Ultrasonic imaging method, device, ultrasonic equipment and storage medium

Abstract

The present invention discloses an ultrasonic imaging method, device, ultrasonic equipment and storage medium. The method includes: performing flight time sampling on the original echo signal to obtain the full sampling point signal; performing beam synthesis processing on the full sampling point signal to obtain the original composite signal corresponding to each original sampling point; performing signal correlation analysis based on the full sampling point signal to determine the secondary sampling point from the original sampling point; performing resampling composite processing on the original echo signal corresponding to the secondary sampling point to determine the target composite signal corresponding to each secondary sampling point; performing fusion processing on the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image. The method can greatly restore the interference caused by tissue heterogeneity or tissue movement, which helps to ensure the imaging quality of the target ultrasonic image.

Description

Technical Field

[0001] The present invention relates to the field of ultrasonic imaging technology, and in particular to an ultrasonic imaging method, an apparatus, an ultrasonic device and a storage medium. Background Art

[0002] In the field of medical ultrasound imaging, cardiac imaging has always been the most difficult scenario. This is caused by many reasons. The main reason is that medical ultrasound makes a lot of assumptions to simplify the design for the simplicity of real-time imaging system, such as: it is believed that the tissue is basically stationary during the imaging process; it is believed that the sound speed is basically unchanged within the imaging tissue range; for example, it is believed that the signal collected in the imaging only includes the single scattered signal in the main lobe, or the multiple scattered signals can be ignored. But in fact, none of the above three assumptions are valid, especially in the scenario of cardiac imaging, the above three points will have obvious deviations from the facts. As we all know, the heart is a tissue organ that constantly performs periodic motion in the human body, and the speed of myocardial pulsation is relatively fast. It is normal for an adult to beat 60 to 100 times per minute, and on average, it is possible to beat once a second. Therefore, the quasi-static assumption is not valid in the first place. Secondly, there are very significant structural characteristics in the heart, which can be simply divided into two categories: cavity and tissue. The distribution of these two types of areas is very uneven, so the assumption of uniform sound speed is not valid. Finally, since a large number of cavities in the heart area are low-echo areas, and the multiple reflections or multiple scattering signals of the tissues are still stronger, the interference of clutter during cardiac imaging will particularly affect the image quality. Ultimately, these points work together in cardiac imaging, showing that the heart's cavities are cluttered and the heart's ventricular wall myocardium is not fully displayed.

[0003] Among these problems, different types of problems often need to be specially handled to improve image quality. But in fact, the above three points can be attributed to one problem, that is, due to various violations of ideal assumptions, when beamforming, the echo signals of multiple array channels that should have been transmitted multiple times from the same position are weighted coherently compounded. Because the signals are not in the same position, that is, the signals are not aligned or misaligned, the coherent cancellation effect occurs, resulting in the strong parts not being strong, and the weak parts not being weak, thus affecting the imaging quality of ultrasound images. Summary of the invention

[0004] The embodiments of the present invention provide an ultrasonic imaging method, an apparatus, an ultrasonic device and a storage medium to solve the problem of poor image quality in existing ultrasonic imaging.

[0005] An ultrasonic imaging method, comprising:

[0006] Perform flight time sampling on the original echo signal to obtain the full sampling point signal;

[0007] Performing beamforming processing on the all sampling point signals to obtain an original composite signal corresponding to each original sampling point;

[0008] Performing signal correlation analysis based on the full sampling point signals to determine secondary sampling points from the original sampling points;

[0009] Resampling and compounding the original echo signals corresponding to the secondary sampling points to determine a target compound signal corresponding to each of the secondary sampling points;

[0010] The original composite signal and the target composite signal corresponding to the same secondary sampling point are fused to determine the target ultrasonic image.

[0011] Preferably, performing signal correlation analysis based on the full sampling point signal to determine the secondary sampling point from the original sampling point includes:

[0012] Performing signal correlation analysis based on the full sampling point signals to determine the signal correlation corresponding to each original sampling point;

[0013] The original sampling points whose signal correlation satisfies the preset resampling conditions are determined as the secondary sampling points.

[0014] Preferably, performing signal correlation analysis based on the signals of all sampling points to determine the signal correlation corresponding to each original sampling point includes:

[0015] Based on the full sampling point signal, determine the full channel information corresponding to each original sampling point;

[0016] Performing channel correlation analysis on all channel information corresponding to each of the original sampling points to determine the channel correlation corresponding to each of the original sampling points;

[0017] Performing emission correlation analysis on the full channel information corresponding to each of the original sampling points to determine the emission correlation corresponding to each of the original sampling points;

[0018] Based on the channel correlation and the transmission correlation corresponding to each of the original sampling points, the signal correlation corresponding to each of the original sampling points is determined.

[0019] Preferably, determining the original sampling points whose signal correlation satisfies a preset resampling condition as secondary sampling points comprises:

[0020] Normalizing the signal correlations corresponding to all the original sampling points to determine a correlation evaluation value corresponding to each original sampling point;

[0021] The original sampling points whose correlation evaluation values ​​are within a preset threshold range are determined as secondary sampling points.

[0022] Preferably, the normalizing the signal correlations corresponding to all the original sampling points to determine the correlation evaluation value corresponding to each original sampling point includes:

[0023] Determining a maximum signal correlation based on signal correlations corresponding to all the original sampling points;

[0024] Determine a normalized correlation corresponding to each of the original sampling points based on the signal correlation corresponding to each of the original sampling points and the maximum signal correlation;

[0025] A mapping function is used to process the normalized correlation corresponding to each of the original sampling points to determine a correlation evaluation value corresponding to each of the original sampling points.

[0026] Preferably, the resampling and compounding of the original echo signals corresponding to the secondary sampling points to determine the target composite signal corresponding to each secondary sampling point includes:

[0027] Based on the secondary sampling point, determining a neighboring area corresponding to the secondary sampling point;

[0028] Performing high-density resampling on the adjacent area corresponding to the secondary sampling point to determine a plurality of resampled signals corresponding to the secondary sampling point;

[0029] Composite processing is performed on a plurality of resampled signals corresponding to the secondary sampling points to determine a target composite signal.

[0030] Preferably, the fusing the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image includes:

[0031] Determine a first weight coefficient corresponding to the original composite signal and a second weight coefficient corresponding to the target composite signal based on the correlation evaluation value corresponding to each of the secondary sampling points;

[0032] A target ultrasonic image is determined based on the original composite signal, the target composite signal, the first weight coefficient and the second weight coefficient corresponding to the same secondary sampling point.

[0033] An ultrasonic imaging device, comprising:

[0034] A full sampling point signal acquisition module is used to perform flight time sampling on the original echo signal to obtain full sampling point signals;

[0035] An original composite signal acquisition module is used to perform beamforming processing on the all sampling point signals to obtain an original composite signal corresponding to each original sampling point;

[0036] A secondary sampling point determination module, used to perform signal correlation analysis based on the full sampling point signal, and determine the secondary sampling point from the original sampling point;

[0037] A target composite signal determination module, used for resampling and composite processing the original echo signal corresponding to the secondary sampling point, and determining the target composite signal corresponding to each secondary sampling point;

[0038] The target ultrasonic image determination module is used to perform fusion processing on the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image.

[0039] Preferably, the secondary sampling point determination module comprises:

[0040] A signal correlation determination submodule, used to perform signal correlation analysis based on the full sampling point signals to determine the signal correlation corresponding to each original sampling point;

[0041] The secondary sampling point determination submodule is used to determine the original sampling points whose signal correlation meets the preset resampling conditions as secondary sampling points.

[0042] Preferably, the signal correlation determination submodule includes:

[0043] A full channel information determination unit, configured to determine the full channel information corresponding to each original sampling point based on the full sampling point signal;

[0044] A channel correlation determination unit, configured to perform channel correlation analysis on the full channel information corresponding to each of the original sampling points, and determine the channel correlation corresponding to each of the original sampling points;

[0045] A transmission correlation determination unit, configured to perform transmission correlation analysis on the full channel information corresponding to each of the original sampling points, and determine the transmission correlation corresponding to each of the original sampling points;

[0046] The signal correlation determination unit is used to determine the signal correlation corresponding to each of the original sampling points based on the channel correlation and the transmission correlation corresponding to each of the original sampling points.

[0047] Preferably, the secondary sampling point determination submodule includes:

[0048] A correlation evaluation value determination unit, used to perform normalization processing on the signal correlations corresponding to all the original sampling points, and determine the correlation evaluation value corresponding to each original sampling point;

[0049] The secondary sampling point determination unit is used to determine the original sampling points whose correlation evaluation values ​​are within a preset threshold range as secondary sampling points.

[0050] Preferably, the correlation evaluation value determination unit includes:

[0051] A maximum signal correlation determination subunit, used to determine the maximum signal correlation based on the signal correlations corresponding to all the original sampling points;

[0052] a normalized correlation determination subunit, configured to determine a normalized correlation corresponding to each of the original sampling points based on the signal correlation corresponding to each of the original sampling points and the maximum signal correlation;

[0053] The correlation evaluation value determination subunit is used to process the normalized correlation corresponding to each of the original sampling points using a mapping function to determine the correlation evaluation value corresponding to each of the original sampling points.

[0054] Preferably, the target composite signal determination module comprises:

[0055] A neighboring area determination submodule, used to determine a neighboring area corresponding to the secondary sampling point based on the secondary sampling point;

[0056] A resampled signal determination submodule, used to perform high-density resampling on the adjacent area corresponding to the secondary sampling point, and determine a plurality of resampled signals corresponding to the secondary sampling point;

[0057] The target composite signal determination submodule is used to perform composite processing on the multiple resampled signals corresponding to the secondary sampling points to determine the target composite signal.

[0058] Preferably, the target ultrasound image determination module comprises:

[0059] A weight coefficient determination submodule, used to determine a first weight coefficient corresponding to the original composite signal and a second weight coefficient corresponding to the target composite signal based on a correlation evaluation value corresponding to each of the secondary sampling points;

[0060] The target ultrasonic image determination submodule is used to determine the target ultrasonic image based on the original composite signal, the target composite signal, the first weight coefficient and the second weight coefficient corresponding to the same secondary sampling point.

[0061] An ultrasound device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the ultrasound imaging method when executing the computer program.

[0062] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the ultrasonic imaging method is implemented.

[0063] The above-mentioned ultrasonic imaging method, device, ultrasonic equipment and storage medium perform flight time sampling on the original echo signal to obtain the full sampling point signal; then perform beam synthesis processing on the full sampling point signal to determine the original composite signal corresponding to each original sampling point; based on the full sampling point signal, perform signal correlation analysis to determine the secondary sampling points with poor signal correlation from all the original sampling points, and resample and composite the original echo signals corresponding to the secondary sampling points so that the target composite signal contains more information about the tissue detected by ultrasound, which can greatly restore the interference caused by the non-uniformity of the tissue or the movement of the tissue; finally, the original composite signal and the target composite signal are fused to obtain a more natural signal transition, which helps to ensure the imaging quality of the target ultrasonic image. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0065] Figure 1 is a schematic diagram of an application environment of an ultrasonic imaging method in one embodiment of the present invention;

[0066] Figure 2 is a flow chart of an ultrasonic imaging method in one embodiment of the present invention;

[0067] Figure 3 yes Figure 2 A flow chart of step S203;

[0068] Figure 4 yes Figure 3 A flow chart of step S301;

[0069] Figure 5 yes Figure 3 A flow chart of step S302;

[0070] Figure 6 yes Figure 5 A flow chart of step S501;

[0071] Figure 7 yes Figure 2 A flow chart of step S204;

[0072] Figure 8 yes Figure 2 A flow chart of step S205;

[0073] Fig. 9 is a schematic diagram of an ultrasonic imaging device in one embodiment of the present invention. DETAILED DESCRIPTION

[0074] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] The ultrasonic imaging method provided by the embodiment of the present invention can be applied as follows: Figure 1 In the ultrasound device shown, the ultrasound device includes a main controller and an ultrasound probe, a beamforming processor, an image processor and a display screen connected to the main controller.

[0076] The main controller is the controller of the ultrasound device. The main controller is connected to other functional modules in the ultrasound device, including but not limited to the ultrasound probe, beamforming processor, image processor and display screen, and is used to control the operation of each functional module.

[0077] The ultrasonic probe is a device for transmitting and receiving ultrasonic waves. In this example, in order to ensure that ultrasonic images at different angles can have a large lateral scanning coverage, that is, to ensure that ultrasonic images at different angles have a large overlapping range, the existing ultrasonic probe is generally composed of a number of long strips of piezoelectric transducers of the same size (each single piezoelectric transducer is called an array element) arranged at equal intervals; or multiple piezoelectric transducers are arranged in a two-dimensional array, that is, the array elements are arranged in a two-dimensional matrix shape. The piezoelectric transducer in the ultrasonic probe converts the voltage pulse excitation applied to it into mechanical vibration, thereby emitting ultrasonic waves to the outside; ultrasonic waves propagate in media such as human tissue, generating echo data such as reflected waves and scattered waves, and the echo data is converted and processed to send the echo signal to the beamforming processor.

[0078] The beamforming processor is connected to the ultrasound probe and is used to receive the echo signal sent by the ultrasound probe. It is necessary to perform weighted coherent composite on the echo signals of multiple array element channels transmitted multiple times at the same position to obtain target composite information and send the target composite signal to the image processor.

[0079] The image processor is connected to the beamforming processor, and is used to receive the target composite signal sent by the beamforming processor, and perform image pre-processing operations such as data analysis, modulus, logarithmic compression and spatial compounding on the target composite signal. Among them, data analysis is to analyze the target composite signal and arrange it into a two-dimensional matrix of the number of sampling points multiplied by the number of scanning lines, but the signal at each position is a complex signal. In order to be able to image more intuitively, this step modulos the complex signal to obtain the energy of the signal, and use the energy to characterize the signal at this position. Logarithmic compression is to transform the data into a logarithmic function after the modulus operation, compress the dynamic range, and make the organizational level of the image clearer. After this, the spatial compounding operation is generally used to compound the images of the same area transmitted and received at multiple angles, weaken the coherence effect, reduce the speckle noise, and improve the resolution of the overall image. After the image pre-processing operation, the ultrasound image needs to be subjected to image post-processing operations such as gain and dynamic transformation. The processing process is essentially the same as conventional ultrasound imaging, and will not be described in detail here. Among them, spatial compounding refers to the process of emitting multiple ultrasonic waves at different angles to form ultrasonic images at different angles, and then weighted fusion of the ultrasonic images at different angles to obtain an ultrasonic image with less speckle noise and higher contrast resolution, which can significantly improve image quality.

[0080] In one embodiment, if Figure 2 As shown, an ultrasound imaging method is provided, which can be applied to a beamforming processor to optimize and improve the weighted coherent compounding process of echo signals of multiple array element channels transmitted multiple times at the same position, so as to improve the imaging quality of ultrasound images, and specifically includes the following steps:

[0081] S201: Perform flight time sampling on the original echo signal to obtain a full sampling point signal;

[0082] S202: Perform beamforming processing on all sampling point signals to obtain an original composite signal corresponding to each original sampling point;

[0083] S203: performing signal correlation analysis based on all sampling point signals, and determining secondary sampling points from the original sampling points;

[0084] S204: resampling and compounding the original echo signals corresponding to the secondary sampling points to determine the target compound signal corresponding to each secondary sampling point;

[0085] S205: performing fusion processing on the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image.

[0086] The original echo signal is the equally spaced sampling signal received by the array element. Indicates, where i represents the array element number and t represents the sampling time.

[0087] Among them, the full sampling point signal refers to the signal after the original echo signal is sampled by the time of flight. The flight time here refers to the flight time tSeq determined based on the time it takes for the ultrasound to be emitted to the imaging position plus the time it takes for the echo to be reflected from the imaging position to each array element. Based on the determined flight time tSeq, interpolation is performed in the original echo signal to obtain the echo signal scattered back from the imaging position to the corresponding array element.

[0088] As an example, in step S201, the beamforming processor may obtain all original echo signals of each array element in the ultrasound probe at different sampling times. , the original echo signal collected at each sampling time Contains signals at different imaging positions (x, z), each imaging position (x, z) corresponds to a sampling point; then, the beamforming processor processes the original echo signal Perform time-of-flight sampling to obtain the full sampling point signal, which can be mathematically expressed as:

[0089]

[0090] Wherein, R(i,x,z) is the signal at the imaging position (x,z) obtained by interpolation in the ith array element; intepr1D represents a one-dimensional interpolation, which may be, but is not limited to, a value determined by an interpolation algorithm such as linear interpolation or polynomial interpolation; s(i,1:end) represents all original echo signals corresponding to all time sampling sequences in the ith array element, which can be understood as the signal of all original echo signals from the first sampling time to the last sampling time end of the ith array element; tSeq is the time series corresponding to all time samplings, which corresponds one-to-one to s(i,1:end); tof(x,z) is the flight time corresponding to the imaging position (x,z).

[0091] As an example, in step S202, after acquiring the full sampling point signals, the beamforming processor may perform beamforming processing on the full sampling point signals to obtain the original composite signal, specifically including: performing channel composite processing on the full sampling point signals to obtain the channel composite signal corresponding to the same imaging position; and then performing multi-beam composite processing on the channel composite signal corresponding to the same imaging position to obtain the original composite signal. The original composite signal can be understood as the signal after beamforming the full sampling point signals.

[0092] In this example, channel compounding refers to weighted compounding of echo signals of multiple array elements belonging to the same sampling point (i.e., the same imaging position) reflected signal, which can be expressed by the following mathematical formula:

[0093]

[0094] Where R(i,x,z) is the signal at the imaging position (x,z) obtained by interpolation in the i-th array element; w n is the receiving apodization weight corresponding to the position and array element, is the receiving apodization weight of the ith array element at the imaging position (x, z), is the number of array elements, is the channel composite signal corresponding to the imaging position (x, z). This step is also a standard operation in ultrasonic beam synthesis and will not be described in detail.

[0095] In this example, multi-beam compounding refers to weighted compounding of echo signals at the same position obtained during multiple transmissions, which can be expressed mathematically as:

[0096]

[0097] Here, Rn has the same meaning as the previous expression, except that it carries the transmission number j, which is used to indicate that the final channel composite signal is the weighted sum of multiple transmissions, and the number of composites is AccuNum, that is, It refers to the composite signal of the channel corresponding to the imaging position (x, z) at the jth emission. j is the weight of the corresponding position, Specifically, it is the weight corresponding to the imaging position (x, z) at the jth emission. is the original composite signal corresponding to the imaging position (x, z), which is a function of the imaging position (x, z), and a value corresponding to each sampling point (i.e., imaging position). This step is also a standard operation in ultrasound imaging and will not be described in detail.

[0098] The secondary sampling point refers to the sampling point that needs secondary sampling.

[0099] As an example, in step S203, since the full sampling point signal includes echo signals corresponding to all original sampling points collected by different array element channels at different transmissions, the beamforming processor may analyze the signal correlation between all echo signals corresponding to different transmissions and / or different array element channels after acquiring the full sampling point signal; and then determine the original sampling points whose signal correlations meet the preset requirements as secondary sampling points, so as to ensure subsequent resampling based on the secondary sampling points.

[0100] As an example, in step S204, after determining the secondary sampling point, the beamforming processor may re-sample the original echo signal corresponding to the secondary sampling point in time of flight. Specifically, the original echo signal corresponding to the secondary sampling point may be subjected to a higher density interpolation process to obtain a plurality of resampled signals corresponding to each secondary sampling point. Then, the plurality of resampled signals corresponding to each secondary sampling point may be composited to determine the target composite signal. express.

[0101] As an example, in step S205, the beamforming processor may perform fusion processing on the original composite signal and the target composite signal corresponding to the secondary sampling point, and specifically may perform weighted fusion processing on the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasound image. Since the target composite signal is a signal obtained by resampling the original echo signal corresponding to the secondary sampling point with poor signal correlation, it contains greater information about the tissue detected by ultrasound and can greatly restore the interference caused by tissue inhomogeneity or tissue movement; the fusion of the original composite signal and the target composite signal can obtain a more natural signal transition, which helps to ensure the imaging quality of the target ultrasound image.

[0102] In this example, the original echo signal is time-of-flight sampled to obtain the signal of all sampling points; the signal of all sampling points is then processed by beamforming to determine the original composite signal corresponding to each original sampling point; signal correlation analysis is performed based on the signal of all sampling points to determine the secondary sampling points with poor signal correlation from all the original sampling points, and the original echo signal corresponding to the secondary sampling points is resampled and composited so that its target composite signal contains more information about the tissue detected by ultrasound, which can greatly restore the interference caused by tissue heterogeneity or tissue movement; finally, the original composite signal and the target composite signal are fused to obtain a more natural signal transition, which helps to ensure the imaging quality of the target ultrasound image.

[0103] In one embodiment, if Figure 3 As shown, step S203, i.e., performing signal correlation analysis based on all sampling point signals to determine secondary sampling points from the original sampling points, includes:

[0104] S301: Perform signal correlation analysis based on all sampling point signals to determine the signal correlation corresponding to each original sampling point;

[0105] S302: Determine the original sampling points whose signal correlation satisfies the preset resampling condition as secondary sampling points.

[0106] The original sampling point refers to the sampling point in the full sampling point signal, that is, the imaging position (x, z). The secondary sampling point is the sampling point with high signal correlation, which means the sampling point that needs secondary sampling and compound processing.

[0107] As an example, in step S301, since the full sampling point signal includes echo signals corresponding to all original sampling points collected by different transmissions and different array element channels, after acquiring the full sampling point signal, the beamforming processor can use the same original sampling point as a reference to perform signal correlation estimation on the echo signals collected by different transmissions and different array element channels to determine the signal correlation corresponding to each original sampling point. In this example, the beamforming processor can use but is not limited to the CF coherence factor or the GCF factor to perform a correlation algorithm to perform correlation calculation on the echo signals of different transmissions and / or different array element channels corresponding to the same original sampling point to determine the signal correlation corresponding to each original sampling point. The signal correlation can reflect the correlation between all echo signals corresponding to the same original sampling point.

[0108] Among them, the preset resampling condition is a pre-set condition for evaluating whether the signal correlation meets the condition requiring resampling. The preset resampling condition may be a condition determined by a pre-calibration test, and specifically may be a condition for evaluating poor signal correlation.

[0109] As an example, in step S302, after determining the signal correlation corresponding to each original sampling point, the beamforming processor may compare the signal correlations corresponding to all original sampling points with the preset resampling conditions, and determine the secondary sampling points whose signal correlations meet the preset resampling conditions from all the original sampling points, so as to perform subsequent resampling based on the secondary sampling points.

[0110] In this example, signal correlation estimation is performed on all sampling point signals to determine the signal correlation between echo signals of different transmissions and different array element channels corresponding to the same original sampling point; then the original sampling points whose signal correlations meet the preset resampling conditions are determined as secondary sampling points, which helps to ensure the subsequent resampling composite processing based on the secondary sampling points, so that the processed target composite signal contains more information about the tissue detected by ultrasound, and can greatly restore the interference caused by tissue heterogeneity or tissue movement.

[0111] In one embodiment, if Figure 4 As shown, in step S301, signal correlation analysis is performed based on all sampling point signals to determine the signal correlation corresponding to each original sampling point, including:

[0112] S401: Determine the full channel information corresponding to each original sampling point based on the full sampling point signal;

[0113] S402: performing channel correlation analysis on all channel information corresponding to each original sampling point to determine the channel correlation corresponding to each original sampling point;

[0114] S403: performing transmission correlation analysis on the full channel information corresponding to each original sampling point to determine the transmission correlation corresponding to each original sampling point;

[0115] S404: Determine the signal correlation corresponding to each original sampling point based on the channel correlation and the transmission correlation corresponding to each original sampling point.

[0116] The full channel signal corresponding to the original sampling point refers to all echo information corresponding to different transmission positions and different array element channels of the same original sampling point (x, z).

[0117] As an example, in step S401, the beamforming processor obtains the full sampling point signals of multiple transmissions. After that, based on all full sampling point signals , determine the full channel information corresponding to each original sampling point, which can be expressed as R(1:AccuNum,1:chn,x,z); where x,z are used to represent the imaging position of the original sampling point; 1:AccuNum refers to all the transmissions that can generate the signal of the imaging position; 1:chn refers to all array element channels, chn corresponds to different array elements, that is, the echo channels corresponding to different array elements. In other words, each original sampling point corresponds to a matrix formed by the full channel information, and the rows and columns of the matrix correspond to different transmissions and different array element channels, respectively.

[0118] As an example, in step S402, after obtaining the full channel information corresponding to each original sampling point, the beamforming processor may perform channel correlation analysis based on the full channel information corresponding to each original sampling point of the same transmission (such as the jth transmission) to determine the channel correlation corrn(j,x,z) corresponding to each original sampling point. That is, since the full channel information corresponding to each original sampling point corresponds to different transmissions and different array element channels, the echo signals corresponding to multiple array element channels (i.e., 1:chn) corresponding to the same original sampling point (x,z) may be determined from the full channel information for correlation analysis during the same transmission (such as the jth transmission), for example, using but not limited to the CF coherence factor or GCF factor widely used in various literatures to perform correlation analysis to determine the channel correlation corresponding to each original sampling point (x,z). The channel correlation here may be understood as the correlation between different array element channels.

[0119] As an example, in step S403, after obtaining the full channel information corresponding to each original sampling point, the beamforming processor can use the full channel information of any transmission as a reference, and use the full channel information of other transmissions to perform cross-correlation with the full channel information corresponding to the reference to determine the transmission correlation corrt(j,x,z) corresponding to each original sampling point.

[0120] For example, assuming that the ultrasound probe performs N transmissions, after obtaining the full channel information corresponding to each original sampling point, the echo signal matrix corresponding to all array element channels corresponding to the same original sampling point (x, z) is determined for each transmission; the echo signal matrix corresponding to all array element channels of the jth transmission can be used as a reference matrix, and the echo signal matrix corresponding to all array element channels of the other N-1 transmissions is cross-correlated with the reference matrix to determine N-1 cross-correlation values; the N-1 cross-correlation values ​​are then averaged or coefficient-weighted to determine the transmission correlation corrt(j,x,z) corresponding to each original sampling point.

[0121] As an example, in step S404, after obtaining the channel correlation corrn(j,x,z) and the transmit correlation corrt(j,x,z) corresponding to each original sampling point, the beamforming processor may use a preset fusion algorithm to fuse the channel correlation corrn(j,x,z) and the transmit correlation corrt(j,x,z) to determine the signal correlation corresponding to each original sampling point. In this example, the channel correlation corrn(j,x,z) and the transmit correlation corrt(j,x,z) may be weighted to determine the signal correlation corresponding to each original sampling point (x,z) as follows:

[0122]

[0123] In this example, the full channel information corresponding to the same original sampling point is first determined based on the signal of all sampling points. Then, based on the full channel information, the channel correlation corresponding to all array element channels of the same transmission and the transmission correlation between all array element channels determined by different transmissions are determined. Then, based on the channel correlation and transmission correlation, the signal correlation of different dimensions is determined to ensure the accuracy of the signal correlation analysis.

[0124] In one embodiment, if Figure 5 As shown, step S302, that is, determining the original sampling points whose signal correlation satisfies the preset resampling condition as the secondary sampling points, includes:

[0125] S501: performing normalization processing on the signal correlations corresponding to all original sampling points to determine the correlation evaluation value corresponding to each original sampling point;

[0126] S502: Determine the original sampling points whose correlation evaluation values ​​are within a preset threshold range as secondary sampling points.

[0127] The correlation evaluation value is a value obtained by normalizing the correlations of multiple signals. The preset threshold range is a preset threshold range used to evaluate and determine the secondary sampling point, and the preset threshold range can be understood as a kind of preset resampling condition.

[0128] As an example, in step S501, after obtaining the signal correlation corresponding to each original sampling point, the beamforming processor may normalize the signal correlations corresponding to all original sampling points to convert the signal correlations into quantifiable and comparable correlation evaluation values ​​within a specific range, which helps to ensure the accuracy and efficiency of subsequent processing.

[0129] As an example, in step S502, after determining the correlation evaluation value corresponding to each original sampling point, the beamforming processor may compare the correlation evaluation value with a preset threshold range to determine the original sampling point with a correlation evaluation value within the preset threshold range as a secondary sampling point that needs to be repeatedly sampled. This helps to ensure subsequent resampling and compounding based on the secondary sampling points, so that the processed target composite signal contains more information about the tissue detected by ultrasound, and can greatly restore interference caused by tissue heterogeneity or tissue movement.

[0130] In one embodiment, if Figure 6 As shown, step S501, i.e. normalizing the signal correlations corresponding to all original sampling points to determine the correlation evaluation value corresponding to each original sampling point, includes:

[0131] S601: Determine a maximum signal correlation based on signal correlations corresponding to all original sampling points;

[0132] S602: Determine a normalized correlation corresponding to each original sampling point based on a signal correlation corresponding to each original sampling point and a maximum signal correlation;

[0133] S603: Using a mapping function to process the normalized correlation corresponding to each original sampling point, and determining a correlation evaluation value corresponding to each original sampling point.

[0134] As an example, in step S601, the beamforming processor may compare the signal correlations corresponding to all original sampling points to determine a signal correlation with the largest value from all signal correlations, and determine it as the maximum signal correlation.

[0135] As an example, in step S602, the beamforming processor may determine the normalized correlation corresponding to each original sampling point based on the signal correlation corresponding to each original sampling point and the maximum signal correlation. Specifically, the quotient of each signal correlation and the maximum signal correlation may be directly determined as the normalized correlation corresponding to the original sampling point. Alternatively, the quotient of each signal correlation and the maximum signal correlation may be first calculated, and then the product of the quotient and a preset threshold (such as 1, 10 or 100, etc.) may be determined as the correlation evaluation value corresponding to each original sampling point.

[0136] In this example, the beamforming processor may use a mapping function such as but not limited to a smap function, a sigmoid function, a tan function, etc. to process the normalized correlation corresponding to each original sampling point to determine a correlation evaluation value corresponding to each original sampling point.

[0137] For example, after the normalized correlation corresponding to all original sampling points is processed using the smap function, an S curve will be formed, and its correlation evaluation value can be determined using the following formula:

[0138]

[0139] in, is the correlation evaluation value corresponding to the original sampling point (x, z). The larger the value, the greater the correlation; is the signal correlation corresponding to the original sampling point (x, z); is the maximum signal correlation; is the normalized correlation corresponding to the original sampling point (x, z).

[0140] As an example, in step S603, after determining the correlation evaluation value corresponding to each original sampling point, the beamforming processor may divide the correlation change formed by the smap function into the following three regions based on the lower threshold μ1 and the lower threshold μ2 corresponding to the preset threshold range: an uncorrelated region, a fuzzy correlated region and a completely correlated region, and determine all the original sampling points corresponding to the fuzzy correlated region between the lower threshold μ1 and the lower threshold μ2 as secondary sampling points xxs(x,z), so as to subsequently perform resampling and composite processing based on the secondary sampling points corresponding to the fuzzy correlated region, so that the processed target composite signal contains more information about the tissue detected by ultrasound, and can greatly restore the interference caused by tissue heterogeneity or tissue movement.

[0141] In one embodiment, if Figure 7 As shown, step S204, i.e., resampling and compounding the original echo signal corresponding to the secondary sampling point to determine the target composite signal corresponding to each secondary sampling point, includes:

[0142] S701: Based on the secondary sampling point, determine a neighboring area corresponding to the secondary sampling point;

[0143] S702: performing high-density resampling on the adjacent area corresponding to the secondary sampling point to determine a plurality of resampled signals corresponding to the secondary sampling point;

[0144] S703: Perform composite processing on a plurality of resampled signals corresponding to the secondary sampling points to determine a target composite signal.

[0145] As an example, in step S701, the beamforming processor determines the adjacent area ROI corresponding to each secondary sampling point in the fuzzy correlation area based on a preset radius. The preset radius here can be determined independently according to actual conditions, and is generally 2-4 wavelengths.

[0146] As an example, in step 702, after the beamforming processor determines the neighboring area ROI corresponding to each secondary sampling point, it can perform high-density resampling on the original echo signal corresponding to the neighboring area ROI. The high-density resampling here refers to re-sampling the flight time, and its sampling density is higher than the sampling density of the first sampling, generally 2-10 times the sampling density. The high-density resampling here purely relies on the original echo signal of the neighboring area ROI for interpolation, and is not physical sampling, so it will not affect the front-end control. In this example, after high-density resampling of all the original echo signals in the neighboring area corresponding to each secondary sampling point, a high-density signal matrix can be obtained. , here means to interpolate the echo signal of the i-th array element channel of the j-th transmission at the secondary sampling point (x, z) to obtain the resampled signal of the neighborhood of the position nx,nz.

[0147] As an example, in step S703, after obtaining multiple resampled signals corresponding to each secondary sampling point, the beamforming processor may perform composite processing on the multiple resampled signals corresponding to the secondary sampling point, specifically, weighted composite processing may be performed to determine the target composite signal. In this example, weighted processing is performed on multiple resampled signals to determine the target composite signal, which may be expressed by the following formula:

[0148]

[0149] in, is the target composite signal corresponding to the secondary sampling point (x, z); is the preset weight for the jth emission; is the preset weight of the ith array channel at the secondary sampling point (x, z); The resampled signal The corresponding weighting coefficient can be obtained by Perform local autocorrelation determination.

[0150] In this example, the resampled signal The parameters j, i, x, z, etc. in are fixed values. , is the variable corresponding to its neighboring area, which is equivalent to a matrix of nx * nz. Therefore, we use a calculation method similar to the above calculation method for signal correlation. The specific calculation process is as follows: (1) For each nx, there is a column of size nz. The correlation between each column corresponding to nx and the columns corresponding to other nx can be calculated, which is determined as the column correlation; (2) For each nz, there is a row of size nx. The correlation between each row corresponding to nz and the rows corresponding to other nz can be calculated, which is determined as the row correlation. (3) Multiply the row correlation and the column correlation, and determine the product of the two as the weighting coefficient corresponding to nx * nz. .

[0151] In this example, the corresponding adjacent area is determined based on each secondary sampling point, and then the original echo signal corresponding to the adjacent area is locally resampled with high density to determine the corresponding resampled signal, which can ensure the accuracy of the resampled signal; the resampled signal corresponding to the adjacent area corresponding to each secondary sampling point is then composited to determine the target composite signal, so that the target composite signal can integrate more effective information, so that it can more effectively resist the problem of misalignment of echo signals caused by tissue heterogeneity and tissue movement, which helps to ensure the final imaging quality.

[0152] In one embodiment, if Figure 8 As shown, step S205, that is, fusing the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image, includes:

[0153] S801: Determine a first weight coefficient corresponding to the original composite signal and a second weight coefficient corresponding to the target composite signal based on a correlation evaluation value corresponding to each secondary sampling point;

[0154] S802: Determine a target ultrasound image based on the original composite signal, the target composite signal, the first weight coefficient, and the second weight coefficient corresponding to the same secondary sampling point.

[0155] As an example, the beamforming processor converts the correlation evaluation value corresponding to each original sampling point determined in step S603 into , is determined as the first weight coefficient corresponding to the original composite signal; and , determine the second weight coefficient corresponding to the target composite signal; then, for the correlation evaluation value corresponding to the same secondary sampling point, the original composite signal and the target composite signal,

[0156]

[0157] Since the high density of resampling effectively utilizes the coherent signals in the adjacent areas, the signal interference caused by tissue inhomogeneity or movement can be greatly restored, and a more natural signal transition can be obtained through signal fusion.

[0158] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0159] In one embodiment, an ultrasonic imaging device is provided, which corresponds one-to-one to the ultrasonic imaging method in the above embodiment. Fig. 9 As shown, the ultrasonic imaging device includes a full sampling point signal acquisition module 901, an original composite signal acquisition module 902, a secondary sampling point determination module 903, a target composite signal determination module 904 and a target ultrasonic image determination module 905. The functional modules are described in detail as follows:

[0160] The full sampling point signal acquisition module 901 is used to perform time-of-flight sampling on the original echo signal to obtain the full sampling point signal;

[0161] The original composite signal acquisition module 902 is used to perform beamforming processing on all sampling point signals to obtain the original composite signal corresponding to each original sampling point;

[0162] A secondary sampling point determination module 903 is used to perform signal correlation analysis based on the full sampling point signal and determine the secondary sampling point from the original sampling point;

[0163] The target composite signal determination module 904 is used to perform resampling and composite processing on the original echo signal corresponding to the secondary sampling point to determine the target composite signal corresponding to each secondary sampling point;

[0164] The target ultrasonic image determination module 905 is used to perform fusion processing on the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image.

[0165] Preferably, the secondary sampling point determination module 903 includes:

[0166] A signal correlation determination submodule is used to perform signal correlation analysis based on all sampling point signals to determine the signal correlation corresponding to each original sampling point;

[0167] The secondary sampling point determination submodule is used to determine the original sampling points whose signal correlation meets the preset resampling conditions as secondary sampling points.

[0168] Preferably, the signal correlation determination submodule includes:

[0169] A full channel information determination unit, used to determine the full channel information corresponding to each original sampling point based on the full sampling point signal;

[0170] A channel correlation determination unit, used to perform channel correlation analysis on all channel information corresponding to each original sampling point, and determine the channel correlation corresponding to each original sampling point;

[0171] The transmission correlation determination unit is used to perform transmission correlation analysis on the full channel information corresponding to each original sampling point to determine the transmission correlation corresponding to each original sampling point;

[0172] The signal correlation determination unit is used to determine the signal correlation corresponding to each original sampling point based on the channel correlation and the transmission correlation corresponding to each original sampling point.

[0173] Preferably, the secondary sampling point determination submodule includes:

[0174] A correlation evaluation value determination unit, used to perform normalization processing on the signal correlations corresponding to all original sampling points, and determine the correlation evaluation value corresponding to each original sampling point;

[0175] The secondary sampling point determination unit is used to determine the original sampling points whose correlation evaluation values ​​are within a preset threshold range as secondary sampling points.

[0176] Preferably, the correlation evaluation value determination unit includes:

[0177] A maximum signal correlation determination subunit, used to determine the maximum signal correlation based on the signal correlations corresponding to all original sampling points;

[0178] A normalized correlation determination subunit, used to determine the normalized correlation corresponding to each original sampling point based on the signal correlation corresponding to each original sampling point and the maximum signal correlation;

[0179] The correlation evaluation value determination subunit is used to process the normalized correlation corresponding to each original sampling point using a mapping function to determine the correlation evaluation value corresponding to each original sampling point.

[0180] Preferably, the target composite signal determination module 904 includes:

[0181] A neighboring area determination submodule is used to determine the neighboring area corresponding to the secondary sampling point based on the secondary sampling point;

[0182] A resampled signal determination submodule is used to perform high-density resampling on the adjacent area corresponding to the secondary sampling point to determine a plurality of resampled signals corresponding to the secondary sampling point;

[0183] The target composite signal determination submodule is used to perform composite processing on a plurality of resampled signals corresponding to the secondary sampling points to determine the target composite signal.

[0184] Preferably, the target ultrasound image determination module 905 includes:

[0185] A weight coefficient determination submodule, used to determine a first weight coefficient corresponding to the original composite signal and a second weight coefficient corresponding to the target composite signal based on the correlation evaluation value corresponding to each secondary sampling point;

[0186] The target ultrasonic image determination submodule is used to determine the target ultrasonic image based on the original composite signal, the target composite signal, the first weight coefficient and the second weight coefficient corresponding to the same secondary sampling point. For the specific definition of the ultrasonic imaging device, please refer to the definition of the ultrasonic imaging method above, which will not be repeated here. The various modules in the above-mentioned ultrasonic imaging device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the ultrasonic device in the form of hardware, or can be stored in the memory in the ultrasonic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0187] In one embodiment, an ultrasound device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the ultrasound imaging method in the above embodiment is implemented, for example Figure 2 S201-S205 as shown, or Figures 3 to 8 As shown in, to avoid repetition, it will not be repeated here. Alternatively, when the processor executes the computer program, the functions of each module / unit in this embodiment of the ultrasonic imaging device are realized, for example Fig. 9 The functions of the full sampling point signal acquisition module 901, the original composite signal acquisition module 902, the secondary sampling point determination module 903, the target composite signal determination module 904 and the target ultrasonic image determination module 905 are not described here in detail to avoid repetition.

[0188] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the ultrasound imaging method in the above embodiment is implemented, for example Figure 2 S201-S205 as shown, or Figures 3 to 8 Alternatively, when the computer program is executed by the processor, the functions of each module / unit in the above-mentioned ultrasonic imaging device embodiment are realized, for example, Fig. 9The functions of the full sampling point signal acquisition module 901, the original composite signal acquisition module 902, the secondary sampling point determination module 903, the target composite signal determination module 904 and the target ultrasonic image determination module 905 are not described here in detail to avoid repetition.

[0189] Those of ordinary skill 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 memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0190] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0191] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An ultrasonic imaging method, characterized in that: include: Perform flight time sampling on the original echo signal to obtain the full sampling point signal; Performing beamforming processing on the all sampling point signals to obtain an original composite signal corresponding to each original sampling point; Performing signal correlation analysis based on the full sampling point signals, and determining secondary sampling points from all the original sampling points, including: determining full channel information corresponding to each original sampling point based on the full sampling point signals; performing channel correlation analysis on the full channel information corresponding to each original sampling point, and determining the channel correlation corresponding to each original sampling point; performing emission correlation analysis on the full channel information corresponding to each original sampling point, and determining the emission correlation corresponding to each original sampling point; determining the signal correlation corresponding to each original sampling point based on the channel correlation and emission correlation corresponding to each original sampling point; and determining the original sampling point whose signal correlation meets the preset resampling condition as the secondary sampling point; Resampling and compounding the original echo signals corresponding to the secondary sampling points to determine the target compound signal corresponding to each of the secondary sampling points, including: determining the adjacent area corresponding to the secondary sampling point based on the secondary sampling point; performing high-density resampling on the adjacent area corresponding to the secondary sampling point to determine multiple resampled signals corresponding to the secondary sampling point; compounding the multiple resampled signals corresponding to the secondary sampling point to determine the target compound signal; The original composite signal and the target composite signal corresponding to the same secondary sampling point are fused to determine the target ultrasonic image.

2. The ultrasonic imaging method according to claim 1, characterized in that: The step of determining the original sampling points whose signal correlation satisfies the preset resampling condition as the secondary sampling points comprises: Normalizing the signal correlations corresponding to all the original sampling points to determine a correlation evaluation value corresponding to each original sampling point; The original sampling points whose correlation evaluation values ​​are within a preset threshold range are determined as secondary sampling points.

3. The ultrasonic imaging method according to claim 2, characterized in that: The normalizing the signal correlations corresponding to all the original sampling points to determine the correlation evaluation value corresponding to each original sampling point includes: Determining a maximum signal correlation based on signal correlations corresponding to all the original sampling points; Determine a normalized correlation corresponding to each of the original sampling points based on the signal correlation corresponding to each of the original sampling points and the maximum signal correlation; A mapping function is used to process the normalized correlation corresponding to each of the original sampling points to determine a correlation evaluation value corresponding to each of the original sampling points.

4. The ultrasonic imaging method according to claim 2, characterized in that: The fusing process of the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image includes: Determine a first weight coefficient corresponding to the original composite signal and a second weight coefficient corresponding to the target composite signal based on the correlation evaluation value corresponding to each of the secondary sampling points; A target ultrasonic image is determined based on the original composite signal, the target composite signal, the first weight coefficient and the second weight coefficient corresponding to the same secondary sampling point.

5. An ultrasonic imaging device, characterized in that: include: A full sampling point signal acquisition module is used to perform flight time sampling on the original echo signal to obtain full sampling point signals; An original composite signal acquisition module is used to perform beamforming processing on the all sampling point signals to obtain an original composite signal corresponding to each original sampling point; A secondary sampling point determination module, configured to perform signal correlation analysis based on the full sampling point signal, and determine the secondary sampling point from all the original sampling points; A target composite signal determination module, used for resampling and composite processing the original echo signal corresponding to the secondary sampling point, and determining the target composite signal corresponding to each secondary sampling point; A target ultrasonic image determination module is used to perform fusion processing on the original composite signal and the target composite signal corresponding to the same secondary sampling point to determine the target ultrasonic image; The secondary sampling point determination module comprises: A signal correlation determination submodule, used to perform signal correlation analysis based on the full sampling point signals to determine the signal correlation corresponding to each original sampling point; A secondary sampling point determination submodule, used to determine the original sampling points whose signal correlation satisfies a preset resampling condition as secondary sampling points; The signal correlation determination submodule comprises: A full channel information determination unit, configured to determine the full channel information corresponding to each original sampling point based on the full sampling point signal; A channel correlation determination unit, configured to perform channel correlation analysis on the full channel information corresponding to each of the original sampling points, and determine the channel correlation corresponding to each of the original sampling points; A transmission correlation determination unit, configured to perform transmission correlation analysis on the full channel information corresponding to each of the original sampling points, and determine the transmission correlation corresponding to each of the original sampling points; A signal correlation determination unit, configured to determine the signal correlation corresponding to each of the original sampling points based on the channel correlation and the transmission correlation corresponding to each of the original sampling points; The target composite signal determination module comprises: A neighboring area determination submodule, used to determine a neighboring area corresponding to the secondary sampling point based on the secondary sampling point; A resampled signal determination submodule, used to perform high-density resampling on the adjacent area corresponding to the secondary sampling point, and determine a plurality of resampled signals corresponding to the secondary sampling point; The target composite signal determination submodule is used to perform composite processing on the multiple resampled signals corresponding to the secondary sampling points to determine the target composite signal.

6. The ultrasonic imaging device according to claim 5, characterized in that: The secondary sampling point determination submodule includes: A correlation evaluation value determination unit, used to perform normalization processing on the signal correlations corresponding to all the original sampling points, and determine the correlation evaluation value corresponding to each original sampling point; The secondary sampling point determination unit is used to determine the original sampling points whose correlation evaluation values ​​are within a preset threshold range as secondary sampling points.

7. The ultrasonic imaging device according to claim 6, characterized in that: The correlation evaluation value determination unit comprises: A maximum signal correlation determination subunit, used to determine the maximum signal correlation based on the signal correlations corresponding to all the original sampling points; a normalized correlation determination subunit, configured to determine a normalized correlation corresponding to each of the original sampling points based on the signal correlation corresponding to each of the original sampling points and the maximum signal correlation; The correlation evaluation value determination subunit is used to process the normalized correlation corresponding to each of the original sampling points using a mapping function to determine the correlation evaluation value corresponding to each of the original sampling points.

8. The ultrasonic imaging device according to claim 6, characterized in that: The target ultrasound image determination module comprises: A weight coefficient determination submodule, used to determine a first weight coefficient corresponding to the original composite signal and a second weight coefficient corresponding to the target composite signal based on a correlation evaluation value corresponding to each of the secondary sampling points; The target ultrasonic image determination submodule is used to determine the target ultrasonic image based on the original composite signal, the target composite signal, the first weight coefficient and the second weight coefficient corresponding to the same secondary sampling point.

9. An ultrasound device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the ultrasonic imaging method according to any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the ultrasonic imaging method according to any one of claims 1 to 4 is implemented.

Images