Super-resolution ultrasound imaging method and apparatus

Abstract

The application relates to an ultrasonic super-resolution imaging method and device. The method comprises the following steps: acquiring a tissue type of an imaging tissue; determining a tissue motion suppression mode of the imaging tissue according to the tissue type; and controlling an ultrasonic probe to collect an ultrasonic super-resolution image of the imaging tissue according to the tissue motion suppression mode. The method can effectively maintain the relative stability of an imaging section and improve the ultrasonic super-resolution imaging precision.

Description

Technical Field

[0001] This application relates to the field of ultrasound technology, and in particular to a super-resolution ultrasound imaging method and apparatus. Background Technology

[0002] Ultrasound imaging resolution refers to the minimum distance between two points that an ultrasound system can distinguish. It defines the system's ability to differentiate between neighboring targets; higher resolution results in a clearer image. In traditional ultrasound imaging, due to sound wave diffraction, resolution is typically limited to about half a wavelength, restricting ultrasound's diagnostic capabilities for fine structures. In recent years, researchers have explored a novel imaging method—super-resolution ultrasound imaging. This method tracks the actual movement of individual points representing tracers such as microbubbles and nanodroplets within tissues, achieving ultra-high resolution imaging that breaks through the traditional ultrasound diffraction limit, significantly improving ultrasound's ability to resolve fine structures. Because this technology tracks microbubble movement, it can also provide information on the speed, magnitude, and direction of microbubble motion, showing broad application prospects in research on blood flow-related disease progression, exploration of the original mechanisms of organ function, and accurate quantitative diagnosis of blood flow in tumor diseases.

[0003] In traditional ultrasound contrast imaging, the scanning user typically relies on subjective judgment of the cross-sectional position of the 2D tissue image displayed synchronously with the contrast image, manually constraining the probe and using motion compensation methods to maintain the relative stability of the imaging cross-section. Although the 2D tissue image provides structural and textural information of the scanning cross-section, the user's stability is still achieved through subjective judgment of the similarity between the current scanning cross-section and past scanning cross-sections. This subjective judgment introduces errors to some extent, leading to motion errors that go unnoticed. Such motion errors are unacceptable for super-resolution imaging that reconstructs details down to the micrometer level. Therefore, how to...

[0004] Maintaining the relative stability of the imaging section to improve the accuracy of super-resolution ultrasound imaging is a technical problem that needs to be solved. Summary of the Invention

[0005] Therefore, it is necessary to provide a super-resolution ultrasound imaging method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can effectively maintain the relative stability of the imaging section to improve the accuracy of super-resolution ultrasound imaging, in order to address the above-mentioned technical problems.

[0006] In a first aspect, this application provides a super-resolution ultrasound imaging method, comprising:

[0007] Obtain the tissue type of the imaged tissue;

[0008] Determine the tissue motion suppression method for the imaging tissue based on the tissue type;

[0009] Based on the tissue motion inhibition method, the ultrasound probe is controlled to acquire super-resolution ultrasound images of the imaging tissue.

[0010] In one embodiment, determining the tissue motion suppression method of the imaging tissue based on the tissue type includes:

[0011] When the tissue type is a relatively static or slightly moving tissue, the tissue motion suppression mode of the imaging tissue is determined to be the first tissue motion suppression mode;

[0012] When the tissue type is a tissue with a large amplitude of motion, the tissue motion suppression mode of the imaging tissue is determined to be the second tissue motion suppression mode.

[0013] In one embodiment, controlling the ultrasound probe to acquire super-resolution ultrasound images of the tissue, based on the tissue motion suppression method, includes:

[0014] When the tissue motion inhibition mode is the first tissue motion inhibition mode, the ultrasound probe is fixed by the clamping component in the fixing structure;

[0015] Super-resolution ultrasound images of the tissue are acquired using an ultrasound probe.

[0016] In one embodiment, the fixing structure includes a main body and an adjusting arm mounted on the main body; an adjusting button is mounted on the main body, and the adjusting arm is connected to the clamping member;

[0017] Acquiring high-resolution ultrasound images of tissues using an ultrasound probe includes:

[0018] The adjustment arm is adjusted by the adjustment button on the control body to move the clamping component, thereby moving the ultrasound probe fixed by the clamping component to acquire super-resolution ultrasound images of the imaging tissue.

[0019] In one embodiment, the adjusting arm includes a vertical adjusting arm, a horizontal adjusting arm connected to the vertical adjusting arm, and a serpentine arm connected to the horizontal adjusting arm; a clamping member is installed at the tail of the serpentine arm;

[0020] The adjustment buttons on the main body are used to control the vertical adjustment arm and the horizontal adjustment arm to move in the vertical and horizontal directions respectively, so as to adjust the position of the ultrasonic probe fixed by the clamp.

[0021] The serpentine arm is used to adjust the clamping components to move the ultrasonic probe that is fixed in place by the clamping components.

[0022] In one embodiment, controlling the ultrasound probe to acquire super-resolution ultrasound images of the tissue, based on the tissue motion suppression method, includes:

[0023] When the tissue motion inhibition mode is the second tissue motion inhibition mode, the ultrasound probe is fixed by the clamping component in the fixing structure;

[0024] The ideal image data of the ideal tissue of interest section of the imaging tissue is found by the ultrasound probe, and the ideal mask image corresponding to the ideal image data is generated.

[0025] Scanning cross-sectional images of the imaging tissue are acquired using an ultrasound probe, and a scanning mask image of the scanning cross-sectional image is generated.

[0026] The correlation parameters between the ideal mask image and the scanned mask image are determined, and the ultrasound probe is constrained according to the correlation parameters to keep the ultrasound probe and the scanned section relatively stationary, so as to realize the acquisition of super-resolution ultrasound images of the imaging tissue.

[0027] In one embodiment, determining the correlation parameters between the ideal mask image and the scanned mask image includes:

[0028] The two-dimensional correlation coefficient between the ideal mask image and the scanned mask image is determined based on the ideal mask image, the size of the ideal mask image, the mean of the ideal mask image, the scanned mask image, the size of the scanned mask image, and the mean of the scanned mask image.

[0029] The two-dimensional correlation coefficient parameter is defined as the correlation parameter between the ideal mask image and the scanned mask image.

[0030] In one embodiment, the method further includes:

[0031] Extract edge features from the ideal mask image;

[0032] The edge features are denoised, and the denoised edge features are made transparent and displayed on the scanning section image. The ultrasound probe is constrained based on the scanning section image with transparent edge features.

[0033] In one embodiment, the method further includes:

[0034] The correlation parameters are color-coded, and the correlation color codes are displayed on the scanned section image. The ultrasound probe is constrained according to the correlation color codes.

[0035] Secondly, this application also provides a super-resolution ultrasound imaging device, comprising:

[0036] The type acquisition module is used to obtain the tissue type of the imaged tissue.

[0037] The mode determination module is used to determine the tissue motion suppression mode of the imaging tissue based on the tissue type.

[0038] The motion suppression module is used to control the ultrasound probe to acquire super-resolution ultrasound images of the tissue based on the tissue motion suppression method.

[0039] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0040] Obtain the tissue type of the imaged tissue;

[0041] Determine the tissue motion suppression method for the imaging tissue based on the tissue type;

[0042] Based on the tissue motion inhibition method, the ultrasound probe is controlled to acquire super-resolution ultrasound images of the imaging tissue.

[0043] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0044] Obtain the tissue type of the imaged tissue;

[0045] Determine the tissue motion suppression method for the imaging tissue based on the tissue type;

[0046] Based on the tissue motion inhibition method, the ultrasound probe is controlled to acquire super-resolution ultrasound images of the imaging tissue.

[0047] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0048] Obtain the tissue type of the imaged tissue;

[0049] Determine the tissue motion suppression method for the imaging tissue based on the tissue type;

[0050] Based on the tissue motion inhibition method, the ultrasound probe is controlled to acquire super-resolution ultrasound images of the imaging tissue.

[0051] The aforementioned super-resolution ultrasound imaging methods, devices, computer equipment, storage media, and computer program products propose a complete set of motion suppression methods for motion problems in the super-resolution ultrasound imaging process under different tissue types. These methods can alleviate motion artifacts in super-resolution ultrasound imaging caused by motion and effectively maintain the relative stability of the imaging section, thereby improving the accuracy of super-resolution ultrasound imaging. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart illustrating a super-resolution ultrasound imaging method in one embodiment;

[0054] Figure 2 This is a schematic diagram of the process of controlling the ultrasound probe to acquire super-resolution ultrasound images of tissues according to the tissue motion suppression method in one embodiment;

[0055] Figure 3 This is a schematic diagram of the fixed structure in one embodiment;

[0056] Figure 4 This is a schematic diagram of the process of controlling the ultrasound probe to acquire super-resolution ultrasound images of tissues according to the tissue motion suppression method in another embodiment;

[0057] Figure 5 This is a schematic diagram illustrating a high correlation between the scanned cross-sectional image and the ideal image data in one embodiment.

[0058] Figure 6 This is a schematic diagram illustrating the low correlation between the scanned cross-sectional image and the ideal image data in one embodiment.

[0059] Figure 7 This is a flowchart illustrating a super-resolution ultrasound imaging method in another embodiment;

[0060] Figure 8 This is a structural block diagram of a super-resolution ultrasound imaging device in one embodiment;

[0061] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0063] In one embodiment, such as Figure 1 As shown, a super-resolution ultrasound imaging method is provided. This embodiment illustrates the application of this method to an ultrasound imaging device. In this embodiment, the method includes the following steps:

[0064] Step 102: Obtain the tissue type of the imaging tissue.

[0065] Imaging tissues refer to human biological tissues that require ultrasound scanning, such as the brain, liver, and kidneys. Imaging tissues are injected with contrast tracers such as microbubbles and nanodroplets.

[0066] Optionally, the tissue type of the imaging tissue can be determined based on the amplitude of motion of the imaging tissue. Tissue types include tissues that are relatively stationary or undergo minimal motion, as well as tissues with a large amplitude of motion. For example, the brain and breast are relatively stationary or undergo minimal motion, while the liver and kidneys are tissues with a large amplitude of motion.

[0067] Step 104: Determine the tissue motion suppression method for the imaging tissue based on the tissue type.

[0068] Step 106: Based on the tissue motion inhibition method, control the ultrasound probe to acquire super-resolution ultrasound images of the imaging tissue.

[0069] Maintaining relative stability of the imaging plane has always been a challenge in super-resolution ultrasound imaging. In actual ultrasound imaging, for relatively stationary or slightly moving biological tissues, the motion of the subject itself is already relatively weak. In these cases, the main motion affecting super-resolution ultrasound imaging comes from the scanning user. Although most professional scanning techniques are relatively mature, for super-resolution ultrasound imaging, which is extremely sensitive to motion, imperceptible probe movement may occur over a long scan period. This movement between the imaging plane and the probe, caused by the tissue itself or the scanning user, leads to numerous motion artifacts in the super-resolution ultrasound imaging results, impairing image quality. On the other hand, for biological tissues with larger motion amplitudes, in addition to the scanning user's movement, the patient's own heartbeat and respiration also generate relatively large amplitudes of motion. Therefore, for biological tissues with different motion amplitudes, a method that can effectively suppress motion and maintain relative stability of the imaging plane is needed to meet the requirements of super-resolution ultrasound imaging.

[0070] After determining the tissue type for imaging, a corresponding tissue motion suppression method is determined based on the tissue type. When the tissue type is relatively static or exhibits minimal movement, the employed tissue motion suppression method physically fixes the ultrasound probe of the ultrasound imaging device, maintaining relative stillness between the ultrasound probe and the imaging tissue during imaging, thus meeting the fixation requirements of super-resolution ultrasound imaging. When the tissue type exhibits significant movement, the employed tissue motion suppression method not only physically fixes the ultrasound probe of the ultrasound imaging device but also quantitatively guides the movement of the ultrasound probe. This allows for the constraint of the probe to maintain relative stillness between the probe and the scanning plane even when there is significant tissue movement, meeting the quality control requirements of super-resolution ultrasound imaging. Specifically, the super-resolution ultrasound image generated in this embodiment is an ultra-high resolution image of the microvascular network of the imaging tissue.

[0071] In the above-mentioned super-resolution ultrasound imaging method, a set of motion suppression methods are proposed for different tissue types in the super-resolution ultrasound imaging process. This can alleviate motion artifacts caused by motion in super-resolution ultrasound imaging, effectively maintain the relative stability of the imaging section, and improve the accuracy of super-resolution ultrasound imaging.

[0072] In an exemplary embodiment, step 104, determining the tissue motion suppression mode of the imaging tissue according to the tissue type, includes: when the tissue type is a relatively static or slightly moving tissue, determining the tissue motion suppression mode of the imaging tissue as a first tissue motion suppression mode; when the tissue type is a tissue with a large amplitude of motion, determining the tissue motion suppression mode of the imaging tissue as a second tissue motion suppression mode.

[0073] The ultrasound imaging device pre-stores two tissue motion suppression modes: a first mode and a second mode. For relatively stationary or minimally moving tissues, the first mode is used to physically fix the ultrasound probe and control it to acquire super-resolution ultrasound images of the tissue. For tissues with significant motion, the second mode is used to physically fix the ultrasound probe and quantitatively guide its movement during imaging, controlling the acquisition of super-resolution ultrasound images of the tissue.

[0074] In this embodiment, corresponding tissue motion suppression methods are selected for relatively stationary or slightly moving tissues and tissues with large motion amplitudes, respectively. This allows for targeted motion suppression of different tissues, enabling flexible and effective maintenance of the relative stability of the imaging section.

[0075] In one alternative embodiment of the above embodiments, such as Figure 2As shown, step 106 involves controlling the ultrasound probe to acquire super-resolution ultrasound images of the imaging tissue according to the tissue motion suppression method, including steps 202 to 204. Wherein:

[0076] Step 202: When the tissue motion inhibition mode is the first tissue motion inhibition mode, the ultrasound probe is fixed by the clamping component in the fixing structure.

[0077] Step 204: Acquire super-resolution ultrasound images of the imaging tissue using an ultrasound probe.

[0078] For relatively stationary or minimally moving tissues, the motion of the imaging section is primarily generated by the scanning user. To prevent the scanning user from being unable to detect the movement induced by minute motion outside the imaging section, a first tissue motion suppression method can be used. This method involves fixing the ultrasound probe in the ultrasound imaging device using a fixed structure, and controlling the movement of the ultrasound probe through the fixed structure. This tracks the actual movement trajectory of individual points of contrast tracers such as microbubbles and nanodroplets within the tissue. The tracked trajectories are then accumulated to obtain a super-resolution ultrasound image of the imaging tissue.

[0079] Specifically, the fixing structure can be a fixing bracket, including clamps, which can fix different types of ultrasound probes. After the ultrasound probe is properly fixed, the position and elevation angle of the ultrasound probe can be adjusted by adjusting the position of the clamps to determine the ideal imaging position. By determining the ideal imaging position, it is possible to ensure that the super-resolution imaging scanning section is the section of interest; during the super-resolution data acquisition process, the consistency between the probe and the section of interest is maintained. That is, during a relatively long super-resolution data acquisition period, the relative stability between the probe and the section of interest is maintained, ensuring the effectiveness of the acquired super-resolution data. Subsequently, the super-resolution imaging data acquisition process can be performed.

[0080] The super-resolution imaging data acquisition process is as follows: An image sequence of a specific imaging section of the injected contrast tracer tissue is acquired under ultrafast plane wave or diffuse wave scanning mode. This image sequence may include contrast image data or 2D grayscale image data. The acquired image sequence undergoes rigid, non-rigid, or a combination of both subpixel-level motion compensation processing to minimize motion on the imaging section. Subsequently, the motion-compensated image sequence is processed using spatiotemporal filtering or temporal-frequency domain filtering to separate the contrast tracer signal. The separated contrast tracer signal is then located, and Kalman filtering and other methods are used to track individual points of the tracer. The tracking trajectory within a preset time period is accumulated to obtain an ultra-high resolution imaging tissue microvascular network image, which serves as the super-resolution ultrasound image.

[0081] It should be noted that, in this embodiment, a super-resolution ultrasound imaging algorithm well known to those skilled in the art can also be used to control the movement of the ultrasound probe in order to acquire super-resolution ultrasound images.

[0082] Furthermore, considering the convenience of ultrasound examinations, the fixation bracket can move freely with the ultrasound imaging equipment. Additionally, due to differences in the body position and posture of different patients, the fixation bracket must have a certain degree of freedom in space. For ease of scanning, the fixation bracket can also be installed on ultrasound imaging equipment, hospital beds, and other facilities.

[0083] In this embodiment, by physically fixing the probe with a fixed structure, the probability of the ultrasound probe moving away from the imaging plane can be effectively reduced, thus achieving super-resolution ultrasound imaging of biological tissues that are relatively stationary or exhibit minute movements.

[0084] In the above-mentioned optional method, the fixing structure includes a main body and an adjusting arm mounted on the main body; an adjusting button is installed on the main body, and the adjusting arm is connected to the clamping member; acquiring super-resolution ultrasound images of the imaging tissue through the ultrasound probe includes: adjusting the adjusting arm by controlling the adjusting button on the main body to move the clamping member, thereby driving the ultrasound probe fixed by the clamping member to acquire super-resolution ultrasound images of the imaging tissue.

[0085] The fixing structure includes a main body and an adjusting arm mounted on the main body, with a clamping component connected to the end of the adjusting arm. The main body supports the adjusting arm; its volume is larger than the adjusting arm, and this relatively larger support body ensures a lower center of gravity, making operation more stable. An adjustment button is also installed on the main body. During ultrasound imaging, the adjusting arm is adjusted by manipulating the adjustment button to change the position of the clamping component, which in turn moves the ultrasound probe fixed to the clamping component.

[0086] In this embodiment, the position of the ultrasound probe is adjusted by setting an adjustment arm, which realizes the degree of freedom of the fixed structure. It can freely adjust the position and elevation angle of the ultrasound probe according to the differences in body position and posture of different subjects, which facilitates ultrasound scanning and expands the application range of the support.

[0087] In the above-mentioned optional method, the adjusting arm includes a vertical adjusting arm, a horizontal adjusting arm connected to the vertical adjusting arm, and a serpentine arm connected to the horizontal adjusting arm; a clamping component is installed at the tail of the serpentine arm; the adjusting button on the main body is used to control the vertical adjusting arm and the horizontal adjusting arm to move in the vertical and horizontal directions respectively, so as to adjust the position of the ultrasonic probe fixed by the clamping component; the serpentine arm is used to adjust the clamping component to drive the ultrasonic probe fixed by the clamping component.

[0088] The vertical and horizontal adjustment arms on the top of the support body can be moved freely in the vertical and horizontal directions via mechanical control buttons on the body, thereby adjusting the position of the ultrasonic probe fixed by the clamp. A serpentine arm is attached to the end of the horizontal adjustment arm. This serpentine arm has a certain degree of freedom and can be bent at will. By bending the serpentine arm, the clamp can be adjusted, thereby moving the ultrasonic probe fixed by the clamp.

[0089] A structural diagram of a fixed structure can be shown as follows: Figure 3 As shown, the fixing structure 100 includes a main body 10 with a button 11 mounted on it, a vertical adjusting arm 20 mounted on the main body 10, a horizontal adjusting arm 30 connected to the vertical adjusting arm 20, a serpentine arm 40 connected to the horizontal adjusting arm 30, a clamp 50 (i.e., a holding member) mounted on the tail of the serpentine arm 40, a base 60 mounted below the main body 10, and rollers 70 below the base. The button 11 on the main body 10 includes four directional arrows: up, down, left, and right. The up and down arrows control the vertical adjusting arm 20 to move vertically, and the left and right arrows control the horizontal adjusting arm 30 to move horizontally. The rollers 70 below the base 60 are lockable, enabling free movement and fixation of the fixing structure 100. The clamp 50 is used to fix the probe 80.

[0090] In this embodiment, by setting up a vertical adjustment arm, a horizontal adjustment arm, and a serpentine arm, the vertical and horizontal adjustment arms are used to drive the ultrasonic probe fixed by the clamping component to move in the vertical and horizontal directions, respectively, while the serpentine arm can be bent at will, which can expand the movement range of the ultrasonic probe under the limited degrees of freedom of the vertical and horizontal adjustment arms, and also greatly expand the application of the fixing structure.

[0091] In one alternative embodiment of the above embodiments, such as Figure 4 As shown, step 106, controlling the ultrasound probe to acquire super-resolution ultrasound images of the tissue according to the tissue motion suppression method includes:

[0092] Step 402: When the tissue motion inhibition mode is the second tissue motion inhibition mode, the ultrasound probe is fixed by the clamping component in the fixing structure.

[0093] Step 404: Find the ideal image data of the ideal tissue of interest section of the imaging tissue using the ultrasound probe, and generate the ideal mask image corresponding to the ideal image data.

[0094] Step 406: Acquire scanned cross-sectional images of the imaging tissue using an ultrasound probe, and generate a scan mask image of the scanned cross-sectional images.

[0095] Step 408: Determine the correlation parameters between the ideal mask image and the scanned mask image, and constrain the ultrasound probe according to the correlation parameters so that the ultrasound probe and the scanned section remain relatively stationary, thereby acquiring a super-resolution ultrasound image of the imaging tissue.

[0096] Both the ideal image data and the scanned cross-sectional images are 2D tissue images.

[0097] For tissues with significant motion, in addition to the movement of the ultrasound probe, the patient's own heartbeat and respiration also contribute to considerable organ movement. In such cases, simply using a fixed structure for physical fixation is insufficient for the fixation requirements of super-resolution ultrasound imaging. A second tissue motion suppression method can be employed: after fixing the ultrasound probe in the ultrasound imaging device using a fixed structure, dual-modal imaging combined with a section-guided algorithm can be used to intervene and alleviate motion. Dual-modal imaging refers to the simultaneous display of contrast images and 2D tissue images, hereinafter referred to as 2D images.

[0098] Since subjective judgment of the scanning section position using 2D images in synchronously displayed dual-modal imaging has a large error, a real-time section guidance algorithm is provided to reduce the movement caused by such subjective judgment errors. This algorithm provides guidance information to the scanning user based on the correlation between the scanning section and the ideal tissue of interest section, and quantitatively guides the user's ultrasound probe movement process.

[0099] Specifically, after fixing the ultrasound probe with clamps in the fixed structure, the probe is moved to find the ideal tissue of interest section, and the corresponding ideal image data is stored. The ideal tissue of interest section can be simply referred to as the ideal section. The pixel distribution range of the ideal image data can be 0-255. For 2D images with a pixel distribution of 0-255, multiple thresholds can be determined using the Otsu thresholding algorithm. The pixel sets distinguished by these thresholds maintain consistent internal variance. The Otsu thresholding algorithm is one of the best threshold selection algorithms in image segmentation. It is computationally simple, unaffected by image brightness and contrast, and widely used in digital image processing. This algorithm can adaptively generate multiple thresholds corresponding to the dynamic range of the image. The scanning user can manually adjust the threshold size as needed for mask image calculation.

[0100] A target threshold is determined from the threshold set adaptively defined by the Otsu thresholding algorithm. The target threshold can be the threshold that maximizes the inter-class variance. Then, the ideal slice image data can be binarized based on this threshold to obtain the ideal mask image corresponding to the ideal image data.

[0101] By controlling the movement of the ultrasound probe through a fixed structure, real-time scanning cross-sectional images of the imaging tissue are acquired. The scanning cross-sectional images are then binarized according to a target threshold to obtain the corresponding scanning mask image.

[0102] Based on the correlation evaluation index, the correlation parameters between the ideal mask image and the scanned mask image are determined. These correlation parameters indicate the correlation between the ideal tissue of interest section and the real-time scanned section. By displaying the correlation parameters on the scanned section image, the scanning user is provided with an indication of the current section's motion. Furthermore, the correlation constrains the ultrasound probe, keeping it relatively stationary relative to the scanned section during ultrasound imaging.

[0103] Furthermore, the correlation evaluation index can include at least one of various image evaluation parameters, such as the two-dimensional correlation coefficient parameter, peak signal-to-noise ratio parameter, image similarity parameter, and mean square error parameter. When the correlation evaluation index includes at least two image evaluation parameters, multiple image evaluation parameters can be coupled together to evaluate the correlation between the ideal mask image and the scanned mask image. Specifically, multi-parameter coupling can use the average value, product, or other methods of multiple parameters to calculate an index, thereby guiding the motion between the current scanned section and the ideal scanned section from multiple perspectives.

[0104] Furthermore, the step of determining the correlation parameter between the ideal mask image and the scanned mask image based on the two-dimensional correlation coefficient parameter includes: determining the two-dimensional correlation coefficient between the ideal mask image and the scanned mask image based on the ideal mask image, the size of the ideal mask image, the mean of the ideal mask image, the scanned mask image, the size of the scanned mask image, and the mean of the scanned mask image; and determining the two-dimensional correlation coefficient parameter as the correlation parameter between the ideal mask image and the scanned mask image.

[0105] The two-dimensional correlation coefficient parameter is defined as:

[0106]

[0107] Where r represents the two-dimensional correlation coefficient between the ideal mask image and the scanned mask image, maskA represents the ideal mask image, maskB represents the scanned mask image, m = 1:M, n = 1:N, and M and N represent the horizontal and axial dimensions of the mask image, respectively. , represents the mean of the ideal mask image and the scanned mask image, respectively.

[0108] The two-dimensional correlation coefficient between the ideal mask image and the scanned mask image is calculated using the formula described above, and this two-dimensional correlation coefficient is used as the correlation parameter. For each scanned section image generated during real-time scanning, a correlation coefficient can be calculated between the mask image and the ideal mask image corresponding to the ideal tissue of interest section. The larger the correlation coefficient, the closer the real-time scanned section is to the ideal tissue of interest section. Since the two-dimensional correlation coefficient supports numerical variables and does not require data standardization, it has high applicability, can measure the linear correlation between variables, is helpful in identifying association patterns between variables, is simple to calculate, and the correlation coefficient always ranges between [-1, 1], making it easy to interpret and compare. It also has high reliability, enabling rapid and accurate calculation of the correlation between the ideal mask image and the scanned mask image.

[0109] In this embodiment, physically fixing the ultrasound probe with a fixed structure effectively reduces the probability of movement away from the imaging plane. Furthermore, based on the 2D image data displayed simultaneously with the contrast image, a plane-guided algorithm quantifies the correlation between the scanning plane and the ideal tissue of interest plane, reducing errors in the user's subjective judgment and enabling super-resolution ultrasound imaging of biological tissues with significant movement. Combining these two methods alleviates motion problems during super-resolution ultrasound imaging, which is beneficial for its clinical application.

[0110] In the above-mentioned optional method, the method further includes: color-coding the correlation parameters, displaying the correlation color codes on the scanned section image, and constraining the ultrasound probe according to the correlation color codes.

[0111] After determining the correlation between the ideal mask image and the scanned mask image, the correlation parameters can be color-coded in real time to more intuitively display the motion. The corresponding colors can then be displayed at specific locations on the ultrasound imaging device's screen. For example, a green border can be added to the edge of the scanned section image when the correlation is strong, and a red border can be added when the correlation is weak. The specific coding colors can be adjusted according to preferences, and multiple coding color methods can even be developed to meet the needs of scanning users, thus intuitively displaying the motion of the scanned section.

[0112] In this embodiment, the color-coded section guidance algorithm intuitively reflects the motion between the real-time scanning section and the ideal section, which can provide guidance information for the user's scanning process, better maintain the stability of the scanning section, and alleviate image motion during super-resolution imaging.

[0113] In the above optional method, the method further includes: extracting edge features of the ideal mask image; denoising the edge features; transparently displaying the denoised edge features on the scanning section image; and constraining the ultrasound probe according to the transparently displayed scanning section image of the edge features.

[0114] The ideal mask image calculated from the ideal image data of the ideal tissue of interest section can be displayed well to provide guidance information for users. However, in order not to hinder the actual scanning process, the calculated ideal mask image needs to be simplified. For example, edge features can be calculated from the ideal mask image, and then the edge features corresponding to some smaller areas can be suppressed as noise. The remaining image edge feature information can then be displayed on the 2D tissue image of the real-time scanning section in a transparent manner combined with a bounding box. That is, on the scanning section image, the degree of transparency can be adjusted by the scanning user.

[0115] If the focus is more on real-time scanning of 2D tissue images, a higher transparency level is acceptable; conversely, if the edge feature information of the ideal mask image is more needed to guide probe movement, a lower transparency level is preferable. This adjustable edge feature information corresponding to the ideal mask image can guide the user's real-time scanning process, maintaining relative stability of the imaging cross-section. For example... Figure 5 The diagram illustrates a high correlation between the scanned cross-sectional image and the ideal image data. The left image represents the scanned cross-sectional image, and the right image represents the contrast image. On the scanned cross-sectional image, the edges of the ideal mask image (thyroid boundary) are calculated and then displayed transparently (the white curved area in the diagram) to guide the scanning user. When the edge features calculated from the real-time scanned cross-sectional image have a high correlation with the edge features of the ideal image data, the border of the scanned cross-sectional image and the correlation color code in the lower right corner can be green, and the star-shaped area in the lower right corner also has a high fill degree, indicating that the scanned cross-section is basically consistent with the ideal cross-section. Figure 6 The diagram illustrates the high or low correlation between the scanned cross-sectional image and the ideal image data. When the edge features calculated from the real-time scanned cross-sectional image have a low correlation with the edge features of the ideal image data, the border of the scanned cross-sectional image and the correlation color code of the lower right corner can be red, and the star-shaped fill degree in the lower right corner is relatively low, indicating that the scanned cross-section deviates from the ideal tissue of interest cross-section.

[0116] Furthermore, the probe movement process can be quantitatively guided based on image features such as corner points and brightness characteristics, or on cross-section guidance algorithms that utilize multiple image features. Cross-section guidance algorithms that utilize multiple image features may provide more robust guidance.

[0117] In one exemplary embodiment, for movements that may occur outside the imaging plane in relatively stationary or minimally moving tissues, in addition to using a fixed structure to stabilize the probe, the ultrasound probe can be integrated into a wearable probe or a patch probe to achieve the same effect. The wearable probe or patch probe is fixed to the person being scanned.

[0118] For tissues with significant movement, subjective judgment of 2D tissue images may produce substantial errors. Other devices can be used to assess the movement, such as implanted motion sensors or magnetic positioning devices, to guide the scanning process. Specifically, motion sensors or magnetic positioning devices can be invasively placed in the moving tissue. The motion sensor transmits the tissue's position information in real time, or the magnetic positioning device responds in a fixed external magnetic field, transmitting position information. After receiving the position information from the motion sensor or magnetic positioning device, the ultrasound imaging equipment adjusts the ultrasound probe according to the actual tissue position to maintain relative stability between the probe and the tissue.

[0119] In another embodiment, such as Figure 7 As shown, a super-resolution ultrasound imaging method is provided, the method comprising:

[0120] Step 702: Obtain the tissue type of the imaging tissue.

[0121] Step 704: When the tissue type is relatively static or slightly moving, determine the tissue motion suppression mode of the imaging tissue as the first tissue motion suppression mode. Proceed to step 708.

[0122] Step 706: When the tissue type is a tissue with a large amplitude of motion, determine the tissue motion suppression mode of the imaging tissue as the second tissue motion suppression mode. Proceed to step 710.

[0123] Step 708: Fix the ultrasound probe with the clamping device in the fixing structure; acquire super-resolution ultrasound images of the imaging tissue with the ultrasound probe.

[0124] Step 710: Secure the ultrasonic probe using the clamping element in the fixing structure.

[0125] Step 712: Find the ideal image data of the ideal tissue of interest section of the imaging tissue using the ultrasound probe, and generate the ideal mask image corresponding to the ideal image data; acquire the scanning section image of the imaging tissue using the ultrasound probe, and generate the scanning mask image of the scanning section image; determine the correlation parameters between the ideal mask image and the scanning mask image.

[0126] Step 714: Color-encode the correlation parameters, display the correlation color codes on the scanned section image, extract the edge features of the ideal mask image, denoise the edge features, and display the denoised edge features transparently on the scanned section image. Constrain the ultrasound probe according to the correlation color codes and the transparently displayed edge features to keep the ultrasound probe relatively stationary with the scanned section, thereby achieving the acquisition of super-resolution ultrasound images of the imaging tissue.

[0127] In this embodiment, a set of motion suppression methods is proposed for different cases of motion problems in the super-resolution ultrasound imaging process under different tissue types. This can alleviate motion artifacts in super-resolution ultrasound imaging caused by motion, effectively maintain the relative stability of the imaging section, and improve the accuracy of super-resolution ultrasound imaging.

[0128] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0129] Based on the same inventive concept, this application also provides a super-resolution ultrasound imaging device for implementing the super-resolution ultrasound imaging method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more super-resolution ultrasound imaging device embodiments provided below can be found in the limitations of the super-resolution ultrasound imaging method described above, and will not be repeated here.

[0130] In one exemplary embodiment, such as Figure 8 As shown, a super-resolution ultrasound imaging device is provided, including: a type acquisition module 802, a mode determination module 804, and a motion suppression module 806, wherein:

[0131] The type acquisition module 802 is used to acquire the tissue type of the imaging tissue.

[0132] The mode determination module 804 is used to determine the tissue motion suppression mode of the imaging tissue based on the tissue type.

[0133] The motion suppression module 806 is used to control the ultrasound probe to acquire super-resolution ultrasound images of the tissue according to the tissue motion suppression mode.

[0134] In an exemplary embodiment, the mode determination module 804 is further configured to determine the tissue motion suppression mode of the imaging tissue as a first tissue motion suppression mode when the tissue type is a relatively static or slightly moving tissue; and to determine the tissue motion suppression mode of the imaging tissue as a second tissue motion suppression mode when the tissue type is a tissue with a large amplitude of motion.

[0135] In an exemplary embodiment, the motion suppression module 806 is further configured to fix the ultrasound probe by a clamping member in the fixing structure when the tissue motion suppression mode is the first tissue motion suppression mode; and to acquire super-resolution ultrasound images of the imaging tissue by the ultrasound probe.

[0136] In one exemplary embodiment, the fixing structure includes a main body and an adjusting arm mounted on the main body; an adjusting button is mounted on the main body, and the adjusting arm is connected to the clamping member;

[0137] The motion suppression module 806 is also used to adjust the adjusting arm via the adjustment button on the control body to move the clamping member, thereby driving the ultrasound probe fixed by the clamping member to acquire super-resolution ultrasound images of the imaging tissue.

[0138] In an exemplary embodiment, the adjusting arm includes a vertical adjusting arm, a horizontal adjusting arm connected to the vertical adjusting arm, and a serpentine arm connected to the horizontal adjusting arm; a clamping member is installed at the tail of the serpentine arm; an adjusting button on the main body is used to control the vertical adjusting arm and the horizontal adjusting arm to move in the vertical and horizontal directions respectively, so as to adjust the position of the ultrasonic probe fixed by the clamping member; the serpentine arm is used to adjust the clamping member to drive the ultrasonic probe fixed by the clamping member.

[0139] In an exemplary embodiment, the motion suppression module 806 is further configured to: fix the ultrasound probe by a clamping member in the fixing structure when the tissue motion suppression mode is the second tissue motion suppression mode; find ideal image data of the ideal tissue of interest section of the imaging tissue using the ultrasound probe, and generate an ideal mask image corresponding to the ideal image data; acquire a scanning section image of the imaging tissue using the ultrasound probe, and generate a scanning mask image of the scanning section image; determine the correlation parameter between the ideal mask image and the scanning mask image, and constrain the ultrasound probe according to the correlation parameter so that the ultrasound probe and the scanning section remain relatively stationary, thereby realizing the acquisition of a super-resolution ultrasound image of the imaging tissue.

[0140] In an exemplary embodiment, a two-dimensional correlation coefficient between the ideal mask image and the scanned mask image is determined based on the ideal mask image, the size of the ideal mask image, the mean of the ideal mask image, the scanned mask image, the size of the scanned mask image, and the mean of the scanned mask image; the two-dimensional correlation coefficient parameter is determined as the correlation parameter between the ideal mask image and the scanned mask image.

[0141] In one exemplary embodiment, the device further includes:

[0142] Edge display module, used to extract edge features of the ideal mask image;

[0143] The edge features are denoised, and the denoised edge features are made transparent and displayed on the scanning section image. The ultrasound probe is constrained based on the scanning section image with transparent edge features.

[0144] In one exemplary embodiment, the device further includes:

[0145] The color display module is used to color-code the correlation parameters, display the correlation color codes on the scanned section image, and constrain the ultrasound probe according to the correlation color codes.

[0146] Each module in the aforementioned super-resolution ultrasound imaging device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0147] In one exemplary embodiment, a computer device is provided, the internal structure of which can be as shown in the figure. Figure 9As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a super-resolution ultrasound imaging method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0148] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0149] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0150] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0151] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0152] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0153] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0154] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0155] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A super-resolution ultrasound imaging method, characterized in that, The method includes: Obtain the tissue type of the imaged tissue; The tissue motion suppression mode of the imaging tissue is determined based on the tissue type; Based on the tissue motion inhibition method, the ultrasound probe is controlled to acquire super-resolution ultrasound images of the imaging tissue; The step of determining the tissue motion suppression mode of the imaging tissue based on the tissue type includes: When the tissue type is a relatively static or slightly moving tissue, the tissue motion suppression mode of the imaging tissue is determined to be the first tissue motion suppression mode; When the tissue type is a tissue with a large amplitude of motion, the tissue motion suppression mode of the imaging tissue is determined to be the second tissue motion suppression mode; The step of controlling the ultrasound probe to acquire super-resolution ultrasound images of the tissue based on the tissue motion suppression method includes: When the tissue motion inhibition method is the second tissue motion inhibition method, the ultrasound probe is fixed by the clamping component in the fixing structure; The ideal image data of the ideal tissue of interest section of the imaging tissue is found by the ultrasound probe, and an ideal mask image corresponding to the ideal image data is generated. The ultrasound probe acquires a scanning section image of the imaging tissue, and generates a scanning mask image of the scanning section image; wherein, the ultrasound probe is moved by the fixed structure to acquire a real-time scanning section image of the imaging tissue, and the scanning section image is binarized according to a target threshold to obtain the scanning mask image corresponding to the scanning section image. A correlation parameter is determined between the ideal mask image and the scanned mask image. By displaying the correlation parameter on the scanned section image, the scanning user is provided with an indication of the current section's motion. The ultrasound probe is constrained according to the correlation parameter to keep it relatively stationary with the scanned section, thereby achieving the acquisition of super-resolution ultrasound images of the imaging tissue. Specifically, for each scanned section image generated during real-time scanning, a correlation coefficient is calculated between the scanned mask image and the ideal mask image corresponding to the ideal image data. The larger the correlation coefficient, the closer the real-time scanned section is to the ideal tissue of interest section.

2. The method according to claim 1, characterized in that, The step of controlling the ultrasound probe to acquire super-resolution ultrasound images of the tissue based on the tissue motion suppression method includes: When the tissue motion inhibition method is the first tissue motion inhibition method, the ultrasound probe is fixed by the clamping component in the fixing structure; The ultrasound probe is used to acquire super-resolution ultrasound images of the tissue.

3. The method according to claim 2, characterized in that, The fixing structure includes a main body and an adjusting arm mounted on the main body; an adjusting button is mounted on the main body, and the adjusting arm is connected to the clamping member; the acquisition of super-resolution ultrasound images of the imaging tissue through the ultrasound probe includes: The adjustment arm is adjusted by the adjustment button on the control body to move the clamping member, thereby driving the ultrasound probe fixed by the clamping member to acquire super-resolution ultrasound images of the imaging tissue.

4. The method according to claim 3, characterized in that, The adjusting arm includes a vertical adjusting arm, a horizontal adjusting arm connected to the vertical adjusting arm, and a serpentine arm connected to the horizontal adjusting arm; the clamping member is installed at the tail of the serpentine arm; The adjustment button on the main body is used to control the vertical adjustment arm and the horizontal adjustment arm to move in the vertical and horizontal directions respectively, so as to adjust the position of the ultrasonic probe fixed by the clamping member; The serpentine arm is used to adjust the clamping member to move the ultrasonic probe fixed by the clamping member.

5. The method according to claim 1, characterized in that, The correlation parameters for determining the ideal mask image and the scanned mask image include: The two-dimensional correlation coefficient between the ideal mask image and the scanned mask image is determined based on the ideal mask image, the size of the ideal mask image, the mean of the ideal mask image, the scanned mask image, the size of the scanned mask image, and the mean of the scanned mask image. The two-dimensional correlation coefficient parameter is determined as the correlation parameter between the ideal mask image and the scanned mask image.

6. The method according to claim 1, characterized in that, The method further includes: Extract the edge features of the ideal mask image; The edge features are denoised, and the denoised edge features are made transparent and displayed on the scanning section image. The ultrasound probe is constrained based on the scanning section image with the edge features made transparent.

7. The method according to claim 1, characterized in that, The method further includes: The correlation parameters are color-coded, and the correlation color codes are displayed on the scanned section image. The ultrasound probe is constrained according to the correlation color codes.

8. A super-resolution ultrasound imaging device, characterized in that, Performing the method according to any one of claims 1-7, comprising: The type acquisition module is used to obtain the tissue type of the imaged tissue. The mode determination module is used to determine the tissue motion suppression mode of the imaging tissue based on the tissue type. The motion suppression module is used to control the ultrasound probe to acquire super-resolution ultrasound images of the tissue according to the tissue motion suppression mode.

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