CN113243936A

CN113243936A - Ultrasonic wave beam forming method and device, ultrasonic equipment and storage medium

Info

Publication number: CN113243936A
Application number: CN202110611037.8A
Authority: CN
Inventors: 黄灿
Original assignee: Shenzhen Wisonic Medical Technology Co ltd
Current assignee: Shenzhen Wisonic Medical Technology Co ltd
Priority date: 2021-06-02
Filing date: 2021-06-02
Publication date: 2021-08-13
Anticipated expiration: 2041-06-02
Also published as: CN113243936B

Abstract

The invention discloses an ultrasonic wave beam forming method, an ultrasonic wave beam forming device, ultrasonic equipment and a storage medium. The method comprises the following steps: acquiring an original information matrix corresponding to a target pixel point; adopting K directional deflection filters to perform directional filtering on an original information matrix corresponding to a target pixel point to obtain K directional response characteristic matrices; determining K target response characteristic matrixes and corresponding associated response characteristic matrixes according to the K directional response characteristic matrixes; acquiring K directional confidence coefficients according to the K target response characteristic matrixes and the corresponding associated response characteristic matrixes; acquiring target echo signals according to K directional confidence coefficients and K target response characteristic matrixes corresponding to the target pixel points; and carrying out coherent superposition on the target echo signal to obtain a synthesized echo signal corresponding to the target pixel point. The synthesized echo signal is obtained after effective filtering and removing of the echo signal, and the signal containing more real and effective information is obtained, so that the signal to noise ratio and the resolution of the finally imaged ultrasonic image are guaranteed.

Description

Ultrasonic wave beam forming method and device, ultrasonic equipment and storage medium

Technical Field

The present invention relates to the field of ultrasound imaging technologies, and in particular, to an ultrasound beam forming method and apparatus, an ultrasound device, and a storage medium.

Background

Ultrasound imaging is widely used in medical practice in multiple departments to assist physicians in diagnosis and treatment. Generally, the basis of modern medical ultrasound imaging systems is a beam-forming imaging method of Delay And Sum (DAS), which is based on the basic principle that an ultrasound probe transmits ultrasound waves to human tissues, then each array element of the ultrasound probe receives echo signals of different times, And the echo signals of each array element are subjected to Delay correction And then are subjected to coherent superposition to obtain a high-resolution ultrasound image. In the process, the effect influence of the number of the array elements of the ultrasonic probe on the final image is large, because each array element can obtain the information of the tissue, the more the array elements are, the richer the information is, and the better the quality of the ultrasonic image is. In addition, due to the interference characteristic of the ultrasonic wave, if the delay of each array element is inaccurate when the ultrasonic waves are coherently superimposed, the signal-to-noise ratio of the ultrasonic wave is significantly reduced. Because the reason for inaccurate time delay is mainly caused by the difference between the system design and the real situation, the design of the ultrasonic equipment is often based on a series of basic assumptions, such as uniform tissue and only the main lobe, but in the actual ultrasonic imaging, the real tissue is obviously non-uniform, and the side lobe is not negligible when the real ultrasonic probe emits. The differences between the design of these systems and the real situation result in the ultrasound images containing a large amount of non-negligible noise, which degrades the images.

In order to improve the quality of an ultrasound image and suppress the influence of clutter, the clutter suppression ideas of the existing DAS mainly include the following two categories: in the first category, clutter suppression is performed in a multi-channel data synthesis stage, specifically, a clutter factor is calculated based on multi-channel beam data and is used as a weighting coefficient when the multi-channel beam data are coherently superposed, so that the signal-to-noise ratio of an ultrasound image after coherent superposition can be effectively improved. And in the second category, clutter suppression is performed after a multi-channel data synthesis stage, specifically, after multi-channel beam data are coherently superposed, a weighting coefficient matrix for multi-channel beam data synthesis is calculated based on ultrasonic images transmitted and received for multiple times, so that the ultrasonic images after the multi-channel beam data have higher signal-to-noise ratio.

When clutter suppression is carried out in the current multi-channel data synthesis stage, clutter factors calculated based on multi-channel beam data are utilized to carry out the processing process of a weighting processing process, and clutter cannot be truly removed mainly by utilizing the clutter factors to lower position signals with larger clutter. The process of weighting by adopting clutter factors is equivalent to rough contrast stretching, so that clutter is low in pressure, a real effective signal can be reduced, more image details cannot be presented, and the resolution of a final imaging ultrasonic image is low.

Disclosure of Invention

The embodiment of the invention provides an ultrasonic wave beam forming method, an ultrasonic wave beam forming device, ultrasonic equipment and a storage medium, and aims to solve the problem that clutter cannot be effectively filtered in the existing ultrasonic wave beam forming process, so that the resolution of a finally-imaged ultrasonic image is low.

An ultrasonic beamforming method comprising:

acquiring an original information matrix corresponding to a target pixel point, wherein the original information matrix comprises M × N original echo signals, N is the number of superposition times, and M is the number of channels;

adopting K directional deflection filters to perform directional filtering on the original information matrix corresponding to the target pixel point to obtain K directional response characteristic matrices corresponding to the target pixel point;

determining K target response characteristic matrixes corresponding to the target pixel points and an associated response characteristic matrix corresponding to each target response characteristic matrix according to the K directional response characteristic matrixes;

acquiring K directional confidence coefficients corresponding to the target pixel points according to the K target response characteristic matrixes and the associated response characteristic matrix corresponding to each target response characteristic matrix;

acquiring target echo signals corresponding to the target pixel points according to the K directional confidence coefficients corresponding to the target pixel points and the K target response characteristic matrixes;

and performing coherent superposition on the target echo signal corresponding to the target pixel point to obtain a synthesized echo signal corresponding to the target pixel point.

An ultrasonic beam forming apparatus comprising:

the original information matrix acquisition module is used for acquiring an original information matrix corresponding to a target pixel point, wherein the original information matrix comprises M × N original echo signals, N is the superposition times, and M is the channel number;

a directional response characteristic matrix obtaining module, configured to perform directional filtering on the original information matrix corresponding to the target pixel point by using K directional deflection filters, and obtain K directional response characteristic matrices corresponding to the target pixel point;

a target response characteristic matrix determining module, configured to determine, according to the K directional response characteristic matrices, K target response characteristic matrices corresponding to the target pixel point and an associated response characteristic matrix corresponding to each of the target response characteristic matrices;

a direction confidence coefficient obtaining module, configured to obtain K direction confidence coefficients corresponding to the target pixel points according to the K target response feature matrices and associated response feature matrices corresponding to each target response feature matrix;

a target echo signal obtaining module, configured to obtain a target echo signal corresponding to the target pixel point according to the K directional confidence coefficients and the K target response feature matrices corresponding to the target pixel point;

and the synthesized echo signal acquisition module is used for performing coherent superposition on the target echo signal corresponding to the target pixel point to acquire the synthesized echo signal corresponding to the target pixel point.

An ultrasound device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the ultrasound beamforming method when executing the computer program.

A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, implements the ultrasound beamforming method described above.

According to the ultrasonic wave beam synthesis method, the ultrasonic wave beam synthesis device, the ultrasonic equipment and the storage medium, the direction deflection filters corresponding to the K specific directions are adopted to perform direction filtering on the original information matrix of the target pixel point, so that the K direction response characteristic matrixes can be obtained, the information of the K specific directions can be clearly displayed, the finally obtained synthesized echo signal can contain more image information, and the signal-to-noise ratio and the resolution ratio of the finally imaged ultrasonic image can be guaranteed. Firstly, according to K directional response characteristic matrixes, K target response characteristic matrixes and K directional confidence coefficients are determined, then, according to K directional confidence coefficients and K corresponding to target pixel points, target echo signals corresponding to the target pixel points are obtained so as to effectively filter out clutter in all directions, real effective signals based on human tissue reflection or heat dissipation are reserved, synthetic echo signals obtained after coherent superposition is carried out on the target echo signals are made, the clutter can be effectively filtered out, more real effective information is contained, and the signal-to-noise ratio and the resolution ratio of a final imaging ultrasonic image are favorably guaranteed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.

FIG. 1 is a schematic view of an ultrasound image in accordance with an embodiment of the present invention;

FIG. 2 is a schematic diagram of ultrasonic beamforming in the prior art;

FIG. 3 is a flow chart of an ultrasonic beamforming method according to an embodiment of the present invention;

FIG. 4 is another flow chart of an ultrasonic beamforming method according to an embodiment of the present invention;

FIG. 5 is another flow chart of an ultrasonic beamforming method according to an embodiment of the present invention;

FIG. 6 is another flow chart of an ultrasonic beamforming method according to an embodiment of the present invention;

FIG. 7 is another flow chart of an ultrasonic beamforming method according to an embodiment of the present invention;

fig. 8 is a schematic diagram of an ultrasonic beam forming apparatus according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The ultrasonic wave beam forming method provided by the embodiment of the invention can be applied to the ultrasonic equipment shown in fig. 1, and the ultrasonic equipment comprises a main controller, an ultrasonic probe connected with the main controller, a beam forming processor, an image processor and a display screen.

The main controller is a controller of the ultrasonic equipment, and the main controller is connected with other functional modules in the ultrasonic equipment, including but not limited to an ultrasonic probe, a beam forming processor, an image processor, a display screen and the like, and is used for controlling the work of each functional module.

An ultrasound probe is a transmitting and receiving device of ultrasound waves. In this example, in order to ensure that the original ultrasound images at different angles can have a larger coverage of transverse scanning, and thus ensure that the original ultrasound images at different angles have a larger overlapping range, the conventional ultrasound probe generally comprises a plurality of strip-shaped piezoelectric transducers (each piezoelectric transducer is an array element) with the same size arranged at equal intervals; or a plurality of piezoelectric transducers are arranged in a two-dimensional array, namely array elements are arranged in a two-dimensional matrix shape.

A piezoelectric transducer in the ultrasonic probe excites and converts voltage pulses applied to the piezoelectric transducer into mechanical vibration, so that ultrasonic waves are emitted outwards; ultrasonic waves propagate through media such as human tissue, and reflected waves and scattered waves are generated. Each piezoelectric transducer can receive ultrasonic echo data such as reflected waves, scattered waves and the like, and the ultrasonic echo data are converted into electric signals, namely analog echo signals; and then, performing low noise amplification processing, time gain compensation and other conventional signal amplification processing on the analog echo signal, then performing analog-to-digital conversion processing to convert the analog echo signal into a digital echo signal, and sending the digital echo signal to the beam synthesis processor. In this example, each piezoelectric transducer (i.e., an array element) corresponds to one channel, and the plurality of piezoelectric transducers transmit digital echo signals acquired by the piezoelectric transducers to the beamforming processor, so that the beamforming processor can receive the digital echo signals of multiple channels.

The beam forming processor is connected with the ultrasonic probe and used for receiving the digital echo signals sent by the ultrasonic probe, carrying out beam forming on the digital echo signals of one or more channels, acquiring the synthesized echo signals and sending the synthesized echo signals to the image processor.

The image processor is connected with the beam synthesis processor and used for receiving the synthesized echo signals sent by the beam synthesis processor, carrying out image processing processes such as image synthesis and spatial compounding on the synthesized echo signals, forming an ultrasonic image, and sending the ultrasonic image to a display screen so that the ultrasonic image is displayed on the display screen.

As an example, the image processor may be a Graphics Processing Unit (GPU), which is a processor designed to perform mathematical and geometric calculations necessary for rendering complex Graphics, and is helpful to improve the generation efficiency of the ultrasound image. In the example, the image processor is specially used for image processing, so that the main controller is liberated from the task of image processing, more system tasks can be executed, and the overall performance of the ultrasonic equipment can be improved.

As shown in fig. 2, 8 piezoelectric transducers are provided in the ultrasonic probe, and are controlled to transmit ultrasonic waves at 4 different positions in succession, each piezoelectric transducer can receive a set of reflected waves and scattered waves to form ultrasonic echo data, the example with an arrow in fig. 2 shows that the ultrasonic waves are transmitted 4 times at different positions, and the example without an arrow shows that the multi-channel ultrasonic echo data are received each time. As shown in fig. 2, although the positions of the ultrasonic echo data of 8 channels formed by transmitting ultrasonic waves each time are shifted continuously, 4 transmissions are included in 2 positions, and in the conventional DAS, it is necessary to perform coherent superposition on multi-channel digital echo signals obtained by converting the ultrasonic echo data in which 4 transmissions are overlapped to obtain a synthesized echo signal, so as to acquire an ultrasonic image with better signal-to-noise ratio by using the synthesized echo signal. Because the ultrasonic echo data acquired by each ultrasonic wave transmission is synthesized by the signals at the corresponding positions in all the channels, in the ultrasonic image acquired after the existing beam forming is adopted, the synthesized echo signal corresponding to each target pixel point is as follows:

wherein,

to synthesize an echo signal;

is a target pixel point at

When the secondary ultrasonic wave is emitted, the

The digital echo signals corresponding to the channels are subjected to time delay correction to obtain signals; n is the number of superposition times, and M is the number of channels;

the target pixel point is at

Weight at the time of secondary ultrasound transmission.

From the above formula, in the conventional beam forming process, the digital echo signal corresponding to each target pixel point

And the synthesized echo signal corresponding to the target pixel point can be obtained only by channel summation and superposition times summation. When clutter suppression is carried out in the conventional multi-channel data synthesis stage, if clutter in a target pixel point is large, the strategy of carrying out the clutter suppression is to obtain a finally obtained synthesized echo signal

Multiplication by smaller clutterFactor to suppress the synthesized echo signal

. In this manner, in the digital echo signal

When both contained true effective signal, contained great clutter again, unable difference is handled, not only with the clutter low pressure, also probably with true effective signal depression for the final ultrasonic image that obtains can not show more image detail, leads to the resolution ratio of the ultrasonic image of final formation of image lower.

In one embodiment, as shown in fig. 3, an ultrasound beamforming method is provided, which is exemplified by the beamforming processor in fig. 1, and includes the following steps:

s301: and acquiring an original information matrix corresponding to the target pixel point, wherein the original information matrix comprises M × N original echo signals, N is the number of superposition times, and M is the number of channels.

S302: and adopting K directional deflection filters to perform directional filtering on the original information matrix corresponding to the target pixel point to obtain K directional response characteristic matrices corresponding to the target pixel point.

S303: and determining K target response characteristic matrixes corresponding to the target pixel points and an associated response characteristic matrix corresponding to each target response characteristic matrix according to the K directional response characteristic matrixes.

S304: and acquiring K directional confidence coefficients corresponding to target pixel points according to the K target response characteristic matrixes and the associated response characteristic matrix corresponding to each target response characteristic matrix.

S305: and acquiring a target echo signal corresponding to the target pixel point according to the K directional confidence coefficients and the K target response characteristic matrixes corresponding to the target pixel point.

S306: and carrying out coherent superposition on the target echo signals corresponding to the target pixel points to obtain the synthetic echo signals corresponding to the target pixel points.

The original information matrix is a matrix formed by sequencing M × N original echo signals according to a specific sequence. The original echo signal is an echo signal that has not been subjected to beamforming processing.

As an example, in step S301, the master controller may control an ultrasonic probe having M piezoelectric transducers (i.e., array elements) to sequentially emit ultrasonic waves at different positions, where after the ultrasonic waves emitted at each position scan human tissue, ultrasonic echo data such as reflected waves and scattered waves are formed; each piezoelectric transducer (namely an array element) of the ultrasonic probe can receive ultrasonic echo data corresponding to each time of transmitting ultrasonic waves, convert the ultrasonic echo data into analog echo signals, and form digital echo signals through amplification or analog conversion processing; the ultrasound probe sends the Tx digital echo signals corresponding to the Tx ultrasound waves to the beamforming processor, where Tx is the number of times the ultrasound waves are transmitted.

In this example, the beam forming processor may receive Tx digital echo signals sent by the ultrasound probe, where each digital echo signal includes information corresponding to all pixel points in the ultrasound imaging region, that is, a digital echo signal received by each array element each time. The beam forming processor can adopt a pre-configured signal processing logic to process all received digital echo signals so as to extract the information of each target pixel point, and the information of each target pixel point is expressed as an original information matrix in a matrix form. M × N original echo signals are recorded in the original information matrix, N is the number of superposition times, M is the number of channels (namely the number of array elements), the number of superposition times can be understood as the number of times of superposing the digital echo signals to the same target pixel point, and N is less than or equal to Tx.

The directional deflection filter is a filter that deflects in a specific direction, and K is the number of directional deflection filters. The directional response characteristic matrix is a response characteristic matrix obtained after filtering the original information matrix by adopting a directional deflection filter.

As an example, in step S302, the beam synthesis processor may employ K directional deflection filters to perform directional filtering on the original information matrix corresponding to the target pixel point, that is, each directional deflection filter performs filtering on the original information matrix, so as to obtain K directional response feature matrices corresponding to the target pixel point. In this example, the elements in each original information matrix are M × N original echo signals, and the elements in each directional response feature matrix are M × N directional response features. The directional deflection filter is a characteristic obtained after the original echo signal is filtered by the directional deflection filter.

For example, the beam synthesis processor may employ K directional deflection filters, for example, directional deflection filters corresponding to specific directions of 0, 30, 60, 90, 120, and 150 (i.e., K = 6), and perform filtering processing on the original information matrix corresponding to the target pixel point respectively to obtain a directional response feature matrix output by each directional deflection filter. In this example, the directional deflection filter may be a Gabor directional deflection filter, or may be a tensor-based deflection filter, and the filter used may be determined autonomously by the user according to actual needs.

The target response characteristic matrix refers to a direction response characteristic matrix corresponding to a specific direction. The associated response characteristic matrix refers to other directional response characteristic matrixes except the target response characteristic matrix.

As an example, in step S303, the beam synthesis processor may determine, according to the K directional response feature matrices, K target response feature matrices corresponding to the target pixel point and an associated response feature matrix corresponding to each target response feature matrix, and may specifically adopt the following implementation manners: any one of K directional response characteristic matrixes corresponding to the target pixel points is determined as a target response characteristic matrix, and the rest K-1 directional response characteristic matrixes are determined as associated response characteristic matrixes.

In one example, there are K directional response feature matrices for each target pixel point, and the beamforming processor may sequentially determine one of the directional response feature matrices as the target response feature matrix and the other directional response feature matrices as the associated response feature matrix. That is, the 1 st directional response feature matrix of the K directional response feature matrices is determined as the target response feature matrix, and the 2 nd, 3 … … K-1 th and K directional response feature matrices are determined as the 1 st, 2 … … K-2 nd and K-1 th associated response feature matrices, respectively. In this example, the 6 directional response feature matrices formed by the 6 directional deflection filters are M (0), M (30), M (60), M (90), M (120), and M (150), respectively, M (0) may be determined as the target response feature matrix, and M (30), M (60), M (90), M (120), and M (150) may be determined as the associated response feature matrix corresponding to the target response feature matrix M (0).

The direction confidence is the confidence corresponding to a specific direction.

As an example, in step S304, the beam synthesis processor may obtain K directional confidence levels corresponding to target pixel points according to the K target response feature matrices and the associated response feature matrix corresponding to each target response feature matrix, and may specifically adopt the following implementation manners: (1) and determining the direction confidence corresponding to each target response characteristic matrix based on each target response characteristic matrix and the corresponding associated response characteristic matrix. In this example, a direction confidence formula may be adopted to calculate each target response feature matrix and the associated response feature matrix corresponding thereto, and determine the direction confidence corresponding thereto. The direction confidence coefficient formula is a preset formula for calculating the confidence coefficient of the target response characteristic matrix corresponding to the specific direction. (2) And determining K direction confidence degrees corresponding to the target pixel points based on the direction confidence degrees corresponding to the K target response characteristic matrixes.

As an example, in step S305, the beam synthesis processor may obtain the target echo signal corresponding to the target pixel point according to K directional confidences and K target response feature matrices corresponding to the target pixel point, and may specifically adopt the following implementation manners: and performing directional weighting processing on the K directional confidence coefficients and the K target response characteristic matrixes corresponding to the same target pixel point to obtain a target echo signal corresponding to the target pixel point.

As an example, in step S306, the beamforming processor may perform coherent superposition on M × N target echo signals corresponding to the same target pixel point to obtain a synthesized echo signal, so as to subsequently obtain an ultrasound image with better signal-to-noise ratio by using the synthesized echo signal. In this example, the beam synthesis processor performs coherent superposition on M × N target echo signals corresponding to the same target pixel point to obtain a processing formula of a synthesized echo signal as follows:

wherein,

to synthesize an echo signal;

is a target pixel point at

When the secondary ultrasonic wave is emitted, the

Target echo signals corresponding to the channels; n is the number of superposition times, and M is the number of channels;

the target pixel point is at

Weight at the time of secondary ultrasound transmission.

In the ultrasonic wave beam synthesis method provided by this embodiment, the direction deflection filters corresponding to the K specific directions are adopted to perform direction filtering on the original information matrix of the target pixel point, so that the K direction response characteristic matrices can be obtained, and the information of the K specific directions can be clearly displayed, so that the finally obtained synthesized echo signal can contain more image information, which is helpful for ensuring the signal-to-noise ratio and the resolution of the finally imaged ultrasonic image. According to the K directional response characteristic matrixes, K target response characteristic matrixes and K directional confidence coefficients are determined, then, according to the K directional confidence coefficients and the K target response characteristic matrixes corresponding to the target pixel points, target echo signals corresponding to the target pixel points are obtained, clutter in all directions is effectively filtered, real effective signals based on human tissue reflection or heat dissipation are reserved, synthesized echo signals obtained after coherent superposition is carried out on the basis of the target echo signals can contain more real effective information, and the signal-to-noise ratio and the resolution ratio of the finally imaged ultrasonic image are favorably guaranteed.

In an embodiment, as shown in fig. 4, step S301, namely, acquiring an original information matrix corresponding to a target pixel point, includes:

s401: and receiving a digital echo signal sent by the ultrasonic probe.

S402: and carrying out time delay correction processing on the digital echo signals to obtain corrected echo signals corresponding to the digital echo signals.

S403: and acquiring an original information matrix corresponding to the target pixel point based on the corrected echo signal.

As an example, the main controller may control an ultrasonic probe provided with M piezoelectric transducers (i.e., array elements) to sequentially emit ultrasonic waves at different positions, where the ultrasonic waves emitted at each position form ultrasonic echo data such as reflected waves and scattered waves after scanning human tissues; each piezoelectric transducer (namely an array element) of the ultrasonic probe can receive ultrasonic echo data corresponding to each time of transmitting ultrasonic waves, convert the ultrasonic echo data into analog echo signals, and form digital echo signals through amplification or analog conversion processing; the ultrasound probe sends the Tx digital echo signals corresponding to the Tx ultrasound waves to the beamforming processor.

As an example, in step S401, the beamforming processor may receive Tx digital echo signals sent by the ultrasound probe, where the Tx digital echo signals are a matrix of M × Tx × Tseq, and M is the number of channels, i.e., the number of array elements; tx is the transmission frequency of the ultrasonic wave; tseq is the number of pixels, which can be understood as the number of pixels in a beam line, determined by the sampling frequency.

As an example, in step S402, the beamforming processor may perform a delay correction process on each digital echo signal by using a delay correction algorithm, so as to obtain a corrected echo signal corresponding to the digital echo signal. For example, the beam synthesis processor may perform delay correction processing on the received Tx digital echo signals by using a delay correction algorithm in a conventional DAS algorithm, so as to obtain corrected echo signals corresponding to the digital echo signals, where the corrected echo signals are a matrix of M × N × PntNum × LineNum, N is the number of times of superposition in an ultrasound image region, N is equal to or less than Tx, PntNum is the number of longitudinal pixel points in an imaging range, LineNum is the number of transverse pixel points in the imaging range, and understandably, PntNum includes all pixel points in the imaging range, and each target pixel point corresponds to a matrix of M × N.

As an example, in step S403, the beamforming processor may determine the M × N matrix corresponding to each target pixel point from the matrix of the corrected echo signal, i.e., M × N × PntNum LineNum, as the original information matrix corresponding to the target pixel point. In this example, the elements in the original information matrix are original echo signals, and M × N original echo signals are sorted according to the channel order and the superimposed ultrasound order. The channel sequence refers to the arrangement sequence of M piezoelectric transducers (i.e. array elements) in the ultrasonic probe. The sequence of the superposed ultrasonic waves refers to the sequence of the ultrasonic probes transmitting the ultrasonic waves for N times. For example, each original echo signal in the original information matrix corresponding to the target pixel point can be used

It is shown that,

is a target pixel point at

When the secondary ultrasonic wave is emitted, the

；

。

in the ultrasonic wave beam forming method provided in this embodiment, because in the ultrasonic imaging technology, information corresponding to a certain target pixel point is dispersed in digital echo signals received by transmitting ultrasonic waves for multiple times, in this example, M × N digital echo signals corresponding to the target pixel point are buffered in an original information matrix, so that beam forming processing is performed subsequently based on the original information matrix, which is helpful to ensure the integrity of information, so that a finally obtained synthesized echo signal contains more detailed information, which can both reduce the signal-to-noise ratio of an ultrasonic image synthesized based on the synthesized echo signal and improve the resolution of the ultrasonic image.

In an embodiment, as shown in fig. 5, step S302, that is, performing directional filtering on the original information matrix corresponding to the target pixel point by using K directional deflection filters, to obtain K directional response feature matrices corresponding to the target pixel point, includes:

s501: and processing the original information matrix corresponding to the target pixel point by adopting directional filtering kernels corresponding to the K directional deflection filters to obtain K directional response intensity matrixes.

S502: and processing the original information matrix corresponding to the target pixel point by adopting K directional response intensity matrixes to obtain K directional response characteristic matrixes corresponding to the target pixel point.

The directional filter kernel is a filter kernel corresponding to the directional deflection filter, and can be understood as a convolution kernel. Generally, each directional deflection filter has a different deflection angle, and its corresponding directional filter kernel is also different. The directional response intensity matrix is formed by processing an original information matrix corresponding to the target pixel point by adopting a directional filter core.

As an example, in step S501, the beam synthesis processor first uses the directional filter kernels corresponding to the K directional deflection filters to process the original information matrix corresponding to the target pixel point, for example, convolve the original information matrix, so as to obtain the directional response intensity matrix corresponding to each target pixel point. In this example, the directional deflection filter may be a Gabor directional deflection filter, or may also be a tensor-based deflection filter, and a user may autonomously determine an adopted filter according to actual needs, where each directional deflection filter has a corresponding directional filtering kernel, and the directional filtering kernel is determined based on a corresponding standard image processing algorithm.

As an example, in step S502, the beam synthesis processor may use K directional response intensity matrices to respectively process the original information matrices corresponding to the target pixel point, and obtain K directional response feature matrices corresponding to the target pixel point, which specifically includes: and adopting elements in the directional response intensity matrix and point-by-point products of the elements in the original information matrix corresponding to the target pixel points respectively to obtain K elements of the directional response characteristic matrix corresponding to the target pixel points. For example, when the original information matrix corresponding to each target pixel point is a matrix formed by M × N original echo signals, a directional response feature matrix formed by M × N directional response features is obtained when the elements of the directional response intensity matrix corresponding to each directional deflection filter and the elements of the original information matrix are multiplied point by point. The directional response characteristic matrix is a result matrix processed by adopting a directional response intensity matrix and an original information matrix. The directional response features are elements in a directional response feature matrix, specifically result features obtained by multiplying the elements in the directional response intensity matrix and the elements in the original information matrix point by point, and the number of the directional response features is M × N.

In this embodiment, the direction deflection filters corresponding to the K specific directions are adopted to perform direction filtering on the original information matrix of the target pixel point, and the acquired K direction response characteristic matrices can clearly display image information in the K specific directions, so that when beam synthesis is performed by using the K direction response characteristic matrices in the subsequent process, a finally acquired synthesized echo signal contains clearer image information, which can reduce the signal-to-noise ratio of an ultrasonic image synthesized based on the synthesized echo signal and improve the resolution of the ultrasonic image.

In an embodiment, as shown in fig. 6, the step S303 of determining K target response feature matrices corresponding to the target pixel point and an associated response feature matrix corresponding to each target response feature matrix according to the K directional response feature matrices includes:

s601: and acquiring a neighboring region corresponding to the target pixel point, wherein the neighboring region comprises L neighborhood pixel points, and K direction response characteristic matrixes corresponding to each neighborhood pixel point.

S602: and acquiring K neighborhood response feature matrixes corresponding to the target pixel points according to the K × L direction response feature matrixes corresponding to the L neighborhood pixel points.

S603: any one of K neighborhood response characteristic matrixes corresponding to the target pixel point is sequentially determined as a target response characteristic matrix, and the rest K-1 neighborhood response characteristic matrixes are determined as associated response characteristic matrixes.

As an example, in step S601, the beam synthesis processor may first determine a neighboring area of the target pixel point based on the position of the target pixel point, where the neighboring area of the target pixel point may be understood as an area formed by a plurality of pixel points centered on the target pixel point. The neighborhood pixels refer to pixels located in a neighborhood, and the neighborhood pixels comprise target pixels and neighboring pixels adjacent to the target pixels. In this example, if the target pixel point P (100 ) constructs a 3 × 3 corresponding neighboring area, the coordinate range of the neighboring area is X =99-101, Y =99-101, that is, the coordinate range includes pixel points such as P1(99,99), P2(99,100), P3(99,101), P4(100,99), P5(100 ), P6(100,101), P7(101,99), P8(101,100), and P9(101 ), that is, the target pixel point is P5, and the neighboring pixel points are P1, P2, P3, P4, P6, P7, P8, and P9.

In this example, the neighborhood region includes L neighborhood pixels, and each neighborhood pixel corresponds to K directional response feature matrices. The neighborhood pixel points comprise target pixel points and L-1 adjacent pixel points adjacent to the target pixel points. Since all the pixel points in the adjacent region correspond to the K directional response feature matrices, the adjacent region corresponding to the target pixel point corresponds to the K × L directional response feature matrices.

For example, the beam synthesis processor performs directional filtering on the original information matrices of all target pixels corresponding to the ultrasound image region by using directional deflection filters corresponding to specific directions of 0, 30, 60, 90, 120, and 150, so as to obtain K =6 directional response feature matrices. When the target pixel point is P5 and the neighboring pixel points are P1, P2, P3, P4, P6, P7, P8 and P9, 9 neighboring pixel points are shared in the neighboring region corresponding to the target pixel point, so that the neighboring region corresponding to the target pixel point contains 54 directional response feature matrices, and M × N directional response features are recorded in each directional response feature matrix.

As an example, in step S602, the beam synthesis processor may obtain K neighborhood response feature matrices corresponding to the target pixel point according to K × L directional response feature matrices corresponding to L neighborhood pixel points in the neighborhood region, and the specific implementation process is as follows: the method comprises the steps that L neighborhood pixel points are contained in a neighborhood region corresponding to a target pixel point, each neighborhood pixel point corresponds to K directional response feature matrixes, and M × N directional response features are recorded in each directional response feature matrix; and obtaining K neighborhood response feature matrixes according to the K-L directional response feature matrixes.

For example, in the above example, the original information matrix corresponding to the neighborhood pixel point P1 is processed by the above 6 directional deflection filters, and the formed 6 directional response feature matrices are M1 (0), M1 (30), M1 (60), M1 (90), M1 (120), and M1 (150), respectively; correspondingly, 6 directional response feature matrices corresponding to the neighborhood pixel point P2 are M2 (0), M2 (30), M2 (60), M2 (90), M2 (120), M2 (150) … …, and so on, and 6 directional response feature matrices corresponding to the neighborhood pixel point P9 are M9 (0), M9 (30), M9 (60), M9 (90), M9 (120), and M9 (150), respectively. As can be seen from the above, each specific direction forms a directional response feature matrix matching the number of the pixel points in the neighboring region corresponding to the target pixel point. In this example, obtaining K neighborhood response feature matrices according to K × L directional response feature matrices specifically includes: forming a neighborhood response characteristic by using L directional response characteristics corresponding to the same matrix position in K x L directional response characteristic matrixes; and acquiring a neighborhood response characteristic matrix based on the neighborhood response characteristics corresponding to all the same matrix positions.

For example, when the specific direction is 0, the 9 directional response feature matrices are M1 (0), M2 (0), M3 (0), M4 (0), M5 (0), M6 (0), M7 (0), M8 (0), and M9 (0), respectively,

，

，

，

，

，

，

，

，

and E is an element in the directional response characteristic matrix, namely the directional response characteristic. A neighborhood response feature may be formed based on the L directional response features at the same location, for example, the 9 directional response features in the 1 st row and the 1 st column may be obtained according to the locations of all neighborhood pixels in the neighborhood region, and the neighborhood response feature is a matrix matching the number of pixels in the neighborhood region, such as

And repeating the steps to obtain M × N neighborhood response characteristics. Finally, M × N neighborhood responses may be identifiedCharacterizing and forming a neighborhood response feature matrix

By analogy, the neighborhood response feature matrixes corresponding to the 30, 60, 90, 120 and 150 specific directions can be obtained

、

、

、

And

。

understandably, in order to find out real and effective signals from the K directional response characteristic matrices corresponding to the target pixel points, a corresponding adjacent region of each target pixel point needs to be selected, so that the K directional response characteristic matrices corresponding to all the neighborhood pixel points corresponding to the adjacent region are used for structure evaluation and comprehensive judgment, and the finally obtained neighborhood response characteristic matrices can contain information of all the neighborhood pixel points in the adjacent region, thereby being beneficial to ensuring that the finally obtained synthesized echo signals contain clearer detail information, not only reducing the signal-to-noise ratio of the ultrasonic images synthesized based on the synthesized echo signals, but also improving the resolution of the ultrasonic images.

As an example, in step S603, each target pixel point corresponds to K neighborhood response feature matrices, and the beam forming processor may sequentially determine one of the neighborhood response feature matrices as a target response feature matrix and determine the other neighborhood response feature matrices as associated response feature matrices. For example, the 1 st neighborhood response feature matrix of the K neighborhood response feature matrices may be determined as the target response feature matrix, and the 2 nd, 3 … … K-1 th and K neighborhood response feature matrices may be determined as the target response feature matrix, respectivelyThe 1 st, 2 … … k-2 nd and k-1 st associative response feature matrices. For example, the above 6 neighborhood response feature matrices

、

、

、

、

And

in, if the neighborhood response feature matrix

Is a target response feature matrix, then

、

、

、

And

is a correlation response feature matrix.

In the ultrasonic wave beam synthesis method provided by this embodiment, according to the neighboring region corresponding to each target pixel point, structure evaluation and comprehensive judgment are performed on K directional response feature matrices corresponding to all neighborhood pixel points in the neighboring region, so that the finally obtained neighborhood response feature matrix may include information of all neighborhood pixel points in the neighboring region, which is helpful for ensuring that the finally obtained synthesized echo signal includes clearer detail information, which not only can reduce the signal-to-noise ratio of the ultrasonic image synthesized based on the synthesized echo signal, but also can improve the resolution of the ultrasonic image. In this example, the target response feature matrix and the associated response feature matrix corresponding to the target response feature matrix are determined based on the K neighborhood response feature matrices, which is helpful for ensuring that a synthesized echo signal acquired by performing beam synthesis based on the target response feature matrix subsequently contains more image information, thereby improving the resolution of a finally imaged ultrasonic image.

In an embodiment, as shown in fig. 7, step S304, namely, obtaining K directional confidences corresponding to target pixel points according to the K target response feature matrices and the associated response feature matrix corresponding to each target response feature matrix, includes:

s701: and performing cross-correlation calculation on the target response characteristic matrix and the K-1 associated response characteristic matrices respectively to obtain K-1 cross-correlation matrices corresponding to the target response characteristic matrix.

S702: and summing K-1 cross correlation matrixes corresponding to the target response characteristic matrix to obtain the direction confidence corresponding to the target response characteristic matrix.

S703: and acquiring K direction confidence coefficients corresponding to the target pixel points based on the direction confidence coefficients corresponding to the K target response characteristic matrixes.

As an example, in step S701, the beam synthesis processor may perform cross-correlation calculation on the target response feature matrix and K-1 associated response feature matrices, respectively, to obtain K-1 cross-correlation matrices corresponding to the target response feature matrix, that is, perform cross-correlation calculation on the target response feature matrix and each associated response feature matrix, to obtain a cross-correlation matrix. For example, the target response feature matrix and the 1 st associated response feature matrix are cross-correlated, i.e., 1 cross-correlation matrix … … is obtained, and so on, i.e., K-1 cross-correlation matrices are obtained.

For example, of the 6 directional response feature matrices M (0), M (30), M (60), M (90), M (120), and M (150), if the directional response feature matrix M (0) is the target response feature matrix, M (30), M (60), M (90), M (120), and M (150) are associated response feature matrices; calculating a 1 st cross-correlation matrix corresponding to M (1) according to M (0) and M (30), calculating a 2 nd cross-correlation matrix corresponding to M (1) according to M (0) and M (60), calculating a 3 rd cross-correlation matrix corresponding to M (1) according to M (0) and M (90), calculating a 4 th cross-correlation matrix corresponding to M (1) according to M (0) and M (120), and calculating a 1 st cross-correlation matrix corresponding to M (1) according to M (0) and M (150).

For example, the above 6 neighborhood response feature matrices

、

、

、

、

And

in, if the neighborhood response feature matrix

Is a target response feature matrix, then

、

、

、

And

is a correlation response characteristic matrix; according to

And

computing

Corresponding 1 st cross-correlation matrix according to

And

computing

Corresponding 2 nd cross-correlation matrix according to

And

computing

Corresponding 3 rd cross-correlation matrix according to

And

computing

Corresponding 4 th cross-correlation matrix according to

And

computing

And obtaining K-1 cross correlation matrixes in the corresponding 5 th cross correlation matrix.

As an example, in step S702, the beam synthesis processor may sum K-1 cross-correlation matrices corresponding to the target response feature matrix, so as to obtain a directional confidence corresponding to the target response feature matrix. Understandably, the target response characteristic matrix corresponding to each specific direction needs to be subjected to cross-correlation calculation with other K-1 associated response characteristic matrices to determine K-1 cross-correlation matrices corresponding to the target response characteristic matrix, and the K-1 cross-correlation matrices need to be summed to determine a direction confidence coefficient corresponding to the target response characteristic matrix, namely, the direction confidence coefficient of the specific direction corresponding to the target response characteristic matrix.

As an example, in step S703, since one of the K directional response feature matrices is sequentially selected and determined as the target response feature matrix, the number of the target response feature matrices is K; and each target response characteristic matrix corresponds to one direction confidence, so the beam synthesis processor can acquire K direction confidences.

In this example, in step S701 and step S702, the direction confidence corresponding to each target response feature matrix is determined by using the following direction confidence formula:

wherein,

is as follows

The direction confidence corresponding to each target response characteristic matrix;

is as follows

A target response characteristic matrix for storing the target pixel point at the second

When the secondary ultrasonic wave is emitted, the

Target response characteristics corresponding to the channels;

is as follows

Corresponding to the target response characteristic matrix

An associative response feature matrix; is a cross-correlation operation.

In this example, the target response feature matrix

For storing the target pixel point at

When the secondary ultrasonic wave is emitted, the

And target response characteristics corresponding to the channels. Correlation response feature matrix

For storing the target pixel point at

When the secondary ultrasonic wave is emitted, the

And the corresponding associated response characteristics of each channel. The target response characteristic is an element in a target response characteristic matrix, specifically a neighborhood response characteristic, and is a matrix matched with the number of pixel points in a neighboring region. The correlation response characteristic is an element in a correlation response characteristic matrix, is also a neighborhood response characteristic, and is a matrix matched with the number of pixel points in a neighboring region. In this example, when the target response characteristic matrix is a directional response characteristic matrix, the elements of the target response characteristic matrix (i.e., the target response characteristics) are directional response characteristics; when the target response feature matrix is a direction neighborhood feature matrix, the elements of the target response feature matrix (i.e., the target response features) are neighborhood response features.

In an embodiment, the step S305, obtaining the target echo signal corresponding to the target pixel point according to the K directional confidences and the K target response feature matrices corresponding to the target pixel point, includes:

weighting K directional confidence coefficients and K target response characteristic matrixes corresponding to the target pixel points by adopting a target echo signal formula to obtain target echo signals corresponding to the target pixel points;

the target echo signal is formulated as

；

Wherein,

is a target pixel point at

When the secondary ultrasonic wave is emitted, the

Target echo signals corresponding to the channels;

is as follows

is as follows

And (5) a target response characteristic matrix.

Understandably, only by performing weighting processing on the direction confidence coefficients of the K characteristic directions and the target response characteristic matrix, only performing summation processing in the directions, the size of the matrix of the obtained M × N target echo signals is the same as that of the matrix of the M × N original echo signals, but the target echo signals effectively filter the clutter in the original echo signals, and only the real effective signals are retained, so that the finally obtained synthesized echo signals contain more detailed information, which not only can reduce the signal-to-noise ratio of the ultrasonic image synthesized based on the synthesized echo signals, but also can improve the resolution of the ultrasonic image.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

In one embodiment, an ultrasonic beam forming apparatus is provided, which corresponds to the ultrasonic beam forming method in the above-described embodiments one to one. As shown in fig. 8, the ultrasonic beam forming apparatus includes an original information matrix acquisition module 801, a directional response feature matrix acquisition module 802, a target response feature matrix determination module 803, a directional confidence acquisition module 804, a target echo signal acquisition module 805, and a synthesized echo signal acquisition module 806. The functional modules are explained in detail as follows:

an original information matrix obtaining module 801, configured to obtain an original information matrix corresponding to a target pixel, where the original information matrix includes M × N original echo signals, N is a number of superposition times, and M is a number of channels.

The directional response feature matrix obtaining module 802 is configured to perform directional filtering on the original information matrix corresponding to the target pixel point by using K directional deflection filters, and obtain K directional response feature matrices corresponding to the target pixel point.

A target response feature matrix determining module 803, configured to determine, according to the K directional response feature matrices, K target response feature matrices corresponding to the target pixel point and an associated response feature matrix corresponding to each target response feature matrix.

A direction confidence obtaining module 804, configured to obtain K direction confidences corresponding to the target pixel points according to the K target response feature matrices and the associated response feature matrix corresponding to each target response feature matrix.

And a target echo signal obtaining module 805, configured to obtain, according to the K directional confidence coefficients and the K target response feature matrices corresponding to the target pixel points, a target echo signal corresponding to the target pixel point.

A synthesized echo signal obtaining module 806, configured to perform coherent superposition on the target echo signal corresponding to the target pixel point, so as to obtain a synthesized echo signal corresponding to the target pixel point.

In an embodiment, the original information matrix obtaining module 801 includes:

and the digital echo signal receiving unit is used for receiving the digital echo signal sent by the ultrasonic probe.

And the corrected echo signal acquisition unit is used for carrying out delay correction processing on the digital echo signal and acquiring a corrected echo signal corresponding to the digital echo signal.

And the original information matrix acquisition unit is used for acquiring an original information matrix corresponding to the target pixel point based on the corrected echo signal.

In an embodiment, the directional response feature matrix obtaining module 802 includes:

and the directional response intensity matrix acquisition unit is used for processing the original information matrix corresponding to the target pixel point by adopting directional filtering kernels corresponding to the K directional deflection filters to acquire K directional response intensity matrices.

And the direction response characteristic matrix acquisition unit is used for processing the original information matrix corresponding to the target pixel point by adopting the K direction response intensity matrixes to acquire the K direction response characteristic matrixes corresponding to the target pixel point.

In an embodiment, the target response feature matrix determination module 803 includes:

and the adjacent region acquisition unit is used for acquiring an adjacent region corresponding to the target pixel point, the adjacent region comprises L adjacent pixel points, and K directional response characteristic matrixes corresponding to each adjacent pixel point.

And the neighborhood response characteristic matrix obtaining unit is used for obtaining K neighborhood response characteristic matrixes corresponding to the target pixel points according to the K × L directional response characteristic matrixes corresponding to the L neighborhood pixel points.

And the target response characteristic matrix determining unit is used for sequentially determining any one of the K neighborhood response characteristic matrixes corresponding to the target pixel point as a target response characteristic matrix, and determining the rest K-1 neighborhood response characteristic matrixes as associated response characteristic matrixes.

In an embodiment, the direction confidence obtaining module 804 includes:

and the cross-correlation matrix acquisition unit is used for performing cross-correlation calculation on the target response characteristic matrix and the K-1 associated response characteristic matrices respectively to acquire the K-1 cross-correlation matrices corresponding to the target response characteristic matrix.

And the cross-correlation matrix summation unit is used for summing K-1 cross-correlation matrixes corresponding to the target response characteristic matrix to obtain the direction confidence corresponding to the target response characteristic matrix.

And the direction confidence acquisition unit is used for acquiring K direction confidences corresponding to the target pixel points based on the direction confidences corresponding to the K target response characteristic matrixes.

In an embodiment, the target echo signal obtaining module 805 is configured to perform weighting processing on K directional confidence coefficients and K target response feature matrices corresponding to a target pixel point by using a target echo signal formula, so as to obtain a target echo signal corresponding to a target pixel point;

the target echo signal is formulated as

；

Wherein,

is a target pixel point at

When the secondary ultrasonic wave is emitted, the

Target echo signals corresponding to the channels;

is as follows

is as follows

And (5) a target response characteristic matrix.

For specific limitations of the ultrasound beamforming apparatus, reference may be made to the above limitations of the ultrasound beamforming method, which are not described herein again. The modules in the ultrasonic beam forming apparatus can be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the ultrasound device, and can also be stored in a memory in the ultrasound device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, an ultrasound apparatus is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the ultrasound beamforming method in the above embodiments is implemented, for example, as shown in S301-S306 in fig. 3, or as shown in fig. 4 to 7, which is not described herein again to avoid repetition. Alternatively, when the processor executes the computer program, the functions of the modules/units in the embodiment of the ultrasonic beam synthesis apparatus, such as the functions of the original information matrix obtaining module 801, the directional response characteristic matrix obtaining module 802, the target response characteristic matrix determining module 803, the directional confidence obtaining module 804, the target echo signal obtaining module 805, and the synthesized echo signal obtaining module 806 shown in fig. 8, are not described herein again to avoid repetition.

In an embodiment, a computer-readable storage medium is provided, and a computer program is stored on the computer-readable storage medium, and when being executed by a processor, the computer program implements the ultrasonic beam forming method in the foregoing embodiments, for example, S301 to S306 shown in fig. 3, or S301 to S306 shown in fig. 4 to 7, which are not repeated herein to avoid repetition. Alternatively, when being executed by the processor, the computer program implements the functions of the modules/units in the embodiment of the ultrasonic beam forming apparatus, such as the functions of the original information matrix obtaining module 801, the directional response characteristic matrix obtaining module 802, the target response characteristic matrix determining module 803, the directional confidence obtaining module 804, the target echo signal obtaining module 805, and the synthesized echo signal obtaining module 806 shown in fig. 8, which are not repeated herein for avoiding repetition.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims

1. An ultrasonic beam forming method, comprising:

2. The ultrasonic beam forming method according to claim 1, wherein said acquiring the original information matrix corresponding to the target pixel point comprises:

receiving a digital echo signal sent by an ultrasonic probe;

performing time delay correction processing on the digital echo signal to obtain a corrected echo signal corresponding to the digital echo signal;

and acquiring an original information matrix corresponding to the target pixel point based on the corrected echo signal.

3. The ultrasonic wave beam forming method according to claim 1, wherein the performing directional filtering on the original information matrix corresponding to the target pixel point by using K directional deflection filters to obtain K directional response feature matrices corresponding to the target pixel point includes:

processing an original information matrix corresponding to the target pixel point by adopting directional filtering kernels corresponding to K directional deflection filters to obtain K directional response intensity matrixes;

and processing the original information matrix corresponding to the target pixel point by adopting the K directional response intensity matrixes to obtain K directional response characteristic matrixes corresponding to the target pixel point.

4. The method according to claim 1, wherein said determining K target response feature matrices corresponding to said target pixel points and associated response feature matrices corresponding to each of said target response feature matrices according to K said directional response feature matrices comprises:

acquiring a neighboring region corresponding to the target pixel point, wherein the neighboring region comprises L neighborhood pixel points, and K directional response characteristic matrixes corresponding to each neighborhood pixel point;

acquiring K neighborhood response feature matrixes corresponding to the target pixel point according to K × L direction response feature matrixes corresponding to the L neighborhood pixel points;

and sequentially determining any one of the K neighborhood response characteristic matrixes corresponding to the target pixel point as a target response characteristic matrix, and determining the rest K-1 neighborhood response characteristic matrixes as associated response characteristic matrixes.

5. The method according to claim 1, wherein the obtaining K directional confidences corresponding to the target pixel points according to the K target response feature matrices and the associated response feature matrix corresponding to each target response feature matrix comprises:

performing cross-correlation calculation on the target response characteristic matrix and the K-1 associated response characteristic matrices respectively to obtain K-1 cross-correlation matrices corresponding to the target response characteristic matrix;

summing K-1 cross correlation matrixes corresponding to the target response characteristic matrix to obtain a direction confidence coefficient corresponding to the target response characteristic matrix;

and acquiring K directional confidence degrees corresponding to the target pixel points based on the directional confidence degrees corresponding to the K target response characteristic matrixes.

6. The method according to claim 1, wherein the obtaining the target echo signal corresponding to the target pixel point according to the K directional confidences corresponding to the target pixel point and the K target response feature matrices comprises:

weighting K directional confidence coefficients and K target response characteristic matrixes corresponding to the target pixel point by adopting a target echo signal formula to obtain a target echo signal corresponding to the target pixel point;

the target echo signal is formulated as

；

Wherein,

for the target pixel point is at

When the secondary ultrasonic wave is emitted, the

Target echo signals corresponding to the channels;

is as follows

is as follows

And (5) a target response characteristic matrix.

7. An ultrasonic beam forming apparatus, comprising:

8. The ultrasonic beam forming apparatus of claim 7, wherein the raw information matrix acquisition module comprises:

the digital echo signal receiving unit is used for receiving a digital echo signal sent by the ultrasonic probe;

a corrected echo signal acquiring unit, configured to perform delay correction processing on the digital echo signal to acquire a corrected echo signal corresponding to the digital echo signal;

9. The ultrasound beamforming apparatus according to claim 7 wherein said directional response characteristic matrix acquisition module comprises:

a directional response intensity matrix obtaining unit, configured to process an original information matrix corresponding to the target pixel point by using directional filtering kernels corresponding to K directional deflection filters, so as to obtain K directional response intensity matrices;

and the directional response characteristic matrix acquisition unit is used for processing the original information matrix corresponding to the target pixel point by adopting the K directional response intensity matrixes to acquire K directional response characteristic matrixes corresponding to the target pixel point.

10. The ultrasonic beam forming apparatus of claim 7 wherein the target response characteristic matrix determination module comprises:

a neighborhood region obtaining unit, configured to obtain a neighborhood region corresponding to the target pixel point, where the neighborhood region includes L neighborhood pixel points, and K directional response feature matrices corresponding to each of the neighborhood pixel points;

a neighborhood response feature matrix obtaining unit, configured to obtain K neighborhood response feature matrices corresponding to the target pixel point according to K × L directional response feature matrices corresponding to the L neighborhood pixel points;

11. The ultrasound beamforming apparatus according to claim 7 wherein said directional confidence acquisition module comprises:

a cross-correlation matrix obtaining unit, configured to perform cross-correlation calculation on the target response feature matrix and K-1 correlation response feature matrices, respectively, to obtain K-1 cross-correlation matrices corresponding to the target response feature matrix;

the cross-correlation matrix summation unit is used for summing K-1 cross-correlation matrixes corresponding to the target response characteristic matrix to obtain the direction confidence corresponding to the target response characteristic matrix;

and the direction confidence coefficient acquisition unit is used for acquiring K direction confidence coefficients corresponding to the target pixel points based on the direction confidence coefficients corresponding to the K target response characteristic matrixes.

12. The ultrasonic beam forming apparatus according to claim 7, wherein the target echo signal acquiring module is configured to perform weighting processing on the K directional confidence coefficients and the K target response feature matrices corresponding to the target pixel point by using a target echo signal formula, so as to acquire a target echo signal corresponding to the target pixel point;

the target echo signal is formulated as

；

Wherein,

for the target pixel point is at

When the secondary ultrasonic wave is emitted, the

Target echo signals corresponding to the channels;

is as follows

is as follows

And (5) a target response characteristic matrix.

13. An ultrasound device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the ultrasound beamforming method according to any of claims 1 to 6 when executing the computer program.

14. A computer-readable storage medium storing a computer program which, when executed by a processor, implements the ultrasound beamforming method according to any of claims 1 to 6.