A method for automatic identification and elimination of liver blood vessels in acoustic attenuation imaging

Abstract

The present application provides a method for automatic identification and elimination of liver blood vessels in acoustic attenuation imaging, comprising acquiring ultrasonic echo data of a target identification area and setting a ROI frame; performing ATI imaging calculation on points within the ROI frame to generate an initial ATI image; constructing a Nakagami distribution map based on the initial ATI image, and determining the vascular tissue in the liver through a preset liver blood vessel threshold, and performing tissue labeling; and performing liver blood vessel elimination based on the tissue labeling and the initial ATI image to generate a target ATI map.

Description

Technical Field

[0001] The present application relates to the technical field of liver recognition, and in particular to a method for automatically recognizing and eliminating liver blood vessels in acoustic attenuation imaging. Background Art

[0002] At present, ultrasonic attenuation imaging provides a quantitative tool for the non-invasive diagnosis of fatty liver and liver fibrosis. Ultrasound is a mechanical wave. During the propagation of human tissue, it is attenuated by small interface scattering, large interface reflection, diffusion of the sound beam, and absorption of ultrasonic energy by soft tissue. Fat is an acoustic attenuation medium, and the propagation of ultrasound in fatty liver will be attenuated. The greater the proportion of fat tissue in the liver, the higher the ultrasonic attenuation. The acoustic attenuation is a function of the attenuation coefficient generated during the propagation of ultrasound. Using the law of acoustic attenuation to form a two-dimensional image and measure the attenuation of human tissue is of great significance, especially for the diagnosis of fatty liver and liver fibrosis.

[0003] In the prior art, the ultrasonic attenuation detection algorithm mainly uses the reflected echo of the B image to predict the acoustic attenuation coefficient through signal processing technology.

[0004] There is an attenuation imaging method based on a hybrid evaluation algorithm, which calculates the attenuation coefficient by finding the relationship between the center frequency and the power spectrum amplitude at different depths.

[0005] There is an attenuation imaging method based on the least squares evaluation algorithm. This method introduces a model containing attenuation parameters to fit the power spectrum ratio, and uses the least squares algorithm to minimize the cost function, thereby evaluating the local attenuation coefficient.

[0006] The amplitude value of the ultrasonic echo data is subjected to logarithmic fitting processing according to the least mean square estimation method, the attenuation coefficient is calculated, and finally the ultrasonic attenuation imaging is realized.

[0007] However, although the above methods are all applied in tissues such as the liver, they all focus on the method design, signal link, processing process, etc. of the ultrasound attenuation imaging method. No technology or patent has paid attention to the actual liver application environment, and has not considered the impact of blood vessels in the liver on ultrasound attenuation imaging.

[0008] The calculation of acoustic attenuation imaging requires uniform liver tissue to avoid interference from vascular echoes. The liver has blood vessels such as the hepatic artery, portal vein, hepatic vein, interlobular veins, and interlobular arteries. These blood vessels will form abnormal echoes, affecting the calculation of acoustic attenuation imaging. Summary of the invention

[0009] The present application provides a method for automatically identifying and removing liver blood vessels in acoustic attenuation imaging, so as to solve the problems in the above-mentioned background technology.

[0010] A method for automatically identifying and removing liver blood vessels in acoustic attenuation imaging, comprising:

[0011] Acquire the ultrasonic echo data of the target identification area and set the ROI frame;

[0012] Perform ATI imaging calculation on the points within the ROI frame to generate an initial ATI image;

[0013] Constructing a Nakagami distribution map based on the initial ATI image, and determining the vascular tissue in the liver through a preset intra-liver vascular threshold, and performing tissue labeling;

[0014] According to the tissue markers and the initial ATI image, the liver vessels were removed to generate the target ATI image.

[0015] Preferably, the ultrasonic echo data is a plane wave of B-ultrasound reflection echo.

[0016] Preferably, the ATI imaging calculation includes performing single-point calculation on points within the ROI frame, and arranging the results of the single-point calculation into an ATI data matrix; wherein,

[0017] In single-point calculation, the current calculation point is taken as the center of the ATI data matrix to determine the amplitude matrix of the current calculation point;

[0018] The length and width of the ATI data matrix are determined by the length and width of the ROI box;

[0019] The value of each point in the ATI data matrix is ​​the sound attenuation coefficient.

[0020] Preferably, the value of the amplitude matrix is ​​the logarithm of the current calculation point; wherein,

[0021] The logarithm includes the following calculation steps:

[0022] Based on the ROI frame, determine the real and imaginary parts of the current calculation point and determine the amplitude value

[0023]

[0024] Wherein, A represents the amplitude value of ultrasonic echo data, I represents the real part, and Q represents the imaginary part;

[0025] According to the amplitude value, determine the depth logarithm column of the current calculation point and determine the logarithm:

[0026]

[0027] in, , Represents the values ​​of different columns; is a logarithm.

[0028] Preferably, the sound attenuation coefficient includes the following calculation steps:

[0029] Perform weighted averaging on the amplitude matrix and convert it into a one-dimensional row vector;

[0030]

[0031] in, , ,… , represents the weight coefficients of different columns; Y is a one-dimensional row vector along the depth direction;

[0032] According to the one-dimensional row vector, the least square method is used to fit along the ultrasonic depth direction to determine the slope of the fitting coefficient; where,

[0033] The coefficient slope conforms to the following formula:

[0034]

[0035] Divide the coefficient slope by the transmission frequency of B-ultrasound to determine the attenuation coefficient; where,

[0036] The attenuation coefficient conforms to the following formula:

[0037]

[0038] In the above example , Transmitting frequency , attenuation coefficient .

[0039] Preferably, the Nakagami distribution map is a tissue scattering distribution map of vascular tissue in the liver.

[0040] Preferably, the tissue scattering distribution map includes the scattering distribution coefficient of each calculated single point; wherein,

[0041] When the scattering distribution coefficient is greater than the blood vessel threshold in the liver, it is normal liver tissue;

[0042] When the scattering distribution coefficient is less than the threshold of blood vessels in the liver, it is a blood vessel with strong echoes.

[0043] Preferably, the tissue marker is an ATI image marker of attenuation imaging; wherein,

[0044] ATI image marking generates tissue marking synchronously from the blood vessel coordinate position. The tissue marking includes blood vessel marking and strong echo tissue marking. The tissue marking method is coordinate marking.

[0045] Preferably, the liver vascular removal comprises:

[0046] By tissue marking, blood vessels and strong echoes are marked on the ATI image to obtain the marked ATI marked image;

[0047] The ATI marker image is overlaid on the B-ultrasound image of the ultrasonic echo data to generate a target ATI image.

[0048] The beneficial effects of this application are:

[0049] The present application is based on the calculation method of ATI, in which the data acquisition method of collecting echo data using plane waves can effectively avoid the interference of the focusing mode on the focus energy, ensure that the echo signal is relatively balanced, and ensure the accuracy and stability of the ATI calculation.

[0050] The weighted summation of columns in the ATI calculation of the present application can effectively reduce data interference and ensure the stability of the algorithm.

[0051] In the application of the acoustic attenuation function, the present application automatically identifies and removes blood vessels in the liver, thereby ensuring the accuracy and stability of ATI acoustic attenuation measurement.

[0052] The algorithm of this application has high real-time performance and meets the functional requirements of detecting blood vessels in the liver and real-time calculation.

[0053] The solution of removing blood vessels and strong echoes from the acoustic attenuation image of the present application and replacing them with B-images is not only beneficial to the measurement of acoustic attenuation, but can also effectively enrich the information of B-images, display blood vessels and strong echo points in the liver, and produce better clinical effects of B-images.

[0054] This application further derives that blood vessels and strong echoes in other tissues of the human body can be identified and removed by this method.

[0055] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description and the drawings.

[0056] The technical solution of the present application is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide a further understanding of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings:

[0058] Figure 1 This is a method flow chart of a method for automatically identifying and removing liver blood vessels in acoustic attenuation imaging in an embodiment of the present application;

[0059] Figure 2 An image of the liver collected in an embodiment of the present application;

[0060] Figure 3 is a slope diagram of the attenuation coefficient in the embodiment of the present application;

[0061] Figure 4 It is the ATI image in the embodiment of the present application;

[0062] Figure 5 This is Figure B in which blood vessels are not removed in the embodiment of the present application;

[0063] Figure 6 This is a fusion effect diagram of the ATI and B images without blood vessels in the embodiment of the present application;

[0064] Figure 7 This is a flow chart of the steps for generating Figure B in the embodiment of the present application. DETAILED DESCRIPTION

[0065] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application.

[0066] (Attenuation Imaging - ATI)

[0067] This application proposes a method for automatic identification and removal of liver blood vessels in acoustic attenuation imaging, including:

[0068] Acquire the ultrasonic echo data of the target identification area and set the ROI frame;

[0069] Perform ATI (attenuation imaging) imaging calculation on the points within the ROI (Region Of Interest) box to generate an initial ATI image;

[0070] Construct a Nakagami distribution map based on the initial ATI image (Nakagam-m distribution is a fast fading model proposed by Japanese scholar Nakagami in a paper in 1960). And determine the vascular tissue in the liver through the preset intra-liver vascular threshold, and perform tissue labeling;

[0071] According to the tissue markers and the initial ATI image, the liver vessels were removed to generate the target ATI image.

[0072] The working principle of the above technical solution is:

[0073] As attached Figure 1As shown, the present application is a method for automatically identifying and removing liver blood vessels during imaging based on acoustic attenuation to prevent interference from tube echoes and liver tissue in the acquired B-ultrasound images.

[0074] In specific implementations, acoustic attenuation calculation requires uniform liver tissue to avoid interference from vascular echoes. In order to ensure the accuracy and stability of the acoustic attenuation function, it is necessary to automatically remove blood vessels and strong echo points in the liver.

[0075] In the specific implementation, the accuracy of the acoustic attenuation function measurement is ensured by automatically identifying and eliminating the blood vessels and strong echo points in the liver.

[0076] In specific implementation, the identification of blood vessels in the liver is mainly applied to the theory of tissue scattering distribution imaging. Because the blood vessel scattering satisfies the Nakagami distribution, the Nakagami parameter m of each point in the ROI box is calculated, and the calculated Nakagami parameter m is compared with the blood vessel threshold in the liver. When it is lower than a specific threshold, it is judged as vascular tissue in the liver and identified.

[0077] In a specific implementation, the blood vessels in the liver are eliminated. After the blood vessel positions are successfully identified in the liver, the blood vessel coordinate positions are synchronized to the attenuation imaging image, the blood vessel positions are eliminated, and the B image is used to replace them. The attenuation imaging is calculated after the blood vessels are eliminated to ensure the accuracy of the acoustic attenuation measurement.

[0078] In the above embodiment, the B image refers to the B mode (Brightness-mode) of the ultrasonic device, in which an ultrasonic probe is used to transmit ultrasonic waves to the tissue, the echo of the internal structure of the tissue is recorded, and the echo is processed to form a grayscale image to reflect the internal structure of the tissue.

[0079] Medical ultrasound imaging systems use the propagation of ultrasound in the human body to obtain ultrasonic characteristic information of human tissue and organ structures. In current medical ultrasound imaging systems, high-voltage pulse waves are loaded on each array element of the probe, which excites the array element to generate high-frequency ultrasound and then forms a transmit beam into the human body. Each array element of the probe receives echoes scattered or reflected by the human tissue structure to form a receive beam. The ultrasound imaging system extracts information from the ultrasound echo, performs beam synthesis, and processes the echo to form a grayscale image. The grayscale image here is the B image, which reflects the internal structure of the tissue.

[0080] In the implementation process of this application, Figure B is composed of the following 6 steps, as shown in the attached Figure 7 As shown:

[0081] (1) At the receiving end of the ultrasonic probe, after obtaining the ultrasonic echo data, ADC sampling is performed to collect RF (Radio Frequency) radio frequency data;

[0082] (2) Perform orthogonal demodulation on the RF data to generate I and Q data;

[0083] (3) Sampling channel data at a given sampling rate (typical value 15M);

[0084] (4) After channel data sampling, beam synthesis is performed;

[0085] (5) Scan conversion after beamforming;

[0086] (6) After the scan conversion is completed, the B image is displayed and is visible on the ultrasound equipment interface.

[0087] The beneficial effects of the above technical solution are:

[0088] The present application is based on the calculation method of ATI, in which the data acquisition method of collecting echo data using plane waves can effectively avoid the interference of the focusing mode on the focus energy, ensure that the echo signal is relatively balanced, and ensure the accuracy and stability of the ATI calculation.

[0089] The weighted summation of columns in the ATI calculation of the present application can effectively reduce data interference and ensure the stability of the algorithm.

[0090] In the application of the acoustic attenuation function, the present application automatically identifies and removes blood vessels in the liver, thereby ensuring the accuracy and stability of ATI acoustic attenuation measurement.

[0091] The algorithm of this application has high real-time performance and meets the functional requirements of detecting blood vessels in the liver and real-time calculation.

[0092] The solution of removing blood vessels and strong echoes from the acoustic attenuation image of the present application and replacing them with B-images is not only beneficial to the measurement of acoustic attenuation, but can also effectively enrich the information of B-images, display blood vessels and strong echo points in the liver, and produce better clinical effects of B-images.

[0093] This application further derives that blood vessels and strong echoes in other tissues of the human body can be identified and removed by this method.

[0094] Preferably, the ultrasonic echo data is a plane wave of B-ultrasound reflection echo.

[0095] The working principle of the above technical solution is:

[0096] In this embodiment, the calculation of ATI (Attenuation Imaging) acoustic attenuation is a process of acquiring ultrasound echo data of a target area based on B-ultrasound reflection echoes and performing signal processing.

[0097] Ultrasonic waves are mainly emitted by focused waves and plane waves. The sound field generated by the focused wave has stronger energy and higher signal-to-noise ratio near the focal area, while the sound field of the plane wave is relatively balanced in the imaging area.

[0098] ATI acoustic attenuation imaging requires a plane wave pattern for transmission and reception. When the focus mode collects data at the same depth, the focus energy will be strong and the non-focus energy will be weak. The focus will affect the ATI energy attenuation assessment.

[0099] Plane waves are not affected by focus. When TGC (Time Gain Compensate) is set to the same value at different depths, the attenuation coefficient can be effectively evaluated by fitting the depth based on the energy of the echo.

[0100] Preferably, the ATI imaging calculation includes performing single-point calculation on points within the ROI frame, and arranging the results of the single-point calculation into an ATI data matrix; wherein,

[0101] In single-point calculation, the current calculation point is taken as the center of the ATI data matrix to determine the amplitude matrix of the current calculation point;

[0102] The length and width of the ATI data matrix are determined by the length and width of the ROI box;

[0103] The value of each point in the ATI data matrix is ​​the sound attenuation coefficient.

[0104] The working principle of the above technical solution is:

[0105] As attached Figure 2 As shown in the figure, in actual implementation, the liver image collected shows clear blood vessels and liver capsule in the liver; the ROI frame is in the attached Figure 2 In the middle, the position and size of the ROI box can be determined. The size of the ROI box is set by the user;

[0106] In the specific calculation process, each point in the ROI frame needs to be calculated by the ATI algorithm. The single-point calculation of each point is combined into the ATI calculation results of all points in the ROI frame, which are organized into an ATI data matrix to form a complete ATI image.

[0107] In the specific implementation process, as shown in the attached Figure 4 As shown, in the ROI frame, start moving the index from the upper left corner and scan row by row to the lower right corner, and all points in the frame can calculate a sound attenuation coefficient result. The calculation results of the sound attenuation coefficients of all points are saved in an ATI data matrix and displayed to form an ATI image in the ROI frame.

[0108] For single-point calculation of each point, the input of the algorithm is a matrix centered on the point, and the length and width of the matrix are given by the computing system.

[0109] Preferably, the value of the amplitude matrix is ​​the logarithm of the current calculation point; wherein,

[0110] The logarithm includes the following calculation steps:

[0111] Based on the ROI frame, determine the real and imaginary parts of the current calculation point and determine the amplitude value

[0112]

[0113] In, A represents the amplitude value of ultrasonic echo data, I represents the real part, and Q represents the imaginary part;

[0114] According to the amplitude value, determine the depth logarithm column of the current calculation point and determine the logarithm:

[0115]

[0116] in, ; Represents the values ​​of different columns; is a logarithm.

[0117] The working principle of the above technical solution is:

[0118] The above calculation of logarithms is to calculate the ATI value of a single point. During the calculation process, a matrix of a given length and width is used as input with the calculation point as the center and input into the single-point calculation algorithm function of ATI. First, the amplitude of each point in the matrix is ​​calculated, and then the amplitude value is taken logarithm by finding the law of amplitude change with depth. The matrix is ​​logarithmic by column to determine the logarithm of each point in the amplitude matrix.

[0119] Preferably, the sound attenuation coefficient includes the following calculation steps:

[0120] Step 1: Perform weighted averaging on the amplitude matrix and convert it into a one-dimensional row vector;

[0121]

[0122] in, , ,… , represents the weight coefficients of different columns; Y is a one-dimensional row vector along the depth direction;

[0123] Step 2: According to the one-dimensional row vector, the least square method is used to fit along the ultrasonic depth direction to determine the slope of the fitting coefficient; where,

[0124] The coefficient slope conforms to the following formula:

[0125]

[0126] Step 3: Divide the coefficient slope by the transmission frequency of B-ultrasound to determine the attenuation coefficient; where,

[0127] The attenuation coefficient conforms to the following formula:

[0128]

[0129] In the above example , transmission frequency, attenuation coefficient .

[0130] The principle of the above technical solution is:

[0131] In the specific implementation process, in order to effectively reduce the interference of data and ensure the stability of the algorithm. Perform weighted averaging on the amplitude matrix and weighted average the data in the column dimension. Divide the values ​​of each row into different columns for weighted summation. The weight of the center is heavy, and the weights on both sides gradually decrease. The data is converted from a two-dimensional matrix to a one-dimensional row vector. In this process, the weight of the center of the measurement point is heavy, and the weights on both sides gradually decrease. The coefficient of the weight conforms to the normal distribution, as shown in step 1.

[0132] Then in step 2, the one-dimensional row vector data Y after weighted summation is linearly fitted along the ultrasonic depth direction, as shown in the attached figure. Figure 3 As shown, the horizontal axis x is the point sequence along the depth direction, and the vertical axis Y is the weighted logarithmic amplitude value. Using the linear fitting model and the least squares fitting method, the slope of the fitting coefficient is obtained.

[0133] In step 3, the slope result obtained by the fitting calculation is divided by the transmission frequency to obtain the attenuation coefficient.

[0134] Preferably, the Nakagami distribution map is a tissue scattering distribution map of vascular tissue in the liver.

[0135] The principle of the above technical solution is:

[0136] In the specific implementation process, when the acoustic attenuation function is applied in tissues such as the liver, uniform liver tissue is required to avoid interference from vascular echoes. However, the liver has blood vessels such as the hepatic artery, portal vein, hepatic vein, interlobular vein, and interlobular artery, which will form abnormal echoes and affect the calculation of acoustic attenuation imaging.

[0137] When there are other strong reflection points such as the liver blood vessels or liver capsule, abnormal echoes will be formed, which will affect the calculation results of ATI. Based on this algorithm, it is necessary to effectively identify the liver blood vessels and strong reflection points and remove them in the ATI image. Prevent strong reflection points such as blood vessels and liver capsule from affecting ATI imaging.

[0138] The tissue scattering distribution map is used to identify blood vessels in the liver. According to the theory of tissue scattering distribution, blood vessel scattering satisfies the Nakagami distribution. The Nakagami parameter m of each point in the ROI box is calculated, and the calculated Nakagami parameter m is compared with the blood vessel threshold in the liver. If it is lower than a specific threshold, it is judged as vascular tissue in the liver.

[0139] Preferably, the tissue scattering distribution map includes the scattering distribution coefficient of each calculated single point; wherein,

[0140] When the scattering distribution coefficient is greater than the blood vessel threshold in the liver, it is normal liver tissue;

[0141] When the scattering distribution coefficient is less than the threshold of blood vessels in the liver, it is a blood vessel with strong echoes.

[0142] The principle of the above technical solution is:

[0143] The tissue scattering distribution is a pixel-by-pixel map based on the shape parameters of the Nakagami distribution, which reflects the arrangement and concentration of scatterers. The scattering distribution coefficient is also defined as the "Nakagami parameter m". As the Nakagami parameter m changes, the distribution of the backscattered signal envelope changes. From the front Rayleigh distribution to the back Rayleigh distribution, the front Rayleigh distribution indicates that there are several scatterers randomly distributed in the tissue. In contrast, the back Rayleigh distribution indicates that there are local high concentrations of scatterers with periodic scatterers.

[0144] Therefore, the change of Nakagami parameter m from 0 to greater than 1 indicates that the backscatter signal envelope changes from the anterior Rayleigh distribution to the posterior Rayleigh distribution (Rayleigh distribution). The blood vessels and uniform tissues in the liver have different scattering characteristics, and their scattering distribution coefficients, that is, Nakagami parameter m, will also be different. Based on this difference, the blood vessels and uniform tissues in the liver can be effectively distinguished by calculating the Nakagami parameter m.

[0145] The calculation process for the Nakagami parameter is as follows:

[0146] The result of calculating the Nakagami parameter m of a single point is centered on the single point and the matrix of length and width given by the system is used as input to the single point calculation algorithm function of the Nakagami parameter m:

[0147] Blood vessel scattering satisfies the Nakagami distribution, and the calculation formula of the Nakagami fading parameter m is as follows:

[0148]

[0149]

[0150] Where R represents the amplitude value matrix of a two-dimensional area of ​​given length and width.

[0151] Where I represents the real part and Q represents the imaginary part.

[0152] molecular Represents the mean of R-squared, then squared.

[0153] Denominator Represents the difference between the mean and the numerator of R fourth power.

[0154] Then, the single point scattering distribution coefficient is calculated, and then a threshold judgment is performed. If it is less than the threshold, it is identified as a blood vessel and a strong echo. If it is greater than the threshold, it is identified as normal liver tissue.

[0155] The threshold setting is related to the identified tissue. For blood vessels and strong echo points in the liver, the threshold is set to 0.5. The scattering distribution coefficients of all points are stored in the Nakagami two-dimensional matrix.

[0156] Preferably, the tissue marker is an ATI image marker of attenuation imaging; wherein,

[0157] ATI image marking generates tissue marking synchronously from the blood vessel coordinate position. The tissue marking includes blood vessel marking and strong echo tissue marking. The tissue marking method is coordinate marking.

[0158] The working principle of the above technical solution is:

[0159] In the specific implementation process, the scattering distribution coefficient value and the threshold are used for judgment. For points less than the liver threshold, the vascular coordinate position is synchronized to the attenuation imaging image and marked in the ATI matrix as blood vessels and highly echogenic tissues.

[0160] The marked index is the basis for processing blood vessels and strong echoes in the ATI image.

[0161] Preferably, the liver vascular removal comprises:

[0162] By tissue marking, blood vessels and strong echoes are marked on the ATI image to obtain the marked ATI marked image;

[0163] The ATI marker image is overlaid on the B-ultrasound image of the ultrasonic echo data to generate a target ATI image.

[0164] The working principle of the above technical solution is:

[0165] As attached Figure 5 and Figure 6 As shown in the figure, it is the effect image after removing blood vessels and strong echoes. In the removal of liver blood vessels, ATI and B image are fused. Specifically, the ATI image is overlaid on the B image, and the indexes of blood vessels and strong echo tissues marked in ATI are replaced by the results of B image, and the remaining normal tissues show the ATI image.

[0166] After the ATI image and B image are superimposed, blood vessels and strong echoes can be clearly seen on the B image.

[0167] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for automatically identifying and removing liver blood vessels in acoustic attenuation imaging, characterized in that: include: Acquire the ultrasonic echo data of the target identification area and set the ROI frame; Perform ATI imaging calculation on the points within the ROI frame to generate an initial ATI image; The ATI imaging calculation includes performing single-point calculation on points within the ROI frame, and arranging the results of the single-point calculation into an ATI data matrix; wherein, In single-point calculation, the current calculation point is taken as the center of the ATI data matrix to determine the amplitude matrix of the current calculation point; The length and width of the ATI data matrix are determined by the length and width of the ROI box; The value of each point in the ATI data matrix is ​​the sound attenuation coefficient; Constructing a Nakagami distribution map based on the initial ATI image, and determining the vascular tissue in the liver through a preset intra-liver vascular threshold, and performing tissue labeling; Wherein, the Nakagami distribution map is a tissue scattering distribution map of vascular tissue in the liver; The tissue scattering distribution map includes a scattering distribution coefficient for each calculated single point; Among them, when the scattering distribution coefficient is greater than the blood vessel threshold in the liver, it is normal liver tissue; When the scattering distribution coefficient is less than the threshold of blood vessels in the liver, it is a blood vessel and has strong echoes; The tissue marker is marked by an ATI image of attenuation imaging; Among them, the ATI image mark generates a tissue mark synchronously by the blood vessel coordinate position, and the tissue mark includes a blood vessel mark and a strong echo tissue mark, and the tissue mark is in the form of a coordinate mark; According to the tissue markers and the initial ATI image, the liver vessels were removed to generate the target ATI image.

2. The method for automatic identification and elimination of liver blood vessels in acoustic attenuation imaging according to claim 1, characterized in that: The ultrasonic echo data is a plane wave of B-ultrasound reflection echo.

3. The method for automatic identification and elimination of liver blood vessels in acoustic attenuation imaging according to claim 1, characterized in that: The value of the amplitude matrix is ​​the logarithm of the current calculation point; wherein, The logarithm includes the following calculation steps: Based on the ROI frame, determine the real and imaginary parts of the current calculation point and determine the amplitude value Wherein, A represents the amplitude value of ultrasonic echo data, I represents the real part, and Q represents the imaginary part; According to the amplitude value, determine the depth logarithm column of the current calculation point and determine the logarithm: in, ; Represents the values ​​of different columns; is a logarithm.

4. The method for automatic identification and elimination of liver blood vessels in acoustic attenuation imaging according to claim 3, characterized in that: The sound attenuation coefficient comprises the following calculation steps: Perform weighted averaging on the amplitude matrix and convert it into a one-dimensional row vector; in, , ,… , represents the weight coefficients of different columns; Y is a one-dimensional row vector along the depth direction; According to the one-dimensional row vector, the least square method is used to fit along the ultrasonic depth direction to determine the slope of the fitting coefficient; where, The coefficient slope conforms to the following formula: Divide the coefficient slope by the transmission frequency of B-ultrasound to determine the attenuation coefficient; where, The attenuation coefficient conforms to the following formula: in, , the transmission frequency , attenuation coefficient .

5. The method for automatic identification and elimination of liver blood vessels in acoustic attenuation imaging according to claim 1, characterized in that: The liver devascularization comprises: By tissue marking, blood vessels and strong echoes are marked on the initial ATI image to obtain the marked ATI image; The marked ATI image is overlaid on the B-ultrasound image of the ultrasonic echo data to generate a target ATI image.

Images