obtain pixel difference values of the pixel point and each other pixel point in a designated neighborhood of the pixel point based on a pixel value of the pixel point and pixel values of the each other pixel point; and

[0208] determining other pixel points with maximum pixel difference as intermediate pixel points, assigning pixel mean values of each pixel point in the neighborhood based on the intermediate pixel points to obtain energy values of the intermediate pixel points;

[0209] sorting the intermediate pixel points in descending order according to the energy values of the intermediate pixel points corresponding to each pixel point in the endocardial region, and determining the first specified number of intermediate pixel points as the center points of the target contrast microbubbles, respectively;

[0210] obtaining the target contrast microbubbles by taking each center point as a center and a specified length as a radius, and determining the position of the center point of each target contrast microbubble as the recognition position of the target contrast microbubble.

[0211] In an embodiment, the microbubble target position determination module 1050 is specifically configured to:

[0212] obtaining a position range of the target contrast microbubble based on the recognition position of the target contrast microbubble;

[0213] obtaining a confidence degree of any position in the position range based on the pixel values of each pixel point in the specified neighborhood of the position in the current frame of cardiac ultrasound image and the pixel values of each pixel point in the specified neighborhood of the position in the previous frame of cardiac ultrasound image;

[0214] determining the position with the highest confidence degree in the position range as the target position of the target contrast microbubble.

[0215] In an embodiment, the microbubble target position determination module 1050 performs the obtaining of the confidence degree of the position based on the pixel values of each pixel point in the specified neighborhood of the position in the current frame of cardiac ultrasound image and the pixel values of each pixel point in the specified neighborhood of the position in the previous frame of cardiac ultrasound image, and is specifically configured to:

[0216] multiplying the pixel value of the pixel point at the position in the current frame of cardiac ultrasound image by the pixel value of the pixel point at the position in the previous frame of cardiac ultrasound image to obtain a first intermediate confidence degree; and

[0217] multiplying the pixel value of any pixel point in the specified neighborhood of the position in the current frame of cardiac ultrasound image by the pixel value of the pixel point in the previous frame of cardiac ultrasound image to obtain a second intermediate confidence degree of the pixel point; and

[0218] adding the second intermediate confidence degrees of each pixel point in the specified neighborhood to obtain a third intermediate confidence degree;

[0219] adding the third intermediate confidence to the first intermediate confidence to obtain a confidence of the position.

[0220] In one embodiment, the microbubble instantaneous velocity determination module 1060 is specifically configured to:

[0221] obtaining a displacement of the target contrast microbubble according to the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the previous frame of cardiac ultrasound image;

[0222] dividing the displacement of the target contrast microbubble by a target time to obtain an instantaneous velocity of the target contrast microbubble, wherein the target time is a time interval between the current frame of cardiac ultrasound image and the previous frame of cardiac ultrasound image.

[0223] In one embodiment, the blood flow parameter determination module 1070 is specifically configured to:

[0224] obtaining a parameter value according to the instantaneous velocity of each target contrast microbubble and the displacement of each target contrast microbubble;

[0225] multiplying the parameter value by a preset fluid viscosity to obtain the wss.

[0226] After introducing the method and device for determining a cardiac blood flow hemodynamic parameter according to an example embodiment of the present disclosure, next, an electronic device according to another example embodiment of the present disclosure is introduced.

[0227] Those skilled in the art can understand that each aspect of the present disclosure can be implemented as a system, a method or a program product. Therefore, each aspect of the present disclosure can be specifically implemented as follows: a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system" here.

[0228] In some possible embodiments, the electronic device according to the present disclosure can at least include at least one processor and at least one computer storage medium. The computer storage medium stores program codes, which, when executed by the processor, cause the processor to perform the steps in the method for determining a cardiac blood flow hemodynamic parameter according to various example embodiments of the present disclosure described above in the specification. For example, the processor can perform steps 201-207 as shown in Figure 2

[0229] The electronic device 1100 according to this embodiment of the present disclosure is described below with reference to Figure 11 Figure 11 ​​The electronic device 1100 shown is merely one example. It should be understood, however, that the functionality of the disclosed embodiments can be carried out by any electronic device, regardless of having or not having a touch interface.

[0230] As shown Figure 11 The electronic device 1100 is, optionally, in the form of a general purpose electronic device. Components of the electronic device 1100 can include, but are not limited to, the at least one processor 1101, the at least one computer storage medium 1102, and a bus 1103 that connects the various system components, including the computer storage medium 1102 and the processor 1101.

[0231] The bus 1103 represents one or more of any of several bus structures, including a computer storage bus or computer storage bus controller, a peripheral bus, and a local bus using any of a variety of bus architectures.

[0232] The computer storage medium 1102 can include read-only computer storage media, such as read-only memory (ROM) 1123, and / or random access computer storage media (RAM) 1121, in the form of volatile computer storage media, and / or cache memory 1122.

[0233] The computer storage medium 1102 can further include a program / utility 1125 having a set of programs / modules 1124, including an operating system, one or more application programs, other program modules, and program data, each of which can implement aspects of a network environment, for example, as described in one or more of the examples.

[0234] The electronic device 1100 can also communicate with one or more external devices 1104, such as a keyboard or a pointing device, through an input / output (I / O) interface(s) 1105. And, the electronic device 1100 can communicate with one or more devices that enable user interaction with the electronic device 1100, and / or one or more devices that enable communication of the electronic device 1100 with one or more other electronic devices. Such communication can be via an I / O interface 1105. The electronic device 1100 can communicate with one or more networks, such as a local area network (LAN), a wide area network (WAN), and / or the public network, such as the Internet, through a network adapter 1106. As depicted, the network adapter 1106 is communicatively coupled to the other components of the electronic device 1100 through the bus 1103. It should be understood that, although not shown explicitly, other hardware and / or software components can be used in conjunction with the electronic device 1100. These components include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0235] In some possible implementation, each aspect of the method for determining a cardiac hemodynamic parameter provided by the present disclosure can also be implemented in the form of a program product, which includes program codes for causing a computer device to perform the steps of the method for determining a cardiac hemodynamic parameter according to various exemplary embodiments of the present disclosure described above in the specification when the program product is run on the computer device.

[0236] The program product can employ any combination of one or more computer readable media. The computer readable media can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical computer storage device, a magnetic computer storage device, or any suitable combination of the above.

[0237] The program product for determining a cardiac hemodynamic parameter of the embodiments of the present disclosure can employ a portable compact disc read-only memory (CD-ROM) and include program codes, and can be run on an electronic device. However, the program product of the present disclosure is not limited thereto, and in the present document, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0238] The computer readable signal medium can include a computer readable data signal embodied in a carrier wave, where the carrier wave carries the computer readable program code. The computer readable program code can be transmitted over a variety of mediums including, but not limited to, wireless, wired, optical fiber cable, RF, and the like, or any suitable combination of the above.

[0239] The program code contained on the computer readable medium can be transmitted using any suitable medium, including, but not limited to, wireless, wired, optical fiber cable, RF, and the like, or any suitable combination of the above.

[0240] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's electronic device, partially on the user's device, as a standalone software package, partially on the user's electronic device and partially on a remote electronic device, or entirely on a remote electronic device or server. In cases involving remote electronic devices, the remote electronic device can be connected to the user's electronic device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external electronic device (e.g., via the Internet using an Internet service provider).

[0241] It should be noted that although several modules of the apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided and embodied by multiple modules.

[0242] Furthermore, although the operations of the methods disclosed herein are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0243] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk computer storage media, CD-ROMs, optical computer storage media, etc.) containing computer-usable program code.

[0244] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0245] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0246] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0247] Obviously, numerous modifications and variations of the present disclosure are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the present disclosure can be practiced otherwise than as specifically described.

Claims

1. An electronic device, comprising: The device comprises a processor and a memory connected by a bus; The memory stores a computer program, and the processor is configured to execute the following operations based on the computer program: In response to a user-sent cardiac hemodynamic parameter determination instruction, a current frame of cardiac ultrasound image corresponding to the cardiac hemodynamic parameter determination instruction is acquired; In the current frame of cardiac ultrasound image, a cardiac tissue signal is extracted to obtain a cardiac tissue image, and a contrast microbubble signal is extracted in the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size; A preset algorithm is used to identify an endocardial region of the cardiac tissue image to obtain a position of the endocardial region; Based on pixel values of each pixel point in the endocardial region of the contrast microbubble image and pixel values of neighboring pixel points of the each pixel point, an identification position of each target contrast microbubble in the current frame of cardiac ultrasound image is obtained; For any one target contrast microbubble, a target position of the target contrast microbubble in the current frame of cardiac ultrasound image is obtained through the identification position of the target contrast microbubble in the current frame of cardiac ultrasound image; and Based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and a target position of the target contrast microbubble in a previous frame of cardiac ultrasound image, an instantaneous velocity of the target contrast microbubble is obtained; The instantaneous velocities of the target contrast microbubbles are used to obtain a viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image.

2. The electronic device of claim 1, wherein, The processor executing the operation of extracting a cardiac tissue signal in the current frame of cardiac ultrasound image to obtain a cardiac tissue image is specifically configured to: extract a linear signal in an echo signal corresponding to the current frame of cardiac ultrasound image to obtain the cardiac tissue image; The processor executing the operation of extracting a contrast microbubble signal in the current frame of cardiac ultrasound image to obtain a contrast microbubble image is specifically configured to: extract a nonlinear signal in an echo signal corresponding to the current frame of cardiac ultrasound image to obtain the contrast microbubble image.

3. The electronic device of claim 1, wherein, The processor is further configured to: Before the operation of obtaining an identification position of each target contrast microbubble in the current frame of cardiac ultrasound image based on pixel values of each pixel point in the endocardial region of the contrast microbubble image and pixel values of neighboring pixel points of the each pixel point, the contrast microbubble image is subjected to clutter filtering to obtain a filtered contrast microbubble image, and the filtered contrast microbubble image is determined as the contrast microbubble image.

4. The electronic device of claim 1, wherein, The processor executing the operation of obtaining an identification position of each target contrast microbubble in the current frame of cardiac ultrasound image based on pixel values of each pixel point in the endocardial region of the contrast microbubble image and pixel values of neighboring pixel points of the each pixel point is specifically configured to: For any one pixel point in the endocardial region of the contrast microbubble image, pixel difference values of the pixel point and each other pixel point in a specified neighborhood of the pixel point are obtained based on a pixel value of the pixel point and pixel values of the each other pixel point. and, determining other pixel points with maximum pixel difference values as intermediate pixel points, and specifying pixel mean values of the pixel points in the neighborhood based on the intermediate pixel points to obtain energy values of the intermediate pixel points; sorting the intermediate pixel points in descending order according to the energy values of the intermediate pixel points corresponding to the pixel points in the endocardial region, and determining the intermediate pixel points with the first specified number as the center points of the target contrast microbubbles, respectively; taking each center point as a center and a specified length as a radius to obtain the target contrast microbubbles, and determining the positions of the center points of the target contrast microbubbles as the recognition positions of the target contrast microbubbles.

5. The electronic device of claim 1, wherein, The processor performs the obtaining of the target position of the target contrast microbubble in the current frame of the heart ultrasound image through the recognition position of the target contrast microbubble in the current frame of the heart ultrasound image, and is specifically configured to: obtain a position range of the target contrast microbubble based on the recognition position of the target contrast microbubble; obtain a confidence degree of the position based on pixel values of the pixel points in the specified neighborhood of the position in the current frame of the heart ultrasound image and pixel values of the pixel points in the specified neighborhood of the position in the previous frame of the heart ultrasound image; determine the position with the highest confidence degree in the position range as the target position of the target contrast microbubble.

6. The electronic device of claim 5, wherein, The processor performs the obtaining of the confidence degree of the position based on the pixel values of the pixel points in the specified neighborhood of the position in the current frame of the heart ultrasound image and the pixel values of the pixel points in the specified neighborhood of the position in the previous frame of the heart ultrasound image, and is specifically configured to: multiply the pixel value of the pixel point at the position in the current frame of the heart ultrasound image by the pixel value of the pixel point at the position in the previous frame of the heart ultrasound image to obtain a first intermediate confidence degree; and multiply the pixel value of each pixel point in the specified neighborhood of the position in the current frame of the heart ultrasound image by the pixel value of the pixel point in the previous frame of the heart ultrasound image to obtain a second intermediate confidence degree of the pixel point; add the second intermediate confidence degrees of the pixel points in the specified neighborhood to obtain a third intermediate confidence degree; add the third intermediate confidence degree and the first intermediate confidence degree to obtain the confidence degree of the position. The processor performs the obtaining of the instantaneous velocity of the target contrast microbubble based on the target position of the target contrast microbubble in the current frame of the heart ultrasound image and the target position of the target contrast microbubble in the previous frame of the heart ultrasound image, and is specifically configured to:

7. The electronic device of claim 1, wherein, obtain the displacement of the target contrast microbubble according to the target position of the target contrast microbubble in the current frame of the heart ultrasound image and the target position of the target contrast microbubble in the previous frame of the heart ultrasound image; and ​ Divide the displacement of the target contrast microbubble by a target time to obtain a transient velocity of the target contrast microbubble, wherein the target time is a time interval between the current frame of cardiac ultrasound image and the last frame of cardiac ultrasound image.

8. The electronic device of claim 1, wherein, The processor performs the use of the transient velocity of each target contrast microbubble, the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image, and is specifically configured to: According to the transient velocity of each target contrast microbubble and the displacement of each target contrast microbubble, a parameter value is obtained; The parameter value is multiplied by the preset fluid viscosity to obtain the wss.

9. A method of determining a cardiac hemodynamic parameter, characterized in that, The method comprises: In response to a cardiac hemodynamic parameter determination instruction sent by a user, a current frame of cardiac ultrasound image corresponding to the cardiac hemodynamic parameter determination instruction is obtained; In the current frame of cardiac ultrasound image, cardiac tissue signals are extracted to obtain a cardiac tissue image, and contrast microbubble signals are extracted in the current frame of cardiac ultrasound image to obtain a contrast microbubble image, wherein the cardiac tissue image and the contrast microbubble image have the same image size; Using a preset algorithm, the endocardial region of the cardiac tissue image is identified to obtain the position of the endocardial region; Based on the pixel value of each pixel point in the endocardial region of the contrast microbubble image and the pixel value of the neighborhood pixel points of the pixel point, the identification position of each target contrast microbubble in the current frame of cardiac ultrasound image is obtained; For any one target contrast microbubble, the target position of the target contrast microbubble in the current frame of cardiac ultrasound image is obtained through the identification position of the target contrast microbubble in the current frame of cardiac ultrasound image; and Based on the target position of the target contrast microbubble in the current frame of cardiac ultrasound image and the target position of the target contrast microbubble in the last frame of cardiac ultrasound image, the transient velocity of the target contrast microbubble is obtained; Using the transient velocity of each target contrast microbubble, the viscosity blood flow friction wss corresponding to the current frame of cardiac ultrasound image is obtained.

10. The method of claim 9, wherein, The extraction of cardiac tissue signals in the current frame of cardiac ultrasound image to obtain a cardiac tissue image comprises: Extracting linear signals in echo signals corresponding to the current frame of cardiac ultrasound image to obtain the cardiac tissue image; The extraction of contrast microbubble signals in the current frame of cardiac ultrasound image to obtain a contrast microbubble image comprises: Extracting non-linear signals in echo signals corresponding to the current frame of cardiac ultrasound image to obtain the contrast microbubble image.

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