A method, system and electronic device for predictive reconstruction of down-sampled ultrasonic plane waves

Abstract

The application discloses a down-sampling ultrasonic plane wave prediction reconstruction method and system and electronic equipment, and relates to the technical field of ultrasonic imaging. The method comprises the following steps: obtaining the measurement values of echo data of 2P+1 angle-continuous ultrasonic plane waves of a region to be imaged; determining the (P+1)th ultrasonic plane wave as a key frame and other ultrasonic plane waves as non-key frames; respectively performing blocking on each echo data according to a preset block size to obtain a plurality of echo blocks; randomly setting a measurement matrix for the echo blocks of each non-key frame based on the preset block size; sampling each echo block based on the measurement matrix to obtain sampling data; searching for adjacent echo blocks with the center of a current echo block as the origin to obtain a current hypothesis set; determining a prediction value based on the measurement matrix and the current hypothesis set; determining a reconstruction value based on the sampling data of the current echo block, the measurement matrix and the prediction value; and determining a reconstructed ultrasonic plane wave based on all reconstruction values to realize imaging. The application improves the prediction reconstruction precision of the ultrasonic plane wave.

Description

Technical Field

[0001] This invention relates to the field of ultrasound imaging technology, and in particular to a method, system, and electronic device for predicting and reconstructing downsampled ultrasound plane waves. Background Technology

[0002] Ultrasound, due to its concentrated energy, good directivity, economy, and safety, is widely used in non-destructive testing and medical diagnostics. To achieve a higher signal-to-noise ratio, ultrasound imaging typically requires multiple signal channels to obtain echo signals, placing a significant burden on the hardware's data sampling capabilities. Plane wave imaging, as an ultrafast ultrasound imaging method, uses multi-frame composite technology to improve image quality, but it also generates a large amount of echo data. This results in substantial data storage and transmission for portable ultrasound instruments, further increasing the hardware complexity and impacting instrument performance. The compressed sensing (CS) framework indicates that sparse signals can be accurately reconstructed under conditions far below the Nyquist sampling rate. Since ultrasound echo signals exhibit sparse characteristics in certain transform domains, CS reconstruction algorithms can reconstruct sparsely sampled ultrasound echo signals, reducing the sampling rate and subsequent data storage pressure.

[0003] However, traditional sparsity reconstruction algorithms often use the minimum 1 or 0 norm of the sparse domain as the signal reconstruction criterion, ignoring the characteristics of the imaging mode and other prior knowledge of the ultrasound signal, resulting in inaccurate signal reconstruction. Furthermore, signal sparseness (CS) relies heavily on signal sparsity. When the signal lacks sufficient sparsity or the noise level is too high, significant errors may occur in signal reconstruction, leading to artifacts in the beamforming image. This results in problems such as the image being heavily covered by artifacts, low contrast, and high sidelobes, causing a severe loss of useful information.

[0004] In summary, in addition to sparsity, there is an urgent need for a reconstruction algorithm that can effectively utilize the characteristics of ultrasound imaging modes and their echo signals to reconstruct the original signal with high accuracy at a low sampling rate, thus ensuring the quality of ultrasound imaging. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, and electronic device for predicting and reconstructing downsampled ultrasound plane waves, which improves the accuracy of ultrasound plane wave prediction and reconstruction and enhances ultrasound imaging quality.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A predictive reconstruction method for downsampled ultrasonic plane waves, comprising:

[0008] Acquire the measured values ​​of echo data of 2P+1 consecutive ultrasonic plane waves at different angles in the region to be imaged;

[0009] The P+1th ultrasonic plane wave is identified as a key frame, and all ultrasonic plane waves in the 2P+1 ultrasonic plane waves except for the key frame are identified as non-key frames.

[0010] Each echo data is divided into blocks according to a preset block size to obtain multiple corresponding echo blocks; based on the preset block size, a corresponding measurement matrix is ​​set for each echo block of each non-key frame at random.

[0011] The sampling data is obtained by sampling each echo block based on the measurement matrix;

[0012] Determine the reconstruction value of each echo block in each frame; wherein, the process of determining the reconstruction value of the current echo block in any current frame includes:

[0013] Using the center of the current echo block as the origin, search for neighboring echo blocks to obtain the corresponding current hypothesis set;

[0014] Based on the measurement matrix corresponding to the current echo block and the current hypothesis set, the predicted value of the current echo block is determined;

[0015] Based on the sampling data, measurement matrix, and predicted value of the current echo block, the reconstruction value of the current echo block is determined;

[0016] Based on the reconstruction values ​​of all echo blocks, the reconstructed ultrasonic plane wave is determined, thereby achieving imaging.

[0017] Optionally, each echo block is sampled based on the measurement matrix to obtain sampled data, specifically including:

[0018] The measurement values ​​of each non-key frame are sparsely sampled using all the measurement matrices corresponding to each non-key frame to obtain the corresponding sampled data;

[0019] Non-sparse sampling is performed on the measurements of keyframes to obtain sampled data.

[0020] Optionally, based on the measurement matrix corresponding to the current echo block and the current hypothesis set, the predicted value of the current echo block is determined, specifically including:

[0021] Calculate the prediction weight coefficients of the current echo block based on the measurement matrix corresponding to the current echo block and the current hypothesis set;

[0022] The predicted value of the current echo block is calculated based on the current set of assumptions and the prediction weight coefficient of the current echo block.

[0023] Optionally, based on the sampling data, measurement matrix, and predicted value of the current echo block, the reconstruction value of the current echo block is determined, specifically including:

[0024] The residual of the current echo block is calculated based on the sampling data, measurement matrix, and predicted value of the current echo block.

[0025] The residual reconstruction algorithm is used to reconstruct the residual of the current echo block to obtain the reconstructed residual value of the current echo block;

[0026] The reconstruction value of the current echo block is calculated based on the reconstruction residual value and the prediction value of the current echo block.

[0027] Optionally, based on the reconstructed values ​​of all echo blocks, the reconstructed ultrasound plane wave is determined to achieve imaging, specifically including:

[0028] Based on the reconstruction values ​​of all echo blocks corresponding to each frame, the reconstructed ultrasonic plane wave of the corresponding frame is determined.

[0029] The reconstructed ultrasonic plane wave is determined based on the reconstructed ultrasonic plane wave of all frames, thereby achieving imaging.

[0030] A predictive reconstruction system for downsampled ultrasonic plane waves, comprising:

[0031] The measurement acquisition module is used to acquire the measurement values ​​of echo data of 2P+1 consecutive ultrasonic plane waves at different angles in the area to be imaged;

[0032] The framing module is used to determine the P+1th ultrasonic plane wave as a key frame and to determine all ultrasonic plane waves other than the key frame in the 2P+1 ultrasonic plane waves as non-key frames.

[0033] The block segmentation module is used to divide each echo data into blocks according to a preset block size to obtain multiple corresponding echo blocks; based on the preset block size, a corresponding measurement matrix is ​​set for each echo block of each non-key frame randomly.

[0034] The sampling module is used to sample each echo block based on the measurement matrix to obtain sampling data;

[0035] The reconstruction value determination module is used to determine the reconstruction value of each echo block in each frame; wherein, the process of determining the reconstruction value of the current echo block in any current frame includes:

[0036] Using the center of the current echo block as the origin, search for neighboring echo blocks to obtain the corresponding current hypothesis set;

[0037] Based on the measurement matrix corresponding to the current echo block and the current hypothesis set, the predicted value of the current echo block is determined;

[0038] Based on the sampling data, measurement matrix, and predicted value of the current echo block, the reconstruction value of the current echo block is determined;

[0039] The imaging module is used to determine the reconstructed ultrasonic plane wave based on the reconstruction values ​​of all echo blocks, thereby achieving imaging.

[0040] An electronic device includes a memory and a processor, the memory storing a computer program, and the processor running the computer program to enable the electronic device to perform the aforementioned predictive reconstruction method for downsampled ultrasonic plane waves.

[0041] Optionally, the memory is a readable storage medium.

[0042] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0043] This invention discloses a prediction and reconstruction method, system, and electronic device for downsampled ultrasound plane waves. First, measurements of echo data from 2P+1 consecutive angled ultrasound plane waves in the region to be imaged are acquired. The (P+1)th ultrasound plane wave is designated as a keyframe, and all ultrasound plane waves in the 2P+1 waves except the keyframe are designated as non-keyframes. Each echo data is divided into blocks according to a preset block size, resulting in multiple corresponding echo blocks. Based on the preset block size, a corresponding measurement matrix is ​​set for each random echo block of each non-keyframe. Based on the measurement matrix, each echo... The process involves sampling echo blocks to obtain sampled data. Next, the reconstructed values ​​of each echo block in each frame are determined. The determination of the reconstructed value of the current echo block in any given frame includes: searching for neighboring echo blocks with the center of the current echo block as the origin to obtain the corresponding current hypothesis set; determining the predicted value of the current echo block based on the measurement matrix and the current hypothesis set; determining the reconstructed value of the current echo block based on the sampled data, measurement matrix, and predicted value; and finally, determining the reconstructed ultrasound plane wave based on the reconstructed values ​​of all echo blocks, thus achieving imaging. Compared to traditional sparse reconstruction methods, the reference frame multi-hypothesis prediction method has better prediction and reconstruction capabilities for ultrasound plane wave signals, while reducing the dependence on the sparsity of the original echo signal, thereby improving the prediction and reconstruction accuracy of ultrasound plane waves and enhancing ultrasound imaging quality. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the prediction and reconstruction method for downsampled ultrasonic plane waves provided in Embodiment 1 of the present invention;

[0046] Figure 2 A schematic diagram of the predictive reconstruction method flow;

[0047] Figure 3 This is a schematic diagram of the imaging results for a point target with full sampling.

[0048] Figure 4 A schematic diagram of the point target imaging results from block-based compressed sensing;

[0049] Figure 5 A schematic diagram of the point target imaging results from multi-hypothesis prediction compressed sensing;

[0050] Figure 6 A schematic diagram of the point target imaging results reconstructed using multiple hypotheses prediction with reference frames;

[0051] Figure 7 This is a schematic diagram of the imaging results of the sound-absorbing spots from the full sampling.

[0052] Figure 8 A schematic diagram of the sound-absorbing spot imaging results from block-compressed sensing;

[0053] Figure 9 A schematic diagram of the sound-absorbing spot imaging results from multi-hypothesis prediction compressed sensing;

[0054] Figure 10 A schematic diagram of the sound-absorbing spot imaging results reconstructed using multiple assumptions and a reference frame. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] The purpose of this invention is to provide a method, system, and electronic device for predicting and reconstructing downsampled ultrasound plane waves, aiming to improve the accuracy of ultrasound plane wave prediction and reconstruction and improve ultrasound imaging quality.

[0057] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] Example 1

[0059] Figure 1 This is a schematic diagram of the prediction and reconstruction method for downsampling ultrasonic plane waves provided in Embodiment 1 of the present invention. Figure 1As shown, the prediction and reconstruction method for downsampled ultrasonic plane waves in this embodiment includes:

[0060] Step 101: Obtain the measured values ​​of echo data of 2P+1 consecutive ultrasonic plane waves at different angles in the area to be imaged.

[0061] Step 102: Determine the P+1th ultrasonic plane wave as a keyframe, and determine all ultrasonic plane waves other than the keyframes in the 2P+1 ultrasonic plane waves as non-keyframes.

[0062] Step 103: Divide each echo data into blocks according to a preset block size to obtain multiple corresponding echo blocks; based on the preset block size, set the corresponding measurement matrix for each echo block of each non-key frame.

[0063] Step 104: Sample each echo block based on the measurement matrix to obtain sampled data.

[0064] As an optional implementation, step 104 specifically includes:

[0065] The measurement values ​​of each non-key frame are sparsely sampled using all the measurement matrices corresponding to each non-key frame to obtain the corresponding sampled data.

[0066] Specifically, the formula for sparse sampling of the p-th non-keyframe is:

[0067]

[0068] Among them, y p Φ represents the sampled data corresponding to the p-th non-keyframe; Φ is the matrix composed of all measurement matrices corresponding to the p-th non-keyframe; Φ B Let x be the measurement matrix corresponding to an echo block in any non-key frame; the measurement matrices for all echo blocks are identical. p,1 x is the measurement value of the first echo block in the p-th non-keyframe; p,L Let L be the measurement value of the Lth echo block in the pth non-keyframe, where L = (N × M) / B. 2 N is the signal sampling length, M is the number of array elements, and B is the preset block size.

[0069] Non-sparse sampling is performed on the measurements of keyframes to obtain sampled data.

[0070] Step 105: Determine the reconstruction value of each echo block in each frame.

[0071] The process of determining the reconstruction value of the current echo block in any current frame includes:

[0072] Step 1051: Using the center of the current echo block as the origin, search for neighboring echo blocks to obtain the corresponding current hypothesis set.

[0073] Specifically, when the distance between a certain echo block and the current echo block is less than a preset distance, that echo block is considered a neighboring echo block.

[0074] Step 1052: Determine the predicted value of the current echo block based on the measurement matrix corresponding to the current echo block and the current hypothesis set.

[0075] As an optional implementation, step 1052 specifically includes:

[0076] Calculate the prediction weight coefficients for the current echo block based on the measurement matrix corresponding to the current echo block and the current hypothesis set.

[0077] Specifically, the formula for calculating the prediction weighting coefficient is as follows:

[0078]

[0079] in, H represents the prediction weight coefficient for the l-th echo block in the p-th non-keyframe; p,l Let be the hypothesis set of the l-th echo block in the p-th non-keyframe; λ is the Lagrange multiplier; Γ is the Tikhonov matrix; (·) + For the Moore-Penrose inverse, using this method can avoid due to ((Φ B H p,l ) T (Φ B H p,l )+ λ 2Γ T Γ) The inability to invert leads to inaccurate solutions; y p,l This is the sampled data of the l-th echo block in the p-th non-key frame.

[0080] Calculate the predicted value of the current echo block based on the current set of assumptions and the prediction weight coefficients of the current echo block.

[0081] Specifically, the formula for calculating the predicted value is as follows:

[0082]

[0083] in, This is the predicted value of the l-th echo block in the p-th non-key frame.

[0084] Step 1053: Determine the reconstruction value of the current echo block based on the sampling data, measurement matrix, and predicted value of the current echo block.

[0085] As an optional implementation, step 1053 specifically includes:

[0086] Calculate the residual of the current echo block based on the sampling data, measurement matrix, and predicted values ​​of the current echo block.

[0087] Specifically, the formula for calculating the residual is:

[0088]

[0089] in, It is the residual of the l-th echo block in the p-th non-keyframe.

[0090] The residual reconstruction algorithm is used to reconstruct the residual of the current echo block to obtain the reconstructed residual value of the current echo block.

[0091] Specifically, the formula for calculating the reconstructed residual is as follows:

[0092]

[0093] Where, r p,l Let be the reconstruction residual value of the l-th echo block in the p-th non-keyframe; Algorithm(·,·) is the residual reconstruction algorithm.

[0094] Calculate the reconstruction value of the current echo block based on the reconstruction residual value and the prediction value of the current echo block.

[0095] Specifically, the formula for calculating the reconstructed value is:

[0096]

[0097] in, This is the reconstructed value of the l-th echo block in the p-th non-key frame.

[0098] Step 106: Based on the reconstruction values ​​of all echo blocks, determine the reconstructed ultrasonic plane wave to achieve imaging.

[0099] As an optional implementation, step 106 specifically includes:

[0100] Based on the reconstructed values ​​of all echo blocks corresponding to each frame, the reconstructed ultrasonic plane wave of the corresponding frame is determined.

[0101] Determining the reconstructed ultrasonic plane wave based on the reconstructed ultrasonic plane wave of all frames. This enables imaging.

[0102] Specifically, such as Figure 2 As shown, the more specific process of Example 1 includes:

[0103] Step S1: Divide the ultrasound plane wave into keyframe plane waves and non-keyframe plane waves. Assuming that a total of 2P+1 angles of ultrasound plane waves are emitted to image the same area to be imaged, the ultrasound plane wave at the P+1 angle is regarded as the keyframe, and the ultrasound plane waves at the other angles are regarded as non-keyframes. Sample the keyframes and non-keyframes. The specific steps are as follows:

[0104] S11: At the sampling end, the ultrasound plane wave echo data By dividing the data into blocks, and with a preset block size of B, the measured values ​​of the echo block data after block division can be obtained.

[0105] S12: Use a block-sparse random measurement matrix as the measurement matrix. Where R = SR × B 2 SR is the sampling rate. The sparse random measurement matrix is ​​constructed as follows: First, generate a matrix of size R×B. 2 The all-zero matrix Φ B And R << B 2 Then, select a random position in each row of the matrix and set the selected position to 1.

[0106] S13: Assume that for the non-keyframe plane wave x at angle p (p≠P+1) p Perform sparse sampling to obtain sparse sample y p ,(p=1,…,2P+1),p≠P+1.

[0107] S14: For keyframe x P+1 Non-sparse sampling is performed to obtain y P+1 Compared to sparsely sampled non-keyframes, it retains more feature information about the target region, which is beneficial for providing a high-quality set of multiple hypotheses for subsequent multi-hypothesis prediction. At this point, the sampling of all plane waves is complete.

[0108] S2: Sliding prediction of non-keyframe plane wave signals is performed based on the multi-hypothesis prediction method, and the multi-hypothesis prediction weights are solved to obtain the predicted values ​​of the echo blocks. The specific steps are as follows:

[0109] S21: On a single plane wave, with the current echo block x p,l Using the origin as the center, a search window is constructed and neighboring echo blocks are searched within the adjacent region of the current echo block, i.e., within a radius of (B+2b) / 2, where b is the size of the sub-block. These hypotheses can form a multi-hypothesis set H. p,l =[H p,l H P+1,l ], H P+1,l H p,l These are sets of multiple hypotheses for the corresponding positions of keyframes and non-keyframes, respectively.

[0110] S22: The predicted non-key frames are obtained using the following formula:

[0111]

[0112] This formula is The minimized equation did not yield a solution.

[0113] S23: Solve the current echo block Prediction weighting coefficients:

[0114]

[0115] This formula is The calculation formula.

[0116] S24: Calculate the predicted value of the current echo block based on the current hypothesis set and the prediction weight coefficient of the current echo block.

[0117] S3: Calculate the predicted value of the echo block and the residual of the sampled data of the echo block in the measurement domain, and then reconstruct the echo signal residual to obtain the reconstructed residual value. The specific steps are as follows:

[0118] S31: Based on the sampling data, measurement matrix, and predicted value of the current echo block, obtain the residual of the echo block in the measurement domain.

[0119] S32: Perform residual reconstruction on the predicted values ​​of the echo block to obtain the reconstructed residual value of the current echo block.

[0120] S33: Use the reconstruction residual value to correct the predicted value of the echo block and obtain the reconstruction value of the echo block.

[0121] S4: Combine the echo blocks into a plane wave. After obtaining all the plane waves, image them. The specific steps are as follows:

[0122] S41: Combine the predicted values ​​of echo blocks belonging to the same frame into a single-frame plane wave.

[0123] S42: Combine the frame plane waves of all frames into a complete plane wave until all plane waves are obtained.

[0124] To verify the effectiveness of the method in Example 1, experiments were conducted using the publicly available dataset PICMUS. Imaging comparison experiments were performed on commonly used ultrasonic imaging targets, specifically scattering point targets and absorbing spot targets. Field II, an ultrasonic experimental simulation platform developed by the Technical University of Denmark based on acoustic principles, has gained widespread recognition and use in theoretical research. The simulation used a 128-element linear array probe with a center frequency of 5.2MHz, an element spacing of 0.3mm, a sampling frequency of 20.83MHz, and a sound velocity of 1540m / s. The simulation data used 75 transmissions. The transmission angle ranged from -16° to +16°, with an angle interval of 0.43°, and the imaging dynamic range was set to 50dB. Specifically, in the point target simulation experiment, a group of 20 equally spaced target points were set, horizontally and vertically distributed in an echo-free environment. The imaging area was set to a depth of 0 to 50mm and a side distance of -19mm to 19mm. In the simulation experiment of the sound-absorbing spot target, the background tissue in the imaging area is set to be an isotropic homogeneous tissue, and nine circular sound-absorbing dark spots are set in the tissue, each with a diameter of 7 mm. The dark spots are located at a depth of 15 mm to 45 mm, and the acoustic scattering coefficient in the dark spots is set to 0.

[0125] For the two experimental targets mentioned above, reconstruction imaging experiments were conducted using a block-based compressed sensing algorithm, a multi-hypothesis prediction compressed sensing algorithm, and a reference frame multi-hypothesis prediction reconstruction algorithm. Image restoration quality was evaluated using Mean Square Error (MSE) and Structural Similarity (SSIM) to determine the merits and differences in reconstruction between different algorithms. Furthermore, for point targets, Full Width at Half Maxima (FWHM) was used to evaluate the resolution of the restored point targets. For speckled targets, Contrast Ratio (CR) and Generalized Contrast-to-Noise Ratio (gCNR) were used to evaluate the cyst restoration effect.

[0126] Figures 3-6 The point target reconstruction imaging results are given. Figures 3-6 The horizontal axis represents horizontal distance (in mm); the vertical axis represents vertical distance (in mm). Figures 4-6The table shows the reconstructed signal imaging results under three different methods with the same sparse dictionary and sampling rate of 20%. Comparing the reconstructed image with the original image reveals that the reconstruction using block-based compressed sensing is less effective, failing to distinguish target points and producing numerous artifacts at non-target points. Visually, the image obtained using the reference frame multi-hypothesis prediction reconstruction method is closer to the original image. Table 1 lists the MSE, SSIM, and FWHM at a depth of 15 mm for the reconstructed images using different methods. Table 1 clearly shows that the point target image reconstructed using the reference frame multi-hypothesis prediction reconstruction method has the lowest MSE, indicating that the reconstructed plane wave signal is closest to the original plane wave signal, and the corresponding image also has the highest SSIM. Furthermore, the point target resolution obtained using the reference frame multi-hypothesis prediction reconstruction method is closer to the original image.

[0127] Table 1. Indicators for reconstructing simulated point target images using different methods.

[0128]

[0129]

[0130] Figures 7-10 Simulation results of the sound-absorbing spot target reconstructed using different methods at a sampling rate of 20% are presented. Figures 7-10 The horizontal axis represents horizontal distance, in mm; the vertical axis represents vertical distance, in mm. Figures 7-10 It can be seen that the image reconstructed by the reference frame multi-hypothesis prediction method is closer to the original image, with clearer edge contours, fewer artifacts inside the circle, the highest contrast, and the best image quality. To more intuitively demonstrate the quality of the reconstructed image, Table 2 lists the MSE, SSIM, CR, and gCNR of the reconstructed images from different methods. Table 2 shows that although the reference frame multi-hypothesis prediction method has a higher error in signal reconstruction than the multi-hypothesis prediction compressed sensing method, compared to other methods, the reference frame multi-hypothesis prediction method yields a higher SSIM, and its CR and gCNR are also higher. Figures 7-10 As shown in Table 2, the quality and image evaluation index values ​​of the reconstructed images from different methods are consistent.

[0131] Table 2. Indicators for reconstructing sound-absorbing spot images using different methods.

[0132] Original image 0 1 -40.6621 0.9989 Block compression sensing 9.1178e-04 0.7751 -14.0937 0.8511 Multi-hypothesis prediction compressed sensing 6.4333e-04 0.8163 -20.4022 0.9299 Reference Frame Multi-Hypothesis Prediction Reconstruction 6.5184e-04 0.8348 -23.0531 0.9565

[0133] Example 2

[0134] The downsampled ultrasonic plane wave prediction and reconstruction system in this embodiment includes:

[0135] The measurement acquisition module is used to acquire the measurement values ​​of echo data of 2P+1 consecutive ultrasonic plane waves at different angles in the area to be imaged.

[0136] The framing module is used to determine the P+1th ultrasonic plane wave as a key frame and to determine all ultrasonic plane waves other than the key frames in the 2P+1 ultrasonic plane waves as non-key frames.

[0137] The segmentation module is used to segment each echo data into blocks according to a preset segmentation size to obtain multiple corresponding echo blocks; based on the preset segmentation size, a corresponding measurement matrix is ​​set for each echo block of each non-key frame.

[0138] The sampling module is used to sample each echo block based on the measurement matrix to obtain sampling data.

[0139] The reconstruction value determination module is used to determine the reconstruction value of each echo block in each frame; wherein, the process of determining the reconstruction value of the current echo block in any current frame includes:

[0140] Using the center of the current echo block as the origin, search for neighboring echo blocks to obtain the corresponding current hypothesis set.

[0141] Based on the measurement matrix corresponding to the current echo block and the current set of hypotheses, the predicted value of the current echo block is determined.

[0142] Based on the sampling data, measurement matrix, and predicted values ​​of the current echo block, the reconstruction value of the current echo block is determined.

[0143] The imaging module is used to determine the reconstructed ultrasonic plane wave based on the reconstruction values ​​of all echo blocks, thereby achieving imaging.

[0144] Example 3

[0145] An electronic device includes a memory and a processor, the memory storing a computer program and the processor running the computer program to cause the electronic device to perform the prediction and reconstruction method for downsampled ultrasonic plane waves in Embodiment 1.

[0146] As an optional implementation, the memory is a readable storage medium.

[0147] The beneficial effects of this invention are as follows: In addition to common sparse reconstruction algorithms for reconstructing downsampled ultrasound echo signals, this invention considers the strong correlation of prior information in ultrasound echo signals and constructs the original radio frequency signal as a set of hypotheses in the echo domain, resulting in a downsampled plane wave reconstruction method based on reference frame multi-hypothesis prediction. Compared to traditional sparse reconstruction methods, the reference frame multi-hypothesis prediction method has better prediction and reconstruction capabilities for ultrasound plane wave signals, while reducing the dependence on the sparsity of the original echo signal. Under the same sparse dictionary and compression ratio, its reconstruction error is smaller than that of block-based compressed sensing and multi-hypothesis prediction compressed sensing reconstruction algorithms. It can guarantee good reconstructed image quality at low compression ratios, and its image similarity is better than methods that rely solely on sparsity or simultaneously on both sparsity and correlation. The method presented in this paper completes signal compression and reconstruction from the perspective of signal correlation without affecting image quality.

[0148] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0149] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for predicting and reconstructing downsampled ultrasonic plane waves, characterized in that, The method includes: Acquire the measured values ​​of echo data of 2P+1 consecutive ultrasonic plane waves at different angles in the region to be imaged; The P+1th ultrasonic plane wave is identified as a key frame, and all ultrasonic plane waves in the 2P+1 ultrasonic plane waves except for the key frame are identified as non-key frames. Each echo data is divided into blocks according to a preset block size to obtain multiple corresponding echo blocks; based on the preset block size, a corresponding measurement matrix is ​​set for each echo block of each non-critical frame at random. The sampling data is obtained by sampling each echo block based on the measurement matrix; Determine the reconstruction value of each echo block in each frame; wherein, the process of determining the reconstruction value of the current echo block in any current frame includes: Using the center of the current echo block as the origin, search for neighboring echo blocks to obtain the corresponding current hypothesis set; when the distance between an echo block and the current echo block is less than a preset distance, the echo block is a neighboring echo block; Based on the measurement matrix corresponding to the current echo block and the current hypothesis set, the predicted value of the current echo block is determined; specifically including: Based on the measurement matrix corresponding to the current echo block and the current hypothesis set, calculate the prediction weight coefficients for the current echo block; the formula for calculating the prediction weight coefficients is as follows: ； in, For the first In the non-keyframe Prediction weighting coefficients for each echo block; The measurement matrix is ​​the same for all echo blocks in any non-key frame. For the first In the non-keyframe The set of hypotheses for each echo block; For transpose; For Lagrange factors; It is a Tikhonov matrix; The Moore-Penrose inverse; For the first In the non-keyframe Sampling data of each echo block; Based on the current hypothesis set and the prediction weight coefficients of the current echo block, the predicted value of the current echo block is calculated; the formula for calculating the predicted value is: ； in, For the first In the non-keyframe Predicted values ​​for each echo block; Based on the sampling data, measurement matrix, and predicted values ​​of the current echo block, the reconstructed values ​​of the current echo block are determined; specifically, this includes: Based on the sampling data, measurement matrix, and predicted values ​​of the current echo block, calculate the residual of the current echo block; the formula for calculating the residual is: ； in, For the first In the non-keyframe The residual of each echo block; The residual reconstruction algorithm is used to reconstruct the residual of the current echo block, obtaining the reconstructed residual value of the current echo block; the formula for calculating the reconstructed residual value is: ； in, For the first In the non-keyframe The reconstructed residual values ​​of each echo block; This is a residual reconstruction algorithm; Based on the reconstruction residual and prediction values ​​of the current echo block, calculate the reconstruction value of the current echo block; the formula for calculating the reconstruction value is: ； in, For the first In the non-keyframe Reconstructed values ​​of each echo block; Based on the reconstruction values ​​of all echo blocks, the reconstructed ultrasonic plane wave is determined, thereby achieving imaging.

2. The prediction and reconstruction method for downsampling ultrasonic plane waves according to claim 1, characterized in that, Based on the measurement matrix, each echo block is sampled to obtain sampled data, specifically including: The measurement values ​​of each non-key frame are sparsely sampled using all the measurement matrices corresponding to each non-key frame to obtain the corresponding sampled data; Non-sparse sampling is performed on the measurements of keyframes to obtain sampled data.

3. The prediction and reconstruction method for downsampling ultrasonic plane waves according to claim 1, characterized in that, Based on the reconstructed values ​​of all echo blocks, the reconstructed ultrasonic plane wave is determined, thereby achieving imaging. Specifically, this includes: Based on the reconstruction values ​​of all echo blocks corresponding to each frame, the reconstructed ultrasonic plane wave of the corresponding frame is determined. The reconstructed ultrasonic plane wave is determined based on the reconstructed ultrasonic plane wave of all frames, thereby achieving imaging.

4. A prediction and reconstruction system for downsampled ultrasonic plane waves, characterized in that, The system includes: The measurement acquisition module is used to acquire the measurement values ​​of echo data of 2P+1 consecutive ultrasonic plane waves at different angles in the area to be imaged; The framing module is used to determine the P+1th ultrasonic plane wave as a key frame and to determine all ultrasonic plane waves other than the key frame in the 2P+1 ultrasonic plane waves as non-key frames. The block segmentation module is used to divide each echo data into blocks according to a preset block size to obtain multiple corresponding echo blocks; based on the preset block size, a corresponding measurement matrix is ​​set for each echo block of each non-key frame randomly. The sampling module is used to sample each echo block based on the measurement matrix to obtain sampling data; The reconstruction value determination module is used to determine the reconstruction value of each echo block in each frame; wherein, the process of determining the reconstruction value of the current echo block in any current frame includes: Using the center of the current echo block as the origin, search for neighboring echo blocks to obtain the corresponding current hypothesis set; when the distance between an echo block and the current echo block is less than a preset distance, the echo block is a neighboring echo block; Based on the measurement matrix corresponding to the current echo block and the current hypothesis set, the predicted value of the current echo block is determined; specifically including: Based on the measurement matrix corresponding to the current echo block and the current hypothesis set, calculate the prediction weight coefficients for the current echo block; the formula for calculating the prediction weight coefficients is as follows: ； in, For the first In the non-keyframe, the first Prediction weighting coefficients for each echo block; The measurement matrix is ​​the same for all echo blocks in any non-key frame. For the first In the non-keyframe, the first The set of hypotheses for each echo block; For transpose; For Lagrange factors; It is a Tikhonov matrix; It is the inverse of Moore-Penrose; For the first In the non-keyframe, the first Sampling data of each echo block; Based on the current hypothesis set and the prediction weight coefficients of the current echo block, the predicted value of the current echo block is calculated; the formula for calculating the predicted value is: ； in, For the first In the non-keyframe Predicted values ​​for each echo block; Based on the sampling data, measurement matrix, and predicted values ​​of the current echo block, the reconstructed values ​​of the current echo block are determined; specifically, this includes: Based on the sampling data, measurement matrix, and predicted values ​​of the current echo block, calculate the residual of the current echo block; the formula for calculating the residual is: ； in, For the first In the non-keyframe The residual of each echo block; The residual reconstruction algorithm is used to reconstruct the residual of the current echo block, obtaining the reconstructed residual value of the current echo block; the formula for calculating the reconstructed residual value is: ； in, For the first In the non-keyframe The reconstructed residual values ​​of each echo block; For residual reconstruction algorithm; Based on the reconstruction residual and prediction values ​​of the current echo block, calculate the reconstruction value of the current echo block; the formula for calculating the reconstruction value is: ； in, For the first In the non-keyframe Reconstructed values ​​of each echo block; The imaging module is used to determine the reconstructed ultrasonic plane wave based on the reconstruction values ​​of all echo blocks, thereby achieving imaging.

5. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to cause the electronic device to perform the prediction and reconstruction method for downsampled ultrasonic plane waves according to any one of claims 1 to 3.

6. An electronic device according to claim 5, characterized in that, The memory is a readable storage medium.

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