Clinical anesthesia ultrasonic image assisted positioning guiding method and system

Abstract

The invention relates to the technical field of image processing, in particular to a clinical anesthesia ultrasonic image auxiliary positioning guiding method and system, and the method comprises the steps: obtaining a positioning result according to the distance between each feature point of a target region in each frame of ultrasonic image and each feature point in each interference region, and the gray value of each pixel point in the target region; obtaining the overall enhancement expectation of the target area in each frame of ultrasonic image; according to the overall enhancement expectation of the target area in each frame of ultrasonic image, the included angle between each section of target area and the horizontal direction, the distance between any two pixel points on the edge of each section of target area and the gray value of each pixel point in each section of target area in each frame of ultrasonic image, auxiliary positioning of the puncture needle in the ultrasonic image is achieved. Therefore, according to the high echo characteristic of the puncture needle in the ultrasonic image in the puncture process, the puncture needle area in each frame of ultrasonic image is enhanced, and the positioning accuracy of the puncture needle in the ultrasonic image is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and particularly relates to a method and system for assisting in positioning and guiding clinical anesthesia ultrasound images. Background Art

[0002] Clinical anesthesia ultrasound image-assisted positioning refers to scanning the patient's body surface with an ultrasonic probe to obtain real-time images of internal structures (such as blood vessels, nerves, tissues, etc.), seeing the trajectory of the needle during the puncture process, enabling anesthesiologists to perform operations under visual guidance, and making the puncture more accurate. The traditional blind puncture method highly depends on the doctor's anatomical knowledge and tactile experience and is easily affected by various factors, resulting in inaccurate positioning. The ultrasound image-assisted positioning and guiding method, however, greatly reduces the dependence on anatomical landmarks and makes the puncture operation more objective and accurate. However, during the real-time puncture process, the puncture needle will be interfered by the surrounding tissues, resulting in unclear imaging in the ultrasound image, reducing the accuracy of positioning the puncture needle in the ultrasound image, and thus affecting the doctor's judgment of the real-time position and movement trajectory of the puncture needle. Summary of the Invention

[0003] The present invention provides a method and system for assisting in positioning and guiding clinical anesthesia ultrasound images to solve the existing problems.

[0004] The method and system for assisting in positioning and guiding clinical anesthesia ultrasound images of the present invention adopt the following technical solutions: An embodiment of the present invention provides a method for assisting in positioning and guiding clinical anesthesia ultrasound images, and the method includes the following steps: Obtain a plurality of dynamic object regions in each frame of ultrasound image; each frame of ultrasound image corresponds to a time point; According to the gray values of each pixel point in each dynamic object region in each frame of ultrasound image, screen out a target region and a plurality of interference regions from all dynamic object regions; record the pixel point with the largest gray value in each dynamic object region as a feature point, and according to 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 gray value of each pixel point in the target region, obtain the influence degree of the puncture time on the imaging of the target region in each frame of ultrasound image; According to the influence degree of the puncture time on the imaging of the target region in each frame of ultrasound image, the distance between any two pixel points on the edge of the target region in each frame of ultrasound image, and the distance between the centroid of the target region and each pixel point on the edge of each interference region, obtain the overall enhancement expectation of the target region in each frame of ultrasound image; Divide the target area in each frame of ultrasound image into several segments, and realize the auxiliary positioning of the puncture needle in the ultrasound image according to the overall enhancement expectation of the target area in each frame of ultrasound image, the distance between any two pixel points on the edge of each segment of the target area, and the gray value of each pixel point in each segment of the target area in each frame of ultrasound image.

[0005] Further, the step of screening out a target area and several interference areas from all dynamic object areas according to the gray value of each pixel point in each dynamic object area in each frame of ultrasound image includes the following specific steps: The reciprocal of the information entropy of the gray value information of all pixel points in the th dynamic object area in the th frame of ultrasound image is multiplied by the gray mean value of all pixel points in the th dynamic object area in the th frame of ultrasound image, and is denoted as the degree of compliance with the puncture needle area rule of the th dynamic object area in the th frame of ultrasound image;

[0006] Further, the step of obtaining the influence degree of the puncture time on the development of the target area in each frame of ultrasound image according to the distance between the feature points of the target area and the feature points of each interference area in each frame of ultrasound image and the gray value of each pixel point in the target area includes the following specific steps: The ultrasound images between the th frame of ultrasound image and the th frame of ultrasound image are denoted as the reference images of the th frame of ultrasound image, where is a preset first quantity threshold; Calculate the sum value of the distances between the feature points of the target area in any reference image of the th frame of ultrasound image and the feature points in all interference areas, and denote the absolute value of the difference between the sum values of the distances between the feature points of the target area in any two adjacent reference images of the th frame of ultrasound image and the feature points in all interference areas as the relative position change amount of the feature points of the target area in any two adjacent reference images; In all reference images of the th frame of ultrasound image, the relative position change amounts of the feature points of the target area in all adjacent two reference images are successively formed into the distance sequence of the th frame of ultrasound image; The The time points corresponding to all reference images of the frame ultrasound images form a first-order difference sequence of the time series, denoted as the time difference sequence of the frame ultrasound image; Among all the reference images of the frame ultrasound image, calculate the absolute value of the difference between the grayscale means of all pixel points in the target area of any two adjacent reference images. In turn, the absolute values of the differences between the grayscale means of all pixel points in the target area of all adjacent two reference images form the grayscale value sequence of the frame ultrasound image; Multiply the Pearson correlation coefficient between the distance sequence of the frame ultrasound image and the time difference sequence of the frame ultrasound image, and the Pearson correlation coefficient between the grayscale value sequence of the frame ultrasound image and the time difference sequence of the frame ultrasound image. Denote the product as the influence degree of the puncture time on the development of the target area in the frame ultrasound image.

[0007] Further, the specific steps for obtaining the overall enhancement expectation of the target area in each frame of ultrasound image according to the influence degree of the puncture time on the development of the target area in each frame of ultrasound image, the distance between any two pixel points 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 point on the edge of each interference area are as follows: Calculate the distances between the centroid of the target area in the frame ultrasound image and all pixel points on the edge of each interference area. Denote the minimum value among the distances between all pixel points on the edge of each interference area and the centroid of the target area in the frame ultrasound image as the reference distance between the centroid of the target area in the frame ultrasound image and each interference area; Denote the maximum value among the distances between all arbitrary two pixel points on the edge of the target area in each frame of ultrasound image as the reference length of the target area in each frame of ultrasound image; According to the influence degree 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, obtain the overall enhancement expectation of the target area in each frame of ultrasound image.

[0008] Further, the specific calculation formula for obtaining the overall enhancement expectation of the target area in each frame of ultrasound image according to the influence degree 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: Where, Indicates the overall enhancement expectation of the target area in the n-th frame of ultrasound image, indicating the influence degree of the puncture time on the development of the target area in the n-th frame of ultrasound image, Indicates the number of interference areas in the n-th frame of ultrasound image, Indicates the reference distance between the centroid of the target area and the m-th interference area in the n-th frame of ultrasound image, Indicates the absolute value of the difference between the reference length of the target area in the n-th frame of ultrasound image and the reference length of the target area in the n-th frame of ultrasound image, Indicates the average gray value of all pixel points in the target area in the n-th frame of ultrasound image, Indicates the average gray value of all pixel points in the target area in the n-th frame of ultrasound image, Indicates the linear normalization function, Indicates the absolute value function.

[0009] Furthermore, dividing the target area in each frame of ultrasound image 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 pixel points on the edge of each segment of the target area, and the gray value of each pixel point in each segment of the target area in each frame of ultrasound image, realizing the auxiliary positioning of the puncture needle in the ultrasound image, including the following specific steps: Obtain the minimum circumscribed rectangle of the target area in the n-th frame of ultrasound image, and equally divide the minimum circumscribed rectangle into k segments along the long side of the minimum circumscribed rectangle, taking the target area in each segment as each segment of the target area, where k is a preset second quantity threshold; Calculate the length of the connection line between any two pixel points on the edge of each segment of the target area in each frame of ultrasound image, and record the maximum value among the lengths of all the connection lines between any two pixel points as the reference length of each segment of the target area in each frame of ultrasound image; Record the minimum included angle between the connection line corresponding to the reference length of each segment of the target area in each frame of ultrasound image and the horizontal direction as the included angle between the target area and the horizontal direction; Record the included angle between the n-th segment of the target area and the horizontal direction, which is the maximum value of the average gray values of all pixel points in the n-th segment of the target area in all frames of ultrasound image before the n-th frame and the m-th frame, as the included angle between the Optimal angle for segment target area development; Taking the upper left corner of each frame of ultrasound image as the origin, with the horizontal direction to the right as the horizontal axis and the vertical direction downwards as the vertical axis, a rectangular coordinate system is constructed; According to the overall enhancement expectation of the target area in each frame of ultrasound image, the ordinate 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 for development, the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image is obtained; According to the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image and the gray value of each pixel point in each segment of the target area, the updated gray value of each pixel point in each segment of the target area in each frame of ultrasound image is obtained; According to the updated gray value of each pixel point in each segment of the target area in each frame of ultrasound image, the enhanced image of each frame of ultrasound image is obtained.

[0010] Furthermore, the specific calculation formula for obtaining the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image according to the overall enhancement expectation of the target area in each frame of ultrasound image, the ordinate 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 for development is: Among them, represents the adaptive enhancement coefficient of the th segment of the target area in the th frame of ultrasound image, represents the overall enhancement expectation of the target area in the th frame of ultrasound image, represents the angle between the th segment of the target area and the horizontal direction in the th frame of ultrasound image, represents the optimal angle for development of the th segment of the target area in the th frame of ultrasound image, represents the reference length of the th segment of the target area in the th frame of ultrasound image, is the sine function, represents the minimum value of the ordinates of all pixel points on the edge of the th segment of the target area in the rectangular coordinate system of the th frame of ultrasound image, represents the absolute value function.

[0011] Further, obtaining the updated gray value of each pixel in each target region of each frame of ultrasound image based on the adaptive enhancement coefficient of each target region in each frame of ultrasound image and the gray value of each pixel in each target region includes the following specific steps: In the th frame of ultrasound image, the ceiling value of the sum of the product of the gray value of the th pixel in the th target region and the adaptive enhancement coefficient of the th target region plus a preset constant is denoted as the updated gray value of the th pixel in the th target region in the th frame of ultrasound image.

[0012] Further, obtaining the enhanced image of each frame of ultrasound image based on the updated gray value of each pixel in each target region of each frame of ultrasound image includes the following specific steps: Replacing the gray value of each pixel in each target region in the th frame of ultrasound image with the updated gray value to obtain the enhanced image of the th frame of ultrasound image.

[0013] The present invention also provides a clinical anesthesia ultrasound image-assisted positioning and guiding system, including a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the computer program stored in the memory to implement the steps of the foregoing clinical anesthesia ultrasound image-assisted positioning and guiding method.

[0014] The beneficial effects of the technical solution of the present invention are: In an embodiment of the present invention, a plurality of dynamic object regions in each frame of ultrasound image are acquired; according to the distance between each feature point in the target region and each feature point in each interference region in each frame of ultrasound image and the gray value of each pixel point in the target region, the influence degree of the puncture time on the development of the target region in each frame of ultrasound image is obtained; by screening a plurality of feature points from the target region and the interference region, the most significant pixel points in the region can be captured, and these points often represent the main features of the region. By analyzing each feature point, the accuracy of puncture needle positioning in the ultrasound image is effectively improved. According to the influence degree of the puncture time on the development of the target region in each frame of ultrasound image and the distance between the centroid of the target region and each pixel point on the edge of each interference region, the overall enhancement expectation of the target region in each frame of ultrasound image is obtained; based on the analysis of the target region, the comprehensiveness of the development evaluation of the target region is ensured, the accuracy of the edge features of the target region is improved, and the accuracy of puncture needle positioning in the ultrasound image is further improved. According to the overall enhancement expectation of the target region in each frame of ultrasound image and the angle between each segment of the target region and the horizontal direction, the auxiliary positioning of the puncture needle in the ultrasound image is realized. Thus, according to the high echo characteristics of the puncture needle in the ultrasound image during the puncture process, the puncture needle region in each frame of ultrasound image is enhanced to improve the accuracy of puncture needle positioning in the ultrasound image. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0016] Figure 1 It is a flowchart of the steps of a method for clinically anesthetizing ultrasound image assisted positioning and guiding according to the present invention; Figure 2 It is an ultrasound image during the clinical anesthesia process in this embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in conjunction with the drawings and preferred embodiments, detail the specific implementation manners, structures, features and effects of a method and system for clinically anesthetizing ultrasound image assisted positioning and guiding according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs.

[0019] The following specifically describes the specific solutions of a clinical anesthesia ultrasound image-assisted positioning and guiding method and system provided by the present invention in conjunction with the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of the steps of a clinical anesthesia ultrasound image-assisted positioning and guiding method provided by an embodiment of the present invention. The method includes the following steps: Step S001: Obtain several dynamic object regions in each frame of ultrasound image; each frame of ultrasound image corresponds to a time point.

[0021] Collect several frames of ultrasound images in real time, and each frame of ultrasound image corresponds to a time point.

[0022] It should be noted that: Figure 2 For the ultrasound images during the clinical anesthesia process in this embodiment, it can be found that Figure 2 the information in is relatively blurred. In order to enhance the contrast of the image, each frame of ultrasound image is subjected to gray-level adaptive equalization processing. Among them, gray-level adaptive equalization is a well-known technology, and the specific method is not introduced here.

[0023] During clinical anesthesia under ultrasound guidance, the position and path of the puncture needle need to be monitored in real time and accurately. Therefore, a target tracking algorithm is used to identify and track dynamic objects in consecutive image frames. However, during the puncture process, the puncture needle will pass through soft tissues in the body, and these soft tissues will also move due to the puncture action, resulting in being misidentified as dynamic objects by the algorithm. For example, blood vessels, nerves, muscle tissues, etc. will also be shown as moving or changing in ultrasound images, especially during the operation of the doctor, these structures may exhibit dynamic characteristics due to the compression of instruments or the movement during the operation.

[0024] Use the trained YOLO target detection algorithm to obtain several dynamic object regions in each frame of ultrasound image.

[0025] It should be noted that: Among them, the YOLO target detection algorithm is a well-known technology. The main neural network model used in the YOLO target detection algorithm in this embodiment is a convolutional neural network. The dataset used is ultrasound image data. The pixel points to be segmented are divided into 2 categories. That is, the label annotation process for the training set is: for the single-channel semantic label, the pixel points at the corresponding positions belonging to the background class are labeled as 0, and those belonging to the dynamic object region are labeled as 1. The loss function used is the cross-entropy loss function, and the dynamic object region is output.

[0026] Step S002: According to the gray values of each pixel point in each dynamic object region of each frame of ultrasound image, a target region and several interference regions are screened out from all the dynamic object regions; the pixel point with the largest gray value in each dynamic object region is recorded as a feature point, and according to the distance between the feature point of the target region and the feature points of each interference region in each frame of ultrasound image and the gray value of each pixel point in the target region, the influence degree of the puncture time on the development of the target region in each frame of ultrasound image is obtained.

[0027] The puncture needle is usually made of metal material, and its density is much higher than that of the surrounding tissues, so it appears as a high echo in the ultrasound image. For the surrounding tissues, such as blood vessels, nerves, muscles, etc., their echo characteristics vary depending on the tissue type and structure, but generally they are not as bright as the puncture needle completely, and they are usually medium or low echo structures. Therefore, the gray value of the puncture needle in each frame of ultrasound image is significantly higher than that of the surrounding tissue region.

[0028] In addition to the above-mentioned gray characteristics, the puncture needle is usually a slender structure, shaped like a long strip, and because it is usually made of metal material, it often has a smooth and non-significant concave-convex surface. Therefore, the texture of the puncture needle region is relatively simple. While the surrounding tissues may have more details and textures, such as the branches of blood vessels, the fibers of muscles, etc. Therefore, the degree of texture chaos in the surrounding tissue region in each frame of ultrasound image is significantly higher than that in the puncture needle region. According to the above characteristics, the degree of compliance of each dynamic object region with the puncture needle region rule is obtained.

[0029] The product of the reciprocal of the information entropy of the gray values of all pixel points in the th dynamic object region in the th frame of ultrasound image and the gray mean value of all pixel points in the th dynamic object region in the th frame of ultrasound image is recorded as the degree of compliance of the th dynamic object region in the th frame of ultrasound image with the puncture needle region rule.

[0030] It should be noted that: the information entropy of the gray values of all pixel points in the th dynamic object region in the th frame of ultrasound image represents the degree of texture chaos inside the th dynamic object region. The larger the information entropy, the more chaotic the texture inside the th dynamic object region, and the smaller the degree of compliance of the th dynamic object region with the puncture needle region rule. Among them, the information entropy of the gray values of all pixel points in each dynamic object region is a well-known technology, and the specific method will not be introduced here.

[0031] In the above manner, the degree to which each dynamic object region in each frame of ultrasound image conforms to the pattern of the puncture needle region can be obtained.

[0032] In each frame of ultrasound image, the dynamic object region corresponding to the maximum value in the degree of conformity to the pattern of the puncture needle region is denoted as the target region, and the dynamic object regions other than the target region are denoted as interference regions.

[0033] It should be noted that: if there are multiple dynamic object regions corresponding to the maximum value in the degree of conformity to the pattern of the puncture needle region, the dynamic object region with the largest average gray value of all pixel points is selected for analysis.

[0034] During the puncture process, the puncture needle will exert a squeezing force on the surrounding tissues. This force will cause the soft tissues to deform, thereby causing the surrounding tissues to shift from their original designated positions. As the puncture time progresses, the puncture needle gradually penetrates into the soft tissues, and during this process, physical effects such as squeezing and friction will be exerted on the surrounding tissues. These physical effects will cause a certain degree of displacement of the surrounding tissues, resulting in a change in the relative position between the puncture needle and the surrounding tissues. After being subjected to the physical effects of the puncture needle, the soft tissues will deform, but then they will attempt to restore their original shape. However, due to the persistence of the puncture process and the complexity of the characteristics of the soft tissues, this restoration 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 tissues may be.

[0035] After the puncture needle enters the skin, as it penetrates deeper, it may pass through tissue layers with different compositions and structures. Different tissues have different compositions and structures, and their reflection characteristics of ultrasonic waves are also different. For example, there are significant differences in the reflection intensity of ultrasonic waves by adipose tissue, muscle tissue, blood vessels, etc., resulting in changes in the gray values of the puncture needle region in the ultrasonic image. Therefore, according to the change in the gray value of the target region and the amount of change in the relative position with the surrounding tissues, the influence degree of the puncture time on the visualization of the target region in each frame of ultrasonic image is obtained.

[0036] The pixel point with the largest gray value in each dynamic object region is denoted as the feature point.

[0037] The frame of ultrasound image to the frame of ultrasound image are denoted as the reference image of the frame of ultrasound image.

[0038] It should be noted that: in this embodiment, the preset first quantity threshold is 5, and this is used as an example for description. When is less than the preset first quantity threshold, this frame of ultrasound image is not analyzed. If there are multiple pixel points with the largest gray value in each dynamic object region, any one of them is selected for analysis.

[0039] Calculate the sum of the distances between the feature points in the target region and the feature points in all interference regions in any reference image of the th frame of ultrasonic image. Denote the absolute value of the difference between the sums of the distances between the feature points in the target region and the feature points in all interference regions in any two adjacent reference images of the th frame of ultrasonic image as the relative position change amount of the feature points in the target region in any two adjacent reference images.

[0040] In all reference images of the th frame of ultrasonic image, successively form the relative position change amounts of the feature points in the target region in all adjacent two reference images to constitute the distance sequence of the th frame of ultrasonic image.

[0041] Form the first-order difference sequence of the time points corresponding to all reference images of the th frame of ultrasonic image, and denote it as the time difference sequence of the th frame of ultrasonic image.

[0042] In all reference images of the th frame of ultrasonic image, calculate the absolute value of the difference between the grayscale means of all pixel points in the target region in any two adjacent reference images. Successively form the absolute values of the differences between the grayscale means of all pixel points in the target region in all adjacent two reference images to constitute the grayscale value sequence of the th frame of ultrasonic image.

[0043] Denote the product of the Pearson correlation coefficient between the distance sequence of the th frame of ultrasonic image and the time difference sequence of the th frame of ultrasonic image and the Pearson correlation coefficient between the grayscale value sequence of the th frame of ultrasonic image and the time difference sequence of the th frame of ultrasonic image as the influence degree of the puncture time on the development of the target region in the th frame of ultrasonic image.

[0044] It should be noted that: the Pearson correlation coefficient is a well-known technology, and the specific method will not be introduced here.

[0045] In the above manner, the influence degree of the puncture time on the development of the target region in each frame of ultrasonic image can be obtained.

[0046] Step S003: Obtain the overall enhancement expectation of the target region in each frame of ultrasonic image according to the influence degree of the puncture time on the development of the target region in each frame of ultrasonic image, the distance between any two pixel points on the edge of the target region in each frame of ultrasonic image, and the distances between the centroid of the target region and each pixel point on the edge of each interference region; During the puncture process, the tissue structures and puncture depths around the puncture needle area in each frame of ultrasound image are different. Different tissue structures (such as skin, muscle, blood vessel, nerve, etc.) have different abilities to reflect and absorb ultrasonic waves, so their brightness and contrast performances in the image will also vary. To clearly display the puncture needle area, different degrees of enhancement may be required for different image frames. When the puncture needle is close to surrounding tissues, for example, when the puncture needle approaches blood vessels, nerves or other sensitive tissues, the echo signals of these tissues may overlap with the echo signals of the puncture needle, resulting in the puncture needle area becoming blurred or difficult to identify in the image. At this time, to accurately display the position and state of the puncture needle, a certain degree of enhancement is required for this frame of ultrasound image.

[0047] In addition to the above features, the change in the length of the puncture needle area in adjacent frames of ultrasound images directly reflects the movement of the puncture needle in time and space. If the change in the length of the puncture needle between adjacent frames is large, it may mean that there are problems such as blurring, ghosting or loss of details in capturing the dynamics of the puncture needle in the current frame image, that is, the greater the degree of enhancement required for this frame of ultrasound image, the greater the corresponding overall enhancement expectation.

[0048] Calculate the distances from the centroid of the target area in the th frame of ultrasound image to all pixel points on the edge of each interference area, and record the minimum value among the distances from all pixel points on the edge of each interference area to the centroid of the target area in the th frame of ultrasound image as the reference distance from the centroid of the target area in the th frame of ultrasound image to each interference area.

[0049] Record the maximum value among the distances between any two pixel points on the edge of the target area in each frame of ultrasound image as the reference length of the target area in each frame of ultrasound image.

[0050] Taking the th frame of ultrasound image as an example, the calculation formula for the overall enhancement expectation of the target area in the th frame of ultrasound image is as follows: Among them, represents the overall enhancement expectation of the target area in the th frame of ultrasound image, represents the influence degree of the puncture time on the visualization of the target area in the th frame of ultrasound image, represents the number of interference areas in the th frame of ultrasound image, represents the th frame of ultrasound image, and The reference distance of an interference region denotes the absolute value of the difference between the reference length of the target region in the -th frame of the ultrasonic image and the reference length of the target region in the -th frame of the ultrasonic image denotes the average gray value of all pixel points within the target region in the -th frame of the ultrasonic image denotes the average gray value of all pixel points within the target region in the -th frame of the ultrasonic image denotes the linear normalization function

[0051] Step S004: Divide the target region in each frame of the ultrasonic image into several segments, and realize the auxiliary positioning of the puncture needle in the ultrasonic image according to the overall enhancement expectation of the target region in each frame of the ultrasonic image, the distance between any two pixel points on the edge of each segment of the target region, and the gray value of each pixel point in each segment of the target region in each frame of the ultrasonic image

[0052] As the puncture needle penetrates deeper, the ultrasonic wave will gradually attenuate during propagation. This attenuation is due to the energy loss when the sound wave propagates in the medium, including processes such as scattering and absorption. Therefore, the deeper the puncture needle penetrates, the lower the energy of the ultrasonic wave reaching this part, resulting in a weakening of the reflected signal, and thus showing a decrease in the gray value on the image. Especially in the needle tip part, due to closer contact with soft tissues and more concentrated force, the gray change around it is more significant and the degree of enhancement required is greater

[0053] In addition, during the puncture process, the position and angle of the puncture needle will constantly change. This dynamic change will cause the reflection path and reflection characteristics of the ultrasonic wave to change accordingly, resulting in fluctuations in the gray value and clarity of the puncture needle in the ultrasonic image. When the puncture needle punctures at a certain specific angle, the reflected ultrasonic wave signal is the strongest, the corresponding gray value is the largest, and it is also more obvious in the image. At this time, this angle is the optimal angle for the puncture needle to appear in the ultrasonic image. However, due to the different distances between each local area of the puncture needle and the surrounding tissues and the different puncture depths, the optimal angles for each local area to appear are different. Therefore, the optimal angles for each local area to appear are obtained according to the angles corresponding to the highest gray value of each local area in the historical frame with respect to the horizontal direction

[0054] Obtain the minimum bounding rectangle of the target region in the -th frame of the ultrasonic image. Along the long side of the minimum bounding rectangle, equally divide the minimum bounding rectangle into segments, and use the target region in each segment as each segment of the target region

[0055] 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.

[0056] 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 value of the lengths of the lines between any two pixels as the reference length of each target area in each frame of ultrasound image; 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.

[0057] If there are multiple lines corresponding to the reference length, select any one of them as an example for analysis.

[0058] The first Frame and In 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.

[0059] 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.

[0060] First frame ultrasound image as an example, then Frame ultrasound image The calculation formula of the adaptive enhancement coefficient of the target area is: in, Indicates Frame ultrasound image The adaptive enhancement coefficient of the target area of ​​the segment, Indicates The overall enhancement expectation of the target area in the frame ultrasound image, Indicates Frame ultrasound image The angle between the target area and the horizontal direction, Indicates Frame ultrasound image The optimal angle for developing the target area. Indicates Frame ultrasound image The reference length of the segment target area, is a sine function, Indicates The rectangular coordinate system of the frame ultrasound image The minimum value of the vertical coordinates of all pixel points on the edge of the segment target area Represents the absolute value function

[0061] It should be noted that Represents the relative depth of the segment target area in the

[0062] According to the above steps, the enhancement coefficient required for each local area of the puncture needle is obtained, and the gray values of all pixel points in the puncture needle area are corrected according to the enhancement coefficient required for each local area, so as to obtain the enhanced ultrasonic image

[0063] Among them Represents the updated gray value of the nth pixel point in the segment target area in the mth frame of ultrasonic image Represents the gray value of the nth pixel point in the segment target area in the kth frame of ultrasonic image Represents the adaptive enhancement coefficient of the segment target area in the kth frame of ultrasonic image

[0064] It should be noted that: in this embodiment, the preset constant is 8, and this is taken as an example for description

[0065] Replace the gray value of each pixel point in each segment target area in the kth frame of ultrasonic image with the updated gray value to obtain the enhanced image of the kth frame of ultrasonic image

[0066] It should be noted that: by performing a linear transformation on the gray value of each pixel point in the target area of each frame of ultrasonic image, the updated gray value of each pixel point is obtained, improving the image quality of each frame of ultrasonic image. Therefore, the puncture needle will be clearer in the enhanced image of each frame of ultrasonic image, effectively assisting the doctor in judging the real-time position of the puncture needle and improving the puncture accuracy

[0067] So far, the present invention is completed

[0068] In summary, in the embodiments of the present invention, a plurality of dynamic object regions in each frame of ultrasound image are obtained; each frame of ultrasound image corresponds to a time point; according to the gray values of each pixel point in each dynamic object region in each frame of ultrasound image, a target region and a plurality of interference regions are screened out from all the dynamic object regions; the pixel point with the largest gray value in each dynamic object region is recorded as a feature point, and according to 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 gray value of each pixel point in the target region, the influence degree of the puncture time on the development of the target region in each frame of ultrasound image is obtained; according to the influence degree of the puncture time on the development of the target region in each frame of ultrasound image, the distance between any two pixel points on the edge of the target region in each frame of ultrasound image, and the distance between the centroid of the target region and each pixel point on the edge of each interference region, the overall enhancement expectation of the target region in each frame of ultrasound image is obtained; the target region in each frame of ultrasound image is divided into several segments, and according to the overall enhancement expectation of the target region in each frame of ultrasound image, the distance between any two pixel points on the edge of each segment of the target region, and the gray value of each pixel point in each segment of the target region in each frame of ultrasound image, the auxiliary positioning of the puncture needle in the ultrasound image is realized. Thus, according to the high echo characteristics of the puncture needle in the ultrasound image during the puncture process, the present invention enhances the puncture needle region in each frame of ultrasound image, improving the accuracy of positioning the puncture needle in the ultrasound image.

[0069] The present invention also provides a clinical anesthesia ultrasound image auxiliary positioning and guiding system, including a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the computer program stored in the memory to implement the steps of the foregoing clinical anesthesia ultrasound image auxiliary positioning method.

[0070] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for clinically anesthetizing ultrasound image-assisted positioning and guiding, characterized in that, The method includes the following steps: Obtain a plurality of dynamic object regions in each frame of ultrasound image; each frame of ultrasound image corresponds to a time point; According to the gray values of each pixel point in each dynamic object region of each frame of ultrasound image, screen out a target region and a plurality of interference regions from all the dynamic object regions; mark the pixel point with the largest gray value in each dynamic object region as a feature point, and according to 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 gray value of each pixel point in the target region, obtain the influence degree of the puncture time on the development of the target region in each frame of ultrasound image; According to the influence degree of the puncture time on the development of the target region in each frame of ultrasound image, the distance between any two pixel points on the edge of the target region in each frame of ultrasound image, and the distance between the centroid of the target region and each pixel point on the edge of each interference region, obtain the overall enhancement expectation of the target region in each frame of ultrasound image; Divide the target region in each frame of ultrasound image into several segments, and according to the overall enhancement expectation of the target region in each frame of ultrasound image, the distance between any two pixel points on the edge of each segment of the target region, and the gray value of each pixel point in each segment of the target region in each frame of ultrasound image, realize the auxiliary positioning of the puncture needle in the ultrasound image.

2. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 1, wherein The step of screening out a target region and a plurality of interference regions from all the dynamic object regions according to the gray values of each pixel point in each dynamic object region of each frame of ultrasound image includes the following specific steps: Multiply the reciprocal of the information entropy of the gray values of all pixel points within the th dynamic object region in the th frame of ultrasound image by the gray mean value of all pixel points within the th dynamic object region in the th frame of ultrasound image. Denote the result as the degree to which the th dynamic object region in the th frame of ultrasound image conforms to the puncture needle region pattern; In each frame of ultrasound image, mark the dynamic object region corresponding to the maximum value in the degree of conforming to the puncture needle region rule as the target region, and mark the dynamic object regions other than the target region as interference regions.

3. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 1, wherein The step of obtaining the influence degree of the puncture time on the development of the target region in each frame of ultrasound image according to 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 gray value of each pixel point in the target region includes the following specific steps: From the th frame of ultrasound image to the th frame of ultrasound image, the ultrasound images are denoted as the reference images of the th frame of ultrasound image, where is a preset first quantity threshold; Calculate the sum of the distances between the feature points in the target region and the feature points in all interference regions in any reference image of the frame of ultrasound image. Denote the absolute value of the difference between the sum of the distances between the feature points in the target region and the feature points in all interference regions in any two adjacent reference images of the frame of ultrasound image as the relative position change amount of the feature points in the target region in any two adjacent reference images; Among all the reference images of the frame ultrasound image, the relative position change amounts of the feature points in the target region in all adjacent two reference images are successively formed into the distance sequence of the frame ultrasound image; Construct a first-order difference sequence of the time series from the time points corresponding to all the reference images of the frame ultrasound image, denoted as the time difference sequence of the frame ultrasound image; Among all the reference images of the frame ultrasound image, calculate the absolute value of the difference in the average gray value of all pixel points in the target region between any two adjacent reference images, and successively form the absolute value of the difference in the average gray value of all pixel points in the target region between all adjacent two reference images into the gray value sequence of the frame ultrasound image; The Pearson correlation coefficient between the distance sequence of the -th frame ultrasound image and the time difference sequence of the -th frame ultrasound image, and the product of the Pearson correlation coefficient between the gray value sequence of the -th frame ultrasound image and the time difference sequence of the -th frame ultrasound image are denoted as the influence degree of the puncture time on the development of the target area in the -th frame ultrasound image.

4. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 1, wherein The step of obtaining the overall enhancement expectation of the target region in each frame of ultrasound image according to the influence degree of the puncture time on the development of the target region in each frame of ultrasound image, the distance between any two pixel points on the edge of the target region in each frame of ultrasound image, and the distance between the centroid of the target region and each pixel point on the edge of each interference region includes the following specific steps: Calculate the distance between the centroid of the target region in the -th frame of ultrasound image and all pixel points on the edge of each interference region, and record the minimum value among the distances between all pixel points on the edge of each interference region and the centroid of the target region in the -th frame of ultrasound image as the reference distance between the centroid of the target region in the -th frame of ultrasound image and each interference region; Mark the maximum value among all the distances between any two pixel points on the edge of the target region in each frame of ultrasound image as the reference length of the target region in each frame of ultrasound image; According to the influence degree of the puncture time on the development of the target region in each frame of ultrasound image, the reference length of the target region, and the reference distance between the centroid of the target region and each interference region, obtain the overall enhancement expectation of the target region in each frame of ultrasound image.

5. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 4, characterized in that, The specific calculation formula for obtaining the overall enhancement expectation of the target region in each frame of ultrasound image according to the influence degree of the puncture time on the development of the target region in each frame of ultrasound image, the reference length of the target region, and the reference distance between the centroid of the target region and each interference region is: Among them, represents the overall enhancement expectation of the target region in the nth frame of ultrasound image, represents the influence degree of the puncture time on the visualization of the target region in the nth frame of ultrasound image, represents the number of interference regions in the nth frame of ultrasound image, represents the reference distance between the centroid of the target region and the nth frame of ultrasound image and the mth interference region, represents the absolute value of the difference between the reference length of the target region in the nth frame of ultrasound image and the reference length of the target region in the kth frame of ultrasound image, represents the average gray value of all pixel points in the target region in the nth frame of ultrasound image, represents the average gray value of all pixel points in the target region in the kth frame of ultrasound image, represents the linear normalization function, represents the absolute value function.

6. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 1, wherein 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 pixel points on the edge of each segment of the target area, and the gray value of each pixel point in each segment of the target area in each frame of ultrasound image, the auxiliary positioning of the puncture needle in the ultrasound image is realized, and the specific steps are as follows: Obtain the minimum bounding rectangle of the target region in the th frame of ultrasound image. Along the long side of the minimum bounding rectangle, divide the minimum bounding rectangle into equal segments, and use the target region in each segment as the target region of each segment, where is a preset second quantity threshold; Calculate the length of the line connecting any two pixel points on the edge of each segment of the target area in each frame of ultrasound image, and record the maximum value among the lengths of all the lines connecting any two pixel points as the reference length of each segment of the target area in each frame of ultrasound image; Record the minimum angle between the line corresponding to the reference length of each segment of the target area in each frame of ultrasound image and the horizontal direction as the angle between the target area and the horizontal direction; The maximum value among the gray-scale means of all pixel points in the th frame and all frames before the th frame in the th segment of the target area in the ultrasonic images corresponds to the th segment of the angle between the target area and the horizontal direction, which is denoted as the th segment of the optimal angle for the development of the target area; Taking the upper left corner of each frame of ultrasound image as the origin, the horizontal right direction as the horizontal axis, and the vertical downward direction as the vertical axis, construct a rectangular coordinate system; According to the overall enhancement expectation of the target area in each frame of ultrasound image, the ordinate 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, obtain the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image; According to the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image and the gray value of each pixel point in each segment of the target area, obtain the updated gray value of each pixel point in each segment of the target area in each frame of ultrasound image; According to the updated gray value of each pixel point in each segment of the target area in each frame of ultrasound image, obtain the enhanced image of each frame of ultrasound image.

7. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 6, wherein The specific calculation formula for obtaining the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image according to the overall enhancement expectation of the target area in each frame of ultrasound image, the ordinate 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 is as follows: in, Indicates Frame ultrasound image The adaptive enhancement coefficient of the target area of ​​the segment, Indicates The overall enhancement expectation of the target area in the frame ultrasound image, Indicates Frame ultrasound image The angle between the target area and the horizontal direction, Indicates Frame ultrasound image The optimal angle for developing the target area. Indicates Frame ultrasound image The reference length of the segment target area, is a sine function, Indicates The rectangular coordinate system of the frame ultrasound image The minimum value of the ordinate of all pixels on the edge of the target area. represents the absolute value function.

8. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 6, wherein, The steps for obtaining the updated gray value of each pixel point in each segment of the target area in each frame of ultrasound image according to the adaptive enhancement coefficient of each segment of the target area in each frame of ultrasound image and the gray value of each pixel point in each segment of the target area include the following specific steps: In the frame ultrasound image, the ceiling value of the sum of the product of the gray value of the th pixel in the th target region segment and the adaptive enhancement coefficient of the th target region segment plus a preset constant is denoted as the updated gray value of the th pixel in the th target region segment in the frame ultrasound image.

9. The clinical anesthesia ultrasound image-assisted positioning and guiding method according to claim 6, wherein The steps for obtaining the enhanced image of each frame of ultrasound image according to the updated gray value of each pixel point in each segment of the target area in each frame of ultrasound image include the following specific steps: Replace the gray value of each pixel point in each target area of the frame of ultrasonic image with the updated gray value to obtain the enhanced image of the frame of ultrasonic image.

10. A clinical anesthesia ultrasound image-assisted positioning and guiding system, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the computer program is executed by the processor, it realizes the steps of a method for clinically anesthetizing ultrasound image auxiliary positioning and guiding as described in any one of claims 1-9.

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