An ultrasonic super-resolution imaging method with phase correction and related apparatus

Abstract

This invention discloses an ultrasound super-resolution imaging method and related equipment with phase correction, overcoming the problem of image quality degradation and reduced localization effect caused by phase distortion in transcranial imaging. In the phase correction stage, this invention leverages the high signal similarity of different array elements receiving the same microbubble signal. It calculates the phase distortion delay of the same microbubble signal in different array elements through cross-correlation and combines this with the theoretical delay curve to jointly influence DAS beamforming, ultimately achieving phase correction and restoring the intensity and shape of the microbubble signal. The B-mode image quality is restored after phase correction. Subsequently, the microbubbles in the B-mode image are located. After localization, a microbubble tracking method is used to obtain the cloud motion trajectory of the microbubbles, which is then interpolated and mapped onto the image, thereby obtaining an ultrasound super-resolution image with phase correction.

Description

Technical Field

[0001] This invention belongs to the field of acoustic measurement technology, specifically an ultrasonic super-resolution imaging method and related equipment with phase correction. Background Technology

[0002] In in vivo imaging of cerebral vascular structures, imaging of vascular structure and blood flow is fundamental to research and diagnosis, and research on vascular imaging methods has always been a hot topic. Transcranial Doppler (TCD) is a non-invasive neuromonitoring technique that can assess cerebral blood perfusion and cerebral blood flow velocity, thus providing important information about the condition of cerebral blood vessels. TCD has the advantages of ultrasound, such as non-invasiveness, real-time monitoring, and no radiation. However, due to the presence of the skull, TCD can only detect blood flow through a window in the skull, and therefore cannot provide detailed information about the deep brain. This limits its application in certain situations. Although TCD can provide information such as blood flow velocity, its spatial resolution is relatively low, and it cannot provide detailed images like MRA and CTA.

[0003] With the continuous development of ultrafast plane wave technology and various denoising algorithms (SVD, noise equalization, Hessian matrix angiography, Top Hat, NLM), ultrafast power Doppler imaging technology has been widely used in functional imaging. In 2011, a team led by Professors Tanter and Fink at the Langevin Institute in France achieved the first functional detection of the beard tactile area in the mouse brain, obtaining images of cerebral blood flow with good spatiotemporal resolution. Subsequently, they achieved functional detection of the olfactory area in the brain. Furthermore, in 2022, a study achieved monitoring of changes in brain functional areas in mice under awake conditions, demonstrating high clinical value. In addition, research has combined optogenetics and ultrasound functional imaging to explore the correlation between activation of different cell populations in the superior colliculus of mice and defensive behavior. However, current ultrafast power Doppler imaging has a low signal-to-noise ratio and poor sensitivity in detecting micro-blood flow. Therefore, improving the sensitivity of power Doppler imaging for microvascular detection may provide new insights for disease diagnosis.

[0004] Ultrasound localization microscopy (ULM) technology in the field of ultrasound extracts the temporal location information of individual microbubbles or microbubble clusters from large amounts of radio frequency (RF) or image data. It employs multi-target tracking or data association algorithms to locate and track the movement of microbubbles within tiny blood vessels, and finally, through spatiotemporal accumulation and superposition, creates super-resolution images. Ultrasound super-resolution imaging breaks through the limitations of previous ultrasound imaging methods that restricted half-wavelength diffraction, enabling the acquisition of micron-level high-resolution images of tiny blood vessels in deep tissues under non-invasive conditions.

[0005] Transcranial ultrasound (TCU) is an important brain imaging technique with potential value in neuroscience and cerebrovascular disease research. However, because TCU penetrates the skull, it faces problems of phase distortion and signal attenuation.

[0006] First, phase distortion is caused by acoustic impedance mismatch due to the skull, leading to refraction, scattering, and absorption of ultrasound waves as they pass through the skull, resulting in phase distortion. This distortion causes shape distortion and misalignment of brain structures in imaging, affecting the spatial resolution and accuracy of the image. Phase distortion is a significant factor limiting precise localization, especially for observing small brain regions.

[0007] Secondly, sound waves attenuate as they pass through skull tissue due to the skull's high acoustic impedance. This attenuation gradually weakens the ultrasound signal intensity, limiting imaging depth. For brain structures requiring deep observation, such as deep brain regions or lesions, signal loss due to sound wave attenuation may prevent these structures from being clearly displayed in the image, thus affecting the application range of ultrasound. Summary of the Invention

[0008] The present invention provides a solution to the problem that phase distortion in transcranial imaging causes a decrease in image quality and a decrease in positioning effect during ultrasound super-resolution imaging.

[0009] To achieve the above objectives, the present invention provides the following technical solution:

[0010] A super-resolution ultrasound imaging method with phase correction, comprising:

[0011] Acquire channel RF or channel IQ data, perform beamforming to obtain a B-mode image with angiographic microbubbles, reduce noise in the B-mode image, and select the location in the image with the highest probability of microbubbles.

[0012] Calculate the theoretical time delay curve at the location where the probability of microbubble existence is highest, and extract the signals near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signals and arrange them into a matrix;

[0013] Select a column in the matrix corresponding to the array element closest to the microbubble position as the reference signal, calculate the correlation between the microbubble signals in other columns of the matrix and the reference signal, calculate the relative time delay between the reference signal and the signals in other columns of the matrix through the correlation, and use the relative time delay between array elements as the phase distortion time delay curve;

[0014] In the DAS beamforming process, the theoretical delay curve is calculated and the phase distortion delay curve is added to form the final delay curve. The signals from different array elements are extracted according to the final delay curve and superimposed to form the phase-corrected B-mode image of the angiography microbubble.

[0015] The microbubbles in the phase-corrected image are located using a localization algorithm, and their positions are tracked. The tracked microbubble trajectories are then interpolated and mapped onto the image to obtain a super-resolution image.

[0016] Preferably, beamforming the channel RF or channel IQ data to obtain a B-mode image with contrast microbubbles specifically involves:

[0017] Channel RF or channel IQ data is obtained using video signals output from a commercial machine or using a Verasonics programmable ultrasound machine, and ultrasound B-mode images are obtained using DAS beamforming at conventional sound speeds.

[0018] Preferably, the location where microbubbles are most likely to exist is:

[0019] The location with the highest probability of microbubbles in an image is either the brightest location in the image or the center of the region with the highest similarity to the Gaussian kernel.

[0020] Preferably, the theoretical time delay curve at the location with the highest probability of microbubble existence is calculated, and the signals near the theoretical time delay curve in the channel RF or channel IQ data are extracted as microbubble signals and arranged into a matrix. Specifically:

[0021] Based on the location information of the position with the highest probability of microbubble existence and the location information of each array element, the theoretical time for the reflected signal from the position with the highest probability of microbubble existence to reach each array element is calculated. Then, the theoretical time is converted into theoretical sampling points by sampling frequency. A window length is set, and the signals of the window length near the theoretical sampling point corresponding to each array element are extracted and arranged separately. The formula for calculating the theoretical time is as follows:

[0022]

[0023] In the formula, (x,z) represents the position with the highest probability of microbubble existence, k is the kth array element, (x k ,z k ) represents the position of the kth array element, and c represents the speed of sound, which is typically set to 1540 m / s.

[0024] Preferably, cross-correlation is used to calculate the relative time delay between the reference signal and the signals in other columns of the matrix, where the reference element is the element closest to the position with the highest probability of microbubble existence. The cross-correlation calculation formula is as follows:

[0025]

[0026] Where x(i) is the reference array element signal, y(i) is the other array element signals, and N is the signal length.

[0027] C xy (k) is the correlation coefficient between the two signals when the time delay is k.

[0028] Preferably, after calculating the theoretical time delay curve at each location during the DAS beamforming process, the phase distortion time delay curve is superimposed on it to form the final time delay curve.

[0029] Preferably, after obtaining the phase-corrected ultrasound B-mode image with microbubbles, the image features of the microbubbles are effectively recovered. Therefore, the microbubbles are located in the corrected B-mode image using Gaussian fitting or deep learning microbubble localization methods, and the microbubble localization results are tracked to obtain the trajectory of the microbubbles. After obtaining the microbubble trajectory, it can be mapped into the image to form an ultrasound super-resolution image, thus obtaining an ultrasound super-resolution image with phase correction.

[0030] An ultrasound super-resolution imaging system with phase correction, comprising:

[0031] Location acquisition module: used to acquire channel RF or channel IQ data, perform beamforming to obtain B-mode image with angiographic microbubbles, reduce noise in B-mode image, and select the location in image with the highest probability of microbubble presence;

[0032] Extraction and arrangement module: used to calculate the theoretical time delay curve at the location with the highest probability of microbubble existence, extract the signal near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signal and arrange it into a matrix;

[0033] Curve acquisition module: Used to select a column of the matrix corresponding to the array element closest to the microbubble position as the reference signal, calculate the correlation between the microbubble signals in other columns of the matrix and the reference signal, calculate the relative time delay between the reference signal and the signals in other columns of the matrix through the correlation, and use the relative time delay between array elements as the phase distortion time delay curve;

[0034] Correction module: used to calculate the theoretical time delay curve and add the phase distortion time delay curve to form the final time delay curve during DAS beamforming, and extract the signals from different array elements according to the final time delay curve and superimpose them to form a phase-corrected B-mode image of the angiography microbubble.

[0035] Image acquisition module: Used to locate microbubbles in the phase-corrected image using a localization algorithm, track the positions of the microbubbles, interpolate the tracked microbubble trajectories and map them onto the image to obtain a super-resolution image.

[0036] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of an ultrasound super-resolution imaging method with phase correction.

[0037] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of an ultrasound super-resolution imaging method with phase correction.

[0038] Compared with existing technologies, this invention has the following advantages: This invention provides an ultrasound super-resolution imaging method with phase correction, overcoming the problem of image quality degradation and reduced localization effect caused by phase distortion in transcranial imaging. In the phase correction stage, this invention leverages the high signal similarity of different array elements receiving the same microbubble signal. It calculates the phase distortion delay of the same microbubble signal in different array elements through cross-correlation and combines it with the theoretical delay curve to jointly influence DAS beamforming, ultimately achieving phase correction and restoring the intensity and shape of the microbubble signal. The B-mode image quality is restored after phase correction. Subsequently, microbubbles in the B-mode image are located. After localization, a microbubble tracking method is used to obtain the cloud motion trajectory of the microbubbles, which is then interpolated and mapped onto the image to obtain an ultrasound super-resolution image with phase correction. By superimposing the relative delay with the theoretical delay curve to form the final beamforming curve, the phase correction function is achieved, overcoming the problem in existing technologies where phase distortion increases the probability of erroneous vascular structures appearing during microbubble localization and tracking, thereby improving the quality of ultrasound super-resolution imaging obtained in transcranial situations.

[0039] Furthermore, this invention is applicable to both ultrasound channel RF data and channel IQ data, both of which can be well acquired in open ultrasound platforms, and further reduces processing time when using channel IQ data.

[0040] Furthermore, this invention utilizes the similarity of ultrasonic signals from the same point source received by different array elements. By selecting the location with the highest probability of microbubble existence and extracting nearby signals for correlation calculation, a phase distortion delay curve is obtained. This phase distortion delay curve is then introduced into the subsequent DAS beamforming process for phase correction.

[0041] Furthermore, this invention can perform phase correction on images with severe phase distortion and the presence of microbubbles, effectively restoring the shape and signal amplitude of the microbubbles. Therefore, the use of phase correction can improve the accuracy of microbubble localization during ultrasound super-resolution imaging, which significantly enhances the subsequent microbubble trajectory tracking process. Attached Figure Description

[0042] Figure 1 This is a flowchart of an ultrasound super-resolution imaging method with phase correction;

[0043] Figure 2 This is a block diagram of an ultrasound super-resolution imaging system with phase correction;

[0044] Figure 3 This is a schematic diagram of the ultrasound super-resolution imaging process with phase correction.

[0045] Figure 4 This is a schematic diagram of the calculation results of the phase distortion delay curve.

[0046] Figure 5 This is a schematic diagram of the data results of the present invention applied to the Sono403 phantom.

[0047] Figure 6 This is a schematic diagram showing the results of microbubble imaging and localization applied to the transcranial context of the present invention. Detailed Implementation

[0048] 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.

[0049] 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0055] like Figure 1 As shown, the present invention provides an ultrasound super-resolution imaging method with phase correction, comprising:

[0056] S101 acquires channel RF or channel IQ data, performs beamforming to obtain a B-mode image with angiographic microbubbles, performs noise reduction processing on the B-mode image, and selects the location in the image with the highest probability of microbubbles.

[0057] S102 calculates the theoretical time delay curve at the location where the probability of microbubble existence is highest, and extracts the signal near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signal and arranges it into a matrix;

[0058] S103 selects a column of the matrix corresponding to the array element closest to the microbubble position as the reference signal, calculates the correlation between the microbubble signals in other columns of the matrix and the reference signal, calculates the relative time delay between the reference signal and the signals in other columns of the matrix through the correlation, and uses the relative time delay between array elements as the phase distortion time delay curve.

[0059] S104 calculates the theoretical time delay curve during DAS beamforming, adds the phase distortion time delay curve to form the final time delay curve, and extracts signals from different array elements according to the final time delay curve and superimposes them to form a phase-corrected B-mode image of the angiography microbubble.

[0060] S105 uses a localization algorithm to locate microbubbles in the phase-corrected image, tracks the positions of the microbubbles, interpolates the tracked microbubble trajectories, and maps them onto the image to obtain a super-resolution image.

[0061] Specifically, beamforming is performed on channel RF or channel IQ data to obtain a B-mode image with contrast microbubbles:

[0062] Channel RF or channel IQ data is obtained using video signals output from a commercial machine or using a Verasonics programmable ultrasound machine, and ultrasound B-mode images are obtained using DAS beamforming at conventional sound speeds.

[0063] The location where microbubbles are most likely to exist is:

[0064] The location with the highest probability of microbubbles in an image is either the brightest location in the image or the center of the region with the highest similarity to the Gaussian kernel.

[0065] Calculate the theoretical time delay curve at the location with the highest probability of microbubble existence, and extract the signals near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signals and arrange them into a matrix. Specifically:

[0066] Based on the location information of the position with the highest probability of microbubble existence and the location information of each array element, the theoretical time for the reflected signal from the position with the highest probability of microbubble existence to reach each array element is calculated. Then, the theoretical time is converted into theoretical sampling points by sampling frequency. A window length is set, and the signals of the window length near the theoretical sampling point corresponding to each array element are extracted and arranged separately. The formula for calculating the theoretical time is as follows:

[0067]

[0068] In the formula, (x,z) represents the position with the highest probability of microbubble existence, k is the kth array element, (x k ,z k ) represents the position of the kth array element, and c represents the speed of sound, which is typically set to 1540 m / s.

[0069] The relative time delay between each array element signal and the reference array element signal is calculated using cross-correlation, where the reference array element is the element closest to the position with the highest probability of microbubble existence. The cross-correlation calculation formula is as follows:

[0070]

[0071] Where x(i) is the reference array element signal, y(i) is the other array element signals, and N is the signal length.

[0072] C xy (k) is the correlation coefficient between the two signals when the time delay is k.

[0073] In the DAS beamforming process, the theoretical time delay curve at each location is calculated, and then the phase distortion time delay curve is superimposed on it to form the final time delay curve.

[0074] After obtaining the phase-corrected ultrasound B-mode image with microbubbles, the image features of the microbubbles are effectively recovered. Therefore, Gaussian fitting or deep learning microbubble localization methods are used to locate the microbubbles in the corrected B-mode image, and the microbubble localization results are tracked to obtain the trajectory of the microbubbles. After obtaining the microbubble trajectory, it can be mapped into the image to form an ultrasound super-resolution image, thus obtaining an ultrasound super-resolution image with phase correction.

[0075] Specific applications:

[0076] See Figure 3 The flowchart of the ultrasound super-resolution imaging method with phase correction is shown in the figure. The method proposed in this invention can use channel RF data or channel IQ data.

[0077] After obtaining the channel RF data or channel IQ data, DAS beamforming is performed using a conventional sound velocity (typically 1540 m / s). The resulting B-mode image contains a large number of microbubble signals. These microbubble signals can be manually selected or extracted from the image at the location with the highest brightness as the location with the highest probability of microbubble presence.

[0078] After determining the location with the highest probability of microbubble existence, the time required for the reflected signal at that location to reach each array element can be calculated. Based on the sampling frequency, the signal at that location in each array element can be converted into a sampling point. The signal at that location can be extracted separately as the microbubble signal, and the signal of the array element closest to that location can be used as the reference signal.

[0079] The relative time delay between the reference signal and the signals of each array element is calculated using cross-correlation calculations. This relative time delay is then superimposed with the theoretical time delay curve to form the final phase distortion time delay curve. In subsequent DAS beamforming, the phase distortion time delay curve is used to extract and superimpose signal points for phase correction.

[0080] After phase correction, ultrasound super-resolution imaging is required. First, the microbubble localization method is used to locate the microbubble signals in the phase-corrected image. Then, the localization results are input into the microbubble tracking algorithm to obtain the microbubble trajectory. After interpolating the microbubble trajectory, the ultrasound super-resolution image can be obtained.

[0081] See Figure 4(a) The figure shows the microbubble channel RF signal obtained from Verasonics simulation. The black curve in the figure represents the theoretical time delay curve. The microbubble signals near the theoretical time delay curve are extracted and arranged as shown in Figure (c). In the DAS beamforming process, the signals in Figure (c) are added horizontally. Since there are different time delay differences between each column of signals in Figure (c), it cannot be guaranteed that the signals are effectively coherently superimposed. (b) The black curve in the figure is the actual time delay curve after the phase distortion curve is calculated by correlation. Figure (d) shows the result of extracting and arranging the microbubble signals near the black curve in Figure (b). It can be seen that the signal arrangement is more orderly after the correlation calculation. Therefore, when the signals are horizontally superimposed in the DAS beamforming process, the signal coherence and superposition are more complete, thus achieving the effect of phase distortion.

[0082] See Figure 5 (a) Figure shows the transcranial Sono403 point source imaging result before phase correction, and (b) Figure shows the transcranial Sono403 point source imaging result after phase correction. The solid arrow at a depth of 30mm in the figure points to the location where the artificially selected microbubble has the highest probability of existence. After phase correction, the size of the point source in the image is effectively reduced, specifically reflected in the location pointed to by the dashed arrow at the bottom of the image. This indicates that the shape of the microbubble is well restored, which is beneficial for subsequent microbubble localization operations.

[0083] See Figure 6 (a) The image shows the B-mode image after phase correction; (b) The image shows the B-mode image before phase correction; * represents the localization result in the images. (c) The image shows the B-mode image after phase correction; (d) The image shows the B-mode image before phase correction; * represents the localization result in the images. After phase correction, the microbubbles become more complex Gaussian distributed, and the image contrast is also improved to a certain extent, thus improving the microbubble localization effect.

[0084] like Figure 2 As shown, the present invention provides an ultrasound super-resolution imaging system with phase correction, comprising:

[0085] Location acquisition module: used to acquire channel RF or channel IQ data, perform beamforming to obtain B-mode image with angiographic microbubbles, reduce noise in B-mode image, and select the location in image with the highest probability of microbubble presence;

[0086] Extraction and arrangement module: used to calculate the theoretical time delay curve at the location with the highest probability of microbubble existence, extract the signal near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signal and arrange it into a matrix;

[0087] Curve acquisition module: Used to select a column of the matrix corresponding to the array element closest to the microbubble position as the reference signal, calculate the correlation between the microbubble signals in other columns of the matrix and the reference signal, calculate the relative time delay between the reference signal and the signals in other columns of the matrix through the correlation, and use the relative time delay between array elements as the phase distortion time delay curve;

[0088] Correction module: used to calculate the theoretical time delay curve and add the phase distortion time delay curve to form the final time delay curve during DAS beamforming, and extract the signals from different array elements according to the final time delay curve and superimpose them to form a phase-corrected B-mode image of the angiography microbubble.

[0089] Image acquisition module: Used to locate microbubbles in the phase-corrected image using a localization algorithm, track the positions of the microbubbles, interpolate the tracked microbubble trajectories and map them onto the image to obtain a super-resolution image.

[0090] An embodiment of the present invention provides a terminal device. This terminal device 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.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] Although embodiments of the present invention have been described above in conjunction with the accompanying drawings, the present invention is not limited to the specific embodiments and application fields described above. The specific embodiments described above are merely illustrative and instructive, and not restrictive. Those skilled in the art, guided by the specification, can make many other modifications without departing from the scope of the claims of the present invention, and all of these modifications are within the scope of protection of the present invention.

Claims

1. A method for ultrasound super-resolution imaging with phase correction, characterized in that, include: Acquire channel RF or channel IQ data, perform beamforming to obtain a B-mode image with angiographic microbubbles, reduce noise in the B-mode image, and select the location in the image with the highest probability of microbubbles. Calculate the theoretical time delay curve at the location where the probability of microbubble existence is highest, and extract the signals near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signals and arrange them into a matrix; Select a column in the matrix corresponding to the array element closest to the microbubble position as the reference signal, calculate the correlation between the microbubble signals in other columns of the matrix and the reference signal, calculate the relative time delay between the reference signal and the signals in other columns of the matrix through the correlation, and use the relative time delay between array elements as the phase distortion time delay curve; In the DAS beamforming process, the theoretical delay curve is calculated and the phase distortion delay curve is added to form the final delay curve. The signals from different array elements are extracted according to the final delay curve and superimposed to form the phase-corrected B-mode image of the angiography microbubble. The microbubbles in the phase-corrected image are located using a localization algorithm, and their positions are tracked. The tracked microbubble trajectories are then interpolated and mapped onto the image to obtain a super-resolution image.

2. The ultrasound super-resolution imaging method with phase correction according to claim 1, characterized in that, Specifically, beamforming is performed on channel RF or channel IQ data to obtain a B-mode image with contrast microbubbles: Channel RF or channel IQ data is obtained using video signals output from a commercial machine or using a Verasonics programmable ultrasound machine, and ultrasound B-mode images are obtained using DAS beamforming at conventional sound speeds.

3. The ultrasound super-resolution imaging method with phase correction according to claim 1, characterized in that, The location where microbubbles are most likely to exist is: The location with the highest probability of microbubbles in an image is either the brightest location in the image or the center of the region with the highest similarity to the Gaussian kernel.

4. The ultrasound super-resolution imaging method with phase correction according to claim 1, characterized in that, Calculate the theoretical time delay curve at the location with the highest probability of microbubble existence, and extract the signals near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signals and arrange them into a matrix. Specifically: Based on the location information of the position with the highest probability of microbubble existence and the location information of each array element, the theoretical time for the reflected signal from the position with the highest probability of microbubble existence to reach each array element is calculated. Then, the theoretical time is converted into theoretical sampling points by sampling frequency. A window length is set, and the signals of the window length near the theoretical sampling point corresponding to each array element are extracted and arranged separately. The formula for calculating the theoretical time is as follows: In the formula, (x,z) represents the position with the highest probability of microbubble existence, k is the kth array element, (x k ,z k ) represents the position of the kth array element, and c represents the speed of sound, which is typically set to 1540 m / s.

5. The ultrasound super-resolution imaging method with phase correction according to claim 1, characterized in that, The relative time delay between the reference signal and the signals in other columns of the matrix is ​​calculated using cross-correlation, where the reference element is the element closest to the position with the highest probability of microbubble existence. The cross-correlation calculation formula is as follows: Where x(i) is the reference array element signal, y(i) is the other array element signals, and N is the signal length. C xy (k) is the correlation coefficient between the two signals when the time delay is k.

6. The ultrasound super-resolution imaging method with phase correction according to claim 1, characterized in that, In the DAS beamforming process, the theoretical time delay curve at each location is calculated, and then the phase distortion time delay curve is superimposed on it to form the final time delay curve.

7. The ultrasound super-resolution imaging method with phase correction according to claim 1, characterized in that, After obtaining the phase-corrected ultrasound B-mode image with microbubbles, the image features of the microbubbles are effectively recovered. Therefore, Gaussian fitting or deep learning microbubble localization methods are used to locate the microbubbles in the corrected B-mode image, and the microbubble localization results are tracked to obtain the trajectory of the microbubbles. After obtaining the microbubble trajectory, it is mapped into the image to form an ultrasound super-resolution image, thus obtaining an ultrasound super-resolution image with phase correction.

8. An ultrasound super-resolution imaging system with phase correction, characterized in that, include: Location acquisition module: used to acquire channel RF or channel IQ data, perform beamforming to obtain B-mode image with angiographic microbubbles, reduce noise in B-mode image, and select the location in image with the highest probability of microbubble presence; Extraction and arrangement module: used to calculate the theoretical time delay curve at the location with the highest probability of microbubble existence, extract the signal near the theoretical time delay curve in the channel RF or channel IQ data as microbubble signal and arrange it into a matrix; Curve acquisition module: Used to select a column of the matrix corresponding to the array element closest to the microbubble position as the reference signal, calculate the correlation between the microbubble signals in other columns of the matrix and the reference signal, calculate the relative time delay between the reference signal and the signals in other columns of the matrix through the correlation, and use the relative time delay between array elements as the phase distortion time delay curve; Correction module: used to calculate the theoretical time delay curve and add the phase distortion time delay curve to form the final time delay curve during DAS beamforming, and extract the signals from different array elements according to the final time delay curve and superimpose them to form a phase-corrected B-mode image of the angiography microbubble. Image acquisition module: Used to locate microbubbles in the phase-corrected image using a localization algorithm, track the positions of the microbubbles, interpolate the tracked microbubble trajectories and map them onto the image to obtain a super-resolution image.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the ultrasound super-resolution imaging method with phase correction 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 ultrasound super-resolution imaging method with phase correction as described in any one of claims 1 to 7.

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