Method and device for quantitatively evaluating muscle lesion through medical ultrasonic equipment

Abstract

The invention provides a method and device for quantitatively evaluating muscle lesions through medical ultrasonic equipment. The method comprises the steps that a series of different pulse waves are alternately emitted to human tissue, and echo signals returned by the human tissue are received; the echo signals are subjected to type distinguishing and caching, one type is a two-dimensional gray level echo signal used for implementing a two-dimensional gray level image, and the other type is a two-dimensional attenuation echo signal used for implementing attenuation imaging; according to the two-dimensional gray echo signal, a two-dimensional gray image is obtained through calculation, and then a two-dimensional texture image is obtained through calculation; calculating an attenuation image according to the two-dimensional attenuation echo signal; according to the two-dimensional grayscale image, the two-dimensional texture image and the attenuation image, quantitative parameters of the muscle tissue are obtained through calculation, and the quantitative parameters comprise grayscale feature parameters, texture feature parameters and attenuation feature parameters of the muscle tissue; the two-dimensional grayscale image, the two-dimensional texture image and the attenuation image are displayed in a combined mode, and quantitative parameters are synchronously displayed. The invention can quantitatively assess muscle lesions using a medical ultrasound device.

Description

Technical Field

[0001] The present invention relates to the technical field of medical ultrasonic equipment, and in particular to a method and device for quantitatively evaluating muscle lesions using medical ultrasonic equipment. Background Art

[0002] Muscle diseases are very common in clinical practice. There are many types and the classification is also very complicated. Muscle diseases can usually be divided into two categories: ① neuromuscular junction diseases, including myasthenia gravis, myasthenia gravis-like, botulism, and myasthenic syndrome; ② muscle diseases, including muscular dystrophy, myotonic myopathy, inflammatory myopathy, metabolic myopathy, endocrine myopathy, congenital and infantile myopathy, and miscellaneous myopathy. Since skeletal muscle is the main organ for executing body movement and an important organ for the body's energy metabolism, and the human body has more than 600 muscles, its weight accounts for about 40% of an adult's body weight. Therefore, muscle lesions can cause patients to experience symptoms such as limb weakness, decreased muscle tone, and muscle lesions, which seriously affect the patient's quality of life and work.

[0003] For muscle lesions, X-rays, CT, MRI, and pathological biopsy are generally used for comprehensive diagnosis. In recent years, quantitative ultrasound can provide quantitative data on real-time changes in muscle structure and its contraction process. It has gradually become a reliable research and clinical tool, and plays an increasingly important role in evaluating muscle function. However, existing quantitative ultrasound has certain limitations. Conventional two-dimensional grayscale images can only be preliminarily judged through the doctor's subjective experience, and cannot provide fixed quantitative parameters for diagnosis. Therefore, it is of great clinical significance to study the ultrasound quantitative parameters for quantitatively evaluating the degree or nature of muscle tissue lesions. Summary of the invention

[0004] In order to solve the technical problems existing in the above-mentioned prior art, the present invention provides a method for quantitatively evaluating muscle lesions using medical ultrasound equipment, and the technical solution is as follows:

[0005] In one aspect, a method for quantitatively evaluating muscle pathology using a medical ultrasound device is provided, the method comprising:

[0006] Step S01, alternately transmitting a series of different pulse waves to human tissue and receiving echo signals returned by the human tissue;

[0007] Step S02: distinguishing the types of the received series of echo signals, one type is a two-dimensional grayscale echo signal for implementing a two-dimensional grayscale image, and the other type is a two-dimensional attenuation echo signal for implementing attenuation imaging;

[0008] Step S03, buffering the two-dimensional grayscale echo signal and the two-dimensional attenuated echo signal;

[0009] Step S04, first calculating and obtaining a two-dimensional grayscale image according to the two-dimensional grayscale echo signal, and then calculating and obtaining a two-dimensional texture image from the two-dimensional grayscale image;

[0010] Step S05, calculating and obtaining grayscale characteristic parameters of muscle tissue according to the two-dimensional grayscale image;

[0011] Step S06, calculating and obtaining texture feature parameters of muscle tissue according to the two-dimensional texture image;

[0012] Step S07, calculating an attenuation image according to the two-dimensional attenuated echo signal;

[0013] Step S08, calculating and obtaining attenuation characteristic parameters of muscle tissue according to the attenuation image;

[0014] Step S09, combining and displaying the two-dimensional grayscale image, the two-dimensional texture image, and the attenuation image, and synchronously displaying quantitative parameters, wherein the quantitative parameters include the grayscale characteristic parameters of the muscle tissue, the texture characteristic parameters of the muscle tissue, and the attenuation characteristic parameters of the muscle tissue.

[0015] Optionally, the S04 specifically includes:

[0016] According to the two-dimensional grayscale echo signal BSignal(i,j), the two-dimensional grayscale image BImage(i,j) is first calculated. The calculation formula is as follows:

[0017]

[0018] Among them: ABS() is a complex modulus operation, DR is the dynamic range of the image, and Log[] is a logarithmic function with base 10;

[0019] Then, the two-dimensional texture image TImage(i,j) is calculated by the two-dimensional grayscale image BImage(i,j) by using operator filtering. The formula is as follows:

[0020]

[0021] Wherein: Sober is a differential operator, sober(m,n) here defines a 3*3 window, and this 3*3 window is used to slide and sum on the two-dimensional grayscale image BImage(i,j), traverse all pixels, and obtain the two-dimensional texture image TImage(i,j), i, j represent the row label and column label of the image respectively, m, n represent the horizontal line number and vertical point number label of the window respectively, M, N represent the horizontal line number and vertical point number of the window respectively.

[0022] Optionally, the step S05 specifically includes:

[0023] Calculate the grayscale characteristic parameters of the muscle tissue according to the two-dimensional grayscale image BImage(i,j), wherein the grayscale characteristic parameters of the muscle tissue include: the average value of the grayscale of the local tissue, the contrast value of the local tissue and various mathematical and physical quantities derived therefrom (variance, histogram, etc.);

[0024] The calculation method of the average value of the local tissue grayscale and the contrast value of the local tissue is as follows:

[0025] The user uses the measurement tool to select the area to be measured. The area can be of any shape, and the average grayscale value is represented as Mean1;

[0026] After measuring Mean1, select a tissue area of ​​the same size that needs to be compared, calculate its grayscale average value Mean2, and use the ratio of the two as the contrast value, recorded as Contrast.

[0027] Optionally, the step S06 specifically includes:

[0028] The texture feature parameters of the muscle tissue are calculated based on the two-dimensional texture image TImage(i,j), and the texture feature parameters of the muscle tissue include the fascia and the muscle distribution amount P, and the calculation method is as follows:

[0029] Set two thresholds Ath and Bth to determine texture boundaries and muscle tissues, then:

[0030]

[0031] P=mean(P(k)),P(k)>Bth

[0032] Where: ABS() is a complex modulus operation, i, j represent the row label and column label of the image respectively.

[0033] Optionally, the step S07 specifically includes:

[0034] The attenuation image AImage(i, j) is calculated in the frequency space according to the two-dimensional attenuated echo signal ASignal(i, j), and the calculation method is as follows:

[0035] Perform short-time Fourier transform on each line of the two-dimensional attenuated echo signal ASignal(i,j) to obtain the two-dimensional frequency domain distribution map P_M(i,j,f) in the j direction within the ROI region of interest, and calculate the average value of P_M(i,j,f) in the frequency direction. The formula is as follows:

[0036]

[0037] The attenuation coefficient value of each point in the ROI region of interest is obtained by P(i,j), and the formula is as follows:

[0038]

[0039] Where: X is the number of frequency samples, x is the frequency point, f is the frequency label, F is the average frequency, R0 represents the upper boundary of the ROI region of interest, R1 represents the lower boundary of the ROI region of interest, and lge represents the 10-base logarithmic function of the e exponent.

[0040] Optionally, the step S08 specifically includes:

[0041] The attenuation characteristic parameters of the muscle tissue are calculated according to the attenuation image A(i, j), and the attenuation characteristic parameters of the muscle tissue include: the average muscle attenuation coefficient Atten Coe in the user-selected area, the upper boundary attenuation value AT, the center attenuation value AC, the lower boundary attenuation value AB and the average attenuation value AM of the user-selected area, and the calculation method is as follows:

[0042] The user uses a rectangular box to select the muscle tissue area to be measured in the ROI region of interest. The size of the rectangular box can be adjusted arbitrarily. The average value of all attenuation coefficients in the rectangular box is calculated as the average attenuation coefficient Atten Coe of the muscle in the user-selected area.

[0043] Multiply the pixel value of the intersection of the center line of the rectangular box and the upper boundary, the pixel value of the midpoint of the center line of the rectangular box, and the pixel value of the intersection of the center line of the rectangular box and the lower boundary by the current transmission frequency to obtain AT, AC, and AB values, and average these values ​​to obtain the AM value.

[0044] Optionally, the combined display in step S09 includes four-image, three-image, double-image, and single-image display modes;

[0045] The attenuation image is displayed superimposed on the two-dimensional grayscale image to form an image;

[0046] The quantitative parameters are a collection of three types of quantitative parameters: grayscale, attenuation, and texture. The parameters are displayed in real time or statically in a frozen state.

[0047] In another aspect, a device for quantitatively evaluating muscle lesions using a medical ultrasound device is provided, the device comprising:

[0048] A transmitting and receiving module, used for alternately transmitting a series of different pulse waves to human tissue and receiving echo signals returned by the human tissue;

[0049] A signal classification module is used to distinguish the types of a series of received echo signals, one type is a two-dimensional grayscale echo signal used to implement a two-dimensional grayscale image, and the other type is a two-dimensional attenuation echo signal used to implement attenuation imaging;

[0050] A storage module, used for caching the two-dimensional grayscale echo signal and the two-dimensional attenuated echo signal;

[0051] A grayscale image generation module, used for first calculating and obtaining a two-dimensional grayscale image according to the two-dimensional grayscale echo signal;

[0052] A texture image generation module, used for calculating and obtaining a two-dimensional texture image from the two-dimensional grayscale image;

[0053] An attenuation image generation module, used for calculating an attenuation image according to the two-dimensional attenuation echo signal;

[0054] A quantitative parameter calculation module, used for calculating and obtaining quantitative parameters of muscle tissue according to the two-dimensional grayscale image, the two-dimensional texture image, and the attenuation image, wherein the quantitative parameters include grayscale characteristic parameters of the muscle tissue, texture characteristic parameters of the muscle tissue, and attenuation characteristic parameters of the muscle tissue;

[0055] The combined display module is used for combining and displaying the two-dimensional grayscale image, the two-dimensional texture image, the attenuation image, and synchronously displaying the quantitative parameters.

[0056] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the above-mentioned method for quantitatively evaluating muscle lesions using medical ultrasound equipment.

[0057] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the above-mentioned method for quantitatively evaluating muscle lesions using medical ultrasound equipment.

[0058] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0059] The present invention proposes a method based on medical ultrasound equipment, which adopts a non-invasive method to quantitatively evaluate muscle lesions, utilizes a variety of ultrasound imaging methods and ultrasound quantitative parameter indicators to evaluate the nature and severity of muscle lesions, and provides a decision-making basis for clinical diagnosis and treatment. The method can be conveniently and quickly deployed in a medical color ultrasound equipment system, and has the following advantages: 1. It is easy to implement, real-time, and highly accurate; 2. It is not affected by user-adjustable parameters, and can output a variety of quantitative parameters at the same time; 3. Multiple different feature images are displayed at the same time, and the user operation is simple; 4. The data and parameters of all feature images can be stored at the same time, which is convenient for playback and repeated confirmation; 5. It can be simply and quickly deployed in medical ultrasound equipment without being limited by the amount of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 This is a flow chart of a method for quantitatively evaluating muscle lesions using a medical ultrasound device provided by an embodiment of the present invention;

[0062] Figure 2 It is a schematic diagram of calculating a texture image based on a two-dimensional grayscale image provided by an embodiment of the present invention;

[0063] Figure 3 It is a schematic diagram of displaying a measured attenuation characteristic parameter provided by an embodiment of the present invention;

[0064] Figure 4 It is a schematic diagram of displaying various images and quantitative parameters provided by an embodiment of the present invention;

[0065] Figure 5 It is a block diagram of a device for quantitatively evaluating muscle lesions using medical ultrasound equipment provided by an embodiment of the present invention;

[0066] Figure 6 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0068] An embodiment of the present invention provides a method for quantitatively evaluating muscle lesions using a medical ultrasound device. The method can be implemented by an electronic device, which can be a terminal or a server. Figure 1 The flowchart of the method is shown, and the processing flow may include the following steps:

[0069] Step S01, alternately transmitting a series of different pulse waves to human tissue and receiving echo signals returned by the human tissue;

[0070] The embodiment of the present invention alternately transmits a series of different pulse waves to human tissue and receives echo signals returned by the human tissue, wherein the alternate transmission first transmits a set of characteristic pulse waves in the entire probe range, and then transmits a set of characteristic pulse waves in the ROI (user region of interest, such as ROI) selected by the user. Figure 3 The frame (as shown in S30) transmits a second set of characteristic pulse waves, and the received echo signal includes a radio frequency signal RF or a baseband IQ signal of two characteristic pulse waves.

[0071] Step S02: distinguishing the types of the received series of echo signals, one type is a two-dimensional grayscale echo signal for implementing a two-dimensional grayscale image, and the other type is a two-dimensional attenuation echo signal for implementing attenuation imaging;

[0072] The type distinction of the embodiment of the present invention includes the distinction between one line, multiple lines or complete frame signals: the first group of characteristic pulse wave receiving signals is used to implement two-dimensional grayscale images, and the second group of characteristic pulse wave receiving signals is used to implement attenuation imaging; suppose the two-dimensional grayscale image signal is recorded as BSignal(i, j), and the two-dimensional attenuation image signal is recorded as ASignal(i, j). Both types of images obtain baseband IQ signals, that is, complex signals.

[0073] Step S03, buffering the two-dimensional grayscale echo signal and the two-dimensional attenuated echo signal;

[0074] The embodiment of the present invention can directly cache complex signals, and directly cache them in floating point form as system memory for easy retrieval, while opening up corresponding storage space in the hard disk space. The cache can cache data in real time or in a frozen state.

[0075] Step S04, first calculating and obtaining a two-dimensional grayscale image according to the two-dimensional grayscale echo signal, and then calculating and obtaining a two-dimensional texture image from the two-dimensional grayscale image;

[0076] Optionally, the S04 specifically includes:

[0077] According to the two-dimensional grayscale echo signal BSignal(i,j), the two-dimensional grayscale image BImage(i,j) is first calculated. The calculation formula is as follows:

[0078]

[0079] Among them: ABS() is a complex modulus operation, DR is the dynamic range of the image, and Log[] is a logarithmic function with base 10;

[0080] Then, the two-dimensional grayscale image BImage(i,j) is used to calculate the two-dimensional texture image TImage(i,j) by using operator filtering (based on the grayscale image, the texture image can be directly calculated. The texture image is composed of various boundaries of the tissue. Assume that a muscle texture presents a longitudinal distribution, such as Figure 2 As shown), the formula is as follows:

[0081]

[0082]

[0083] Wherein: Sober is a differential operator, sober(m,n) here defines a 3*3 window, and this 3*3 window is used to slide and sum on the two-dimensional grayscale image BImage(i,j), traverse all pixels, and obtain the two-dimensional texture image TImage(i,j), i, j represent the row label and column label of the image respectively, m, n represent the horizontal line number and vertical point number label of the window respectively, M, N represent the horizontal line number and vertical point number of the window respectively.

[0084] Step S05, calculating and obtaining grayscale characteristic parameters of muscle tissue according to the two-dimensional grayscale image;

[0085] Optionally, the step S05 specifically includes:

[0086] Calculating the grayscale characteristic parameters of the muscle tissue according to the two-dimensional grayscale image BImage(i,j), wherein the grayscale characteristic parameters of the muscle tissue include: the average grayscale value of the local tissue, the contrast value of the local tissue and various mathematical and physical quantities derived therefrom;

[0087] The calculation method of the average value of the local tissue grayscale and the contrast value of the local tissue is as follows:

[0088] The user uses the measurement tool to select the area to be measured. The area can be of any shape, and the average grayscale value is represented as Mean1;

[0089] After measuring Mean1, select a tissue area of ​​the same size that needs to be compared, calculate its grayscale average value Mean2, and use the ratio of the two as the contrast value, recorded as Contrast.

[0090] Step S06, calculating and obtaining texture feature parameters of muscle tissue according to the two-dimensional texture image;

[0091] Optionally, the step S06 specifically includes:

[0092] The texture feature parameters of the muscle tissue are calculated based on the two-dimensional texture image TImage(i,j), and the texture feature parameters of the muscle tissue include the fascia and the muscle distribution amount P, and the calculation method is as follows:

[0093] Set two thresholds Ath and Bth to determine texture boundaries and muscle tissues, then:

[0094]

[0095]

[0096] P=mean(P(k)),P(k)>Bth

[0097] Where: ABS() is a complex modulus operation, i, j represent the row label and column label of the image respectively.

[0098] Step S07, calculating an attenuation image according to the two-dimensional attenuated echo signal;

[0099] Optionally, the step S07 specifically includes:

[0100] The attenuation image AImage(i, j) is calculated in the frequency space according to the two-dimensional attenuated echo signal ASignal(i, j), and the calculation method is as follows:

[0101] Perform short-time Fourier transform on each line of the two-dimensional attenuated echo signal ASignal(i,j) to obtain the two-dimensional frequency domain distribution map P_M(i,j,f) in the j direction within the ROI region of interest, and calculate the average value of P_M(i,j,f) in the frequency direction. The formula is as follows:

[0102]

[0103] The attenuation coefficient value of each point in the ROI region of interest is obtained by P(i,j), and the formula is as follows:

[0104]

[0105] Where: X is the number of frequency samples, x is the frequency point, f is the frequency label, F is the average frequency, R0 represents the upper boundary of the ROI region of interest, R1 represents the lower boundary of the ROI region of interest, and lge represents the 10-base logarithmic function of the e exponent.

[0106] Step S08, calculating and obtaining attenuation characteristic parameters of muscle tissue according to the attenuation image;

[0107] Optionally, the step S08 specifically includes:

[0108] The attenuation characteristic parameters of the muscle tissue are calculated according to the attenuation image A(i, j), and the attenuation characteristic parameters of the muscle tissue include: the average muscle attenuation coefficient Atten Coe in the user-selected area, the upper boundary attenuation value AT, the center attenuation value AC, the lower boundary attenuation value AB and the average attenuation value AM of the user-selected area, and the calculation method is as follows:

[0109] The user uses a rectangular frame to select the muscle tissue area to be measured in the ROI region of interest (such as Figure 3 In S32, the rectangular frame can be adjusted in size, and the average value of all attenuation coefficients in the rectangular frame (the specific calculation method is the existing technology and will not be repeated here) is calculated as the average muscle attenuation coefficient Atten Coe (in dB / cm / MH) in the user-selected area. Figure 3(shown in S33);

[0110] The center line of the rectangular frame ( Figure 3 The pixel value of the intersection of the vertical line in the rectangular box and the upper boundary, the pixel value of the midpoint of the center line of the rectangular box, and the pixel value of the intersection of the center line of the rectangular box and the lower boundary are multiplied by the current transmission frequency to obtain AT, AC, and AB values, and these values ​​are averaged to obtain the AM value (such as Figure 3 (as shown in S34 in FIG. 1 ).

[0111] Step S09, combining and displaying the two-dimensional grayscale image, the two-dimensional texture image, and the attenuation image, and synchronously displaying quantitative parameters, wherein the quantitative parameters include the grayscale characteristic parameters of the muscle tissue, the texture characteristic parameters of the muscle tissue, and the attenuation characteristic parameters of the muscle tissue.

[0112] Optionally, the combined display in step S09 includes four-image, three-image, double-image, and single-image display modes;

[0113] The attenuation image is displayed superimposed on the two-dimensional grayscale image to form an image;

[0114] The quantitative parameters are a collection of three types of quantitative parameters: grayscale, attenuation, and texture. The parameters are displayed in real time or statically in a frozen state.

[0115] like Figure 4 As shown, S40 is the image display area on the display, S41 is a two-dimensional grayscale image, S42 is an attenuation image covered on the grayscale image, S43 is the muscle texture of the tissue, and S44 is a muscle texture image generated based on the grayscale image. Figure 2 As shown in S21; S45 is a parameter display area, which can display the local average grayscale, local contrast, attenuation coefficient and attenuation value derived from the attenuation coefficient, texture distribution law value and other mathematical and physical parameters derived therefrom of the grayscale image.

[0116] like Figure 5 As shown, an embodiment of the present invention further provides a device for quantitatively evaluating muscle lesions using medical ultrasound equipment, the device comprising:

[0117] The transmitting and receiving module 510 is used to alternately transmit a series of different pulse waves to human tissue and receive echo signals returned by the human tissue;

[0118] A signal classification module 520 is used to classify a series of received echo signals into two types: one type is a two-dimensional grayscale echo signal for implementing a two-dimensional grayscale image, and the other type is a two-dimensional attenuation echo signal for implementing attenuation imaging;

[0119] A storage module 530, used for caching the two-dimensional grayscale echo signal and the two-dimensional attenuated echo signal;

[0120] A grayscale image generation module 540 is used to calculate and obtain a two-dimensional grayscale image according to the two-dimensional grayscale echo signal;

[0121] A texture image generation module 550, configured to obtain a two-dimensional texture image by calculating the two-dimensional grayscale image;

[0122] An attenuation image generating module 560, configured to calculate an attenuation image according to the two-dimensional attenuation echo signal;

[0123] A quantitative parameter calculation module 570, configured to calculate quantitative parameters of the muscle tissue according to the two-dimensional grayscale image, the two-dimensional texture image, and the attenuation image, wherein the quantitative parameters include grayscale characteristic parameters of the muscle tissue, texture characteristic parameters of the muscle tissue, and attenuation characteristic parameters of the muscle tissue;

[0124] The combined display module 580 is used to display the two-dimensional grayscale image, the two-dimensional texture image, the attenuation image in combination, and to display the quantitative parameters synchronously.

[0125] An apparatus for quantitatively evaluating muscle lesions using a medical ultrasound device provided in an embodiment of the present invention has a functional structure corresponding to a method for quantitatively evaluating muscle lesions using a medical ultrasound device provided in an embodiment of the present invention, and will not be described in detail herein.

[0126] Figure 6 It is a structural schematic diagram of an electronic device 600 provided in an embodiment of the present invention. The electronic device 600 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 601 and one or more memories 602, wherein the memory 602 stores at least one instruction, and the at least one instruction is loaded and executed by the processor 601 to implement the steps of the method for quantitatively evaluating muscle lesions using the above-mentioned medical ultrasound equipment.

[0127] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including instructions, which can be executed by a processor in a terminal to complete the method for quantitatively evaluating muscle lesions using a medical ultrasound device. For example, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0128] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0129] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for quantitatively evaluating muscle lesions using medical ultrasound equipment, characterized in that: The method comprises: Step S01, alternately transmitting a series of different pulse waves to human tissue and receiving echo signals returned by the human tissue; Step S02: distinguishing the types of the received series of echo signals, one type is a two-dimensional grayscale echo signal for implementing a two-dimensional grayscale image, and the other type is a two-dimensional attenuation echo signal for implementing attenuation imaging; Step S03, buffering the two-dimensional grayscale echo signal and the two-dimensional attenuated echo signal; Step S04, first calculating and obtaining a two-dimensional grayscale image according to the two-dimensional grayscale echo signal, and then calculating and obtaining a two-dimensional texture image from the two-dimensional grayscale image; Step S05, calculating and obtaining grayscale characteristic parameters of muscle tissue according to the two-dimensional grayscale image; Step S06, calculating and obtaining texture feature parameters of muscle tissue according to the two-dimensional texture image; Step S07, calculating an attenuation image according to the two-dimensional attenuated echo signal; Step S08, calculating and obtaining attenuation characteristic parameters of muscle tissue according to the attenuation image; Step S09, combining and displaying the two-dimensional grayscale image, the two-dimensional texture image, and the attenuation image, and synchronously displaying quantitative parameters, wherein the quantitative parameters include the grayscale characteristic parameters of the muscle tissue, the texture characteristic parameters of the muscle tissue, and the attenuation characteristic parameters of the muscle tissue.

2. The method according to claim 1, characterized in that The S04 specifically includes: According to the two-dimensional grayscale echo signal BSignal(i,j), the two-dimensional grayscale image BImage(i,j) is first calculated. The calculation formula is as follows: Where: ABS() is a complex modulus operation, DR is the dynamic range of the image, and Log[] is a logarithmic function with base 10; Then, the two-dimensional texture image TImage(i,j) is calculated by the two-dimensional grayscale image BImage(i,j) by using operator filtering. The formula is as follows: Wherein: Sober is a differential operator, sober(m,n) here defines a 3*3 window, and this 3*3 window is used to slide and sum on the two-dimensional grayscale image BImage(i,j), traverse all pixels, and obtain the two-dimensional texture image TImage(i,j), i, j represent the row label and column label of the image respectively, m, n represent the horizontal line number and vertical point number label of the window respectively, M, N represent the horizontal line number and vertical point number of the window respectively.

3. The method according to claim 1, characterized in that The step S05 specifically includes: Calculate the grayscale characteristic parameters of the muscle tissue according to the two-dimensional grayscale image BImage(i,j), wherein the grayscale characteristic parameters of the muscle tissue include: the average grayscale value of the local tissue, the contrast value of the local tissue and various mathematical and physical quantities derived therefrom; The calculation method of the average value of the local tissue grayscale and the contrast value of the local tissue is as follows: The user uses the measurement tool to select the area to be measured. The area can be of any shape, and the average grayscale value is represented as Mean1; After measuring Mean1, select a tissue area of ​​the same size that needs to be compared, calculate its grayscale average value Mean2, and use the ratio of the two as the contrast value, recorded as Contrast.

4. The method according to claim 1, characterized in that: The step S06 specifically includes: The texture feature parameters of the muscle tissue are calculated based on the two-dimensional texture image TImage(i,j), and the texture feature parameters of the muscle tissue include the fascia and the muscle distribution amount P, and the calculation method is as follows: Set two thresholds Ath and Bth to determine texture boundaries and muscle tissues, then: P=mean(P(k)),P(k)>Bth Where: ABS() is a complex modulus operation, i, j represent the row label and column label of the image respectively.

5. The method according to claim 1, characterized in that The step S07 specifically includes: The attenuation image AImage(i, j) is calculated in the frequency space according to the two-dimensional attenuated echo signal ASignal(i, j), and the calculation method is as follows: Perform short-time Fourier transform on each line of the two-dimensional attenuated echo signal ASignal(i,j) to obtain the two-dimensional frequency domain distribution map P_M(i,j,f) in the j direction within the ROI region of interest, and calculate the average value of P_M(i,j,f) in the frequency direction. The formula is as follows: The attenuation coefficient value of each point in the ROI region of interest is obtained by P(i,j), and the formula is as follows: Where: X is the number of frequency samples, x is the frequency point, f is the frequency label, F is the average frequency, R0 represents the upper boundary of the ROI region of interest, R1 represents the lower boundary of the ROI region of interest, and lge represents the 10-base logarithmic function of the e exponent.

6. The method according to claim 1, characterized in that The step S08 specifically includes: The attenuation characteristic parameters of the muscle tissue are calculated according to the attenuation image A(i, j), and the attenuation characteristic parameters of the muscle tissue include: the average muscle attenuation coefficient Atten Coe in the user-selected area, the upper boundary attenuation value AT, the center attenuation value AC, the lower boundary attenuation value AB and the average attenuation value AM of the user-selected area, and the calculation method is as follows: The user uses a rectangular box to select the muscle tissue area to be measured in the ROI region of interest. The size of the rectangular box can be adjusted arbitrarily. The average value of all attenuation coefficients in the rectangular box is calculated as the average attenuation coefficient Atten Coe of the muscle in the user-selected area. Multiply the pixel value of the intersection of the center line of the rectangular box and the upper boundary, the pixel value of the midpoint of the center line of the rectangular box, and the pixel value of the intersection of the center line of the rectangular box and the lower boundary by the current transmission frequency to obtain AT, AC, and AB values, and average these values ​​to obtain the AM value.

7. The method according to claim 1, characterized in that The combined display in step S09 includes four-image, three-image, double-image, and single-image display modes; The attenuation image is displayed superimposed on the two-dimensional grayscale image to form an image; The quantitative parameters are a collection of three types of quantitative parameters: grayscale, attenuation, and texture. The parameters are displayed in real time or statically in a frozen state.

8. A device for quantitatively evaluating muscle lesions using medical ultrasound equipment, characterized in that: The device comprises: A transmitting and receiving module, used for alternately transmitting a series of different pulse waves to human tissue and receiving echo signals returned by the human tissue; A signal classification module is used to distinguish the types of a series of received echo signals, one type is a two-dimensional grayscale echo signal used to implement a two-dimensional grayscale image, and the other type is a two-dimensional attenuation echo signal used to implement attenuation imaging; A storage module, used for caching the two-dimensional grayscale echo signal and the two-dimensional attenuated echo signal; A grayscale image generation module, used for first calculating and obtaining a two-dimensional grayscale image according to the two-dimensional grayscale echo signal; A texture image generation module, used for calculating and obtaining a two-dimensional texture image from the two-dimensional grayscale image; An attenuation image generation module, used for calculating an attenuation image according to the two-dimensional attenuation echo signal; A quantitative parameter calculation module, used for calculating and obtaining quantitative parameters of muscle tissue according to the two-dimensional grayscale image, the two-dimensional texture image, and the attenuation image, wherein the quantitative parameters include grayscale characteristic parameters of the muscle tissue, texture characteristic parameters of the muscle tissue, and attenuation characteristic parameters of the muscle tissue; The combined display module is used for combining and displaying the two-dimensional grayscale image, the two-dimensional texture image, the attenuation image, and synchronously displaying the quantitative parameters.

9. An electronic device, comprising a processor and a memory, wherein at least one instruction is stored in the memory, wherein: The at least one instruction is loaded and executed by the processor to implement the method for quantitatively evaluating muscle lesions using a medical ultrasound device according to any one of claims 1 to 7.

10. A computer-readable storage medium, wherein at least one instruction is stored in the storage medium, characterized in that: The at least one instruction is loaded and executed by the processor to implement the method for quantitatively evaluating muscle lesions using a medical ultrasound device according to any one of claims 1 to 7.

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