Sidelobe anonymous beam forming method combined with symbol coherence

Abstract

The invention discloses a sidelobe anonymous wave beam forming method combined with symbol coherence, and relates to the field of ultrasonic imaging. The method comprises the following steps: performing focusing delay on sampled echo data to obtain time-aligned echo signals; a complete ultrasonic array is divided into two sub-arrays, and a delay superposition beam forming algorithm is performed on echo signals of the two sub-arrays to obtain two groups of output signals; respectively adding and subtracting the two groups of output signals to preliminarily obtain output signals of the main beam former and the auxiliary beam former; performing simplification processing on the symbol multiplied by the coherence factor, and weighting the output of the main beam former to obtain the final output of the main beam former; weighting the output of the auxiliary beam former by adopting the anonymous parameters to obtain the final output of the auxiliary beam former; the output data of the main beam former and the output data of the auxiliary beam former are compared, and final imaging data are obtained and imaged; according to the invention, the resolution ratio and contrast ratio of ultrasonic imaging are obviously improved.

Description

Technical Field

[0001] The invention relates to the field of ultrasonic imaging, and in particular to a sidelobe-annihilating beamforming method combined with symbol coherence. Background Art

[0002] Ultrasonic imaging technology is a detection technology with high sensitivity, accurate defect positioning, high efficiency, low cost, harmlessness to the human body and ease of on-site use. It is widely used in medical, industrial and other detection fields. Among them, digital beamforming is the most important link in ultrasonic imaging. At present, the most basic and widely used ultrasonic imaging method is the delay and summation beamforming method (DAS), which obtains imaging data by simply superimposing the echo data after delay. However, the DAS beamforming method will have a wide main lobe and high side lobes, resulting in a decrease in imaging resolution and contrast, and obtaining poor quality ultrasonic images.

[0003] In 1969, Capon first proposed the minimum variance adaptive beamforming method (MV) for narrowband radar, which was subsequently improved and applied to ultrasonic imaging. The core of the MV algorithm is to minimize the variance of the output signal by adjusting the weighting vector while keeping the gain in the desired direction unchanged. Although the MV algorithm has a significant effect in improving image resolution, it is less effective in dealing with clutter and noise. In addition, the MV algorithm requires the inversion of the covariance matrix, which has high complexity and long imaging time. Coherence Factor (CF) is another adaptive beamforming method. The coherence factor is defined as the ratio between coherent energy and incoherent energy in the echo signal. However, the CF method will over-suppress incoherent signals, resulting in black spot artifacts and reducing the background level. The above two adaptive beamforming methods cannot meet the requirements of high resolution, high contrast and low complexity at the same time. Therefore, while ensuring the improvement of imaging quality, reducing computational complexity is a problem that still needs to be solved.

[0004] In summary, there is an urgent need for an adaptive beamforming method that can significantly improve the resolution and contrast of ultrasound imaging with lower complexity. Summary of the invention

[0005] The object of the present invention is to provide a sidelobe-annihilating beamforming method combined with symbol coherence, which can improve the resolution and contrast of ultrasonic imaging with lower complexity.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for sidelobe-masking adaptive beamforming combined with symbol coherence comprises the following steps:

[0008] S1: performing focusing delay processing on the echo signal obtained by sampling the ultrasonic array element to obtain a time-aligned ultrasonic echo signal x(p);

[0009] S2: a complete ultrasound array of length N is divided into two sub-arrays of length N / 2, and delay-addition beamforming is performed on the two sub-arrays respectively to obtain two sets of output signals;

[0010] S3: adding and subtracting the two sets of output data to obtain the output signal of the main beamformer and the output signal of the auxiliary beamformer respectively;

[0011] S4: simplify the processing of multiplying the symbol by the coherence factor and weighting the main beamformer to obtain the output signal of the main beamformer with suppressed clutter and noise;

[0012] S5: weighting the auxiliary beamformer using the anonymity parameter to obtain an output signal of the auxiliary beamformer;

[0013] S6: Compare the output signal of the main beamformer with the output signal of the auxiliary beamformer to obtain final imaging data, and perform imaging.

[0014] Furthermore, step S2 includes the following contents:

[0015] S21, performing delay-addition beamforming on the sub-array data:

[0016]

[0017] In the formula, Σ represents the summation symbol, N represents the number of array elements, and x i (p) and x j (p) respectively represent the echo data of the i-th and j-th array elements of the two sub-arrays after time alignment, and s1(p) and s2(p) respectively represent the output signals after superposition of the two sub-arrays.

[0018] Furthermore, step S3 includes the following contents:

[0019] S31, respectively adding and subtracting the signals obtained after the sub-array delay-addition beamforming:

[0020] s M (p) = s1(p) + s2(p)

[0021] s A (p) = s1(p) - s2(p)

[0022] In the formula, s M (p) and s A (p) represent the output signals of the main beamformer and the auxiliary beamformer, respectively.

[0023] Furthermore, step S4 includes the following contents:

[0024] S41. When x(p) is positive, let b(p) be +1; when x(p) is zero, let b(p) be 0; when x(p) is negative, let b(p) be -1:

[0025]

[0026] Where b(p) represents the symbol value of the echo data of the corresponding array element, and x(p) represents the echo data of each array;

[0027] S42, calculate SMCF and simplify it to obtain an improved SMCF, i.e., ISMCF:

[0028]

[0029] In the formula, Σ represents the summation symbol, N represents the number of array elements, and b i (p) and b j (p) represent the symbol values ​​of the i-th and j-th array data respectively;

[0030] S43, using ISMCF to weight the output signal of the main beamformer to obtain the final output of the main beamformer:

[0031] s FM (p) = ISMCF (p) s M (p)

[0032] In the formula, s FM (p) represents the final main beamformer output signal.

[0033] Furthermore, step S5 includes the following contents:

[0034] S51, weighting the output of the auxiliary beamformer by using the anonymity parameter:

[0035] s FA (p) = ω·s A (p)

[0036] In the formula, ω represents the anonymity parameter, s FA (p) represents the output signal of the auxiliary beamformer;

[0037] Furthermore, step S6 includes the following contents:

[0038] S61, comparing the output signals of the main beamformer and the auxiliary beamformer. When the output signal of the main beamformer is greater than the output signal of the auxiliary beamformer, the final output is equal to the output of the main beamformer; when the output signal of the main beamformer is less than the output signal of the auxiliary beamformer, the final output is equal to the output of the main beamformer divided by the anonymization parameter:

[0039]

[0040] In the formula, s CSC-SC (p) represents the final imaging data, ω represents the anonymization parameter, s FA (p) represents the output signal of the auxiliary beamformer, s FM (p) represents the final main beamformer output signal.

[0041] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the present invention can significantly improve the resolution and contrast of ultrasonic imaging, does not involve matrix inversion, only includes simple numerical operations, has low computational complexity, and can be used in ultrasonic imaging systems for real-time imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1 is a flow chart of the method of the present invention;

[0044] Figure 2 These are the steel block defect imaging images of the four algorithms;

[0045] Figure 3 The lateral resolution curves of steel block imaging using four algorithms are shown below;

[0046] Figure 4 This is a comparison chart of steel block imaging parameters using four algorithms;

[0047] Figure 5 These are the steel plate weld imaging images of 4 algorithms;

[0048] Figure 6 The lateral resolution curves of steel plate weld imaging using four algorithms;

[0049] Figure 7 This is a comparison chart of steel plate weld imaging parameters using four algorithms. DETAILED DESCRIPTION

[0050] 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 only 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.

[0051] The purpose of the present invention is to provide a sidelobe-annihilating beamforming method combined with symbol coherence to solve the problems of insufficient resolution and contrast and high computational complexity in existing ultrasonic imaging, and is suitable for real-time ultrasonic imaging.

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] Example 1

[0054] like Figure 1 As shown, the sidelobe-anonymous beamforming method combined with symbol coherence provided by the present invention comprises the following steps:

[0055] S1: performing focusing delay processing on the echo signal sampled by the ultrasonic array element to obtain a time-aligned ultrasonic echo signal x(p);

[0056] S2: a complete ultrasound array of length N is divided into two sub-arrays of length N / 2, and delay-addition beamforming is performed on the two sub-arrays respectively to obtain two sets of output signals;

[0057] Specifically, step S2 includes the following contents:

[0058] S21, performing delay-addition beamforming on the sub-array data:

[0059]

[0060] In the formula, ∑ represents the summation symbol, N represents the number of array elements, and x i (p) and x j (p) respectively represent the echo data of the i-th and j-th array elements of the two sub-arrays after time alignment, and s1(p) and s2(p) respectively represent the output signals after superposition of the two sub-arrays.

[0061] S3: adding and subtracting the two sets of output data to obtain the output signal of the main beamformer and the output signal of the auxiliary beamformer respectively;

[0062] Specifically, step S3 includes the following contents:

[0063] S31, respectively adding and subtracting the signals obtained after the sub-array delay-addition beamforming:

[0064] s M (p) = s1(p) + s2(p)

[0065] s A (p) = s1(p) - s2(p)

[0066] In the formula, s M (p) and s A (p) represent the output signals of the main beamformer and the auxiliary beamformer, respectively.

[0067] S4: simplify the processing of multiplying the symbol by the coherence factor and weighting the main beamformer to obtain the output signal of the main beamformer with suppressed clutter and noise;

[0068] Specifically, step S4 includes the following contents:

[0069] S41. When x(p) is positive, let b(p) be +1; when x(p) is zero, let b(p) be 0; when x(p) is negative, let b(p) be -1:

[0070]

[0071] Where b(p) represents the symbol value of the echo data of the corresponding array element, and x(p) represents the echo data of each array;

[0072] S42, calculate SMCF and simplify it to obtain an improved SMCF, i.e., ISMCF:

[0073]

[0074] In the formula, Σ represents the summation symbol, N represents the number of array elements, and b i (p) and b j (p) represent the symbol values ​​of the i-th and j-th array data respectively;

[0075] S43, using ISMCF to weight the output signal of the main beamformer to obtain the final output of the main beamformer:

[0076] s FM (p) = ISMCF (p) s M (p)

[0077] In the formula, s FM (p) represents the final main beamformer output signal.

[0078] S5: weighting the auxiliary beamformer using the anonymity parameter to obtain an output signal of the auxiliary beamformer;

[0079] Specifically, step S5 includes the following contents:

[0080] S51, weighting the output of the auxiliary beamformer by using the anonymity parameter:

[0081] s FA (p) = ω·s A (p)

[0082] In the formula, ω represents the anonymity parameter, s FA (p) represents the output signal of the auxiliary beamformer.

[0083] S6: comparing the output signal of the main beamformer with the output signal of the auxiliary beamformer to obtain final imaging data, and performing imaging;

[0084] Specifically, step S6 includes the following contents:

[0085] S61, comparing the output signals of the main beamformer and the auxiliary beamformer. When the output signal of the main beamformer is greater than the output signal of the auxiliary beamformer, the final output is equal to the output of the main beamformer; when the output signal of the main beamformer is less than the output signal of the auxiliary beamformer, the final output is equal to the output of the main beamformer divided by the anonymization parameter:

[0086]

[0087] In the formula, s CSC-SC (p) represents the final imaging data, ω represents the anonymization parameter, s FA (p) represents the output signal of the auxiliary beamformer, s FM (p) represents the final main beamformer output signal.

[0088] In this example, the beneficial effects of the present invention are demonstrated by experimental verification:

[0089] This experiment uses the 5L128 ultrasonic probe produced by Guangdong Shantou Ultrasonic Electronics Co., Ltd. to collect ultrasonic echo data, and the algorithm is verified in MATLAB R2024a. In the imaging target area of ​​the steel block experiment, 12 defect points with equal spacing (spacing of 2 mm) and a depth of 8 mm are arranged. Figure 2The results of imaging the steel block using the Delay and Sum algorithm (DAS), Coherence Factor (CF), Sign Coherence Factor (SCF) and the method proposed in this invention (Sidelobe Concealment Combined with Sign Correlation, CSC-SC) are intuitively displayed. The results show that the DAS algorithm has the worst imaging effect, with a lot of noise and clutter, and the main lobe width of its defect point is the widest and the sidelobe level is the highest. Compared with DAS, the images of the CF and SCF algorithms significantly reduce noise and clutter. Compared with all the above algorithms, CSC-SC further improves the resolution while suppressing clutter to the point where it is almost invisible. CSC-SC has the highest resolution and contrast. In short, the algorithm proposed in this article has the best imaging effect.

[0090] Figure 3 The lateral resolution curves of steel block defects with different algorithms show that the sidelobe suppression effect of the invention is the best and the main lobe width is the smallest. On this basis, we calculated the full width at half maximum (Full Width at Half Maximum, FWHM), array performance index (Array Performance Index, API), and contrast ratio (Contrast Ratio, CR) of all defect points. For detailed data, see Table 1.

[0091] Table 1 FWMH, API and CR values ​​of steel block imaging using different algorithms

[0092]

[0093] According to Table 1, the CSC-SC method proposed in the present invention has the smallest FWHM and API value, and the largest CR value. In order to intuitively compare the performance of each algorithm, we visualized its parameters in the form of a bar graph, as shown in Figure 4 As shown, it can be seen that the CSC-SC method proposed in the present invention has the best imaging resolution and contrast.

[0094] In order to further improve the performance of the algorithm, this experiment imaged the weld defects of the steel plate. The imaging results are as follows: Figure 5 As shown in the figure, the DAS algorithm has the worst imaging effect and has a lot of noise and clutter. The CSC-SC method proposed in the present invention maximizes the resolution and greatly suppresses noise and clutter.

[0095] Figure 6Table 2 shows the lateral resolution curves of defects in steel plate welds using different algorithms. It can be seen that the sidelobe suppression effect of the present invention is the best and the main lobe width is the smallest. On this basis, we calculated the FWHM, API and CR values ​​of steel plate weld imaging using different algorithms, as shown in Table 2.

[0096] Table 2 FWMH, API and CR values ​​of steel plate weld imaging using different algorithms

[0097]

[0098] According to Table 2, the CSC-SC method proposed in the present invention has the smallest FWHM and API value, and the largest CR value. Figure 7 As shown, the CSC-SC method proposed in the present invention has the lowest API and FWHM values ​​and the highest CR value among all algorithms.

[0099] In summary, the CSC-SC method proposed in the present invention has the highest resolution, contrast and best imaging effect among the four methods.

[0100] Example 2

[0101] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the sidelobe-annihilating beamforming method combined with symbol coherence in embodiment 1.

[0102] Example 3

[0103] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the sidelobe-annihilating beamforming method combined with symbol coherence in embodiment 1.

[0104] Example 4

[0105] A computer program product includes a computer program, which, when executed by a processor, implements the sidelobe-annihilating beamforming method combined with symbol coherence in embodiment 1.

[0106] Example 5

[0107] A computer device, which may be a database. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store pending transactions. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the sidelobe-annihilating beamforming method combined with symbol coherence in Example 1 is implemented.

[0108] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0109] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided by the present invention may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited thereto. The processor involved in each embodiment provided by the present invention may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited thereto.

[0110] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A sidelobe-annihilating beamforming method combined with symbol coherence, characterized in that: The method comprises the following steps: S1: performing focusing delay processing on the echo signal obtained by sampling the ultrasonic array element to obtain a time-aligned ultrasonic echo signal x(p); S2: a complete ultrasound array of length N is divided into two sub-arrays of length N / 2, and delay-addition beamforming is performed on the two sub-arrays respectively to obtain two sets of output signals; S3: adding and subtracting the two sets of output data to obtain the output signal of the main beamformer and the output signal of the auxiliary beamformer respectively; S4: simplify the processing of multiplying the symbol by the coherence factor and weighting the main beamformer to obtain the output signal of the main beamformer with suppressed clutter and noise; S5: weighting the auxiliary beamformer using the anonymity parameter to obtain an output signal of the auxiliary beamformer; S6: Compare the output signal of the main beamformer with the output signal of the auxiliary beamformer to obtain final imaging data, and perform imaging.

2. The sidelobe-masking beamforming method combined with symbol coherence according to claim 1, characterized in that: Step S2: a complete ultrasound array of length N is divided into two sub-arrays of length N / 2, and delay-addition beamforming is performed on the two sub-arrays respectively to obtain two groups of output signals. The specific steps are as follows: S21, performing delay-addition beamforming on the sub-array data: In the formula, ∑ represents the summation symbol, N represents the number of array elements, and x i (p) and x j (p) represents the echo data of the i-th and j-th array elements of the two sub-arrays after time alignment, and s1(p) and s2(p) represent the output signals of the two sub-arrays after superposition.

3. The sidelobe-masking beamforming method combined with symbol coherence according to claim 1, characterized in that: Step S3: Add and subtract the two sets of output data to obtain the output signal s of the main beamformer respectively. M (p) and the output signal s of the auxiliary beamformer A (p), the specific steps are as follows: S31, respectively adding and subtracting the signals obtained after the sub-array delay-addition beamforming: s M (p)=s1(p)+s2(p) s A (p)=s1(p)-s2(p) In the formula, s M (p) and s A (p) represent the output signals of the main beamformer and the auxiliary beamformer, respectively.

4. The sidelobe-masking beamforming method combined with symbol coherence according to claim 1, characterized in that: Step S4: Simplify the processing of multiplying the symbol by the coherence factor and weight the main beamformer to obtain the output signal of the main beamformer with suppressed clutter and noise. The specific steps are as follows: S41. When x(p) is positive, let b(p) be +1; when x(p) is 0, let b(p) be 0; When x(p) is negative, let b(p) be -1: Where b(p) represents the symbol value of the echo data of the corresponding array element, and x(p) represents the echo data of each array; S42, calculate SMCF and simplify it to obtain an improved SMCF, i.e., ISMCF: In the formula, Σ represents the summation symbol, N represents the number of array elements, and b i (p) and b j (p) represent the symbol values ​​of the i-th and j-th array data respectively; S43, using ISMCF to weight the output signal of the main beamformer to obtain the final output of the main beamformer: s FM (p)=ISMCF(p)·s M (p) In the formula, s FM (p) represents the final main beamformer output signal.

5. The sidelobe-masking beamforming method combined with symbol coherence according to claim 1, characterized in that: Step S5: weighting the auxiliary beamformer with the anonymity parameter to obtain the output signal of the auxiliary beamformer. The specific steps are as follows: S51, weighting the output of the auxiliary beamformer using the anonymity parameter: s FA (p)=ω·s A (p) In the formula, ω represents the anonymity parameter, s FA (p) represents the output signal of the auxiliary beamformer.

6. The sidelobe-masking beamforming method combined with symbol coherence according to claim 1, characterized in that: Step S6: Compare the output signal of the main beamformer with the output signal of the auxiliary beamformer to obtain final imaging data, and perform imaging. The specific steps are as follows: S61, comparing the output signals of the main beamformer and the auxiliary beamformer. When the output signal of the main beamformer is greater than the output signal of the auxiliary beamformer, the final output is equal to the output of the main beamformer; when the output signal of the main beamformer is less than the output signal of the auxiliary beamformer, the final output is equal to the output of the main beamformer divided by the anonymization parameter: In the formula, s CSC-SC (p) represents the final imaging data, ω represents the anonymization parameter, s FA (p) represents the output signal of the auxiliary beamformer, s FM (p) represents the final main beamformer output signal.

Images