Beam forming method and device, computer equipment and storage medium

Abstract

The invention relates to a beam forming method and device, computer equipment and a storage medium. The method comprises the following steps: carrying out region division on an ultrasonic echo signal of a target object to obtain a plurality of segmented regions; the plurality of segmented regions comprise important regions and non-important regions; according to a preset grid density ratio, performing grid division on each segmented region to obtain a grid point coordinate of each grid point in each segmented region; the grid density proportion represents the ratio of the grid density value of the important area to the grid density value of the non-important area in each segmented area; the grid density value of the important area is greater than that of the non-important area; and determining a beam forming result of the ultrasonic echo signal according to the grid point coordinate of each grid point. By adopting the method, the diagnosis precision can be improved under the condition of not wasting computing power resources.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a beamforming method, apparatus, computer device and storage medium. Background Art

[0002] In ultrasound examinations, in order to improve the diagnostic effect, the images are usually made as delicate, full and show more details as possible.

[0003] In related technologies, the degree of image detail is directly related to the density of the beamforming grid in the ultrasound imaging link. The denser the beamforming grid, the finer the image and the greater the computing power consumption. Since beamforming is the main computing power consumption module of the ultrasound imaging link, in the case of limited computing power resources, ultrasound manufacturers often make full use of computing power to make the computing grid of the entire image as dense as possible to further improve the resolution of image details. However, this approach actually results in a waste of computing power resources, as it is diagnosis-oriented.

[0004] Therefore, how to improve diagnostic accuracy without wasting computing resources has become a pressing issue to be solved. Summary of the invention

[0005] Based on this, it is necessary to provide a beamforming method, device, computer equipment and storage medium to address the above technical problems, which can improve diagnostic accuracy without wasting computing resources.

[0006] In a first aspect, an embodiment of the present application provides a beamforming method, including:

[0007] Performing regional division on the ultrasonic echo signal of the target object to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions;

[0008] According to the preset grid density ratio, each segmented area is grid-divided to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area;

[0009] According to the grid point coordinates of each grid point, the beamforming result of the ultrasonic echo signal is determined.

[0010] In one embodiment, each segmented area is grid-divided according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area, including:

[0011] Determine the number of grid points in each segmented region according to the area and grid density ratio of each segmented region;

[0012] Each segmented area is divided into grids according to the number of grid points in each segmented area, and the grid point coordinates of each grid point in each segmented area are obtained.

[0013] In one embodiment, determining the number of grid points of each segmented region according to the area and grid density ratio of each segmented region includes:

[0014] According to the area and grid density ratio of each segmented area, determine the proportion of grid points in important areas and the proportion of grid points in unimportant areas;

[0015] Determine the number of grid points in important areas based on the proportion of grid points in important areas, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value;

[0016] Determine the number of grid points in each non-important area based on the proportion of grid points in the non-important area, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value;

[0017] The number of grid points in the important area and the number of grid points in the unimportant area are determined as the number of grid points in each segmented area.

[0018] In one embodiment, determining the beamforming result of the ultrasonic echo signal according to the grid point coordinates of each grid point includes:

[0019] According to the grid point coordinates of each grid point, beam synthesis is performed on each segmented area to obtain the beam synthesis result of each segmented area;

[0020] The beamforming results of each segmented area are fused to obtain the beamforming result of the ultrasonic echo signal.

[0021] In one of the embodiments, the beam synthesis results of each segmented area include the beam synthesis results of the important area and the beam synthesis results of the unimportant area; the beam synthesis results of each segmented area are subjected to signal fusion to obtain the beam synthesis results of the ultrasonic echo signal, including:

[0022] Re-dividing the grid of the non-important area according to the grid points of the important area, obtaining a plurality of updated grid points of the non-important area and updated grid point coordinates of each updated grid point;

[0023] Determine an updated beamforming result of a non-important area according to updated grid point coordinates of each updated grid point;

[0024] The updated beamforming result of the non-important area is fused with the beamforming result of the important area to obtain the beamforming result of the ultrasonic echo signal.

[0025] In one embodiment, determining the updated beamforming result of the non-important area according to the updated grid point coordinates of each updated grid point includes:

[0026] According to the coordinates of each updated grid point, a plurality of original grid points corresponding to each updated grid point are obtained;

[0027] An updated beamforming result of the non-important area is determined according to the beamforming result of the non-important area and each original grid point.

[0028] In one embodiment, determining an updated beamforming result of the non-important area according to the beamforming result of the non-important area and each original grid point includes:

[0029] According to the beamforming results of the non-important area, the beamforming value of each original grid point is obtained;

[0030] Determine the beamforming value of each updated grid point according to the beamforming value of each original grid point;

[0031] The beamforming value of each updated grid point is determined as the updated beamforming result of the non-important area.

[0032] In a second aspect, an embodiment of the present application further provides a beamforming device, including:

[0033] A region division module is used to divide the ultrasonic echo signal of the target object into regions to obtain multiple segmented regions; the multiple segmented regions include important regions and non-important regions;

[0034] A grid division module is used to grid each segmented area according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area;

[0035] The beamforming module is used to determine the beamforming result of the ultrasonic echo signal according to the grid point coordinates of each grid point.

[0036] In a third aspect, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps in any one of the embodiments of the first aspect when executing the computer program.

[0037] In a fourth aspect, the embodiments of the present application further provide a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in any one of the embodiments of the first aspect are implemented.

[0038] In a fifth aspect, the embodiments of the present application further provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps in any one of the embodiments in the first aspect are implemented.

[0039] The beam synthesis method, device, computer equipment and storage medium provided in the embodiments of the present application perform regional segmentation on the ultrasonic echo signal of the target object to obtain multiple segmented areas, and then grid each segmented area according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area, and then determine the beam synthesis result of the ultrasonic echo signal according to the grid point coordinates of each grid point, wherein the multiple segmented areas include important areas and unimportant areas; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each of the segmented areas, and the grid density value of the important area is greater than the grid density value of the unimportant area. In the method, after acquiring the ultrasonic echo signal of the target object, the ultrasonic echo signal is first divided into regions to obtain multiple segmented regions, and then each segmented region is gridded based on a preset grid density ratio, and the grid density ratio is the ratio between the grid density value of the important region and the grid density value of the unimportant region in each segmented region, and the grid density value of the important region is set to be greater than the grid density value of the unimportant region. After the grid is divided based on the grid density ratio, the grid of the important region is denser and the grid of the unimportant region is sparser. In this way, under the condition that the overall computing power consumption remains unchanged, more computing power can be used for beam synthesis in the important region, and no waste of computing power will be caused. At the same time, the important region is more accurately beamformed because the grids are divided denser, thereby making the imaging quality of the important region higher, thereby improving the diagnostic accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 is an application environment diagram of a beamforming method in an embodiment;

[0042] Figure 2 is a schematic flow chart of a beamforming method in one embodiment;

[0043] Figure 3 is a schematic diagram of a segmented area in one embodiment;

[0044] Figure 4A schematic diagram of a process of meshing each segmented area in one embodiment;

[0045] Figure 5 A schematic diagram of a flow chart for determining the number of grid points in each segmented area in one embodiment;

[0046] Figure 6 A schematic diagram of a grid of an important area and a non-important area in one embodiment;

[0047] Figure 7 A schematic diagram of a process for determining a beamforming result in one embodiment;

[0048] Figure 8 is a schematic diagram of a flow chart of determining a beamforming result in another embodiment;

[0049] Fig. 9 is a schematic diagram of a segmented area after the grid is re-divided in one embodiment;

[0050] Fig.10 A schematic diagram of a process for determining and updating a beamforming result in one embodiment;

[0051] Fig.11 is a schematic flow chart of a beamforming method in another embodiment;

[0052] Fig.12 is a schematic structural diagram of a beamforming device in one embodiment;

[0053] Fig.13 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] The technical background of the embodiments of the present application is first described below.

[0056] In clinical ultrasound examinations, in order to improve the diagnostic effect, it is often hoped that the image is as delicate and full as possible and shows more details. This requirement is directly related to the density of the beamforming computing grid in the ultrasound imaging link: the denser the ultrasound beamforming grid, the more delicate the image will be, but it will cause a significant consumption of computing power. Since beamforming is the main computing power consumption module of the ultrasound imaging link, in the case of limited computing power resources, related technologies often make full use of computing power to make the computing grid of the entire image as dense as possible to further improve the resolution of image details, but diagnosis-oriented, this approach actually causes a waste of computing power resources.

[0057] During clinical ultrasound examinations, clinical examinations focus more on whether key organs have lesions than on the overall image style of ultrasound images. Therefore, compared to evenly distributing computing power over the entire image, if the beam synthesis grid can be made finer for the area of ​​interest and sparser for the area of ​​non-interest, the diagnostic value can be further improved while the overall computing power consumption remains unchanged.

[0058] Based on this, an embodiment of the present application provides a beam synthesis method. After acquiring the ultrasonic echo signal of the target object, the ultrasonic echo signal is first divided into regions to obtain multiple segmented regions, and then each segmented region is grid-divided based on a preset grid density ratio. The grid density ratio is the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented region. The grid density value of the important area is preset to be greater than the grid density value of the unimportant area. After dividing the grid based on the grid density ratio, the grid of the important area is denser and the grid of the unimportant area is sparser. In this way, under the condition that the overall computing power consumption remains unchanged, more computing power can be used for beam synthesis of important areas, and no waste of computing power will be caused. At the same time, because the important areas are divided into denser grids, the beam synthesis results of the important areas are more accurate, thereby making the imaging quality of the important areas higher, thereby improving the diagnostic accuracy.

[0059] It should be noted that the beneficial effects brought about by the embodiments of the present application or the technical problems solved are not limited to this one, but may also include other implicit or related problems. For details, please refer to the description of the following embodiments.

[0060] The following describes the application environment of the beamforming method provided in the embodiment of the present application, which can be applied to: Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. Optionally, the server 104 can be a server connected to a medical ultrasound device, and the medical ultrasound device includes a probe for collecting ultrasonic echo signals, and the medical ultrasound device can also be connected to the terminal 102 for display. After the probe collects the ultrasonic echo signal of the target object in the medical ultrasound device, the server performs beam synthesis on the collected ultrasonic echo signal. Among them, the terminal 102 can be used to display the beam synthesis results, and can also display the ultrasonic image generated based on the beam synthesis results. Among them, the terminal 102 can be but not limited to various personal computers, laptops, smart phones, tablet computers, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers. In addition, the server 104 can also be integrated on the medical ultrasound device.

[0061] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0062] In an exemplary embodiment, Figure 2 As shown, a beam synthesis method is provided, which is applied to Figure 1 The server 104 in the example is used as an example to illustrate, including the following steps 201 to 203. Among them:

[0063] S201, dividing the ultrasonic echo signal of the target object into regions to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and unimportant regions.

[0064] Among them, the ultrasonic echo signal refers to the signal sent by the ultrasonic probe to the target object and received by the target object.

[0065] In the embodiment of the present application, the server acquires an ultrasonic echo signal of the target object collected by an ultrasonic probe, and processes the ultrasonic echo signal to obtain a plurality of segmented regions.

[0066] In one possible implementation, the ultrasonic echo signal of the target object can be divided into regions through a segmentation model to obtain multiple segmented regions. For example, the ultrasonic echo signal of the target object is input into a pre-trained segmentation model to obtain multiple segmented regions output by the segmentation model. The segmentation model is trained based on multiple historical ultrasonic echo signals and the segmentation results of each historical ultrasonic echo signal. The segmented regions include important regions and non-important regions, which can be regions where organs are located and regions where organs are not located, or lesion regions and non-lesion regions, etc. Figure 3 As shown, the segmented areas are divided, where A is an important area and B is a non-important area.

[0067] This embodiment performs regional segmentation on the ultrasonic echo signal mainly in order to be able to distinguish in advance the important parts closely related to the diagnosis based on the ultrasonic echo signal, so as to perform special processing on the important parts to improve the imaging quality of the important parts and thus improve the diagnostic accuracy.

[0068] S202, gridding each segmented area according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area.

[0069] Among them, the grid density ratio is the ratio between the grid density value of the important area and the grid density of the unimportant area in each segmented area. The grid density ratio can be set by the user according to actual needs. For example, in order to make the imaging quality of important areas such as lesions higher, the grid density value of the important area can be set to be greater than the grid density value of the unimportant area. In this way, the grids in the important areas are denser and the grids in the unimportant areas are sparser. After the ultrasonic echo signal is beamformed, the imaging quality of the important areas in the image generated based on the result of beamformation is higher, thereby improving the diagnostic accuracy. Among them, the grid density value refers to the number of grids per unit area or unit volume. When the grid density value increases, it means that the number of grids increases in the same area or volume, that is, the grid becomes denser.

[0070] In an embodiment of the present application, each segmented area is gridded based on a preset grid density ratio. In one embodiment, the number of grid points in the important area and the number of grid points in the unimportant area can be determined respectively according to the area of ​​the important area and the area of ​​the unimportant area in each segmented area, combined with the grid density ratio, and then the important area is gridded according to the number of grid points in the important area, and the unimportant area is gridded according to the number of grid points in the unimportant area. After the grids are divided, the grid point coordinates of each grid point in the important area and the grid point coordinates of each grid point in the unimportant area are obtained. Among them, when the important area is gridded according to the number of grid points in the important area, the important area can be directly divided evenly according to the number of grid points in the important area. Similarly, when the unimportant area is gridded according to the number of grid points in the unimportant area, the unimportant area can also be directly divided evenly according to the number of grid points in the unimportant area.

[0071] S203, determining the beamforming result of the ultrasonic echo signal according to the grid point coordinates of each grid point.

[0072] After obtaining the grid point coordinates of each grid point in each segmented area, the beam synthesis result of each segmented area can be calculated respectively according to the grid point coordinates, and then based on the beam synthesis result of each segmented area, the beam synthesis result of the entire ultrasonic echo signal can be obtained.

[0073] In the embodiment of the present application, a suitable beam synthesis method can be selected according to actual needs, such as a linear array method, a convex array method, a Doppler method or a phased array method, etc. The selected beam synthesis method is used to process the channel echo data in combination with the grid point coordinates of each grid point in each segmented area to obtain the beam synthesis results of each segmented area, and then the beam synthesis results of each segmented area are processed to obtain the beam synthesis results of the ultrasonic echo signal.

[0074] After obtaining the beamforming result of the ultrasonic echo signal, the ultrasonic image of the target object is further obtained through filtering processing, time gain compensation, envelope detection, secondary sampling, compression and other processes.

[0075] In the image reconstruction method provided in the embodiment of the present application, the ultrasonic echo signal of the target object is segmented into regions to obtain a plurality of segmented regions, and then each segmented region is gridded according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented region, and then the beam synthesis result of the ultrasonic echo signal is determined according to the grid point coordinates of each grid point, wherein the plurality of segmented regions include important regions and unimportant regions; the grid density ratio represents the ratio between the grid density value of the important region and the grid density value of the unimportant region in each of the segmented regions, and the grid density value of the important region is greater than the grid density value of the unimportant region. In the method, after acquiring the ultrasonic echo signal of the target object, the ultrasonic echo signal is first divided into regions to obtain multiple segmented regions, and then each segmented region is gridded based on a preset grid density ratio, and the grid density ratio is the ratio between the grid density value of the important region and the grid density value of the unimportant region in each segmented region. The grid density value of the important region is preset to be greater than the grid density value of the unimportant region. After the grid is divided based on the grid density ratio, the grid of the important region is denser and the grid of the unimportant region is sparser. In this way, under the condition that the overall computing power consumption remains unchanged, more computing power can be used for beam synthesis in the important region, and no waste of computing power will be caused. At the same time, the important region is more accurately beamformed because the grids are denser, thereby making the imaging quality of the important region higher, thereby improving the diagnostic accuracy.

[0076] Based on the above embodiment, an embodiment is provided to illustrate the process of dividing each segmented area into grids.

[0077] In an exemplary embodiment, Figure 4 As shown, each segmented area is grid-divided according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area, including:

[0078] S301, determining the number of grid points of each segmented region according to the area of ​​each segmented region and the ratio of the grid density.

[0079] In an embodiment of the present application, based on the obtained grid density ratio, the number of grid points in the important area and the number of grid points in the unimportant area are determined in combination with the area of ​​each segmented area, and the corresponding area is gridded based on each number of grid points. Among them, the number of grid points in the important area is greater than the number of grid points in the unimportant area. After the grid division, the grids in the important area are denser, and the grids in the unimportant area are sparser.

[0080] In one embodiment, Figure 5 As shown, the process of determining the number of grid points in each segmented area may include:

[0081] S401, determining the proportion of grid points in important areas and the proportion of grid points in unimportant areas according to the area and grid density ratio of each segmented area.

[0082] The proportion of grid points in important areas refers to the proportion of grid points in important areas to the total number of grid points. The proportion of grid points in non-important areas refers to the proportion of grid points in non-important areas to the total number of grid points.

[0083] In the embodiment of the present application, the proportion of grid points in the important area and the proportion of grid points in the unimportant area can be determined based on the area of ​​the important area, the area of ​​the unimportant area, and the ratio of grid density. For example, the proportion of grid points in the important area and the proportion of grid points in the unimportant area can be determined based on the following formulas (1) and (2).

[0084] (1)

[0085] (2)

[0086] in, is the grid density ratio; The area of ​​the region that is the important area; The area of ​​the region is not a significant area; is the proportion of grid points in important areas; is the proportion of grid points in non-important areas.

[0087] S402, determining the number of grid points in the important area according to the proportion of the number of grid points in the important area, the total beamforming computing power consumption value and the single-point beamforming computing power consumption value.

[0088] The total computing power consumption value of beamforming refers to the total computing power resources required to complete the beamforming operation, and the computing power consumption value of single-point beamforming refers to the computing power resources required to complete the beamforming operation of one grid point.

[0089] Based on the proportion of grid points in the above important areas and the beamforming computing power consumption, the number of grid points in the important areas is determined. For example, the following formula (3) can be used to determine the number of grid points in the important areas based on the proportion of grid points in the important areas, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value.

[0090] (3)

[0091] in, is the number of grid points in the important area; is the total computing power consumption of beamforming; It is the computing power consumption value of single-point beamforming.

[0092] S403, determining the number of grid points in each non-important area according to the proportion of grid points in the non-important area, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value.

[0093] S404: Determine the number of grid points in the important area and the number of grid points in the unimportant area as the number of grid points in each segmented area.

[0094] Based on the proportion of grid points in the above non-important areas and the beamforming computing power consumption, the number of grid points in the non-important areas is determined. For example, the following formula (4) can be used to determine the number of grid points in the non-important areas based on the proportion of grid points in the non-important areas, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value.

[0095] (4)

[0096] in, is the number of grid points in the non-important area.

[0097] After obtaining the number of grid points in the important area and the number of grid points in the unimportant area, the number of grid points in the important area and the number of grid points in the unimportant area are directly determined as the grid point data of each segmented area. It should be noted that the above steps S402 and S403 can also be performed simultaneously, that is, the number of grid points in the important area and the number of grid points in the unimportant area are determined at the same time, which is not limited to the above example.

[0098] In this embodiment, based on the regional area of ​​important areas and the regional area of ​​unimportant areas, combined with the grid density ratio, the proportion of grid points in important areas and the proportion of grid points in unimportant areas are quickly determined. Therefore, based on the proportion of grid points in different areas, under the constraint of beamforming computing power resources, the number of grid points in important areas and the number of grid points in unimportant areas are quickly and accurately determined, making grid division more convenient and accurate, thereby improving the accuracy of beamforming.

[0099] S302, gridding each segmented area according to the number of grid points in each segmented area, and obtaining the grid point coordinates of each grid point in each segmented area.

[0100] After obtaining the number of grid points in the important area and the number of grid points in the unimportant area, the corresponding segmented areas are respectively grid-divided based on the number of grid points to quickly obtain the grid point coordinates of each grid point.

[0101] In practical applications, the important areas can be evenly divided based on the number of grid points in the important areas, and the non-important areas can be evenly divided based on the number of grid points in the non-important areas, and the grid point coordinates of each grid point can be obtained. Figure 6 As shown, the grids are divided based on the number of grid points in the important area and the unimportant area, wherein the grid division in the important area A is denser, while the grid division in the unimportant area B is sparser.

[0102] In the image reconstruction method provided in the embodiment of the present application, the number of grid points of each segmented area is determined according to the area and grid density ratio of each segmented area, and then each segmented area is grid-divided according to the number of grid points of each segmented area to obtain the grid point coordinates of each grid point in each segmented area. In this method, the number of grid points of different segmented areas is calculated according to the area of ​​the segmented area and the grid density ratio, and based on the number of grid points, each segmented area can be quickly grid-divided to obtain the grid point coordinates of each grid point, which provides a convenient and reliable way to quickly divide the grid, thereby improving the efficiency and accuracy of signal processing.

[0103] Based on the above embodiment, an embodiment is provided to illustrate the process of determining the beamforming result of the ultrasonic echo signal.

[0104] In an exemplary embodiment, Figure 7 As shown, according to the grid point coordinates of each grid point, the beamforming result of the ultrasonic echo signal is determined, including:

[0105] S501, performing beam synthesis on each segmented area according to the grid point coordinates of each grid point to obtain the beam synthesis result of each segmented area.

[0106] In the embodiment of the present application, the grid point coordinates of each grid point in the important area and the unimportant area are obtained, beam synthesis is performed for different segmented areas respectively, and the beam synthesis results of the different segmented areas are calculated.

[0107] Taking the important area as an example, first, according to the grid point coordinates and the position of the ultrasonic transducer, the propagation time (or delay) of the ultrasonic wave from the grid point to each transducer is calculated. Secondly, according to the calculated delay, the signal of each transducer is time-aligned so that all signals are phase-consistent during synthesis. Then, the time-aligned signals are weighted and summed according to the weights to obtain the synthesized signal. The above steps are repeated for all grid points in the important area to obtain the synthesized signal of each grid point in the important area.

[0108] S502, performing signal fusion on the beamforming results of each segmented area to obtain the beamforming result of the ultrasonic echo signal.

[0109] After the beamforming results of each segmented area are obtained, the beamforming results of each segmented area are subjected to signal fusion to obtain the beamforming results of the ultrasonic echo signal.

[0110] For example, the beamforming results under different grid densities are first converted to the same coordinate system to ensure that all beamforming results are aligned in time, frequency and other relevant parameters, and then all data are adjusted to the same grid density using resampling technology. After that, weights are assigned to the signals of each segmented area based on the quality, signal-to-noise ratio and other relevant indicators of each segmented area, and the signals of different segmented areas are synthesized into a single output signal using weighted averaging or other statistical merging methods.

[0111] In the image reconstruction method provided in the embodiment of the present application, beam synthesis is performed on each segmented area according to the grid point coordinates of each grid point to obtain the beam synthesis results of each segmented area, and then the beam synthesis results of each segmented area are signal fused to obtain the beam synthesis results of the ultrasonic echo signal. In this method, after gridding each segmented area, beam synthesis is first performed based on different segmented areas, and the beam synthesis results of different segmented areas are calculated respectively. On this basis, the beam synthesis results of the unsegmented areas are signal fused to synthesize the signals of different segmented areas into a single signal, providing an optional method for quickly determining the beam synthesis results, so as to quickly obtain a high-quality ultrasonic image based on the beam synthesis results, thereby improving the efficiency and accuracy of ultrasonic image generation.

[0112] Based on the above embodiment, an embodiment is provided to illustrate the process of determining the beamforming result.

[0113] In an exemplary embodiment, Figure 8 As shown, the beamforming results of each segmented area include the beamforming results of the important area and the beamforming results of the unimportant area; the beamforming results of each segmented area are subjected to signal fusion to obtain the beamforming results of the ultrasonic echo signal, including:

[0114] S601, re-dividing the grid of the non-important area according to the grid points of the important area, to obtain a plurality of updated grid points of the non-important area and updated grid point coordinates of each updated grid point.

[0115] In the embodiment of the present application, the non-important area is re-divided according to the grid points of the important area and the grid density of the important area, so that the grid density of the non-important area is consistent with the grid density of the important area, and the grid points after the re-division of the non-important area are obtained, that is, the updated grid points, and the updated grid point coordinates of each updated grid point are obtained. Fig. 9 As shown, the grid of the non-important area is re-divided into non-important areas, wherein the grid density of the non-important area B is consistent with the grid density of the important area A.

[0116] S602, determining an updated beamforming result of a non-important area according to the updated grid point coordinates of each updated grid point.

[0117] In one embodiment, Fig.10 As shown, the process of determining the updated beamforming result of the non-important area may include:

[0118] S701, according to the coordinates of each updated grid point, obtaining a plurality of original grid points corresponding to each updated grid point.

[0119] The beamforming results of each segmented area include the beamforming results of the important area and the beamforming results of the unimportant area. The original grid points refer to the grid points before the unimportant area is re-divided.

[0120] In an embodiment of the present application, distance calculation can be performed based on the coordinates of each updated grid point and the coordinates of each original grid point in a non-important area to determine a plurality of original grid points corresponding to each updated grid point, thereby solving the beam synthesis value of each updated grid point based on the beam synthesis value of the plurality of original grid points. For any updated grid point, the plurality of original grid points corresponding to the updated grid point may be the original grid points closest to the updated grid point. For example, for any updated grid point, the distance between the updated grid point and each original grid point is calculated based on the updated grid point coordinates of the updated grid point and the coordinates of each original grid point, and then based on the plurality of distances, a plurality of original grid points with the smallest distance to the updated grid point are determined, and the plurality of original grid points are the plurality of original grid points corresponding to the updated grid point.

[0121] S702, determining an updated beamforming result of the non-important area according to the beamforming result of the non-important area and each original grid point.

[0122] Based on the above multiple original grid points and in combination with the beam synthesis result of the non-important area, an updated beam synthesis result of the non-important area is determined to adjust the beam synthesis result of the non-important area to the same grid density as that of the important area.

[0123] In an embodiment of the present application, among the multiple original grid points corresponding to each updated grid point, the beam synthesis value of each original grid point can be obtained from the beam synthesis result of the non-important area, so as to solve the beam synthesis value of each updated grid point through the beam synthesis value of each original grid point, and thus obtain the updated beam synthesis result of the non-important area based on the beam synthesis value of each updated grid point.

[0124] In this embodiment, firstly, according to the coordinates of each updated grid point, multiple original grid points related to each updated grid point are obtained, and the updated beam synthesis results of the non-important area are determined based on the beam synthesis results of the original grid points, thereby providing a reliable method for quickly determining the updated beam synthesis results of the non-important area. On this basis, the updated beam synthesis results of the non-important area and the beam synthesis results of the important area are fused to quickly obtain the beam synthesis results of the ultrasonic echo signal, thereby improving the generation efficiency and accuracy of the ultrasonic image, and further improving the diagnostic accuracy.

[0125] In one embodiment, determining an updated beamforming result for a non-important area includes the following steps:

[0126] Step 1: Obtain the beamforming value of each original grid point according to the beamforming result of the non-important area.

[0127] The beam synthesis value of each original grid point refers to the synthesized signal value of each original grid point in the non-important area, and the synthesized signal value represents the echo signal strength or feature at each original grid point.

[0128] The beam synthesis result of the non-important area is the synthesized signal value of each original grid point. Therefore, the beam synthesis value of each original grid point is directly obtained from the beam synthesis result of the non-important area.

[0129] Step 2: Determine the beamforming value of each updated grid point according to the beamforming value of each original grid point.

[0130] In the embodiment of the present application, a linear interpolation method may be used to determine the beam synthesis value of each updated grid point according to the beam synthesis value of each original grid point. For example, for any updated grid point, the beam synthesis values ​​of multiple original points corresponding to the updated grid point are used as the values ​​of the known data points, the beam synthesis value of the updated grid point is used to determine the value of the unknown data point, and the linear interpolation method is used to derive the beam synthesis value of the updated grid point.

[0131] Step 3: Determine the beamforming value of each updated grid point as the updated beamforming result of the non-important area.

[0132] After the beamforming value of each update grid point is determined, the beamforming value of each update grid point is determined as the update beamforming result of the non-important area.

[0133] In this embodiment, the beam synthesis value of each original grid point in the non-important area is obtained from the beam synthesis result of the non-important area, so that for any updated grid point, the beam synthesis value of the updated grid point can be quickly derived based on the beam synthesis value of the original grid point corresponding to the updated grid point, thereby quickly obtaining the updated beam synthesis result of the non-important area, providing data support for determining the beam synthesis result of the ultrasonic echo signal, so as to quickly and accurately obtain the final beam synthesis result, and lay the foundation for obtaining high-quality ultrasonic images.

[0134] S603: Fusing the updated beamforming result of the non-important area with the beamforming result of the important area to obtain the beamforming result of the ultrasonic echo signal.

[0135] After obtaining the updated beamforming results of the non-important areas, the updated beamforming results of the non-important areas and the beamforming results of the important areas are fused to obtain the beamforming results of the ultrasonic echo signals. For example, the updated beamforming results of the non-important areas and the beamforming results of the important areas can be weighted averaged according to the confidence or weight of the updated beamforming results of the non-important areas and the beamforming results of the important areas to obtain the beamforming results of the ultrasonic echo signals. The weight can be determined according to factors such as signal strength, signal-to-noise ratio, and beamforming gain.

[0136] It is understandable that in order to obtain more accurate beamforming results, the fused signal may be filtered, normalized, and subjected to quality assessment (such as signal-to-noise ratio, resolution, etc.) to ensure the reliability of the fusion result.

[0137] In the image reconstruction method provided in the embodiment of the present application, the grid of the non-important area is re-divided according to the grid points of the important area, and the updated grid points of the non-important area and the updated grid point coordinates of each updated grid point are obtained, and then the updated beam synthesis result of the non-important area is determined according to the updated grid point coordinates of each updated grid point, and then the updated beam synthesis result of the non-important area and the beam synthesis result of the important area are fused to obtain the beam synthesis result of the ultrasonic echo signal. In this method, the grid of the non-important area is re-divided according to the grid points of the important area, so that the grid density of the non-important area is consistent with the grid density of the important area, and then the signal fusion is performed based on the coordinates of the re-divided grid to obtain the beam synthesis result of the ultrasonic echo signal, thereby reducing the complexity of signal processing and improving the efficiency and accuracy of signal fusion.

[0138] In an exemplary embodiment, a beamforming method is proposed, such as Fig.11 As shown, the following steps are included:

[0139] S801, dividing the ultrasonic echo signal of the target object into regions to obtain a plurality of segmented regions.

[0140] The multiple segmented areas include important areas and non-important areas.

[0141] S802: Determine the proportion of grid points in important areas and the proportion of grid points in unimportant areas according to the area and grid density ratio of each segmented area.

[0142] The grid density ratio indicates the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area.

[0143] S803, determining the number of grid points in the important area according to the proportion of the number of grid points in the important area, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value.

[0144] S804: Determine the number of grid points in the non-important area according to the proportion of grid points in the non-important area, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value.

[0145] S805 , gridding each segmented area according to the number of grid points in the important area and the number of grid points in the unimportant area, and obtaining the grid point coordinates of each grid point in each segmented area.

[0146] S806, performing beam synthesis on each segmented area according to the grid point coordinates of each grid point to obtain a beam synthesis result of each segmented area.

[0147] The beamforming results of each segmented area include beamforming results of an important area and beamforming results of an unimportant area.

[0148] S807, re-dividing the grid of the non-important area according to the grid points of the important area, to obtain a plurality of updated grid points of the non-important area and updated grid point coordinates of each updated grid point.

[0149] S808, acquiring a plurality of original grid points corresponding to each updated grid point according to the coordinates of each updated grid point.

[0150] S809, determining an updated beamforming result of the non-important area according to the beamforming result of the non-important area and each original grid point.

[0151] Optionally, based on the beam synthesis result of the non-important area, the beam synthesis value of each original grid point is obtained; based on the beam synthesis value of each original grid point, the beam synthesis value of each updated grid point is determined; and the beam synthesis value of each updated grid point is determined as the updated beam synthesis result of the non-important area.

[0152] S810, fusing the updated beamforming result of the non-important area with the beamforming result of the important area to obtain the beamforming result of the ultrasonic echo signal.

[0153] The above process of S801-S810 can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0154] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0155] Based on the same inventive concept, the embodiment of the present application further provides a beamforming device for implementing the beamforming method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations of one or more beamforming device embodiments provided below can refer to the above limitations on the beamforming method, which will not be repeated here.

[0156] In an exemplary embodiment, Fig.12 As shown, a beamforming device 1 is provided, comprising: a region division module 10, a grid division module 20 and a beamforming module 30, wherein:

[0157] A region division module 10 is used to divide the ultrasonic echo signal of the target object into regions to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions;

[0158] The grid division module 20 is used to grid each segmented area according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area;

[0159] The beamforming module 30 is used to determine the beamforming result of the ultrasonic echo signal according to the grid point coordinates of each grid point.

[0160] In one embodiment, the grid division module 20 is further used for:

[0161] The number of grid points in each segmented area is determined according to the area and grid density ratio of each segmented area; each segmented area is grid-divided according to the number of grid points in each segmented area to obtain the grid point coordinates of each grid point in each segmented area.

[0162] In one embodiment, the number of grid points in each segmented area includes the number of grid points in the important area and the number of grid points in the unimportant area. The grid division module 20 is further used for:

[0163] According to the area and grid density ratio of each segmented area, the proportion of grid points in important areas and the proportion of grid points in unimportant areas are determined; according to the proportion of grid points in important areas, the total computing power consumption of beamforming and the computing power consumption of single-point beamforming, the number of grid points in important areas is determined; according to the proportion of grid points in unimportant areas, the total computing power consumption of beamforming and the computing power consumption of single-point beamforming, the number of grid points in unimportant areas is determined; the number of grid points in important areas and the number of grid points in unimportant areas are determined as the number of grid points in each segmented area.

[0164] In one embodiment, the beamforming module 30 is further configured to:

[0165] According to the grid point coordinates of each grid point, beam synthesis is performed on each segmented area to obtain the beam synthesis results of each segmented area; signal fusion is performed on the beam synthesis results of each segmented area to obtain the beam synthesis results of the ultrasonic echo signal.

[0166] In one embodiment, the beamforming results of each segmented area include the beamforming results of the important area and the beamforming results of the unimportant area; the beamforming module 30 is further used for:

[0167] According to the grid points of the important area, the grid of the non-important area is re-divided to obtain multiple updated grid points of the non-important area and the updated grid point coordinates of each updated grid point; according to the updated grid point coordinates of each updated grid point, the updated beam synthesis result of the non-important area is determined; the updated beam synthesis result of the non-important area and the beam synthesis result of the important area are fused to obtain the beam synthesis result of the ultrasonic echo signal.

[0168] In one embodiment, the beamforming module 30 is further configured to:

[0169] According to the coordinates of each updated grid point, a plurality of original grid points corresponding to each updated grid point are obtained; according to the beamforming result of the non-important area and each original grid point, an updated beamforming result of the non-important area is determined.

[0170] In one embodiment, the beamforming module 30 is further configured to:

[0171] According to the beam synthesis result of the non-important area, the beam synthesis value of each original grid point is obtained; according to the beam synthesis value of each original grid point, the beam synthesis value of each updated grid point is determined; and the beam synthesis value of each updated grid point is determined as the updated beam synthesis result of the non-important area.

[0172] Each module in the above-mentioned beamforming device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0173] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.13 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store beamforming data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a beamforming method is implemented.

[0174] Those skilled in the art will understand that Fig.13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0175] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0176] Performing regional division on the ultrasonic echo signal of the target object to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions;

[0177] According to the preset grid density ratio, each segmented area is grid-divided to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area;

[0178] According to the grid point coordinates of each grid point, the beamforming result of the ultrasonic echo signal is determined.

[0179] The implementation principles and technical effects of each step implemented by the processor in the embodiment of the present application are similar to the principles of the above-mentioned beamforming method, and will not be repeated here.

[0180] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0181] Performing regional division on the ultrasonic echo signal of the target object to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions;

[0182] According to the preset grid density ratio, each segmented area is grid-divided to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area;

[0183] According to the grid point coordinates of each grid point, the beamforming result of the ultrasonic echo signal is determined.

[0184] The implementation principles and technical effects of the steps implemented when the computer program in the embodiment of the present application is executed by the processor are similar to the principles of the above-mentioned beamforming method, and will not be repeated here.

[0185] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0186] Performing regional division on the ultrasonic echo signal of the target object to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions;

[0187] According to the preset grid density ratio, each segmented area is grid-divided to obtain the grid point coordinates of each grid point in each segmented area; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each segmented area; the grid density value of the important area is greater than the grid density value of the unimportant area;

[0188] According to the grid point coordinates of each grid point, the beamforming result of the ultrasonic echo signal is determined.

[0189] The implementation principles and technical effects of the steps implemented when the computer program in the embodiment of the present application is executed by the processor are similar to the principles of the above-mentioned beamforming method, and will not be repeated here.

[0190] It should be noted that the personnel information (including but not limited to personnel equipment information, personnel personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the personnel or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0191] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0192] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0193] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A beamforming method, characterized in that: The method comprises: Performing regional division on the ultrasonic echo signal of the target object to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions; According to a preset grid density ratio, each of the segmented areas is grid-divided to obtain the grid point coordinates of each grid point in each of the segmented areas; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each of the segmented areas; the grid density value of the important area is greater than the grid density value of the unimportant area; The beamforming result of the ultrasonic echo signal is determined according to the grid point coordinates of each of the grid points.

2. The method according to claim 1, characterized in that The grid division of each segmented area according to a preset grid density ratio to obtain the grid point coordinates of each grid point in each segmented area includes: Determining the number of grid points of each of the segmented regions according to the area of ​​each of the segmented regions and the ratio of the grid density; Each of the segmented regions is divided into grids according to the number of grid points in each of the segmented regions to obtain grid point coordinates of each grid point in each of the segmented regions.

3. The method according to claim 2, characterized in that Determining the number of grid points of each segmented region according to the area of ​​each segmented region and the grid density ratio includes: Determine the proportion of the number of grid points in the important area and the proportion of the number of grid points in the unimportant area according to the area of ​​each segmented area and the proportion of the grid density; Determine the number of grid points in the important area according to the proportion of grid points in the important area, the total beamforming computing power consumption value and the single-point beamforming computing power consumption value; Determine the number of grid points in the non-important area according to the proportion of the number of grid points in the non-important area, the total beamforming computing power consumption value, and the single-point beamforming computing power consumption value; The number of grid points in the important area and the number of grid points in the unimportant area are determined as the number of grid points in each of the divided areas.

4. The method according to any one of claims 1 to 3, characterized in that: Determining the beamforming result of the ultrasonic echo signal according to the grid point coordinates of each of the grid points includes: Performing beam synthesis on each of the segmented areas according to the grid point coordinates of each of the grid points to obtain beam synthesis results for each of the segmented areas; Signal fusion is performed on the beamforming results of each of the segmented areas to obtain the beamforming result of the ultrasonic echo signal.

5. The method according to claim 4, characterized in that The beam synthesis results of each of the segmented areas include the beam synthesis results of the important area and the beam synthesis results of the unimportant area; and the signal fusion of the beam synthesis results of each of the segmented areas to obtain the beam synthesis results of the ultrasonic echo signal includes: Re-dividing the grid of the non-important area according to the grid points of the important area to obtain a plurality of updated grid points of the non-important area and updated grid point coordinates of each updated grid point; Determining an updated beamforming result of the non-important area according to the updated grid point coordinates of each of the updated grid points; The updated beamforming result of the non-important area and the beamforming result of the important area are fused to obtain the beamforming result of the ultrasonic echo signal.

6. The method according to claim 5, characterized in that The step of determining the updated beamforming result of the non-important area according to the updated grid point coordinates of each of the updated grid points includes: According to the coordinates of each updated grid point, a plurality of original grid points corresponding to each updated grid point are obtained; An updated beamforming result of the non-important area is determined according to the beamforming result of the non-important area and each of the original grid points.

7. The method according to claim 6, characterized in that The step of determining an updated beamforming result of the non-important area according to the beamforming result of the non-important area and each of the original grid points includes: According to the beam synthesis result of the non-important area, obtaining the beam synthesis value of each of the original grid points; Determining the beamforming value of each of the updated grid points according to the beamforming value of each of the original grid points; The beam synthesis value of each of the update grid points is determined as the update beam synthesis result of the non-important area.

8. A beamforming device, characterized in that: The device comprises: A region division module, used for dividing the ultrasonic echo signal of the target object into regions to obtain a plurality of segmented regions; the plurality of segmented regions include important regions and non-important regions; A grid division module, used to grid each of the segmented areas according to a preset grid density ratio, to obtain the grid point coordinates of each grid point in each of the segmented areas; the grid density ratio represents the ratio between the grid density value of the important area and the grid density value of the unimportant area in each of the segmented areas; the grid density value of the important area is greater than the grid density value of the unimportant area; The beamforming module is used to determine the beamforming result of the ultrasonic echo signal according to the grid point coordinates of each grid point.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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