A clinical anesthesia ultrasound image-assisted positioning guidance method and system

Abstract

The present invention relates to the field of image processing technology, and specifically to a method and system for assisting the positioning and guidance of clinical anesthesia ultrasound images, comprising: obtaining the overall enhancement expectation of the target area in each frame of ultrasound image based on the distance between each feature point in the target area and each feature point in each interference area in each frame of ultrasound image, and the grayscale value of each pixel point in the target area; and achieving auxiliary positioning of the puncture needle in the ultrasound image based on the overall enhancement expectation of the target area in each frame of ultrasound image, the angle between each segment of the target area and the horizontal direction, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel point in each segment of the target area in each frame of ultrasound image. Thus, the present invention enhances the puncture needle area in each frame of ultrasound image based on the high echo characteristics of the puncture needle in the ultrasound image during the puncture process, thereby improving the accuracy of the positioning of the puncture needle in the ultrasound image.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a method and system for clinical anesthesia ultrasound image-assisted positioning guidance. Background Art

[0002] Ultrasound image-assisted positioning for clinical anesthesia involves scanning the patient's body surface with an ultrasonic probe to obtain real-time images of internal structures (such as blood vessels, nerves, and tissues). This allows the anesthesiologist to visualize the needle's trajectory during the puncture process, enabling visual guidance and more accurate punctures. Traditional blind puncture methods rely heavily on the physician's anatomical knowledge and manual experience, and are susceptible to inaccurate positioning due to various factors. Ultrasound image-assisted positioning guidance significantly reduces reliance on anatomical landmarks, making puncture procedures more objective and accurate. However, during the real-time puncture process, the puncture needle may be interfered with by surrounding tissue, resulting in unclear visualization in the ultrasound image. This reduces the accuracy of the needle's positioning in the ultrasound image and affects the physician's judgment of the needle's real-time position and trajectory. Summary of the Invention

[0003] The present invention provides a clinical anesthesia ultrasound image-assisted positioning guidance method and system to solve the existing problems.

[0004] The present invention provides a clinical anesthesia ultrasound image-assisted positioning guidance method and system using the following technical solutions:

[0005] One embodiment of the present invention provides a clinical anesthesia ultrasound image-assisted positioning guidance method, the method comprising the following steps:

[0006] Acquire a plurality of dynamic object regions in each frame of ultrasound image; each frame of ultrasound image corresponds to a time point;

[0007] Based on the grayscale value of each pixel in each dynamic object region in each frame of ultrasound image, a target region and several interference regions are screened from all dynamic object regions; the pixel with the largest grayscale value in each dynamic object region is recorded as a feature point, and the degree of influence of puncture time on the visualization of the target region in each frame of ultrasound image is obtained based on the distance between the feature point of the target region and the feature point of each interference region in each frame of ultrasound image and the grayscale value of each pixel in the target region;

[0008] The overall enhancement expectation of the target area in each frame of ultrasound image is obtained based on the influence of puncture time on the visualization of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of the target area in each frame of ultrasound image, and the distance between the centroid of the target area and each pixel on the edge of each interference area;

[0009] The target area in each frame of ultrasound image is divided into several segments. According to the overall enhancement expectation of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel in each segment of the target area in each frame of ultrasound image, auxiliary positioning of the puncture needle in the ultrasound image is achieved.

[0010] Furthermore, the method of screening out a target region and several interference regions from all dynamic object regions according to the grayscale value of each pixel in each dynamic object region in each frame of ultrasound image includes the following specific steps:

[0011] The first Frame ultrasound image The inverse of the information entropy of the grayscale values of all pixels in the dynamic object area is Frame ultrasound image The product of the grayscale mean values of all pixels in the dynamic object area is recorded as Frame ultrasound image The degree to which the dynamic object area conforms to the regularity of the puncture needle area;

[0012] In each frame of ultrasound image, the dynamic object region corresponding to the maximum value of the degree of compliance with the puncture needle region rule is recorded as the target region, and the dynamic object region other than the target region is recorded as the interference region.

[0013] Furthermore, the method of obtaining the degree of influence of the puncture time on the visualization of the target area in each frame of the ultrasound image based on the distance between the feature point of the target area and the feature point of each interference area in each frame of the ultrasound image and the grayscale value of each pixel in the target area includes the following specific steps:

[0014] The first Frame ultrasound image to The ultrasound image between the frames is recorded as A reference image of a frame ultrasound image, wherein A first quantity threshold is preset;

[0015] Calculate the The sum of the distances between the feature points of the target area and the feature points in all interference areas in any reference image of the frame ultrasound image is used to calculate the distance between the feature points of the target area and all interference areas. The absolute value of the difference between the sum of the distances between the feature points of the target area in any two adjacent reference images of the frame ultrasound image and the feature points in all interference areas is recorded as the relative position change of the feature points of the target area in any two adjacent reference images;

[0016] In the Among all the reference images of the frame ultrasound image, the relative position changes of the feature points of the target area in all two adjacent reference images are sequentially formed into the first A distance sequence of frame ultrasound images;

[0017] The first The time points corresponding to all reference images of the frame ultrasound image constitute the first-order difference sequence of the time series, which is recorded as Time difference sequence of frame ultrasound images;

[0018] In the In all reference images of the frame ultrasound image, the absolute value of the difference between the grayscale means of all pixels in the target area of any two adjacent reference images is calculated, and the absolute value of the difference between the grayscale means of all pixels in the target area of all two adjacent reference images is sequentially calculated to form the first A sequence of grayscale values of a frame ultrasound image;

[0019] The first The distance sequence of the frame ultrasound image and the The Pearson correlation coefficient of the time difference sequence of the frame ultrasound image and the The gray value sequence of the frame ultrasound image is The product of the Pearson correlation coefficient of the time difference sequence of the frame ultrasound image is recorded as the correlation between the puncture time and the first The degree of influence of the visualization of the target area in the frame ultrasound image.

[0020] Furthermore, obtaining the overall enhancement expectation of the target area in each frame of ultrasound image based on the influence of the puncture time on the development of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of the target area in each frame of ultrasound image, and the distance between the centroid of the target area and each pixel on the edge of each interference area includes the following specific steps:

[0021] Calculate the The distance between the centroid of the target area in the frame ultrasound image and all the pixels on the edge of each interference area is calculated. The minimum value of the distance to the centroid of the target area in the frame ultrasound image is recorded as The reference distance between the centroid of the target area and each interference area in the frame ultrasound image;

[0022] The maximum value of the distances between any two pixels on the edge of the target area in each frame of ultrasound image is recorded as the reference length of the target area in each frame of ultrasound image;

[0023] The overall enhancement expectation of the target area in each frame of ultrasound image is obtained based on the influence of puncture time on the visualization of the target area in each frame of ultrasound image, the reference length of the target area, and the reference distance between the center of mass of the target area and each interference area.

[0024] Furthermore, the specific calculation formula for the overall enhancement expectation of the target area in each frame of ultrasound image is obtained based on the degree of influence of the puncture time on the development of the target area in each frame of ultrasound image, the reference length of the target area, and the reference distance between the centroid of the target area and each interference area:

[0025]

[0026] in, Indicates the The overall enhancement expectation of the target area in the frame ultrasound image, Indicates the puncture time for the The degree of influence of the development of the target area in the frame ultrasound image, Indicates the The number of interference areas in the frame ultrasound image, Indicates the The centroid of the target area in the frame ultrasound image is The reference distance of the interference area, Indicates the The reference length of the target area in the frame ultrasound image is The absolute value of the difference in the reference length of the target area in the frame ultrasound image, Indicates the The grayscale mean of all pixels in the target area of the frame ultrasound image, Indicates the The grayscale mean of all pixels in the target area of the frame ultrasound image, represents the linear normalization function, represents the absolute value function.

[0027] Furthermore, the target area in each frame of the ultrasound image is divided into several segments, and auxiliary positioning of the puncture needle in the ultrasound image is achieved based on the overall enhancement expectation of the target area in each frame of the ultrasound image, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel in each segment of the target area in each frame of the ultrasound image. The specific steps include the following:

[0028] Get the The minimum bounding rectangle of the target area in the frame ultrasound image is divided into two equal parts along the long side of the minimum bounding rectangle. segments, and the target area in each segment is used as the target area of each segment, where A second quantity threshold is preset;

[0029] Calculate the length of the line between any two pixels on the edge of each target area in each frame of ultrasound image, and record the maximum length of all the lines between any two pixels as the reference length of each target area in each frame of ultrasound image;

[0030] The minimum angle between the line corresponding to the reference length of each target area in each frame of ultrasound image and the horizontal direction is recorded as the angle between the target area and the horizontal direction;

[0031] The first Frame and All the ultrasound images before the frame The maximum value of the grayscale mean of all pixels in the target area corresponds to the The angle between the target area and the horizontal direction is recorded as The optimal angle for developing the target area;

[0032] A rectangular coordinate system is constructed with the upper left corner of each frame of ultrasound image as the origin, the horizontal axis to the right as the horizontal axis, and the vertical axis downward as the vertical axis;

[0033] According to the overall enhancement expectation of the target area in each frame of ultrasound image, the vertical coordinate of each pixel point on the edge of each segment of the target area in the rectangular coordinate system, the reference length of each segment of the target area in each frame of ultrasound image, and the optimal angle of development, the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image is obtained;

[0034] Obtaining an updated grayscale value of each pixel in each target region in each frame of the ultrasound image according to an adaptive enhancement coefficient of each target region in each frame of the ultrasound image and a grayscale value of each pixel in each target region;

[0035] An enhanced image of each frame of ultrasound image is obtained according to the updated grayscale value of each pixel point in each target area of each frame of ultrasound image.

[0036] Furthermore, the specific calculation formula for the adaptive enhancement coefficient of each target region in each frame of ultrasound image is obtained based on the overall enhancement expectation of the target region in each frame of ultrasound image, the vertical coordinate of each pixel point on the edge of each target region in the rectangular coordinate system, the reference length of each target region in each frame of ultrasound image, and the optimal angle of development:

[0037]

[0038] in, Indicates the Frame ultrasound image Adaptive enhancement coefficient of the target area of the segment, Indicates the The overall enhancement expectation of the target area in the frame ultrasound image, Indicates the Frame ultrasound image The angle between the target area and the horizontal direction, Indicates the Frame ultrasound image The optimal angle for developing the target area. Indicates the Frame ultrasound image The reference length of the segment target area, is a sine function, Indicates the The rectangular coordinate system of the frame ultrasound image The minimum value of the vertical coordinates of all pixels on the edge of the target area. represents the absolute value function.

[0039] Furthermore, the method of obtaining an updated grayscale value of each pixel in each target region in each frame of the ultrasound image according to the adaptive enhancement coefficient of each target region in each frame of the ultrasound image and the grayscale value of each pixel in each target region includes the following specific steps:

[0040] In the In the ultrasound image frame, In the target area of the segment The gray value of the pixel is The product of the adaptive enhancement coefficient of the target area of the segment plus the sum of the preset constants is rounded up to the integer value, which is recorded as Frame ultrasound image In the target area of the segment Updated grayscale value of each pixel.

[0041] Furthermore, obtaining an enhanced image of each frame of ultrasound image according to the updated grayscale value of each pixel in each target area of each frame of ultrasound image includes the following specific steps:

[0042] The first The gray value of each pixel in each target area of the frame ultrasound image is replaced by the updated gray value, and the first Enhanced image of the frame ultrasound image.

[0043] The present invention also proposes a clinical anesthesia ultrasound image-assisted positioning and guidance system, which includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor executes the computer program stored in the memory to implement the steps of the aforementioned clinical anesthesia ultrasound image-assisted positioning and guidance method.

[0044] The beneficial effects of the technical solution of the present invention are:

[0045] In an embodiment of the present invention, several dynamic object regions are acquired in each ultrasound image frame. The degree of influence of puncture time on the visualization of the target region in each ultrasound image frame is determined based on the distance between each feature point in the target region and each feature point in each interference region, as well as the grayscale value of each pixel in the target region. By screening several feature points from the target region and the interference regions, the most significant pixels within the region are captured, which often represent the primary features of the region. By analyzing each feature point, the accuracy of puncture needle positioning in the ultrasound image is effectively improved. Based on the degree of influence of puncture time on the visualization of the target region in each ultrasound image frame and the distance between the target region's centroid and each pixel on the edge of each interference region, the overall enhancement expectation of the target region in each ultrasound image frame is determined. This analysis of the target region ensures comprehensive visualization assessment of the target region, improves the accuracy of the target region's edge features, and further improves the accuracy of puncture needle positioning in the ultrasound image. Based on the overall enhancement expectation of the target region in each ultrasound image frame and the angle between each target region segment and the horizontal direction, auxiliary puncture needle positioning in the ultrasound image is achieved. Thus, the present invention enhances the puncture needle area in each frame of ultrasound image according to the high echo characteristics of the puncture needle in the ultrasound image during the puncture process, thereby improving the accuracy of positioning the puncture needle in the ultrasound image. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 This is a flowchart of the steps of a clinical anesthesia ultrasound image-assisted positioning guidance method of the present invention;

[0048] Figure 2 This is an ultrasound image during clinical anesthesia in this embodiment. DETAILED DESCRIPTION

[0049] To further illustrate the technical means and effectiveness of the present invention to achieve the intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method and system for clinical anesthesia ultrasound image-assisted positioning guidance, including its specific implementation, structure, features, and effectiveness. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0050] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0051] The following describes in detail a specific solution of a clinical anesthesia ultrasound image-assisted positioning and guidance method and system provided by the present invention with reference to the accompanying drawings.

[0052] See also Figure 1 , which shows a flowchart of a method for clinical anesthesia ultrasound image-assisted positioning guidance provided by one embodiment of the present invention, the method comprising the following steps:

[0053] Step S001: Acquire a plurality of dynamic object regions in each frame of ultrasound image; each frame of ultrasound image corresponds to a time point.

[0054] Several frames of ultrasound images are collected in real time, and each frame of ultrasound image corresponds to a time point.

[0055] What needs to be explained is: Figure 2 This is the ultrasound image during clinical anesthesia in this embodiment. It can be found that Figure 2 The information in the image is relatively fuzzy. In order to enhance the contrast of the image, grayscale adaptive equalization is performed on each frame of the ultrasound image. Grayscale adaptive equalization is a well-known technology and the specific method will not be introduced here.

[0056] During clinical anesthesia under ultrasound guidance, the position and path of the puncture needle need to be accurately monitored in real time. Therefore, a target tracking algorithm is used to identify and track dynamic objects in consecutive image frames. However, since the puncture needle passes through soft tissue in the body during the puncture process, these soft tissues will also move due to the puncture action, causing the algorithm to mistakenly identify them as dynamic objects. For example, blood vessels, nerves, muscle tissue, etc. will also appear to move or change in ultrasound images, especially when the doctor is operating. These structures may exhibit dynamic characteristics due to pressure from the instrument or movement during the operation.

[0057] The trained YOLO target detection algorithm is used to obtain several dynamic object regions in each frame of ultrasound image.

[0058] It should be noted that: the YOLO target detection algorithm is a well-known technology. The main neural network model used by the YOLO target detection algorithm in this embodiment is a convolutional neural network. The data set used is ultrasound image data. The pixels to be segmented are divided into two categories, that is, the label annotation process corresponding to the training set is: a single-channel semantic label, the corresponding position pixel belongs to the background class and is labeled as 0, and belongs to the dynamic object area and is labeled as 1. The loss function used is the cross entropy loss function, and the dynamic object area is output.

[0059] Step S002: Based on the grayscale value of each pixel point in each dynamic object area in each frame of ultrasound image, a target area and several interference areas are screened out from all dynamic object areas; the pixel point with the largest grayscale value in each dynamic object area is recorded as a feature point, and the degree of influence of the puncture time on the development of the target area in each frame of ultrasound image is obtained based on the distance between the feature point of the target area and the feature point of each interference area in each frame of ultrasound image and the grayscale value of each pixel point in the target area.

[0060] The puncture needle is typically made of metal, which has a much higher density than the surrounding tissue, resulting in it appearing as hyperechoic in ultrasound images. Surrounding tissues, such as blood vessels, nerves, and muscles, have echogenic properties that vary depending on their tissue type and structure. However, they are generally not as bright as the puncture needle and are typically characterized by medium or low echoes. Therefore, the grayscale value of the puncture needle in each ultrasound image frame is significantly higher than that of the surrounding tissue area.

[0061] In addition to the grayscale features mentioned above, the puncture needle is typically a slender structure with a long, rectangular shape. Since it is usually made of metal, it often has a smooth surface without significant bumps. Therefore, the texture of the puncture needle region is relatively simple. The surrounding tissue may have more details and textures, such as blood vessel branches and muscle fibers. Therefore, the texture disorder of the surrounding tissue region in each ultrasound frame is significantly higher than that of the puncture needle region. Based on the above features, the degree to which each dynamic object region conforms to the regularity of the puncture needle region is determined.

[0062] The first Frame ultrasound image The inverse of the information entropy of the grayscale values of all pixels in the dynamic object area is Frame ultrasound image The product of the grayscale mean values of all pixels in the dynamic object area is recorded as Frame ultrasound image The degree to which the dynamic object area conforms to the regularity of the puncture needle area.

[0063] What needs to be explained is: Frame ultrasound image The information entropy of the grayscale values of all pixels in the dynamic object area represents the The greater the degree of clutter in the texture of the dynamic object area, the greater the information entropy. The more chaotic the texture inside the dynamic object area, the The smaller the degree to which the dynamic object region conforms to the puncture needle region rule, the smaller the degree to which the dynamic object region conforms to the puncture needle region rule. The information entropy of the grayscale values of all pixels in each dynamic object region is a well-known technology, and the specific method is not introduced here.

[0064] According to the above method, the degree to which each dynamic object region in each frame of ultrasound image conforms to the puncture needle region rule can be obtained.

[0065] In each frame of ultrasound image, the dynamic object region corresponding to the maximum value of the degree of compliance with the puncture needle region rule is recorded as the target region, and the dynamic object region other than the target region is recorded as the interference region.

[0066] It should be noted that if there are multiple dynamic object regions corresponding to the maximum value of the degree of compliance with the puncture needle region rule, the dynamic object region with the largest grayscale mean value of all pixels is selected for analysis.

[0067] During the puncture process, the puncture needle will generate a squeezing force on the surrounding tissue. This force will cause the soft tissue to deform, causing the surrounding tissue to shift from its originally designated position. As the puncture time passes, the puncture needle gradually penetrates deeper into the soft tissue, and this process will produce physical effects such as squeezing and friction on the surrounding tissue. These physical effects will cause the surrounding tissue to shift to a certain degree, causing the relative position of the puncture needle and the surrounding tissue to change. The soft tissue will deform after being subjected to the physical effect of the puncture needle, but will then try to restore its original shape. However, due to the continuity of the puncture process and the complexity of the soft tissue characteristics, this recovery may be incomplete or there may be a lag. Therefore, the longer the puncture time, the more obvious the change in the relative position between the puncture needle and the surrounding tissue may be.

[0068] After the puncture needle enters the skin, as it progresses deeper, it may pass through tissue layers of varying composition and structure. These differing tissues reflect ultrasound waves in varying ways. For example, adipose tissue, muscle tissue, and blood vessels reflect ultrasound waves with significantly different intensities, resulting in variations in the grayscale value of the puncture needle region in the ultrasound image. Therefore, the effect of puncture time on the visualization of the target region in each ultrasound image frame is determined by the grayscale changes in the target region and its relative position relative to surrounding tissue.

[0069] The pixel with the largest gray value in each dynamic object area is recorded as a feature point.

[0070] The first Frame ultrasound image to The ultrasound image between the frames is recorded as The reference image of the frame ultrasound image.

[0071] It should be noted that: in this embodiment, the first quantity threshold is preset For example, If the number of pixels is less than a preset first threshold, the frame of ultrasound image is not analyzed. If there are multiple pixels with the largest grayscale value in each dynamic object area, one of them is randomly selected for analysis.

[0072] Calculate the The sum of the distances between the feature points of the target area and the feature points in all interference areas in any reference image of the frame ultrasound image is used to calculate the distance between the feature points of the target area and all interference areas. The absolute value of the difference between the sum of the distances between the feature points of the target area in any two adjacent reference images of the frame ultrasound image and the feature points in all interference areas is recorded as the relative position change of the feature points of the target area in any two adjacent reference images.

[0073] In the Among all the reference images of the frame ultrasound image, the relative position changes of the feature points of the target area in all two adjacent reference images are sequentially formed into the first The distance sequence of the frame ultrasound image.

[0074] The first The time points corresponding to all reference images of the frame ultrasound image constitute the first-order difference sequence of the time series, which is recorded as Time difference sequence of ultrasound image frames.

[0075] In the In all reference images of the frame ultrasound image, the absolute value of the difference between the grayscale means of all pixels in the target area of any two adjacent reference images is calculated, and the absolute value of the difference between the grayscale means of all pixels in the target area of all two adjacent reference images is sequentially calculated to form the first A sequence of grayscale values of an ultrasound image frame.

[0076] The first The distance sequence of the frame ultrasound image and the The Pearson correlation coefficient of the time difference sequence of the frame ultrasound image and the The gray value sequence of the frame ultrasound image is The product of the Pearson correlation coefficient of the time difference sequence of the frame ultrasound image is recorded as the correlation between the puncture time and the first The degree of influence of the visualization of the target area in the frame ultrasound image.

[0077] It should be noted that the Pearson correlation coefficient is a well-known technique and the specific method will not be introduced here.

[0078] According to the above method, the influence degree of the puncture time on the visualization of the target area in each frame of the ultrasound image can be obtained.

[0079] Step S003: obtaining the overall enhancement expectation of the target area in each frame of ultrasound image based on the degree of influence of the puncture time on the visualization of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of the target area in each frame of ultrasound image, and the distance between the centroid of the target area and each pixel on the edge of each interference area;

[0080] During the puncture process, the tissue structure and puncture depth surrounding the puncture needle area are different in each frame of the ultrasound image. Different tissue structures (such as skin, muscle, blood vessels, nerves, etc.) have different reflection and absorption capabilities for ultrasound waves, so the brightness and contrast in the image will also vary. In order to clearly display the puncture needle area, different image frames may need to be enhanced to varying degrees. When the puncture needle is close to the surrounding tissue, for example, when the puncture needle is close to blood vessels, nerves, or other sensitive tissues, the echo signals of these tissues may overlap with the echo signals of the puncture needle, causing the puncture needle area to become blurred or difficult to identify in the image. At this time, in order to accurately display the position and status of the puncture needle, a certain degree of enhancement is required for this frame of ultrasound image.

[0081] In addition to the aforementioned characteristics, changes in the length of the puncture needle region between adjacent ultrasound image frames directly reflect the needle's motion in time and space. Large changes in the needle length between adjacent frames may indicate blurring, ghosting, or loss of detail in the current frame's image capture of the needle's motion. This means that the greater the degree of enhancement required for that frame, the greater the corresponding overall enhancement desired.

[0082] Calculate the The distance between the centroid of the target area in the frame ultrasound image and all the pixels on the edge of each interference area is calculated. The minimum value of the distance to the centroid of the target area in the frame ultrasound image is recorded as The reference distance between the centroid of the target area and each interference area in the frame ultrasound image.

[0083] The maximum value of the distances between any two pixel points on the edge of the target area in each frame of the ultrasound image is recorded as the reference length of the target area in each frame of the ultrasound image.

[0084] First Frame ultrasound image as an example, then the The calculation formula for the overall enhancement expectation of the target area in the frame ultrasound image is:

[0085]

[0086] in, Indicates the The overall enhancement expectation of the target area in the frame ultrasound image, Indicates the puncture time for the The degree of influence of the development of the target area in the frame ultrasound image, Indicates the The number of interference areas in the frame ultrasound image, Indicates the The centroid of the target area in the frame ultrasound image is The reference distance of the interference area, Indicates the The reference length of the target area in the frame ultrasound image is The absolute value of the difference in the reference length of the target area in the frame ultrasound image, Indicates the The grayscale mean of all pixels in the target area of the frame ultrasound image, Indicates the The grayscale mean of all pixels in the target area of the frame ultrasound image, represents the linear normalization function, represents the absolute value function.

[0087] Step S004: Divide the target area in each frame of the ultrasound image into several segments, and implement auxiliary positioning of the puncture needle in the ultrasound image based on the overall enhancement expectation of the target area in each frame of the ultrasound image, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel in each segment of the target area in each frame of the ultrasound image.

[0088] As the puncture needle penetrates deeper, the ultrasonic wave gradually attenuates during propagation. This attenuation is due to energy loss as the sound wave propagates through the medium, including scattering and absorption. Therefore, the deeper the puncture needle is inserted, the lower the energy of the ultrasonic wave reaching that area, resulting in a weakened reflected signal, which manifests as a lower grayscale value on the image. The needle tip is particularly sensitive, as its contact with soft tissue is closer and the applied force is more concentrated, resulting in more significant grayscale changes around it and requiring a greater degree of enhancement.

[0089] In addition, during the puncture process, the position and angle of the puncture needle will continue to change. This dynamic change will cause the reflection path and reflection characteristics of the ultrasound to change accordingly, causing the grayscale value and clarity of the puncture needle in the ultrasound image to fluctuate. When the puncture needle punctures at a certain angle, the reflected ultrasonic signal is the strongest, the corresponding grayscale value is also the largest, and it is more obvious in the image. At this time, this angle is the optimal angle for the puncture needle to be displayed in the ultrasound image. However, due to the different distances between the local areas of the puncture needle and the surrounding tissues and the puncture depth, the optimal display angle of each local area is also different. Therefore, the optimal display angle of each local area is obtained based on the angle between the horizontal direction and the corresponding grayscale value of each local area in the historical frame when the grayscale value is the highest.

[0090] Get the The minimum bounding rectangle of the target area in the frame ultrasound image is divided into two equal parts along the long side of the minimum bounding rectangle. segments, and the target area in each segment is used as the target area of each segment.

[0091] It should be noted that: in this embodiment, the second quantity threshold is preset The value is 3, and this is used as an example for description.

[0092] Calculate the length of the line between any two pixels on the edge of each target area in each frame of ultrasound image, and record the maximum length of all the lines between any two pixels as the reference length of each target area in each frame of ultrasound image;

[0093] The minimum angle between the line corresponding to the reference length of each target area in each frame of ultrasound image and the horizontal direction is recorded as the angle between the target area and the horizontal direction.

[0094] If there are multiple lines corresponding to the reference length, select any one of them as an example for analysis.

[0095] The first Frame and All the ultrasound images before the frame The maximum value of the grayscale mean of all pixels in the target area corresponds to the The angle between the target area and the horizontal direction is recorded as The optimal angle for developing the target area.

[0096] A rectangular coordinate system is constructed with the upper left corner of each frame of ultrasound image as the origin, the horizontal axis to the right as the horizontal axis, and the vertical axis downward as the vertical axis.

[0097] First Frame ultrasound image as an example, then the Frame ultrasound image The calculation formula of the adaptive enhancement coefficient of the target area is:

[0098]

[0099] in, Indicates the Frame ultrasound image Adaptive enhancement coefficient of the target area of the segment, Indicates the The overall enhancement expectation of the target area in the frame ultrasound image, Indicates the Frame ultrasound image The angle between the target area and the horizontal direction, Indicates the Frame ultrasound image The optimal angle for developing the target area. Indicates the Frame ultrasound image The reference length of the segment target area, is a sine function, Indicates the The rectangular coordinate system of the frame ultrasound image The minimum value of the vertical coordinates of all pixels on the edge of the target area. represents the absolute value function.

[0100] What needs to be explained is: Indicates the Frame ultrasound image The relative depth of the segment target area.

[0101] According to the above steps, the enhancement coefficient required for each local area of the puncture needle is obtained, and the grayscale values of all pixels in the puncture needle area are corrected according to the enhancement coefficient required for each local area, thereby obtaining an enhanced ultrasound image.

[0102]

[0103] in, Indicates the Frame ultrasound image In the target area of the segment Updated grayscale value of pixels, Indicates the Frame ultrasound image In the target area of the segment The gray value of a pixel, Indicates the Frame ultrasound image Adaptive enhancement coefficient of the target area of the segment, is a preset constant, is the ceiling function.

[0104] It should be noted that: in this embodiment, the preset constant The value is 8, and this is used as an example for description.

[0105] The first The gray value of each pixel in each target area of the frame ultrasound image is replaced by the updated gray value, and the first Enhanced image of the frame ultrasound image.

[0106] What needs to be explained is that by performing a linear transformation on the grayscale value of each pixel in the target area of each frame of ultrasound image, an updated grayscale value of each pixel is obtained, thereby improving the image quality of each frame of ultrasound image. As a result, the puncture needle will be clearer in the enhanced image of each frame of ultrasound image, effectively assisting the doctor in judging the real-time position of the puncture needle and improving the puncture accuracy.

[0107] So far, the present invention is completed.

[0108] In summary, in an embodiment of the present invention, several dynamic object regions are obtained in each frame of an ultrasound image; each frame of the ultrasound image corresponds to a time point; a target region and several interference regions are screened from all dynamic object regions based on the grayscale value of each pixel in each dynamic object region in each frame of the ultrasound image; the pixel with the largest grayscale value in each dynamic object region is recorded as a feature point, and the degree of influence of the puncture time on the development of the target region in each frame of the ultrasound image is obtained based on the distance between the feature point of the target region and the feature point of each interference region in each frame of the ultrasound image and the grayscale value of each pixel in the target region; Based on the degree of influence of the puncture time on the development of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of the target area in each frame of ultrasound image, and the distance between the center of mass of the target area and each pixel on the edge of each interference area, the overall enhancement expectation of the target area in each frame of ultrasound image is obtained; the target area in each frame of ultrasound image is divided into several segments, and based on the overall enhancement expectation of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel in each segment of the target area in each frame of ultrasound image, auxiliary positioning of the puncture needle in the ultrasound image is achieved. So far, the present invention enhances the puncture needle area in each frame of ultrasound image based on the high echo characteristics of the puncture needle in the ultrasound image during the puncture process, thereby improving the accuracy of puncture needle positioning in the ultrasound image.

[0109] The present invention also provides a clinical anesthesia ultrasound image-assisted positioning and guidance system, comprising a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor executes the computer program stored in the memory to implement the steps of the aforementioned clinical anesthesia ultrasound image-assisted positioning and guidance method.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A clinical anesthesia ultrasound image-assisted positioning guidance method, characterized in that: The method comprises the following steps: Acquire a plurality of dynamic object regions in each frame of ultrasound image; each frame of ultrasound image corresponds to a time point; Based on the grayscale value of each pixel in each dynamic object region in each frame of ultrasound image, a target region and several interference regions are screened from all dynamic object regions; the pixel with the largest grayscale value in each dynamic object region is recorded as a feature point, and the degree of influence of puncture time on the visualization of the target region in each frame of ultrasound image is obtained based on the distance between the feature point of the target region and the feature point of each interference region in each frame of ultrasound image and the grayscale value of each pixel in the target region; The overall enhancement expectation of the target area in each ultrasound image frame is obtained based on the influence of the puncture time on the visualization of the target area in each ultrasound image frame, the distance between any two pixels on the edge of the target area in each ultrasound image frame, and the distance between the centroid of the target area and each pixel on the edge of each interference area. The specific steps include the following: Calculate the The distance between the centroid of the target area in the frame ultrasound image and all the pixels on the edge of each interference area is calculated. The minimum value of the distance to the centroid of the target area in the frame ultrasound image is recorded as The reference distance between the centroid of the target area and each interference area in the frame ultrasound image; The maximum value of the distances between any two pixels on the edge of the target area in each frame of ultrasound image is recorded as the reference length of the target area in each frame of ultrasound image; The overall enhancement expectation of the target area in each frame of ultrasound image is obtained based on the influence of puncture time on the visualization of the target area in each frame of ultrasound image, the reference length of the target area, and the reference distance between the centroid of the target area and each interference area; The target area in each frame of ultrasound image is divided into several segments. Based on the overall enhancement expectation of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel in each segment of the target area in each frame of ultrasound image, auxiliary positioning of the puncture needle in the ultrasound image is achieved, including: Get the The minimum bounding rectangle of the target area in the frame ultrasound image is divided into two equal parts along the long side of the minimum bounding rectangle. segments, and the target area in each segment is used as the target area of each segment, where A second quantity threshold is preset; The length of the line between any two pixel points on the edge of each target area in each frame of ultrasound image is calculated, and the maximum value of the length of the line between all any two pixel points is recorded as the reference length of each target area in each frame of ultrasound image; then, the target area is enhanced in a targeted manner according to the puncture depth and puncture angle.

2. The clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 1, characterized in that: The specific steps of screening out a target region and several interference regions from all dynamic object regions according to the grayscale value of each pixel in each dynamic object region in each frame of ultrasound image are as follows: The first Frame ultrasound image The inverse of the information entropy of the grayscale values of all pixels in the dynamic object area is Frame ultrasound image The product of the grayscale mean values of all pixels in the dynamic object area is recorded as Frame ultrasound image The degree to which the dynamic object area conforms to the regularity of the puncture needle area; In each frame of ultrasound image, the dynamic object region corresponding to the maximum value of the degree of compliance with the puncture needle region rule is recorded as the target region, and the dynamic object region other than the target region is recorded as the interference region.

3. The clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 1, characterized in that: The method of obtaining the degree of influence of the puncture time on the development of the target area in each frame of ultrasound image according to the distance between the feature point of the target area and the feature point of each interference area in each frame of ultrasound image and the grayscale value of each pixel in the target area includes the following specific steps: The first Frame ultrasound image to The ultrasound image between the frames is recorded as A reference image of a frame ultrasound image, wherein A first quantity threshold is preset; Calculate the The sum of the distances between the feature points of the target area in any reference image of the frame ultrasound image and the feature points in all interference areas is calculated. The absolute value of the difference between the sum of the distances between the feature points of the target area in any two adjacent reference images of the frame ultrasound image and the feature points in all interference areas is recorded as the relative position change of the feature points of the target area in any two adjacent reference images; In the Among all the reference images of the frame ultrasound image, the relative position changes of the feature points of the target area in all two adjacent reference images are sequentially formed into the first A distance sequence of frame ultrasound images; The first The time points corresponding to all reference images of the frame ultrasound image constitute the first-order difference sequence of the time series, which is recorded as Time difference sequence of frame ultrasound images; In the In all reference images of the frame ultrasound image, the absolute value of the difference between the grayscale means of all pixels in the target area of any two adjacent reference images is calculated, and the absolute value of the difference between the grayscale means of all pixels in the target area of all two adjacent reference images is sequentially calculated to form the first A sequence of grayscale values of a frame ultrasound image; The first The distance sequence of the frame ultrasound image is The Pearson correlation coefficient of the time difference sequence of the frame ultrasound image and the The gray value sequence of the frame ultrasound image is The product of the Pearson correlation coefficient of the time difference sequence of the frame ultrasound image is recorded as the correlation between the puncture time and the first The degree of influence of the visualization of the target area in the frame ultrasound image.

4. The clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 1, characterized in that: The specific calculation formula for obtaining the overall enhancement expectation of the target area in each frame of ultrasound image based on the influence of the puncture time on the development of the target area in each frame of ultrasound image, the reference length of the target area, and the reference distance between the centroid of the target area and each interference area is: in, Indicates the The overall enhancement expectation of the target area in the frame ultrasound image, Indicates the puncture time for the The degree of influence of the development of the target area in the frame ultrasound image, Indicates the The number of interference areas in the frame ultrasound image, Indicates the The centroid of the target area in the frame ultrasound image is The reference distance of the interference area, Indicates the The reference length of the target area in the frame ultrasound image is The absolute value of the difference in the reference length of the target area in the frame ultrasound image, Indicates the The grayscale mean of all pixels in the target area of the frame ultrasound image, Indicates the The grayscale mean of all pixels in the target area of the frame ultrasound image, represents the linear normalization function, represents the absolute value function.

5. The clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 1, characterized in that: The target area in each frame of ultrasound image is divided into several segments, and auxiliary positioning of the puncture needle in the ultrasound image is achieved based on the overall enhancement expectation of the target area in each frame of ultrasound image, the distance between any two pixels on the edge of each segment of the target area, and the grayscale value of each pixel in each segment of the target area in each frame of ultrasound image. The specific steps include the following: The minimum angle between the line corresponding to the reference length of each target area in each frame of ultrasound image and the horizontal direction is recorded as the angle between the target area and the horizontal direction; The first Frame and All the ultrasound images before the frame The maximum value of the grayscale mean of all pixels in the target area corresponds to the The angle between the target area and the horizontal direction is recorded as The optimal angle for developing the target area; A rectangular coordinate system is constructed with the upper left corner of each frame of ultrasound image as the origin, the horizontal axis to the right as the horizontal axis, and the vertical axis downward as the vertical axis; According to the overall enhancement expectation of the target area in each frame of ultrasound image, the vertical coordinate of each pixel point on the edge of each segment of the target area in the rectangular coordinate system, the reference length of each segment of the target area in each frame of ultrasound image, and the optimal angle of development, the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image is obtained; Obtaining an updated grayscale value of each pixel in each target region in each frame of the ultrasound image according to an adaptive enhancement coefficient of each target region in each frame of the ultrasound image and a grayscale value of each pixel in each target region; An enhanced image of each frame of ultrasound image is obtained according to the updated grayscale value of each pixel point in each target area of each frame of ultrasound image.

6. A clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 5, characterized in that: The specific calculation formula for the adaptive enhancement coefficient of each target region in each frame of ultrasound image is obtained based on the overall enhancement expectation of the target region in each frame of ultrasound image, the vertical coordinate of each pixel point on the edge of each target region in the rectangular coordinate system, the reference length of each target region in each frame of ultrasound image, and the optimal angle of development: in, Indicates the Frame ultrasound image Adaptive enhancement coefficient of the target area of the segment, Indicates the The overall enhancement expectation of the target area in the frame ultrasound image, Indicates the Frame ultrasound image The angle between the target area and the horizontal direction, Indicates the Frame ultrasound image The optimal angle for developing the target area. Indicates the Frame ultrasound image The reference length of the segment target area, is a sine function, Indicates the The rectangular coordinate system of the frame ultrasound image The minimum value of the vertical coordinates of all pixels on the edge of the target area. represents the absolute value function.

7. The clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 5, characterized in that: The method of obtaining the updated grayscale value of each pixel in each target region in each frame of the ultrasound image according to the adaptive enhancement coefficient of each target region in each frame of the ultrasound image and the grayscale value of each pixel in each target region includes the following specific steps: In the In the ultrasound image frame, In the target area of the segment The gray value of the pixel is The product of the adaptive enhancement coefficient of the target area of the segment plus the sum of the preset constants is rounded up to the integer value, which is recorded as Frame ultrasound image In the target area of the segment Updated grayscale value of each pixel.

8. The clinical anesthesia ultrasound image-assisted positioning guidance method according to claim 5, characterized in that: The method of obtaining an enhanced image of each frame of ultrasound image according to the updated grayscale value of each pixel point in each target area of each frame of ultrasound image includes the following specific steps: The first The gray value of each pixel in each target area of the frame ultrasound image is replaced by the updated gray value, and the first Enhanced image of the frame ultrasound image.

9. A clinical anesthesia ultrasound image-assisted positioning guidance system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of a clinical anesthesia ultrasound image-assisted positioning and guidance method as described in any one of claims 1 to 8 are implemented.

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