A method and system for high spatiotemporal resolution ultrasound plane wave contrast-enhanced microvascular imaging

Abstract

This invention discloses a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method and system, belonging to the field of ultrasound imaging technology. It employs a single-frequency or mixed-frequency angiography pulse emission sequence to improve the sensitivity for microbubble detection. Gradient correction and contraction transformation are performed using the characteristics of the microbubble point spread function, and multi-level accumulation in the time domain allows for the accumulation of high-resolution angiography-enhanced microvascular images with fewer image sequences, restoring the original signal amplitude. This significantly improves the signal-to-noise ratio and signal-to-clutter ratio for vascular imaging, enhancing both spatial and temporal resolution of the imaging. Therefore, the high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method proposed in this invention solves the current problem of balancing time and spatial resolution in ultrasound angiography-enhanced vascular imaging, simultaneously improving both temporal and spatial resolution compared to traditional angiography enhancement methods.

Description

Technical Field

[0001] This invention belongs to the field of ultrasound imaging technology and relates to a method and system for high spatiotemporal resolution ultrasound plane wave angiography to enhance microvascular imaging. Background Technology

[0002] Ultrasound imaging, with its real-time dynamic imaging and bedside monitoring capabilities, offers significant advantages in clinical disease diagnosis. Traditional ultrasound imaging, in addition to tissue imaging, provides good blood flow monitoring. To enhance the echo of blood flow signals, microbubble contrast agents are used for ultrasound blood flow enhancement, resulting in contrast-enhanced ultrasound imaging. This allows for the detection of small vessels and slow blood flow, and improves the contrast-to-tissue ratio of blood flow. However, because contrast imaging cannot overcome the half-wavelength limitation, its resolution is relatively low. Furthermore, the presence of some nonlinear echoes in the tissue leads to incomplete tissue suppression, resulting in a low signal-to-noise ratio. Additionally, the presence of both large and small vessels can obscure the small vessels, hindering accurate and rapid imaging of them.

[0003] To overcome the aforementioned problems in contrast-enhanced ultrasound imaging, super-resolution imaging technology has been introduced into ultrasound contrast-enhanced imaging. Most ultrasound super-resolution imaging technologies are based on localization and tracking schemes, which greatly improve the resolution of blood flow imaging. However, they are limited by the accuracy of microbubble localization and imaging speed. Accurate microbubble localization requires that the concentration cannot be too high. The improvement in resolution and the complete blood flow structure are obtained at the expense of temporal resolution. Therefore, it is difficult to balance the imaging spatial and temporal resolution. Summary of the Invention

[0004] The purpose of this invention is to solve the problem that imaging time and spatial resolution cannot be balanced in existing ultrasound contrast imaging, and to provide a high spatiotemporal resolution ultrasound plane wave contrast imaging method and system for enhancing microvascular imaging.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] This invention proposes a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method, comprising the following steps:

[0007] The ratio of the imaging horizontal and vertical resolutions is obtained, and the gradient field is calculated frame by frame for the microbubble imaging image sequence. The ratio of the imaging horizontal and vertical resolutions is used as the gradient correction factor to correct the gradient field, and an isotropic microbubble gradient field sequence is obtained.

[0008] The microbubble shrinkage coefficient within the radius neighborhood is obtained using the isotropic microbubble gradient field sequence, and the microbubble shrinkage coefficient within the radius neighborhood is assigned to the microbubble contrast image sequence in the form of a weight matrix to obtain the shrunken microbubble contrast image sequence.

[0009] The cumulative map is calculated by multi-level time cross-correlation of the microbubble angiography image sequence after shrinkage; the signal amplitude of the cumulative map is adjusted to match the original microbubble angiography image sequence to obtain a high spatiotemporal resolution microvascular image.

[0010] Preferably, the method for obtaining microbubble contrast imaging image sequences is as follows:

[0011] Microbubble angiography data was obtained by using a plane wave angiography pulse sequence. The microbubble angiography data was then subjected to beamforming and multi-angle composite spatiotemporal denoising to obtain a microbubble angiography image sequence.

[0012] Among them, the plane wave angiography pulse sequence adopts a pulse emission amplitude modulation pulse inversion sequence with single-frequency or mixed dual-frequency coding under multiple angles.

[0013] Preferably, the gradient correction factor μ is calculated as follows:

[0014] Among them, vertical resolution Empirical values ​​of lateral resolution of plane waves c is the speed of sound, τ is the pulse length, z is the actual depth of the point, w is the total width of the probe, and k is the empirical coefficient for the lateral resolution of the plane wave.

[0015] Preferably, the method for correcting the gradient field using local gradient correction or gradient correction is as follows:

[0016] 1) If the local gradient correction method is used, the following is true:

[0017]

[0018] Among them, S x (x,y,t) and S y (x,y,t) is the local gradient field, (x,y) is the position index of the pixel value in the microbubble angiography image, I(x+a,y+b,t) is the image at time t in the microbubble angiography image sequence, T is the total acquisition time 1≤t≤T, r is the size of the search box for the selected local gradient calculation, and a and b are the parameters for traversing the search box horizontally and vertically, respectively.

[0019] 2) If the gradient correction method is used, the following is true:

[0020]

[0021] Among them, G x (x,y,t) and G y (x,y,t) represents the gradient field sequence calculated using the traditional gradient operator in the x and y directions of the microbubble angiography image sequence, S. x (x,y,t) and S y(x,y,t) represents the corrected isotropic gradient field. This is the vector dot product operator.

[0022] Preferably, the method for calculating the microbubble shrinkage coefficient γ within the radius neighborhood is as follows:

[0023]

[0024] Among them, (x c ,y c (x) represents the current pixel, i.e., the center point. m ,y m (1≤m≤M) represents the M neighboring pixels within a disk with radius r, where R is the radius of the disk. m ,y m The Euclidean distance from the center point is given by: norm[·] is the normalization operator, |·| is the absolute value operator, sgn(·) is the sign function, and Θ is the vector p = (x... m ,y m ) and vector g = (S x (x n ,y m ),S y (x m ,y m The angle between )) and S x (x,y,t) and S y (x,y,t) represents the local gradient field or the isotropic gradient field calculated by the gradient.

[0025] Preferably, the shrinkage coefficients obtained after traversing each pixel in the image form a shrinkage matrix sequence Γ(x,y,t) as weights. These weights are then assigned to the original microbubble angiography image by multiplying the matrix points by the weights, resulting in the shrunken angiography microbubble image sequence IS(x,y,t) as shown in the following formula:

[0026]

[0027] Where t represents the frame of the image at time t in the time direction, and I(x,y,t) represents the original microbubble angiography image sequence;

[0028] Generate multi-level image sequences using shrunken microbubble imaging images Where, 1≤l≤L, 1≤t≤T, In the image sequence, S represents the microbubble angiography image after shrinkage, l represents the level of the multi-level sequence, and IS... l (x,y,t l ) is the l-th level sequence t l An image of a moment.

[0029] Preferably, multi-level temporal cross-correlation cumulative images <·> t The time-domain averaging operator is used, where Δt is the time shift.

[0030] use The amplitude of the cumulative mapping image signal is adjusted to match the microbubble angiography image sequence by traversing the search box.

[0031] Among them, IR refers to high-resolution microvascular angiography enhanced images. max Let (xi, yi) be the maximum value of the reference image pixels within the current search box, and (xi, yi) be the current calculated pixel position within the search box. low ,y low (x) represents the position of the minimum value of the cumulative map pixels within the search box. max ,x max () represents the position of the maximum value of the cumulative map pixels within the search box.

[0032] This invention proposes a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging system, comprising:

[0033] The gradient field correction module is used to obtain the imaging horizontal and vertical resolution ratio, and to calculate the gradient field frame by frame of the microbubble angiography image sequence; the imaging horizontal and vertical resolution ratio is used as the gradient correction factor to correct the gradient field, thereby obtaining an isotropic microbubble gradient field sequence.

[0034] An image gradient shrinkage module is used to obtain the microbubble shrinkage coefficient in the radius neighborhood using an isotropic microbubble gradient field sequence, and assign the microbubble shrinkage coefficient in the radius neighborhood to the microbubble imaging image sequence in the form of a weight matrix to obtain the shrunken microbubble imaging image sequence.

[0035] The image information matching module is used to calculate a multi-level time cross-correlation cumulative image as a cumulative mapping map based on the shrinking microbubble angiography image sequence; and adjust the signal amplitude of the cumulative mapping map to match the original microbubble angiography image sequence to obtain a high spatiotemporal resolution microvascular image.

[0036] A computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method.

[0037] A computer-readable storage medium storing a computer program that, when executed by a processor, implements steps such as a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This invention proposes a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method. It employs a single-frequency or mixed-frequency angiography pulse emission sequence to improve the sensitivity for microbubble detection. Gradient correction and contraction transformation are performed using the characteristics of the microbubble point spread function, and multi-level accumulation in the time domain allows for the accumulation of high-resolution angiography-enhanced microvascular images with fewer image sequences, restoring the original signal amplitude. This significantly improves the signal-to-noise ratio and signal-to-clutter ratio for vascular imaging, enhancing both spatial and temporal resolution. This method solves the current problem of balancing temporal and spatial resolution in ultrasound angiography-enhanced vascular imaging, simultaneously improving both temporal and spatial resolution compared to traditional angiography-enhanced methods.

[0040] This invention proposes a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging system. By dividing the system into a gradient field correction module, an image gradient contraction module, and an image information matching module, it obtains high spatiotemporal resolution microvascular images, thus achieving high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging. The modular approach ensures that each module is independent, facilitating unified management of all modules. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of the high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method of the present invention.

[0043] Figure 2 This invention provides a simulated microbubble image for the programmable ultrasonic device.

[0044] Figure 3 This is a high spatiotemporal resolution simulation image of the present invention.

[0045] Figure 4 This is a diagram of the high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging system of the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0047] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0048] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0049] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0050] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0051] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances.

[0052] The present invention will now be described in further detail with reference to the accompanying drawings:

[0053] Referring to the figure, this invention proposes a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method, such as... Figure 1 As shown, it includes the following steps:

[0054] S1. Obtain the ratio of the horizontal and vertical resolution of the imaging, and calculate the gradient field frame by frame of the microbubble imaging image sequence; use the ratio of the horizontal and vertical resolution of the imaging as the gradient correction factor to correct the gradient field and obtain the isotropic microbubble gradient field sequence.

[0055] The method for obtaining microbubble imaging image sequences is as follows:

[0056] Microbubble angiography data was obtained by using a plane wave angiography pulse sequence. The microbubble angiography data was then subjected to beamforming and multi-angle composite spatiotemporal denoising to obtain a microbubble angiography image sequence.

[0057] Among them, the plane wave angiography pulse sequence adopts a pulse emission amplitude modulation pulse inversion sequence with single-frequency or mixed dual-frequency coding under multiple angles.

[0058] The gradient correction factor μ is calculated as follows:

[0059] Among them, vertical resolution Empirical values ​​of lateral resolution of plane waves c is the speed of sound, τ is the pulse length, z is the actual depth of the point, w is the total width of the probe, and k is the empirical coefficient for the lateral resolution of the plane wave.

[0060] The methods for correcting the gradient field using local gradient correction or traditional gradient correction are as follows:

[0061] 1) If the local gradient correction method is used, the following is true:

[0062]

[0063] Among them, S x (x,y,t) and S y (x,y,t) is the local gradient field, (x,y) is the position index of the pixel value in the microbubble angiography image, I(x+a,y+b,t) is the image at time t in the microbubble angiography image sequence, T is the total acquisition time, r is the size of the search box for the selected local gradient calculation, and a and b are the parameters for traversing the search box horizontally and vertically, respectively.

[0064] 2) If the traditional gradient correction method is used, the following is true:

[0065]

[0066] Among them, G x (x,y,t) and G y(x,y,t) represents the gradient field sequence calculated using the traditional gradient operator in the x and y directions of the microbubble angiography image sequence, S. x (x,y,t) and S y (x,y,t) represents the corrected isotropic gradient field. This is the vector dot product operator.

[0067] S2. The microbubble shrinkage coefficient in the radius neighborhood is obtained by using the isotropic microbubble gradient field sequence, and the microbubble shrinkage coefficient in the radius neighborhood is assigned to the microbubble contrast image sequence in the form of a weight matrix to obtain the shrunken microbubble contrast image sequence.

[0068] The method for calculating the microbubble shrinkage coefficient γ within the radius neighborhood is as follows:

[0069]

[0070] Among them, (x c ,y c (x) represents the current pixel, i.e., the center point. m ,y m (1≤m≤M) represents the M neighboring pixels within a disk with radius r, where R is the radius of the disk. m ,y m The Euclidean distance from p to the center point is given by: denoted by norm[·], which is the normalization operator; |·|, which is the absolute value operator; sgn(·), which is the sign function; and Θ, which is the vector p = (x...). m ,y m ) and vector g = (S x (x m ,y m ),S y (x m ,y m The angle between )) and S x (x,y,t) and S y (x,y,t) represents the local gradient field or the isotropic gradient field calculated by the gradient.

[0071] The shrinkage coefficients obtained after traversing each pixel in the image form a shrinkage matrix sequence Γ(x,y,t), which is used as weights. These weights are then applied to the original microbubble angiography image by multiplying the matrix points one by one, resulting in the shrunken angiography microbubble image sequence IS(x,y,t) as shown in the following equation:

[0072]

[0073] Where t represents the frame of the image at time t in the time direction, and I(x,y,t) represents the original microbubble angiography image sequence;

[0074] Generate multi-level image sequences using shrunken microbubble imaging images Where, 1≤l≤L, 1≤t≤T, In the image sequence, S represents the microbubble angiography image after shrinkage, l represents the level of the multi-level sequence, and IS... l (x,y,t l ) is the l-th level sequence t l An image of a moment.

[0075] S3. Calculate the multi-level time cross-correlation cumulative image based on the microbubble angiography image sequence after contraction to obtain a cumulative mapping map; adjust the signal amplitude of the cumulative mapping map to match the original microbubble angiography image sequence to obtain a high spatiotemporal resolution microvascular image.

[0076] Multi-level temporal cross-correlation cumulative image <·> t The time-domain averaging operator is used, where Δt is the time shift.

[0077] use The amplitude of the cumulative mapping image signal is adjusted to match the microbubble angiography image sequence by traversing the search box.

[0078] Among them, IR refers to high-resolution microvascular angiography enhanced images. max Let (xi, yi) be the maximum value of the reference image pixels within the current search box, and (xi, yi) be the current calculated pixel position within the search box. low ,y low (x) represents the position of the minimum value of the cumulative map pixels within the search box. max ,x max () represents the position of the maximum value of the cumulative map pixels within the search box.

[0079] The specific steps are as follows:

[0080] Step 1: Repeatedly transmit a plane wave contrast pulse sequence N times using a programmable ultrasound device, wherein the contrast pulse sequence... The amplitude-modulated pulse inversion (AMPI) sequence consists of two pulses (P1, P2): P1 is a 0-phase full-amplitude pulse, and P2 is a π-phase half-amplitude pulse. The pulse frequencies are either dual-frequency mixed short pulses or single-frequency short pulses. The echoes from the contrast pulse sequence are summed using P = P1 + 2·P2 to obtain the microbubble nonlinear signal P. This signal is then beamformed, and inter-frame subtraction removes residual tissue signals. Furthermore, a nonlocal mean spatiotemporal filter is used to remove noise, resulting in a stable microbubble contrast image sequence I. C .

[0081] Step 2: Process the microbubble contrast imaging image sequence I generated in Step 1. C Gradient fields are calculated frame by frame, and the gradient field sequence G in the x and y directions of the contrast image sequence is calculated. x With Gy Because the lateral resolution decreases due to beam defocusing in plane wave imaging, the microbubble PSF appears elliptical. The ratio of the lateral to longitudinal resolution in plane wave imaging is used as a gradient correction factor to correct the gradient field of the microbubble imaging. The corrected gradient field is an isotropic gradient field. The gradient correction factor μ is determined by the longitudinal resolution. The ratio of the empirical value of the transverse resolution of the plane wave The decision is made, and the calculation formula is as follows: Where c is the speed of sound, τ is the pulse length, z is the actual depth of the point, w is the total width of the probe, and k is the empirical coefficient for the lateral resolution of the plane wave, which is usually taken as 1.521.

[0082] Step 3: Iterate through each pixel in the isotropic microbubble gradient field, taking the current pixel as the center point (x). c ,y c ), M neighboring pixels (x, r) within a disk with radius r. m ,y m ), (1≤m≤M), calculate the contraction coefficient γ of the center point in this neighborhood, the calculation formula is as follows:

[0083]

[0084] Where norm[·] is the normalization operator, |·| is the absolute value operator, sgn(·) is the sign function, and Θ is the vector p=(x m ,y m ) and vector g = (S x (x m ,y m ),S y (x m ,y m The angle between (x) and (x) is R, where R is (x) m ,y m The Euclidean distance from the center point is calculated. After traversing each pixel in the gradient field sequence, a shrinkage matrix Γ is generated from the shrinkage coefficient γ of each center point, and then assigned as a weight matrix to the microbubble angiography image sequence to obtain the gradient-shrinked angiography image I. S .

[0085] Step 4: Process the shrunken contrast image sequence I S Calculate multi-level temporal self-accumulation, accumulating microbubbles in the time domain. This multi-level temporal self-accumulation generates a new image sequence by combining two adjacent frames from the shrunk contrast image sequence, using the original shrunk contrast image sequence I as an example. S Let the first-level sequence be denoted as All subsequent generated new image sequences can be represented as L is the maximum level for generating new sequences. The generation of new sequences is represented by the following recursive formula:

[0086]

[0087] After obtaining the multi-level sequences, the self-accumulator is calculated for each level of image sequence. Finally, the multi-level accumulators are added together to obtain the final microvascular image with background filtered out. The multi-level time cross-correlation accumulation calculation formula is shown in the following formula:

[0088]

[0089] Among them, <·> t Let M(x,y) be the obtained multi-level time-cross-correlation cumulative image, and let M(x,y) be the time-domain averaging operator. The amplitude of the image signal in M(x,y) is adjusted to the same dynamic range as the original contrast image by traversing a search box over the multi-level self-cumulative image. This requires selecting an amplitude reference image. The average time-domain image intensity of the original first-level contrast image sequence is calculated to obtain the reference image IR(x,y) for the search box traversal. Using IR as a reference, the following formula is used to locally adjust the dynamic range of the multi-level self-cumulative image within the current search box:

[0090]

[0091] Among them, IR refers to high-resolution microvascular angiography enhanced images. max Let (xi, yi) be the maximum value of the reference image pixels within the current search box, and (xi, yi) be the current calculated pixel position within the search box. low ,y low (x) represents the position of the minimum cumulative mapped image pixels within the search box. max ,x max The search box represents the location of the maximum cumulative mapped image pixels. The search box is linearly scaled for the intensity value of each pixel and then slid across the entire image in parallel in the same manner, ultimately yielding a high-resolution contrast-enhanced vascular image. This completes the process of rapid imaging of microvessels using high-resolution ultrasound plane wave angiography.

[0092] The specific implementation steps are as follows:

[0093] (1) The rats were induced to be anesthetized, placed on a constant temperature surgical pad and their heads were fixed. The craniotomy was performed in preparation for imaging. A 7MHz plane wave angiography pulse sequence with 5 angles (±4°, ±2°, 0°), a pulse repetition frequency of 5kHz, and a length of 2 cycles was emitted using a programmable ultrasound device. The probe width was 38.4mm. The pulses were emitted 200 times and the echoes were received to obtain 200 sets of echo sequences. The echoes were summed, beamformed, subtracted from adjacent frames, and subjected to nonlocal mean spatiotemporal filtering to obtain a 200-frame microbubble angiography image sequence.

[0094] (2) Apply the Sobel operator dx = [-1 0 1] and dy = dx to a sequence of 200 microbubble angiography images. T Calculate the transverse and longitudinal gradient fields G respectively. x With G y From the formula Gradient correction coefficients are calculated and assigned to the horizontal and vertical gradient fields of each frame of the image as global weights, i.e., the gradient fields are corrected to isotropic S through vector dot product. x With S y .

[0095] (3) Calculate the gradient and weighted convergence coefficient of each frame of microbubble image using the isotropic gradient field of each frame. Using 5 pixels as the radius, obtain the coordinates and corrected gradient values ​​of all pixels in the neighborhood of the current center pixel. Calculate the shrinkage coefficient γ in the radius neighborhood using the coordinates and gradient values, which is the weight of the shrinkage coefficient of the center pixel at this time. This algorithm is applied to all pixels, and a shrinkage coefficient is assigned to each pixel to obtain a sequence of 200 shrinkage-reduced microbubble images.

[0096] (4) Perform multi-level sequence expansion on the 200-frame contracted image sequence. The original 200-frame contracted microbubble sequence is used as the first-level sequence. Then, adjacent frames are combined sequentially to form the second-level sequence, and this process is repeated to generate a total of 8 levels of microbubble image sequences. Cross-correlation accumulation is calculated for each level of image. After obtaining the cross-correlation accumulation image for each level, the average of the 8 levels of self-accumulation is taken as the multi-level temporal cross-correlation accumulation image.

[0097] (5) Perform local dynamic range compression on the multi-level time cross-correlation cumulative image. Use the average intensity of the original 200 frames of microbubble images as the reference value for dynamic range linear compression. Traverse each pixel of the image in the form of a search box with a size of 7 to restore the image signal intensity to the original image intensity range, thus obtaining a high-resolution angiography-enhanced vascular image.

[0098] Figure 2 Simulate microbubble imaging for programmable ultrasonic equipment. Figure 3 To obtain the high spatiotemporal resolution microbubble imaging images after performing the above operations, each high spatiotemporal resolution image consists of 16 original images, with an imaging frame rate of 20Hz. This provides a higher frame rate than traditional super-resolution imaging and higher resolution than traditional contrast imaging, achieving a good balance between temporal and spatial resolution.

[0099] This invention proposes a high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging system, such as... Figure 4 As shown, it includes a gradient field correction module, an image gradient shrinkage module, and an image information matching module;

[0100] The gradient field correction module is used to obtain the imaging horizontal and vertical resolution ratio, and to calculate the gradient field frame by frame of the microbubble angiography image sequence; the imaging horizontal and vertical resolution ratio is used as the gradient correction factor to correct the gradient field, and an isotropic microbubble gradient field sequence is obtained.

[0101] The image gradient shrinkage module is used to obtain the microbubble shrinkage coefficient in the radius neighborhood using the isotropic microbubble gradient field sequence, and assign the microbubble shrinkage coefficient in the radius neighborhood to the microbubble contrast image sequence in the form of a weight matrix to obtain the shrunken microbubble contrast image sequence.

[0102] The image information matching module is used to calculate a multi-level time cross-correlation cumulative image as a cumulative mapping map based on the shrinkage microbubble angiography image sequence; the signal amplitude of the cumulative mapping map is adjusted to match the original microbubble angiography image sequence to obtain a high spatiotemporal resolution microvascular image.

[0103] The terminal device provided in this embodiment of the invention includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the various method embodiments described above. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the various device embodiments described above.

[0104] The computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention.

[0105] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0106] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0107] The memory can be used to store the computer program and / or module. The processor implements various functions of the terminal device by running or executing the computer program and / or module stored in the memory and calling the data stored in the memory.

[0108] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0109] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A high spatiotemporal resolution ultrasound plane wave contrast-enhanced microvascular imaging method, characterized in that, Includes the following steps: The ratio of the imaging horizontal and vertical resolutions is obtained, and the gradient field is calculated frame by frame for the microbubble imaging image sequence. The ratio of the imaging horizontal and vertical resolutions is used as the gradient correction factor to correct the gradient field, and an isotropic microbubble gradient field sequence is obtained. The microbubble shrinkage coefficient within the radius neighborhood is obtained using the isotropic microbubble gradient field sequence, and the microbubble shrinkage coefficient within the radius neighborhood is assigned to the microbubble contrast image sequence in the form of a weight matrix to obtain the shrunken microbubble contrast image sequence. The cumulative map is calculated by multi-level time cross-correlation of the microbubble angiography image sequence after shrinkage; the signal amplitude of the cumulative map is adjusted to match the original microbubble angiography image sequence to obtain a high spatiotemporal resolution microvascular image.

2. The high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method according to claim 1, characterized in that, The method for obtaining microbubble imaging image sequences is as follows: Microbubble angiography data was obtained by using a plane wave angiography pulse sequence. The microbubble angiography data was then subjected to beamforming and multi-angle composite spatiotemporal denoising to obtain a microbubble angiography image sequence. Among them, the plane wave angiography pulse sequence adopts a pulse emission amplitude modulation pulse inversion sequence with single-frequency or mixed dual-frequency coding under multiple angles.

3. The high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method according to claim 1, characterized in that, Gradient correction factor The calculation method is as follows ; Among them, vertical resolution Empirical values ​​for the lateral resolution of plane waves ; For the speed of sound, The pulse length, The actual depth of the point. This is the total width of the probe. This is an empirical coefficient for the lateral resolution of plane waves.

4. The high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method according to claim 1, characterized in that, The methods for correcting the gradient field using local gradient correction or gradient correction are as follows: 1) If the local gradient correction method is used, it is as follows: in, and For local gradient fields, This is the location index of the pixel value in the microbubble imaging image. For microbubble imaging image sequences t Images of moments T Total collection time , r The size of the search box calculated for the selected local gradient. a and b These are the parameters for traversing the search box horizontally and vertically, respectively. 2) If the gradient correction method is used, the following is true: in, and For microbubble imaging image sequences x direction and y The gradient field sequence is calculated using traditional gradient operators in the direction. and This is the corrected isotropic gradient field. This is the vector dot product operator.

5. The high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method according to claim 1, characterized in that, Microbubble shrinkage coefficient within the radius neighborhood The calculation method is as follows: in, The current pixel is the center point. For r Within a disk of radius M Each neighboring pixel R for Euclidean distance to the center point For the normalization operator, For absolute value operators, For symbolic functions, For vectors with vector The included angle, and This is an isotropic gradient field calculated for a local gradient field or gradient.

6. The high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method according to claim 1, characterized in that, The shrinkage coefficients obtained after traversing each pixel in the image form a shrinkage matrix sequence. As weights, matrix dot multiplication is used to assign weights to the original microbubble contrast images, resulting in a sequence of shrunken contrast microbubble images. As shown in the following formula: in, t Represents the image in the time direction t A frame of time, This represents the original microbubble imaging image sequence; Generate multi-level image sequences using shrunken microbubble imaging images ;in, middle S This represents a sequence of microbubble imaging images after contraction. l For a multi-level sequence, For the l-th level sequence An image of a moment.

7. The high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method according to claim 1, characterized in that, Multi-level temporal cross-correlation cumulative image , For time-domain averaging operators, For time shift; use The amplitude of the cumulative mapping image signal is adjusted to match the microbubble angiography image sequence by traversing the search box. in, IR To enhance high-resolution microvascular angiography images, The maximum value of the reference image pixels within the current search box. This represents the current calculated pixel position within the search box. This represents the position of the minimum value of the cumulative map pixels within the search box. This represents the position of the maximum value of the cumulative map pixels within the search box.

8. A high spatiotemporal resolution ultrasound plane wave contrast-enhanced microvascular imaging system, characterized in that, include: The gradient field correction module is used to obtain the ratio of the horizontal to vertical resolution of the imaging and to calculate the gradient field frame by frame for the microbubble angiography image sequence. The gradient field was corrected by using the ratio of the imaging horizontal to vertical resolution as the gradient correction factor, and an isotropic microbubble gradient field sequence was obtained. An image gradient shrinkage module is used to obtain the microbubble shrinkage coefficient in the radius neighborhood using an isotropic microbubble gradient field sequence, and assign the microbubble shrinkage coefficient in the radius neighborhood to the microbubble imaging image sequence in the form of a weight matrix to obtain the shrunken microbubble imaging image sequence. The image information matching module is used to calculate a multi-level time cross-correlation cumulative image as a cumulative mapping map based on the shrinking microbubble angiography image sequence; and adjust the signal amplitude of the cumulative mapping map to match the original microbubble angiography image sequence to obtain a high spatiotemporal resolution microvascular image.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes a computer program, it implements the steps of the high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the high spatiotemporal resolution ultrasound plane wave angiography-enhanced microvascular imaging method as described in any one of claims 1 to 7.

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