Imaging Method for Ultrasonic Blood Flow and Electronic Device

Abstract

The present disclosure provides an imaging method and an electronic device for ultrasonic blood flow, which are used to improve the quality of blood flow images. The method includes: in response to a user-triggered vascular region setting operation, determining a target vascular region in a B-mode ultrasound examination image of biological tissue based on the vascular region setting operation; using the Doppler blood flow image and hemodynamic parameters of the target vascular region to obtain a blood flow surface mesh model corresponding to the target vascular region; optimizing the positions of each three-dimensional space discrete point in the blood flow surface mesh model according to the positions of each three-dimensional space discrete point in the blood flow surface mesh model and the positions of each adjacent three-dimensional space discrete point of each three-dimensional space discrete point to obtain an optimized blood flow surface mesh model; in response to a user-triggered blood flow rendering operation, performing a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendering image; and performing a fusion process on the blood flow rendering image and the B-ultrasound image to obtain a target blood flow image.

Description

Background Art

[0002] Ultrasonic color Doppler imaging technology can qualitatively analyze the hemodynamic information in blood vessels. Doctors can observe important information such as the blood flow direction, velocity distribution, and blood flow state in tissue blood vessels in real time, and then screen and evaluate suspected diseased tissues.

[0003] However, since traditional two-dimensional color Doppler images can only present limited hemodynamic information, such as velocity estimation display, power estimation display, variance estimation display, etc., they cannot display the blood vessel structure more clearly and vividly and present more blood flow details. In particular, they cannot effectively identify slow-flowing microvessels and complex blood vessel structures that cross each other, resulting in low-quality ultrasonic blood flow images. Summary of the Invention

[0004] In an exemplary embodiment of the present disclosure, an imaging method for ultrasonic blood flow is provided to improve the quality of ultrasonic blood flow images.

[0005] A first aspect of the present disclosure provides an imaging method for ultrasonic blood flow, the method comprising:

[0006] In response to a user-triggered blood vessel region setting operation, determining a target blood vessel region in a B-mode ultrasound examination image of a biological tissue based on the blood vessel region setting operation;

[0007] Using the Doppler blood flow image and hemodynamic parameters of the target blood vessel region to obtain a blood flow surface mesh model corresponding to the target blood vessel region;

[0008] For any three-dimensional spatial discrete point in the blood flow surface mesh model, obtaining the smoothed position of the three-dimensional spatial discrete point according to the position of the three-dimensional spatial discrete point and the positions of the adjacent three-dimensional spatial discrete points of the three-dimensional spatial discrete point;

[0009] Optimizing the positions of the three-dimensional spatial discrete points through the smoothed positions of the three-dimensional spatial discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model;

[0010] In response to a user-triggered blood flow rendering operation, performing a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendering image;

[0011] Performing a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image.

[0012] In this embodiment, a blood flow surface mesh model corresponding to the target blood vessel region is obtained through the Doppler blood flow image and hemodynamic parameters of the target blood vessel region, and then the blood flow surface mesh model is smoothed and optimized to obtain an optimized blood flow surface mesh model. The blood flow rendering image corresponding to the optimized blood flow surface mesh model is fused with the B-mode ultrasound image to obtain a target blood flow image. Thus, in this embodiment, the hemodynamic information is three-dimensionally visualized, providing more blood flow details to the user and improving the quality of the blood flow image.

[0013] In one embodiment, the obtaining of the blood flow surface mesh model corresponding to the target blood vessel region by using the Doppler blood flow image and hemodynamic parameters of the target blood vessel region includes:

[0014] According to the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters, each three-dimensional space discrete point in the target blood vessel region is obtained;

[0015] Using each three-dimensional space discrete point and the neighborhood three-dimensional space discrete points of each three-dimensional space discrete point, an initial blood flow surface mesh model is obtained;

[0016] For any blood flow surface mesh in the initial blood flow surface mesh model, the attribute of the blood flow surface mesh is set based on the attributes of each three-dimensional space discrete point of the blood flow surface mesh to obtain the blood flow surface mesh model, where the attribute of the blood flow surface mesh includes the color of each three-dimensional space discrete point and the normal vector of the blood flow surface mesh, and the attribute of any three-dimensional space discrete point includes an index and a three-dimensional space discrete point vector.

[0017] In this embodiment, an initial blood flow surface mesh model is constructed by combining hemodynamic parameters, and the attribute of the blood flow surface mesh is set by the attributes of each three-dimensional space discrete point of the blood flow surface mesh to obtain the blood flow surface mesh model. Thus, in this embodiment, the hemodynamic parameters are three-dimensionally visualized, and the attribute of the blood flow surface mesh is set by the attributes of each three-dimensional space discrete point, so that the determined blood flow surface mesh model has more detailed information and further improves the quality of the blood flow image.

[0018] In one embodiment, the obtaining of each three-dimensional space discrete point in the target blood vessel region according to the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters includes:

[0019] Based on the Doppler blood flow image of the target blood vessel region, each two-dimensional space discrete point in the target blood vessel region is obtained;

[0020] Respectively determine the target hemodynamic parameter among the hemodynamic parameters of each two-dimensional space discrete point as the vertical coordinate of each two-dimensional space discrete point, and obtain each three-dimensional space discrete point.

[0021] In this embodiment, each three-dimensional space discrete point is determined by the target hemodynamic parameter among the hemodynamic parameters of each two-dimensional space discrete point, improving the display effect of the blood flow image.

[0022] In one embodiment, the obtaining of the initial blood flow surface mesh model by using each three-dimensional space discrete point and the neighborhood three-dimensional space discrete points of each three-dimensional space discrete point includes:

[0023] For any three-dimensional space discrete point, traverse each three-dimensional space discrete point within the target neighborhood of the three-dimensional space discrete point to determine whether there is a blood flow point among each three-dimensional space discrete point within the target neighborhood;

[0024] If it is determined that there is a blood flow point, generate a patch of a specified shape with the target three-dimensional space discrete point within the target neighborhood and the three-dimensional space discrete point, where the target three-dimensional space discrete point is each three-dimensional space discrete vertex within the target neighborhood;

[0025] If it is determined that there is no blood flow point, generate the patch of the specified shape with each three-dimensional space discrete point within the target neighborhood and the three-dimensional space discrete point respectively;

[0026] Based on the patches of the specified shape corresponding to each three-dimensional space discrete point, obtain the initial blood flow surface mesh model.

[0027] In this embodiment, whether there is a blood flow point among each three-dimensional space discrete point within the target neighborhood of each three-dimensional space discrete point is used to connect each three-dimensional space discrete point in a corresponding manner to obtain the initial blood flow surface mesh model. Thereby, the imaging efficiency is improved.

[0028] In one embodiment, for any blood flow surface mesh in the initial blood flow surface mesh model, setting the attribute of the blood flow surface mesh based on the attributes of each discrete point of the blood flow surface mesh to obtain the blood flow surface mesh includes:

[0029] For any three-dimensional space discrete point in any blood flow surface mesh, use the preset correspondence between the index and color of the three-dimensional space discrete point to determine the target color corresponding to the index of the three-dimensional space discrete point, and set the color of the three-dimensional space discrete point to the target color; and,

[0030] For any blood flow surface grid, interpolate the vectors of the three-dimensional space discrete points in the blood flow surface grid to obtain the normal vector of the blood flow surface grid.

[0031] In this embodiment, the quality of the blood flow image is further improved by setting the colors of the three-dimensional space discrete points and the normal vectors of the blood flow surface grid.

[0032] In one embodiment, the obtaining the smoothed position of the three-dimensional space discrete point according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point includes:

[0033] For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, based on the position coordinates of the three-dimensional space discrete point and the position coordinates of the adjacent three-dimensional space discrete point, obtain the distance between the three-dimensional space discrete point and the adjacent three-dimensional space discrete point;

[0034] According to the distances between the three-dimensional space discrete point and the respective adjacent three-dimensional space discrete points, obtain the weights of the respective adjacent three-dimensional space discrete points;

[0035] Through the weights of the adjacent three-dimensional space discrete points and the position coordinates of the adjacent three-dimensional space discrete points, obtain the smoothed position of the three-dimensional space discrete point.

[0036] In this embodiment, the positions of the three-dimensional space discrete points are smoothed by the position coordinates of the respective adjacent three-dimensional space discrete points and the position coordinates of the respective adjacent three-dimensional space discrete points. Thus, the blood flow surface grid model is made smoother and more continuous, and the quality of the blood flow image is further improved.

[0037] In one embodiment, the obtaining the weights of the respective adjacent three-dimensional space discrete points according to the distances between the three-dimensional space discrete point and the respective adjacent three-dimensional space discrete points includes:

[0038] For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, determine the reciprocal of the distance between the adjacent three-dimensional space discrete point and the three-dimensional space discrete point as the weight of the adjacent three-dimensional space discrete point;

[0039] The obtaining the smoothed position of the three-dimensional space discrete point through the weights of the adjacent three-dimensional space discrete points and the position coordinates of the adjacent three-dimensional space discrete points includes:

[0040] For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, multiply the position coordinates of the adjacent three-dimensional space discrete point by the weight of the adjacent three-dimensional space discrete point to obtain a first intermediate position coordinate;

[0041] Add the corresponding first intermediate position coordinates of adjacent three-dimensional space discrete points to obtain second intermediate position coordinates;

[0042] Divide the second intermediate position coordinates by a target weight to obtain the smoothed position of the three-dimensional space discrete points, where the target weight is obtained by adding the weights of the adjacent three-dimensional space discrete points.

[0043] In one embodiment, the fusing the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image includes:

[0044] For any pixel point in the blood flow rendering image, obtain the transparency of the pixel point based on the three-dimensional position coordinates of the pixel point;

[0045] Use the transparency of the pixel point and the blood flow rendering color of the pixel point in the blood flow rendering image to determine the target rendering color of the pixel point; and,

[0046] Obtain the target intensity of the pixel point according to the transparency of the pixel point and the image intensity of the pixel point in the B-mode ultrasound examination image;

[0047] Obtain the fused display color through the target rendering color and the target intensity of the pixel point;

[0048] Obtain the target blood flow image based on the fused display colors of the pixel points in the blood flow rendering image.

[0049] In this embodiment, by fusing the blood flow rendering image and the B-mode ultrasound examination image, the blood flow foreground is highlighted, so that the quality of the determined blood flow image is better.

[0050] A second aspect of the present disclosure provides an electronic device, including a storage unit and a processor, wherein:

[0051] The storage unit is configured to store B-mode ultrasound examination images of biological tissues;

[0052] The processor is configured to:

[0053] In response to a user-triggered blood vessel region setting operation, determine a target blood vessel region in the B-mode ultrasound examination image of the biological tissue based on the blood vessel region setting operation;

[0054] Use the Doppler blood flow image and hemodynamic parameters of the target blood vessel region to obtain a blood flow surface mesh model corresponding to the target blood vessel region;

[0055] For any three-dimensional spatial discrete point in the blood flow surface grid model, based on the position of the three-dimensional spatial discrete point and the positions of the adjacent three-dimensional spatial discrete points of the three-dimensional spatial discrete point, obtain the smoothed position of the three-dimensional spatial discrete point;

[0056] Optimize the positions of the three-dimensional spatial discrete points through the smoothed positions of the three-dimensional spatial discrete points in the blood flow surface grid model to obtain an optimized blood flow surface grid model;

[0057] In response to a blood flow rendering operation triggered by the user, perform a rendering process on the optimized blood flow surface grid model to obtain a blood flow rendering image;

[0058] Perform a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image.

[0059] In one embodiment, when the processor executes to obtain the blood flow surface grid model corresponding to the target blood vessel region by using the Doppler blood flow image and hemodynamic parameters of the target blood vessel region, it is specifically configured as follows:

[0060] Based on the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters, obtain each three-dimensional spatial discrete point in the target blood vessel region;

[0061] Utilize each three-dimensional spatial discrete point and the neighborhood three-dimensional spatial discrete points of each three-dimensional spatial discrete point to obtain an initial blood flow surface grid model;

[0062] For any blood flow surface grid in the initial blood flow surface grid model, set the attributes of the blood flow surface grid based on the attributes of the three-dimensional spatial discrete points of the blood flow surface grid to obtain the blood flow surface grid model, where the attributes of the blood flow surface grid include the colors of the three-dimensional spatial discrete points and the normal vector of the blood flow surface grid, and the attributes of any three-dimensional spatial discrete point include an index and a three-dimensional spatial discrete point vector.

[0063] In one embodiment, when the processor executes to obtain each three-dimensional spatial discrete point in the target blood vessel region based on the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters, it is specifically configured as follows:

[0064] Based on the Doppler blood flow image of the target blood vessel region, obtain each two-dimensional spatial discrete point in the target blood vessel region;

[0065] Respectively determine the target hemodynamic parameters in the hemodynamic parameters of each two-dimensional spatial discrete point as the vertical coordinates of each two-dimensional spatial discrete point to obtain each three-dimensional spatial discrete point.

[0066] In one embodiment, the processor executes obtaining an initial blood flow surface mesh model by using each three-dimensional spatial discrete point and the neighborhood three-dimensional spatial discrete points of each three-dimensional spatial discrete point, and is specifically configured to:

[0067] For any one three-dimensional spatial discrete point, traverse each three-dimensional spatial discrete point in the target neighborhood of the three-dimensional spatial discrete point to determine whether there is a blood flow point among each three-dimensional spatial discrete point in the target neighborhood;

[0068] If it is determined that there is a blood flow point, generate a patch of a specified shape from the target three-dimensional spatial discrete point in the target neighborhood and the three-dimensional spatial discrete point, where the target three-dimensional spatial discrete point is each three-dimensional spatial discrete vertex in the target neighborhood;

[0069] If it is determined that there is no blood flow point, generate the patch of the specified shape from each three-dimensional spatial discrete point in the target neighborhood and the three-dimensional spatial discrete point respectively;

[0070] Obtain the initial blood flow surface mesh model based on the patches of the specified shape corresponding to each three-dimensional spatial discrete point.

[0071] In one embodiment, the processor executes setting the attribute of any blood flow surface mesh in the initial blood flow surface mesh model based on the attributes of each discrete point of the blood flow surface mesh to obtain the blood flow surface mesh, and is specifically configured to:

[0072] For any three-dimensional spatial discrete point in any blood flow surface mesh, use the preset correspondence between the index and color of the three-dimensional spatial discrete point to determine the target color corresponding to the index of the three-dimensional spatial discrete point, and set the color of the three-dimensional spatial discrete point to the target color; and,

[0073] For any blood flow surface mesh, perform interpolation processing on the vectors of each three-dimensional spatial discrete point in the blood flow surface mesh to obtain the normal vector of the blood flow surface mesh.

[0074] In one embodiment, the processor executes obtaining the smoothed position of the three-dimensional spatial discrete point according to the position of the three-dimensional spatial discrete point and the positions of the adjacent three-dimensional spatial discrete points of the three-dimensional spatial discrete point, and is specifically configured to:

[0075] For any adjacent three-dimensional spatial discrete point of the three-dimensional spatial discrete point, obtain the distance between the three-dimensional spatial discrete point and the adjacent three-dimensional spatial discrete point based on the position coordinates of the three-dimensional spatial discrete point and the position coordinates of the adjacent three-dimensional spatial discrete point;

[0076] Based on the distances between the three-dimensional space discrete points and their respective adjacent three-dimensional space discrete points, the weights of the respective adjacent three-dimensional space discrete points are obtained respectively;

[0077] Through the weights of the adjacent three-dimensional space discrete points and the position coordinates of the adjacent three-dimensional space discrete points, the smoothed position of the three-dimensional space discrete point is obtained.

[0078] In one embodiment, when the processor executes obtaining the weights of the respective adjacent three-dimensional space discrete points based on the distances between the three-dimensional space discrete points and their respective adjacent three-dimensional space discrete points, it is specifically configured as:

[0079] For any one of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point, the reciprocal of the distance between the adjacent three-dimensional space discrete point and the three-dimensional space discrete point is determined as the weight of the adjacent three-dimensional space discrete point;

[0080] When the processor executes obtaining the smoothed position of the three-dimensional space discrete point through the weights of the adjacent three-dimensional space discrete points and the position coordinates of the adjacent three-dimensional space discrete points, it is specifically configured as:

[0081] For any one of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point, the position coordinate of the adjacent three-dimensional space discrete point is multiplied by the weight of the adjacent three-dimensional space discrete point to obtain a first intermediate position coordinate;

[0082] The first intermediate position coordinates of the respective adjacent three-dimensional space discrete points are added correspondingly to obtain a second intermediate position coordinate;

[0083] The second intermediate position coordinate is divided by a target weight to obtain the smoothed position of the three-dimensional space discrete point, where the target weight is obtained by adding the respective weights of the respective adjacent three-dimensional space discrete points.

[0084] In one embodiment, when the processor executes fusing the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image, it is specifically configured as:

[0085] For any pixel point in the blood flow rendering image, based on the three-dimensional position coordinate of the pixel point, the transparency of the pixel point is obtained;

[0086] Using the transparency of the pixel point and the blood flow rendering color of the pixel point in the blood flow rendering image, the target rendering color of the pixel point is determined; and,

[0087] Based on the transparency of the pixel and the image intensity of the pixel in the B-mode ultrasound examination ultrasound image, obtain the target intensity of the pixel;

[0088] Through the target rendering color of the pixel and the target intensity of the pixel, obtain the fused display color;

[0089] Based on the fused display color of each pixel of the blood flow rendering image, obtain the target blood flow image.

[0090] According to the third aspect provided by the embodiments of the present disclosure, there is provided a computer storage medium storing a computer program for executing the method as described in the first aspect. Description of the Drawings

[0091] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0092] Figures 1A - 1C It is a schematic diagram of an applicable scenario according to an embodiment of the present disclosure;

[0093] Figure 2 It is one of the schematic flowcharts of the ultrasonic blood flow imaging method according to an embodiment of the present disclosure;

[0094] Figure 3 It is a schematic diagram of a terminal interface according to an embodiment of the present disclosure;

[0095] Figure 4 It is a schematic flowchart of determining a blood flow surface mesh model according to an embodiment of the present disclosure;

[0096] Figure 5 It is a schematic flowchart of determining each three-dimensional space discrete point according to an embodiment of the present disclosure;

[0097] Figure 6 It is a schematic flowchart of determining an initial blood flow surface mesh model according to an embodiment of the present disclosure;

[0098] Figure 7 It is one of the schematic diagrams of generating patches according to an embodiment of the present disclosure;

[0099] Figure 8 It is the second of the schematic diagrams of generating patches according to an embodiment of the present disclosure;

[0100] Figure 9Schematic diagram of an initial blood flow surface mesh model according to an embodiment of the present disclosure;

[0101] Figure 10 Flow chart of determining a blood flow surface mesh model according to an embodiment of the present disclosure;

[0102] Figure 11 Flow chart of determining the smoothed position of discrete points in three-dimensional space according to an embodiment of the present disclosure;

[0103] Figure 12 Flow chart of determining the smoothed position of discrete points in three-dimensional space according to an embodiment of the present disclosure;

[0104] Figure 13 Schematic diagram of obtaining an optimized blood flow surface mesh model according to an embodiment of the present disclosure;

[0105] Figure 14 Flow chart of fusing a blood flow rendering image and the B-mode ultrasound examination image according to an embodiment of the present disclosure;

[0106] Figure 15 Schematic diagram of a target blood flow image according to an embodiment of the present disclosure;

[0107] Figure 16 Second flow chart of an ultrasonic blood flow imaging method according to an embodiment of the present disclosure;

[0108] Figure 17 Ultrasonic blood flow imaging device according to an embodiment of the present disclosure;

[0109] Figure 18 Schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. Detailed implementation manners

[0110] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0111] In the embodiments of the present disclosure, the term "and / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0112] The application scenarios described in the embodiments of the present disclosure are for more clearly illustrating the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation to the technical solutions provided by the embodiments of the present disclosure. Those of ordinary skill in the art can know that with the emergence of new application scenarios, the technical solutions provided by the embodiments of the present disclosure are equally applicable to similar technical problems. Among them, in the description of the present disclosure, unless otherwise specified, the meaning of "a plurality of" is two or more than two.

[0113] In the prior art, two-dimensional color Doppler images can only present limited hemodynamic information, such as velocity estimation display, power estimation display, variance estimation display, etc., and cannot display blood vessel structures more clearly and realistically and present more blood flow details. In particular, it is impossible to effectively identify slowly flowing tiny blood vessels and complex blood vessel structures that cross each other, resulting in low-quality ultrasonic blood flow images.

[0114] Therefore, the present disclosure provides an imaging method for ultrasonic blood flow. By using the Doppler blood flow image and hemodynamic parameters of a target blood vessel region, a blood flow surface mesh model corresponding to the target blood vessel region is obtained. Then, the blood flow surface mesh model is smoothed and optimized to obtain an optimized blood flow surface mesh model, and the blood flow rendering image corresponding to the optimized blood flow surface mesh model is fused with a B-mode ultrasound image to obtain a target blood flow image. Thus, in this embodiment, the hemodynamic information is three-dimensionally visualized, thereby providing more blood flow details to the user and improving the quality of the blood flow image. Next, the solution of the present disclosure will be introduced in detail with reference to the accompanying drawings.

[0115] As Figure 1A shown, it is an application scenario diagram of an imaging method for ultrasonic blood flow in an embodiment of the present application. The figure includes: a terminal device 10, a server 20, and a memory 30;

[0116] In a possible application scenario, the user sends a blood vessel area setting operation to the server 20 through the terminal device 10. In response to the blood vessel area setting operation triggered by the user, the server 20 obtains the stored B-mode ultrasound examination image of the biological tissue from the memory 30. Then, the server 20 determines the target blood vessel area in the B-mode ultrasound examination image of the biological tissue based on the blood vessel area setting operation; and uses the Doppler blood flow image and hemodynamic parameters of the target blood vessel area to obtain the blood flow surface mesh model corresponding to the target blood vessel area; then, for any three-dimensional space discrete point in the blood flow surface mesh model, the server 20 obtains the smoothed position of the three-dimensional space discrete point according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point; and optimizes the positions of the three-dimensional space discrete points through the smoothed positions of the three-dimensional space discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model; the server 20 performs a rendering process on the optimized blood flow surface mesh model in response to the blood flow rendering operation triggered by the user to obtain a blood flow rendering image; and performs a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image. Finally, the server 20 sends the target blood flow image to the terminal device 10 for display.

[0117] In another possible application scenario, as Figure 1B shown, in the application scenario, there are only the terminal device 10 and the memory 30, and the execution entity is the terminal device 10. The terminal device 10 obtains the stored B-mode ultrasound examination image of the biological tissue from the memory 30 in response to the blood vessel area setting operation triggered by the user. Then, the terminal device 10 determines the target blood vessel area in the B-mode ultrasound examination image of the biological tissue based on the blood vessel area setting operation; and uses the Doppler blood flow image and hemodynamic parameters of the target blood vessel area to obtain the blood flow surface mesh model corresponding to the target blood vessel area; then, for any three-dimensional space discrete point in the blood flow surface mesh model, the terminal device 10 obtains the smoothed position of the three-dimensional space discrete point according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point; and optimizes the positions of the three-dimensional space discrete points through the smoothed positions of the three-dimensional space discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model; the terminal device 10 performs a rendering process on the optimized blood flow surface mesh model in response to the blood flow rendering operation triggered by the user to obtain a blood flow rendering image; and performs a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image. Finally, the terminal device 10 displays the target blood flow image through its own display screen.

[0118] In another possible application scenario, as Figure 1CAs shown, the application scenario includes a terminal device 10 and a server 20. The execution entity is the server 20. The user sends a blood vessel area setting operation to the server 20 through the terminal device 10. The server 20, in response to the blood vessel area setting operation triggered by the user, determines a target blood vessel area in the B-mode ultrasound examination image of the biological tissue based on the blood vessel area setting operation; and uses the Doppler blood flow image and hemodynamic parameters of the target blood vessel area to obtain a blood flow surface mesh model corresponding to the target blood vessel area; then, for any three-dimensional space discrete point in the blood flow surface mesh model, the server 20 obtains the smoothed position of the three-dimensional space discrete point according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point; and optimizes the positions of the three-dimensional space discrete points through the smoothed positions of the three-dimensional space discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model; the server 20, in response to the blood flow rendering operation triggered by the user, performs a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendering image; and performs a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image. Finally, the server 20 sends the target blood flow image to the terminal device 10 for display.

[0119] Among them, Figure 1A and Figure 1C The server 20 and the terminal device 10 can perform information interaction through a communication network. Among them, the communication method adopted by the communication network can be divided into a wireless communication method or a wired communication method.

[0120] Exemplarily, the server 20 can access the network through cellular mobile communication technology and communicate with the terminal device 10. Among them, the cellular mobile communication technology, for example, includes the fifth-generation mobile communication (5th Generation Mobile Networks, 5G) technology.

[0121] Optionally, the server 20 can access the network through a short-range wireless communication method and communicate with the terminal device 10. Among them, the short-range wireless communication method, for example, includes the wireless fidelity (Wireless Fidelity, Wi-Fi) technology.

[0122] Moreover, in the description of the present application, only the single terminal device 10, server 20, and memory 30 are described in detail. However, those skilled in the art should understand that the illustrated terminal device 10, server 20, and memory 30 are intended to represent the operations of the terminal device 10, server 20, and memory 30 involved in the technical solution of the present application. It does not imply any limitation on the number, type, or location of the terminal device 10, server 20, and memory 30. It should be noted that if additional modules are added to or individual modules are removed from the illustrated environment, the underlying concept of the exemplary embodiments of the present application will not be changed. Additionally, although for convenience of illustration, Figure 1A a two-way arrow from the memory 30 to the server 20 is shown in

[0123] it should be understood by those skilled in the art that the transmission and reception of the above data also need to be implemented through a network. Figure 1A 、 Figure 1B and Figure 1C the application scenarios shown, but also applicable to any device with an interface display requirement.

[0124] Exemplarily, the terminal device 10 includes but is not limited to: visualization large screen, tablet computer, notebook computer, palm computer, mobile Internet device (MID), wearable device, virtual reality (VR) device, augmented reality (AR) device, wireless terminal device in industrial control, wireless terminal device in unmanned driving, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, or wireless terminal device in smart home, etc.; relevant clients can be installed on the terminal device, and the client can be software (such as browser, short video software, etc.), or web page, small program, etc.

[0125] The server 20 can be implemented by a single server or by multiple servers. The server 20 can be implemented by a physical server or by a virtual server.

[0126] Next, in combination with the above-described application scenarios, the imaging method of ultrasonic blood flow of the exemplary embodiments of the present application will be described with reference to the accompanying drawings. It should be noted that the above application scenarios are only shown for the convenience of understanding the method and principle of the present application, and the embodiments of the present application are not limited in this regard.

[0127] As Figure 2As shown in the figure, it is a schematic flowchart of the imaging method for ultrasonic blood flow of the present disclosure, which may include the following steps:

[0128] Step 201: In response to a vascular region setting operation triggered by a user, determine a target vascular region in a B-mode ultrasound examination image of biological tissue based on the vascular region setting operation;

[0129] It should be noted that the biological tissue in this embodiment can be a human biological tissue structure such as the neck, lower limbs, arms, etc. This embodiment does not limit the biological tissue here.

[0130] For example, as Figure 3 shown, it is a schematic diagram of the terminal interface of a B-mode ultrasound examination image. Figure 3 Taking the B-mode ultrasound examination image of the carotid artery in the neck as an example for illustration, wherein the user can mark the target vascular region in this terminal interface. Figure 3 The dashed box in

[0131] is the target vascular region marked by the user.

[0132] Next, a detailed introduction to the specific method for determining the blood flow surface mesh model will be given. As Figure 4 shown, it is a schematic flowchart for determining the blood flow surface mesh model, which may include the following steps:

[0133] Step 2021: Obtain each three-dimensional space discrete point in the target vascular region according to the Doppler blood flow image of the target vascular region and the hemodynamic parameters;

[0134] In one embodiment, as Figure 5 shown, it is a schematic flowchart for determining each three-dimensional space discrete point, which may include the following steps:

[0135] Step 501: Based on the Doppler blood flow image of the target vascular region, obtain each two-dimensional space discrete point in the target vascular region;

[0136] Among them, the two-dimensional space discrete point includes the abscissa and ordinate of the discrete point. The abscissa and ordinate of the discrete point are directly obtained from the Doppler image, and thus each two-dimensional space discrete point is obtained.

[0137] Step 502: Respectively determine the target hemodynamic parameter in the hemodynamic parameters of each two-dimensional space discrete point as the vertical coordinate of each two-dimensional space discrete point, so as to obtain each three-dimensional space discrete point.

[0138] The target hemodynamic parameters in this embodiment are pre-set hemodynamic parameters. That is, hemodynamic parameters such as blood flow velocity, energy, and power can all be used as target hemodynamic parameters, and specifically, they can be set according to the actual situation. This embodiment does not limit them here.

[0139] Step 2022: Use the three-dimensional space discrete points and the neighborhood three-dimensional space discrete points of the three-dimensional space discrete points to obtain an initial blood flow surface mesh model.

[0140] Next, a detailed introduction to the specific method for determining the initial blood flow surface mesh model is as follows. Figure 6 As shown, it is a flow chart for determining the initial blood flow surface mesh model, which may include the following steps:

[0141] Step 601: For any one three-dimensional space discrete point, traverse the three-dimensional space discrete points in the target neighborhood of the three-dimensional space discrete point to determine whether there are blood flow points among the three-dimensional space discrete points in the target neighborhood.

[0142] In one embodiment, the following method is used to determine whether there are blood flow points among the three-dimensional space discrete points in the target neighborhood:

[0143] For any one three-dimensional space discrete point in the target neighborhood, if the blood flow velocity in the hemodynamic parameters of the three-dimensional space discrete point is greater than the specified flow rate, it is determined that the three-dimensional space discrete point is a blood flow point; otherwise, it is determined that the three-dimensional space discrete point is not a blood flow point.

[0144] Among them, the specified flow rate in this embodiment is 1 mm / s. For example, if the blood flow velocity of the three-dimensional space discrete point A is 1 mm / s, it is determined that the three-dimensional space discrete point A is a blood flow point. If the blood flow velocity of the three-dimensional space discrete point B is 0 mm / s, it is determined that the three-dimensional space discrete point B is not a blood flow point.

[0145] It should be noted that the value of the specified flow rate in this embodiment is only for illustrative purposes and does not limit the specific value of the specified flow rate, which can be set according to the actual situation.

[0146] Step 602: If it is determined that there are blood flow points, generate a patch with a specified shape between the target three-dimensional space discrete point in the target neighborhood and the three-dimensional space discrete point, where the target three-dimensional space discrete point is each three-dimensional space discrete vertex in the target neighborhood.

[0147] Among them, the specified shape includes triangles, rectangles, hexagons, etc. The specific shape can be set according to the actual situation, and this embodiment does not limit it here.

[0148] For example, asFigure 7 As shown, taking the specified shape as a triangle as an example, Figure 7 As shown in image a in , the target three-dimensional space discrete points of the three-dimensional space discrete point F are the three-dimensional space discrete points A, C, G, and I in the three-dimensional space. Then, the patch generated based on the three-dimensional space discrete point F and the corresponding target three-dimensional space discrete points of the three-dimensional space discrete point F is as Figure 7 shown in image b in .

[0149] It should be noted that when there are blood flow points, each target three-dimensional space discrete point can only generate one corresponding patch, that is, Figure 7 the target three-dimensional space discrete points A, C, G, and I in only have one corresponding patch.

[0150] Step 603: If it is determined that there are no blood flow points, then each three-dimensional space discrete point in the target neighborhood is respectively connected to the three-dimensional space discrete point to generate the patch of the specified shape;

[0151] For example, as Figure 8 shown, when there are no blood flow points, then the three-dimensional space discrete point A is connected to each three-dimensional space discrete point in the target neighborhood to generate the corresponding patch. As Figure 8 shown in image b in , each three-dimensional space discrete point in the target neighborhood of the three-dimensional space discrete point E generates a triangular patch with the three-dimensional space discrete point E.

[0152] Step 604: Based on the patches of the specified shape corresponding to each three-dimensional space discrete point, obtain the initial blood flow surface mesh model.

[0153] For example, as Figure 9 shown, after connecting each three-dimensional space discrete point according to the rules described above, the Figure 9 initial blood flow surface mesh model in is obtained. It should be noted that Figure 9 the initial blood flow surface mesh model in is only used for illustrative purposes and does not limit the specific shape and size of the initial blood flow surface mesh model.

[0154] Step 2023: For any blood flow surface mesh in the initial blood flow surface mesh model, set the attributes of the blood flow surface mesh based on the attributes of each three-dimensional space discrete point of the blood flow surface mesh to obtain the blood flow surface mesh model, where the attributes of the blood flow surface mesh include the color of each three-dimensional space discrete point and the normal vector of the blood flow surface mesh, and the attributes of any three-dimensional space discrete point include an index and a three-dimensional space discrete point vector.

[0155] Next, a detailed introduction to the specific method for determining the blood flow surface mesh model is provided. As Figure 10As shown in the figure, it is a schematic flowchart for determining the surface grid model of blood flow, which may include the following steps:

[0156] Step 1001: For any three-dimensional space discrete point in any blood flow surface grid, use the preset correspondence between the index and color of the three-dimensional space discrete point to determine the target color corresponding to the index of the three-dimensional space discrete point, and set the color of the three-dimensional space discrete point to the target color;

[0157] Step 1002: For any blood flow surface grid, perform interpolation processing on the vectors of each three-dimensional space discrete point in the blood flow surface grid to obtain the normal vector of the blood flow surface grid.

[0158] It should be noted that determining the normal vector of the blood flow surface grid is a method in the prior art, and this embodiment will not elaborate on it here.

[0159] Step 203: For any three-dimensional space discrete point in the blood flow surface grid model, obtain the smoothed position of the three-dimensional space discrete point according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point;

[0160] Next, the method for determining the smoothed position of the three-dimensional space discrete point will be introduced. As Figure 11 shown in the figure, it is a schematic flowchart for determining the smoothed position of the three-dimensional space discrete point, which may include the following steps:

[0161] Step 1101: For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, based on the position coordinates of the three-dimensional space discrete point and the position coordinates of the adjacent three-dimensional space discrete point, obtain the distance between the three-dimensional space discrete point and the adjacent three-dimensional space discrete point; among them, the distance between two three-dimensional space discrete points can be determined by formula (1):

[0162]

[0163] where d is the distance between two three-dimensional space discrete points, x1 is the abscissa of the three-dimensional space discrete point, x2 is the abscissa of the adjacent three-dimensional space discrete point, y1 is the ordinate of the three-dimensional space discrete point, y2 is the ordinate of the adjacent three-dimensional space discrete point, z1 is the vertical coordinate of the three-dimensional space discrete point, and z2 is the vertical coordinate of the adjacent three-dimensional space discrete point.

[0164] Step 1102: According to the distances between the three-dimensional space discrete point and each adjacent three-dimensional space discrete point, obtain the weights of each adjacent three-dimensional space discrete point respectively;

[0165] In one embodiment, step 1102 may be implemented as follows: for any adjacent three-dimensional space discrete point of the three-dimensional space discrete points, the reciprocal of the distance between the adjacent three-dimensional space discrete point and the three-dimensional space discrete point is determined as the weight of the adjacent three-dimensional space discrete point; wherein, the weight of the adjacent three-dimensional space discrete point can be obtained through formula (2):

[0166]

[0167] wherein, d ij is the distance between the three-dimensional space discrete point i and its adjacent three-dimensional space discrete point j, and w j is the weight of the adjacent three-dimensional space discrete point j.

[0168] Step 1103: Obtain the smoothed position of the three-dimensional space discrete point through the weight of the adjacent three-dimensional space discrete point and the position coordinates of the three-dimensional space discrete point.

[0169] Next, a detailed introduction will be given to the specific method of obtaining the smoothed position of the three-dimensional space discrete point through the weight of the adjacent three-dimensional space discrete point and the position coordinates of the three-dimensional space discrete point. As Figure 12 shown, it is a schematic flow diagram for determining the smoothed position of the three-dimensional space discrete point, which may include the following steps:

[0170] Step 1201: For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, multiply the position coordinates of the adjacent three-dimensional space discrete point by the weight of the adjacent three-dimensional space discrete point to obtain the first intermediate position coordinates;

[0171] Step 1202: Add the first intermediate position coordinates of each adjacent three-dimensional space discrete point correspondingly to obtain the second intermediate position coordinates;

[0172] Step 1203: Divide the second intermediate position coordinates by the target weight to obtain the smoothed position of the three-dimensional space discrete point, wherein the target weight is obtained by adding the weights of the adjacent three-dimensional space discrete points.

[0173] Among them, for any three-dimensional space discrete point, the smoothed position of the three-dimensional space discrete point can be obtained through formula (3):

[0174]

[0175] wherein, p new is the smoothed position of the three-dimensional space discrete point, p j is the jth adjacent three-dimensional space discrete point of the three-dimensional space discrete point, and w jis the weight of the j-th adjacent three-dimensional discrete point of the three-dimensional discrete points, and n is the number of adjacent three-dimensional discrete points of the three-dimensional discrete points.

[0176] Step 204: Optimize the positions of the three-dimensional discrete points through the smoothed positions of the three-dimensional discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model;

[0177] In one embodiment, the smoothed positions of the three-dimensional discrete points in the blood flow surface mesh model are determined as the current positions of the three-dimensional discrete points to adjust the positions of the three-dimensional discrete points to obtain an optimized blood flow surface mesh model.

[0178] For example, as Figure 13 shown, transform the position coordinates of the three-dimensional discrete point p old to p new to obtain an optimized blood flow surface mesh model.

[0179] Step 205: In response to a user-triggered blood flow rendering operation, perform a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendering image;

[0180] To display the appearance of the blood flow, it is necessary to perform a rendering process on the optimized blood flow surface mesh model. In the real world, the visual impression of the appearance of an object on the human eye is affected by lighting and the material of the object. Suppose there is light shining on the blood flow surface. Then, part of the light energy is absorbed by the blood flow and converted into heat. Another part of the light energy is reflected by the blood flow, and still another part of the light energy passes through the blood flow and is projected. The intensity and ratio of the reflected light and the projected light reflect the color of the blood flow surface, producing the visual effect perceived by the eyes. The user can control the visual effect of the blood flow appearance by adjusting the light source attributes, blood flow material parameters, diffuse reflection parameters, specular reflection parameters, etc. Among them, for any three-dimensional discrete point in the optimized blood flow surface mesh model, the blood flow rendering color after rendering the three-dimensional discrete point can be obtained through formula (4):

[0181]

[0182]

[0183] where, m A (p) represents the ambient light affected by the material at point p, and l A (p) represents the ambient light affected by the light source at point p; lights represents the total number of light sources, and m D (p) represents the diffuse reflection component affected by the material at point p, represents the diffuse reflection component affected by the i-th light source at point p; m S(p) represents the specular reflection component of point p affected by the material. represents the specular reflection component of point p affected by the i-th light source; L i (p) represents the incident light direction of the i-th light source at point p, N(p) represents the normal vector of point p, R i (p) represents the reflected light direction of the i-th light source at point p, V(p) represents the light direction of point p towards the observer, and shininess(p) represents the specular exponent of point p. k c represents a preset constant attenuation factor, k l represents a preset linear attenuation factor, k q represents a preset quadratic attenuation factor, d i represents the distance between the i-th light source and point p.

[0184] It should be noted that all parameters in formula (4) in this embodiment are pre-set parameters, and the corresponding parameter values can be directly obtained. By using formula (4) to render each three-dimensional space discrete point in the optimized blood flow surface mesh model, a blood flow rendering image is obtained.

[0185] Step 206: Perform a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image.

[0186] Next, a detailed introduction will be given to the specific method of performing a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image. As Figure 14 shown, it is a schematic flow diagram of performing a fusion process on the blood flow rendering image and the B-mode ultrasound examination image, which may include the following steps:

[0187] Step 1401: For any pixel point in the blood flow rendering image, based on the three-dimensional position coordinates of the pixel point, obtain the transparency of the pixel point;

[0188] In one embodiment, the transparency of the pixel point is obtained by the following method:

[0189] For any pixel point, use the preset correspondence between the three-dimensional position coordinates of the pixel point and the transparency to determine the transparency corresponding to the three-dimensional position coordinates of the pixel point.

[0190] Step 1402: Use the transparency of the pixel point and the blood flow rendering color of the pixel point in the blood flow rendering image to determine the target rendering color of the pixel point;

[0191] In one embodiment, step 1402 can be implemented as: multiplying the transparency by the blood flow rendering color to obtain the target rendering color of the pixel point.

[0192] Step 1403: Obtain the target intensity of the pixel based on the transparency of the pixel and the image intensity of the pixel in the B-mode ultrasound examination super image.

[0193] In one embodiment, step 1403 can be implemented as: subtract the preset transparency from the transparency to obtain a transparency difference, and multiply the transparency difference by the image intensity to obtain the target intensity.

[0194] Step 1404: Obtain the fused display color through the target rendering color and the target intensity of the pixel.

[0195] In one embodiment, step 1404 can be implemented as: add the target rendering color of the pixel and the target intensity of the pixel to obtain the fused display color.

[0196] Among them, for any pixel, the fused display color of the pixel can be obtained through formula (5):

[0197] Blend(p) = α·Color(p) + (1 - α)·B(p)……(5);

[0198] Wherein, Blend(p) is the fused display color of the pixel, α is the transparency of the pixel, Color(p) is the blood flow rendering color of the pixel in the blood flow rendering image, and B(p) is the image intensity of the pixel in the B-mode ultrasound examination super image.

[0199] It should be noted that: the execution order of step 1403 and step 1404 is not limited in this embodiment. Step 1403 can be executed first, and then step 1404. Or step 1404 can be executed first, and then step 1403. Or step 1403 and step 1404 can be executed simultaneously.

[0200] Step 1405: Obtain the target blood flow image based on the fused display color of each pixel of the blood flow rendering image.

[0201] In one embodiment, replace the display color of each pixel of the blood flow rendering image with the fused display color to obtain the target blood flow image. For example, as Figure 15 shown, the target blood flow image obtained by the method in the present disclosure. It can be seen from the figure that the obtained target blood flow image is a three-dimensional visualization effect diagram, which can display more detailed information and improve the quality of the image.

[0202] To further understand the technical solution of the present disclosure, the following is combined with Figure 16 for a detailed description, which may include the following steps:

[0203] Step 1601: In response to a vascular region setting operation triggered by a user, determine a target vascular region in a B-mode ultrasound image of biological tissue based on the vascular region setting operation;

[0204] Step 1602: Obtain each three-dimensional space discrete point in the target vascular region according to the Doppler blood flow image of the target vascular region and the hemodynamic parameters;

[0205] Step 1603: Use each three-dimensional space discrete point and the neighborhood three-dimensional space discrete points of each three-dimensional space discrete point to obtain an initial blood flow surface mesh model;

[0206] Step 1604: For any blood flow surface mesh in the initial blood flow surface mesh model, set the attributes of the blood flow surface mesh based on the attributes of each three-dimensional space discrete point of the blood flow surface mesh to obtain the blood flow surface mesh model, where the attributes of the blood flow surface mesh include the color of each three-dimensional space discrete point and the normal vector of the blood flow surface mesh, and the attributes of any three-dimensional space discrete point include an index and a three-dimensional space discrete point vector;

[0207] Step 1605: For any adjacent three-dimensional space discrete point of any three-dimensional space discrete point, obtain the distance between the three-dimensional space discrete point and the adjacent three-dimensional space discrete point based on the position coordinates of the three-dimensional space discrete point and the position coordinates of the adjacent three-dimensional space discrete point;

[0208] Step 1606: Obtain the weights of each adjacent three-dimensional space discrete point respectively according to the distances between the three-dimensional space discrete point and each adjacent three-dimensional space discrete point;

[0209] Step 1607: Obtain the smoothed position of the three-dimensional space discrete point through the weight of the adjacent three-dimensional space discrete point and the position coordinates of the three-dimensional space discrete point;

[0210] Step 1608: Optimize the positions of each three-dimensional space discrete point through the smoothed positions of each three-dimensional space discrete point in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model;

[0211] Step 1609: In response to a blood flow rendering operation triggered by a user, perform a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendering image;

[0212] Step 1610: For any pixel point in the blood flow rendering image, obtain the transparency of the pixel point based on the three-dimensional position coordinates of the pixel point;

[0213] Step 1611: Determine the target rendering color of the pixel point by using the transparency of the pixel point and the blood flow rendering color of the pixel point in the blood flow rendering image;

[0214] Step 1612: Obtain the target intensity of the pixel point according to the transparency of the pixel point and the image intensity of the pixel point in the B-mode ultrasound examination image;

[0215] It should be noted that: The execution order of Step 1611 and Step 1612 is not limited in this embodiment. Step 1611 can be executed first, and then Step 1612. Or Step 1612 can be executed first, and then Step 1611. Or Step 1611 and Step 1612 can be executed simultaneously.

[0216] Step 1613: Obtain the fused display color through the target rendering color of the pixel point and the target intensity of the pixel point;

[0217] Step 1614: Obtain the target blood flow image based on the fused display color of each pixel point of the blood flow rendering image.

[0218] Based on the same inventive concept, the above-described ultrasonic blood flow imaging method of the present disclosure can also be implemented by an ultrasonic blood flow imaging device. The effect of the ultrasonic blood flow imaging device is similar to that of the foregoing method, and will not be elaborated here.

[0219] Figure 17 It is a schematic structural diagram of an ultrasonic blood flow imaging device according to an embodiment of the present disclosure.

[0220] As Figure 17 shown, the ultrasonic blood flow imaging device 1700 of the present disclosure may include a target blood vessel region determination module 1710, a blood flow surface mesh model determination module 1720, a smoothing module 1730, an optimization module 1740, a blood flow rendering module 1750, and a fusion module 1760.

[0221] The target blood vessel region determination module 1710 is configured to, in response to a blood vessel region setting operation triggered by a user, determine a target blood vessel region in the B-mode ultrasound examination image of the biological tissue based on the blood vessel region setting operation;

[0222] The blood flow surface mesh model determination module 1720 is configured to obtain a blood flow surface mesh model corresponding to the target blood vessel region by using the Doppler blood flow image of the target blood vessel region and hemodynamic parameters;

[0223] A smoothing module 1730, configured to obtain a smoothed position of any three-dimensional spatial discrete point in the blood flow surface mesh model according to the position of the three-dimensional spatial discrete point and the positions of the adjacent three-dimensional spatial discrete points of the three-dimensional spatial discrete point;

[0224] An optimization module 1740, configured to optimize the positions of the three-dimensional spatial discrete points through the smoothed positions of the three-dimensional spatial discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model;

[0225] A blood flow rendering module 1750, configured to perform a rendering process on the optimized blood flow surface mesh model in response to a user-triggered blood flow rendering operation to obtain a blood flow rendering image;

[0226] A fusion module 1760, configured to perform a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image.

[0227] In one embodiment, the blood flow surface mesh model determination module 1720 is specifically configured to:

[0228] Obtain each three-dimensional spatial discrete point in the target blood vessel region according to the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters;

[0229] Use each three-dimensional spatial discrete point and the neighborhood three-dimensional spatial discrete points of each three-dimensional spatial discrete point to obtain an initial blood flow surface mesh model;

[0230] For any blood flow surface mesh in the initial blood flow surface mesh model, set the attributes of the blood flow surface mesh based on the attributes of the three-dimensional spatial discrete points of the blood flow surface mesh to obtain the blood flow surface mesh model, where the attributes of the blood flow surface mesh include the colors of the three-dimensional spatial discrete points and the normal vector of the blood flow surface mesh, and the attributes of any three-dimensional spatial discrete point include an index and a three-dimensional spatial discrete point vector.

[0231] In one embodiment, when the blood flow surface mesh model determination module 1720 executes the step of obtaining each three-dimensional spatial discrete point in the target blood vessel region according to the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters, it is specifically configured to:

[0232] Based on the Doppler blood flow image of the target blood vessel region, obtain each two-dimensional spatial discrete point in the target blood vessel region;

[0233] Respectively determine the target hemodynamic parameter in the hemodynamic parameters of each two-dimensional spatial discrete point as the vertical coordinate of each two-dimensional spatial discrete point to obtain each three-dimensional spatial discrete point.

[0234] In one embodiment, the blood flow surface mesh model determination module 1720 executes obtaining an initial blood flow surface mesh model by using the three-dimensional space discrete points and the neighborhood three-dimensional space discrete points of the three-dimensional space discrete points, specifically for:

[0235] For any one of the three-dimensional space discrete points, traverse each of the three-dimensional space discrete points in the target neighborhood of the three-dimensional space discrete point to determine whether there is a blood flow point among the three-dimensional space discrete points in the target neighborhood;

[0236] If it is determined that there is a blood flow point, generate a patch of a specified shape by using the target three-dimensional space discrete point in the target neighborhood and the three-dimensional space discrete point, where the target three-dimensional space discrete point is each of the three-dimensional space discrete vertices in the target neighborhood;

[0237] If it is determined that there is no blood flow point, generate the patch of the specified shape by using each of the three-dimensional space discrete points in the target neighborhood and the three-dimensional space discrete point respectively;

[0238] Obtain the initial blood flow surface mesh model based on the patches of the specified shape corresponding to the three-dimensional space discrete points.

[0239] In one embodiment, the blood flow surface mesh model determination module 1720 executes setting the attribute of any blood flow surface mesh in the initial blood flow surface mesh model based on the attributes of the discrete points of the blood flow surface mesh to obtain the blood flow surface mesh, specifically for:

[0240] For any one of the three-dimensional space discrete points in any one of the blood flow surface meshes, use the correspondence between the index and color of the preset three-dimensional space discrete points to determine the target color corresponding to the index of the three-dimensional space discrete point, and set the color of the three-dimensional space discrete point to the target color; and,

[0241] For any one of the blood flow surface meshes, perform interpolation processing on the vectors of the three-dimensional space discrete points in the blood flow surface mesh to obtain the normal vector of the blood flow surface mesh.

[0242] In one embodiment, the smoothing module 1730 is specifically for:

[0243] For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, obtain the distance between the three-dimensional space discrete point and the adjacent three-dimensional space discrete point based on the position coordinates of the three-dimensional space discrete point and the position coordinates of the adjacent three-dimensional space discrete point;

[0244] Based on the distances between the three-dimensional space discrete points and their respective adjacent three-dimensional space discrete points, the weights of the respective adjacent three-dimensional space discrete points are obtained respectively;

[0245] Based on the weights of the adjacent three-dimensional space discrete points and the position coordinates of the three-dimensional space discrete points, the smoothed position of the three-dimensional space discrete point is obtained.

[0246] In one embodiment, the smoothing module 1730 executes the operation of obtaining the weights of the respective adjacent three-dimensional space discrete points based on the distances between the three-dimensional space discrete points and their respective adjacent three-dimensional space discrete points, and specifically is used for:

[0247] For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, the reciprocal of the distance between the adjacent three-dimensional space discrete point and the three-dimensional space discrete point is determined as the weight of the adjacent three-dimensional space discrete point;

[0248] The operation of obtaining the smoothed position of the three-dimensional space discrete point based on the weights of the adjacent three-dimensional space discrete points and the position coordinates of the three-dimensional space discrete point includes:

[0249] For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, the position coordinates of the adjacent three-dimensional space discrete point are multiplied by the weight of the adjacent three-dimensional space discrete point to obtain a first intermediate position coordinate;

[0250] The first intermediate position coordinates of the respective adjacent three-dimensional space discrete points are added correspondingly to obtain a second intermediate position coordinate;

[0251] The second intermediate position coordinate is divided by the target weight to obtain the smoothed position of the three-dimensional space discrete point, where the target weight is obtained by adding the weights of the respective adjacent three-dimensional space discrete points.

[0252] In one embodiment, the fusion module 1760 is specifically used for:

[0253] For any pixel point in the blood flow rendering image, based on the three-dimensional position coordinates of the pixel point, the transparency of the pixel point is obtained;

[0254] Using the transparency of the pixel point and the blood flow rendering color of the pixel point in the blood flow rendering image, the target rendering color of the pixel point is determined; and,

[0255] Based on the transparency of the pixel point and the image intensity of the pixel point in the B-mode ultrasound examination ultrasound image, the target intensity of the pixel point is obtained;

[0256] Obtain the fused display color based on the target rendering color and the target intensity of the pixel point;

[0257] Based on the fused display color of each pixel point of the blood flow rendering image, obtain the target blood flow image.

[0258] After introducing an imaging method and device for ultrasonic blood flow according to an exemplary embodiment of the present disclosure, next, an electronic device according to another exemplary embodiment of the present disclosure will be introduced.

[0259] Those skilled in the art can understand that various aspects of the present disclosure can be implemented as a system, method, or program product. Therefore, various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which can be collectively referred to as "circuit", "module", or "system" here.

[0260] In some possible embodiments, the electronic device according to the present disclosure may at least include at least one processor and at least one computer storage medium. Among them, the computer storage medium stores program code, and when the program code is executed by the processor, the processor executes the steps in the imaging method of ultrasonic blood flow according to various exemplary embodiments of the present disclosure described above in this specification. For example, the processor can execute steps 201-206 as shown in Figure 2 shown in.

[0261] Next, refer to Figure 18 to describe the electronic device 1800 according to this embodiment of the present disclosure. Figure 18 The illustrated electronic device 1800 is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0262] As Figure 18 shown, the electronic device 1800 is presented in the form of a general-purpose electronic device. The components of the electronic device 1800 may include but are not limited to: the above-mentioned at least one processor 1801, the above-mentioned at least one computer storage medium 1802, and a bus 1803 connecting different system components (including the computer storage medium 1802 and the processor 1801).

[0263] The bus 1803 represents one or more of several types of bus structures, including a computer storage medium bus or a computer storage medium controller, a peripheral bus, a processor, or a local bus using any bus structure in a variety of bus structures.

[0264] Computer storage medium 1802 may include a readable medium in the form of volatile computer storage media, such as random access computer storage medium (RAM) 1821 and / or cache storage medium 1822, and may further include read only computer storage medium (ROM) 1823.

[0265] Computer storage medium 1802 may also include a program / utilities 1825 having a set (at least one) of program modules 1824. Such program modules 1824 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0266] Electronic device 1800 may also communicate with one or more external devices 1804 (such as a keyboard, pointing device, etc.), may also communicate with one or more devices that enable a user to interact with electronic device 1800, and / or may communicate with any device that enables the electronic device 1800 to communicate with one or more other electronic devices (such as a router, modem, etc.). Such communication may be through an input / output (I / O) interface 1805. Also, electronic device 1800 may communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 1806. As shown, network adapter 1806 communicates with other modules for electronic device 1800 through bus 1803. It should be understood that although not shown in the figure, other hardware and / or software modules may be used in conjunction with electronic device 1800, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0267] In some possible implementation manners, various aspects of an ultrasonic blood flow imaging method provided by the present disclosure may also be implemented in the form of a program product, which includes program code. When the program product runs on a computer device, the program code is used to cause the computer device to execute the steps in the ultrasonic blood flow imaging method according to various exemplary implementation manners of the present disclosure described above in this specification.

[0268] The program product can adopt any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access computer storage medium (RAM), a read-only computer storage medium (ROM), an erasable programmable read-only computer storage medium (EPROM or flash memory), an optical fiber, a portable compact disk read-only computer storage medium (CD-ROM), an optical computer storage medium, a magnetic computer storage medium, or any suitable combination of the above.

[0269] The program product for ultrasonic blood flow imaging according to the embodiments of the present disclosure can adopt a portable compact disk read-only computer storage medium (CD-ROM) and include program code, and can run on an electronic device. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0270] The readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable signal medium can also be any readable medium other than the readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0271] The program code contained on the readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination of the above.

[0272] Program code for performing the operations of the present disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's electronic device, partially on the user's device, executed as a stand-alone 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 a remote electronic device, the remote electronic device can be connected to the user's electronic device through any type of network including a local area network (LAN) or a wide area network (WAN), or, alternatively, can be connected to an external electronic device (e.g., through the Internet using an Internet service provider).

[0273] It should be noted that although several modules of the apparatus are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more of the above-described modules 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.

[0274] In addition, although the operations of the method of the present disclosure are described in a specific order in the drawings, this does not require or imply that the 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, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution.

[0275] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, a system, or a computer program product. Therefore, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic computer storage media, CD-ROM, optical computer storage media, etc.) containing computer-usable program code.

[0276] This disclosure is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the disclosure. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a means for implementing the functions specified in one or more flows of the flowchart and / or one or more blocks of the block diagram.

[0277] These computer program instructions can also be stored in a computer-readable computer storage medium that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable computer storage medium produce a manufactured article including an instruction means that implements the functions specified in one or more flows of the flowchart and / or one or more blocks of the block diagram.

[0278] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more flows of the flowchart and / or one or more blocks of the block diagram.

[0279] Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from the spirit and scope of this disclosure. Thus, if these modifications and variations of this disclosure fall within the scope of the claims of this disclosure and their equivalent technologies, this disclosure is also intended to include these modifications and variations.

Claims

1. An imaging method for ultrasonic blood flow, characterized in that, The method includes: In response to a vascular region setting operation triggered by a user, determining a target vascular region in a B-mode ultrasound examination image of biological tissue based on the vascular region setting operation; Using the Doppler blood flow image and hemodynamic parameters of the target vascular region to obtain a blood flow surface mesh model corresponding to the target vascular region; For any three-dimensional spatial discrete point in the blood flow surface mesh model, obtaining the smoothed position of the three-dimensional spatial discrete point according to the position of the three-dimensional spatial discrete point and the positions of its adjacent three-dimensional spatial discrete points; Optimizing the positions of the three-dimensional spatial discrete points through the smoothed positions of the three-dimensional spatial discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model; In response to a blood flow rendering operation triggered by a user, performing a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendering image; Performing a fusion process on the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image.

2. The method according to claim 1, wherein The using the Doppler blood flow image and hemodynamic parameters of the target vascular region to obtain a blood flow surface mesh model corresponding to the target vascular region includes: Obtaining each three-dimensional spatial discrete point in the target vascular region according to the Doppler blood flow image of the target vascular region and the hemodynamic parameters; Using each three-dimensional spatial discrete point and its neighborhood three-dimensional spatial discrete points to obtain an initial blood flow surface mesh model; For any blood flow surface mesh in the initial blood flow surface mesh model, setting the attributes of the blood flow surface mesh based on the attributes of the three-dimensional spatial discrete points of the blood flow surface mesh to obtain the blood flow surface mesh model, where the attributes of the blood flow surface mesh include the colors of the three-dimensional spatial discrete points and the normal vector of the blood flow surface mesh, and the attributes of any three-dimensional spatial discrete point include an index and a three-dimensional spatial discrete point vector.

3. The method according to claim 2, wherein The obtaining each three-dimensional spatial discrete point in the target vascular region according to the Doppler blood flow image of the target vascular region and the hemodynamic parameters includes: Based on the Doppler blood flow image of the target vascular region, obtaining each two-dimensional spatial discrete point in the target vascular region; Determining the target hemodynamic parameter in the hemodynamic parameters of each two-dimensional spatial discrete point as the vertical coordinate of each two-dimensional spatial discrete point to obtain each three-dimensional spatial discrete point.

4. The method according to claim 2, wherein The using each three-dimensional spatial discrete point and its neighborhood three-dimensional spatial discrete points to obtain an initial blood flow surface mesh model includes: For any three-dimensional spatial discrete point, traversing each three-dimensional spatial discrete point in the target neighborhood of the three-dimensional spatial discrete point to determine whether there is a blood flow point among the three-dimensional spatial discrete points in the target neighborhood; If it is determined that there is a blood flow point, generating a patch of a specified shape from the target three-dimensional spatial discrete point in the target neighborhood and the three-dimensional spatial discrete point, where the target three-dimensional spatial discrete point is each three-dimensional spatial discrete vertex in the target neighborhood; If it is determined that there is no blood flow point, each three-dimensional space discrete point in the target neighborhood is respectively used to generate a patch of the specified shape with the three-dimensional space discrete point; Based on the patches of the specified shape corresponding to each three-dimensional space discrete point, the initial blood flow surface mesh model is obtained.

5. The method according to claim 2, characterized in that, For any blood flow surface mesh in the initial blood flow surface mesh model, setting the attributes of the blood flow surface mesh based on the attributes of the discrete points of the blood flow surface mesh to obtain the blood flow surface mesh includes: For any three-dimensional space discrete point in any blood flow surface mesh, using the preset correspondence between the index and color of the three-dimensional space discrete point, determining the target color corresponding to the index of the three-dimensional space discrete point, and setting the color of the three-dimensional space discrete point to the target color; and, For any blood flow surface mesh, performing interpolation processing on the vectors of the discrete points in the blood flow surface mesh to obtain the normal vector of the blood flow surface mesh.

6. The method according to claim 1, characterized in that, The obtaining of the smoothed position of the three-dimensional space discrete point according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point includes: For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, based on the position coordinates of the three-dimensional space discrete point and the position coordinates of the adjacent three-dimensional space discrete point, obtaining the distance between the three-dimensional space discrete point and the adjacent three-dimensional space discrete point; According to the distances between the three-dimensional space discrete point and the respective adjacent three-dimensional space discrete points, respectively obtaining the weights of the respective adjacent three-dimensional space discrete points; Obtaining the smoothed position of the three-dimensional space discrete point through the weights of the adjacent three-dimensional space discrete points and the position coordinates of the adjacent three-dimensional space discrete points.

7. The method according to claim 6, wherein The obtaining of the weights of the respective adjacent three-dimensional space discrete points according to the distances between the three-dimensional space discrete point and the respective adjacent three-dimensional space discrete points includes: For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, determining the reciprocal of the distance between the adjacent three-dimensional space discrete point and the three-dimensional space discrete point as the weight of the adjacent three-dimensional space discrete point; The obtaining of the smoothed position of the three-dimensional space discrete point through the weights of the adjacent three-dimensional space discrete points and the position coordinates of the adjacent three-dimensional space discrete points includes: For any adjacent three-dimensional space discrete point of the three-dimensional space discrete point, multiplying the position coordinates of the adjacent three-dimensional space discrete point by the weight of the adjacent three-dimensional space discrete point to obtain a first intermediate position coordinate; Correspondingly adding the first intermediate position coordinates of the respective adjacent three-dimensional space discrete points to obtain a second intermediate position coordinate; Dividing the second intermediate position coordinate by the target weight to obtain the smoothed position of the three-dimensional space discrete point, where the target weight is obtained by adding the weights of the respective adjacent three-dimensional space discrete points.

8. The method according to any one of claims 1 to 7, characterized in that, The fusion processing of the blood flow rendering image and the B-mode ultrasound examination image to obtain a target blood flow image includes: For any pixel point in the blood flow rendered image, based on the three-dimensional position coordinates of the pixel point, obtain the transparency of the pixel point; Use the transparency of the pixel point and the blood flow rendering color of the pixel point in the blood flow rendered image to determine the target rendering color of the pixel point; and, According to the transparency of the pixel point and the image intensity of the pixel point in the B-mode ultrasound examination image, obtain the target intensity of the pixel point; Obtain the fused display color through the target rendering color of the pixel point and the target intensity of the pixel point; Based on the fused display colors of the pixel points in the blood flow rendered image, obtain the target blood flow image.

9. An electronic device, characterized in that, Includes a storage unit and a processor, where: The storage unit is configured to store B-mode ultrasound examination images of biological tissues; The processor is configured to: In response to a user-triggered blood vessel region setting operation, determine a target blood vessel region in the B-mode ultrasound examination image of the biological tissue based on the blood vessel region setting operation; Use the Doppler blood flow image of the target blood vessel region and hemodynamic parameters to obtain a blood flow surface mesh model corresponding to the target blood vessel region; For any three-dimensional space discrete point in the blood flow surface mesh model, according to the position of the three-dimensional space discrete point and the positions of the adjacent three-dimensional space discrete points of the three-dimensional space discrete point, obtain the smoothed position of the three-dimensional space discrete point; Optimize the positions of the three-dimensional space discrete points through the smoothed positions of the three-dimensional space discrete points in the blood flow surface mesh model to obtain an optimized blood flow surface mesh model; In response to a user-triggered blood flow rendering operation, perform a rendering process on the optimized blood flow surface mesh model to obtain a blood flow rendered image; Perform a fusion process on the blood flow rendered image and the B-mode ultrasound examination image to obtain a target blood flow image.

10. The electronic device according to claim 9, wherein When the processor executes the operation of using the Doppler blood flow image of the target blood vessel region and hemodynamic parameters to obtain a blood flow surface mesh model corresponding to the target blood vessel region, it is specifically configured to: According to the Doppler blood flow image of the target blood vessel region and the hemodynamic parameters, obtain each three-dimensional space discrete point in the target blood vessel region; Use each three-dimensional space discrete point and the neighborhood three-dimensional space discrete points of each three-dimensional space discrete point to obtain an initial blood flow surface mesh model; For any blood flow surface mesh in the initial blood flow surface mesh model, set the attributes of the blood flow surface mesh based on the attributes of the three-dimensional space discrete points of the blood flow surface mesh to obtain the blood flow surface mesh model, where the attributes of the blood flow surface mesh include the colors of the three-dimensional space discrete points and the normal vector of the blood flow surface mesh, and the attributes of any three-dimensional space discrete point include an index and a three-dimensional space discrete point vector.

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