WO2021042242A1 - Ultrasonic imaging device and ultrasonic echo signal processing method thereof - Google Patents

Abstract

Disclosed is an ultrasonic echo signal processing method, comprising the steps of acquiring and analyzing an ultrasonic echo signal of a liver to obtain a quantitative value reflecting the degree of severity of the liver attribute analysis and a credibility of the quantitative value; and displaying the quantitative value and the credibility on a display interface of a display. The quantitative value provides a doctor with the degree of severity of the liver attribute analysis, and the displayed credibility can avoid misleading the doctor, the quantitative value and its credibility can provide the doctor with a comprehensive diagnosis reference, and help the doctor to improve the diagnosis accuracy. Further disclosed is a corresponding ultrasound imaging device.

Description

Ultrasonic imaging equipment and its ultrasonic echo signal processing method Technical field

The invention relates to the field of medical equipment, in particular to an ultrasonic imaging equipment and a processing method of ultrasonic echo signals.

Background technique

With the development of technology, the application of image processing technology and artificial intelligence technology in medicine has become more and more common. At present, most of the applications in clinical products are to process and analyze medical images, and then directly give the analysis results. This method is helpful to provide doctors with reference, but to a certain extent, it will also affect doctors, especially low-age doctors. The doctor's judgment, the doctor may make a final judgment or conclusion based on the analysis results. However, the analysis result is not 100% accurate. If the image processing technology and artificial intelligence technology do not analyze the pathology displayed by the medical image for some reason, the accuracy of the result will not be high, but it will mislead the doctor. It will have a great impact on the patient's follow-up treatment. Especially for fatty liver problems, early fatty liver is a reversible disease, and the correct treatment can be completely cured. However, if the misdiagnosis is caused by the complete belief in artificial intelligence, which delays the patient’s condition and causes the severity of fatty liver to increase or even turn into irreversible liver fibrosis, liver cirrhosis, liver cancer, etc., causing greater harm to the patient, this situation is absolutely impossible. occurring.

Summary of the invention

technical problem

The solution to the problem

Technical solutions

The present invention mainly provides an ultrasonic imaging equipment and a processing method for ultrasonic echo signals thereof.

An embodiment provides an ultrasound imaging device, including:

An ultrasonic probe for transmitting ultrasonic waves to a target area and receiving echoes of the ultrasonic waves to obtain electrical signals of the echoes;

A transmitting/receiving control circuit for controlling the ultrasonic probe to transmit ultrasonic waves to a target area and receive echoes of the ultrasonic waves;

Display, used to output visual information;

Processor for:

Obtain an ultrasonic echo signal according to the electrical signal of the echo, and analyze the ultrasonic echo signal to obtain a quantitative value of the severity of liver fatty liver or liver fibrosis and the reliability of the quantitative value; and

Provide a schematic diagram of the liver, mark the quantitative value as an indicator of the schematic diagram of the liver, and mark the reliability as another indicator of the schematic diagram of the liver. Reliability is displayed visually.

An embodiment provides an ultrasound imaging device, including:

An ultrasonic probe for transmitting ultrasonic waves to a target area and receiving echoes of the ultrasonic waves to obtain electrical signals of the echoes;

The transmitting/receiving control circuit is used to control the ultrasonic probe to transmit ultrasonic waves to the target area and receive echoes of the ultrasonic waves;

Display, used to output visual information;

Processor for:

Obtain an ultrasonic echo signal according to the electrical signal of the echo, analyze the ultrasonic echo signal to obtain a quantitative value reflecting the severity of liver attribute analysis and the credibility of the quantitative value; and

The quantitative value and the credibility are displayed on the display interface of the display.

An embodiment provides a method for processing ultrasonic echo signals, including:

Obtain the ultrasound echo signal of the liver;

Analyze the ultrasonic echo signal, identify the image sign of interest contained therein, and obtain a quantitative value reflecting the degree of interest of the image sign of interest and the credibility of the quantitative value; and

Taking the quantitative value as one dimension and the credibility as another dimension, the degree of interest in the image of interest is displayed in association on the display interface.

According to the ultrasonic imaging device and the ultrasonic echo signal processing method of the foregoing embodiment, the quantitative value and the credibility can be visually displayed on the display interface of the display.

The beneficial effects of the invention

Brief description of the drawings

Description of the drawings

FIG. 1 is a structural block diagram of an ultrasonic imaging device provided by an embodiment of the present invention;

2 is a flowchart of a method for processing ultrasonic echo signals according to an embodiment of the present invention;

Fig. 3 is a flowchart of the method of step 2 in Fig. 2;

4 is a schematic diagram of graphically displaying quantitative values and their credibility on an ultrasound image in an embodiment of the present invention;

Fig. 5a is a schematic diagram of a first graph with low reliability in an embodiment of the present invention;

FIG. 5b is a schematic diagram of a first graph of medium reliability in an embodiment of the present invention;

FIG. 5c is a schematic diagram of a first graphic with high reliability in an embodiment of the present invention; FIG.

Fig. 6 is a schematic diagram of a first graph combining coordinates and graphs in an embodiment of the present invention;

FIG. 7 is a schematic diagram of a first graph showing credibility in text in an embodiment of the present invention;

Fig. 8a is a schematic diagram showing quantitative values and their credibility in a rectangular chart in an embodiment of the present invention;

Fig. 8b is a schematic diagram showing quantitative values and their credibility in a triangular chart in an embodiment of the present invention;

FIG. 9 is a schematic diagram showing the combination of the first graph and the chart to display the quantitative value and its credibility in an embodiment of the present invention;

FIG. 10 is a schematic diagram of a first graph combining coordinates and graphs in an embodiment of the present invention;

FIG. 11 is a flowchart of an embodiment of step 2 in FIG. 2;

Figure 12 is a schematic diagram of a display interface in an embodiment of the present invention;

FIG. 13 is a flowchart of an embodiment of step 2 in FIG. 2.

Invention embodiment

Embodiments of the present invention

Hereinafter, the present invention will be further described in detail through specific embodiments in conjunction with the accompanying drawings. Among them, similar elements in different embodiments use related similar element numbers. In the following embodiments, many detailed descriptions are used to make this application better understood. However, those skilled in the art can easily realize that some of the features can be omitted under different circumstances, or can be replaced by other elements, materials, and methods. In some cases, some operations related to this application are not shown or described in the specification. This is to avoid the core part of this application being overwhelmed by excessive descriptions. For those skilled in the art, these are described in detail. Related operations are not necessary, they can fully understand the related operations based on the description in the manual and the general technical knowledge in the field.

In addition, the features, operations, or features described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be sequentially exchanged or adjusted in a manner obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment, and are not meant to be a necessary sequence, unless it is specified that a certain sequence must be followed.

The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the described objects and do not have any sequence or technical meaning. The "connection" and "connection" mentioned in this application include direct and indirect connection (connection) unless otherwise specified.

As shown in Fig. 1, the ultrasonic imaging equipment provided by the present invention includes an ultrasonic probe 20, a transmitting/receiving circuit 30 (ie, a transmitting circuit 310 and a receiving circuit 320), a processor 40, a memory 50 and a human-computer interaction device.

The ultrasonic probe 20 includes a transducer (not shown in the figure) composed of a plurality of array elements arranged in an array, and the plurality of array elements are arranged in a row to form a linear array, or arranged in a two-dimensional matrix to form a surface array. The array elements can also form a convex array. The array element is used to transmit an ultrasonic beam according to the excitation electrical signal, or to transform the received ultrasonic beam into an electrical signal. Therefore, each array element can be used to realize the mutual conversion of electrical pulse signals and ultrasonic beams, so as to realize the transmission of ultrasonic waves to the target area of human tissue (such as the liver in this embodiment), and it can also be used to receive the echo of the ultrasonic waves reflected by the tissue. wave. During ultrasonic testing, the transmitting circuit 310 and the receiving circuit 320 can control which array elements are used to transmit ultrasonic beams and which array elements are used to receive ultrasonic beams, or control the array elements to be used to transmit ultrasonic beams or receive ultrasonic beams in time slots. Echo. The array elements participating in the ultrasonic transmission can be excited by electrical signals at the same time, thereby simultaneously emitting ultrasonic waves; or the array elements participating in the ultrasonic transmission can also be excited by several electrical signals with a certain time interval, so as to continuously emit ultrasonic waves with a certain time interval.

In this embodiment, the user selects a suitable position and angle by moving the ultrasound probe 20 to transmit ultrasound to the liver 10 and receive the echo of the ultrasound returned from the liver 10, and obtain and output the electrical signal of the echo. The electrical signal of the echo is According to the channel analog electrical signal formed by the receiving array element as the channel, it carries amplitude information, frequency information and time information.

The transmitting circuit 310 is used to generate a transmitting sequence according to the control of the transmitting/receiving sequence control module 410. The transmitting sequence is used to control some or all of the multiple array elements to transmit ultrasonic waves to biological tissues. The parameters of the transmitting sequence include the position of the transmitting array element, The number of array elements and ultrasonic beam emission parameters (such as amplitude, frequency, number of emission, emission interval, emission angle, wave type, focus position, etc.). In some cases, the transmitting circuit 310 is also used to phase delay the transmitted beams, so that different transmitting array elements emit ultrasonic waves at different times, so that each transmitted ultrasonic beam can be focused on a predetermined region of interest. Different working modes, such as B image mode, C image mode and D image mode (Doppler mode), the transmission sequence parameters may be different. The echo signal is received by the receiving circuit 320 and processed by subsequent modules and corresponding algorithms. Generate a B image that reflects the anatomical structure of the tissue, a C image that reflects the anatomical structure of the tissue and blood flow information, and a D image that reflects the Doppler spectrum image.

The receiving circuit 320 is used to receive the electrical signal of the ultrasonic echo from the ultrasonic probe 20 and process the electrical signal of the ultrasonic echo. The receiving circuit 320 may include one or more amplifiers, analog-to-digital converters (ADC), and the like. The data output by the receiving circuit 320 may be output to the beam synthesis module 420 for processing, or output to the memory 50 for storage.

The processor 40 is used to configure a central controller circuit (CPU), one or more microprocessors, a graphics controller circuit (GPU) or any other electronic components that can process input data according to specific logic instructions. Commands or predetermined commands perform control of peripheral electronic components, or perform data reading and/or saving on the memory 50, and input data can also be processed by executing a program in the memory 50, for example, collecting data according to one or more working modes. Perform one or more processing operations on the ultrasound data. The processing operations include, but are not limited to, adjusting or limiting the form of ultrasound emitted by the ultrasound probe 20, generating various image frames for subsequent display on the display 60 of the human-computer interaction device, or adjusting or Define the content and form displayed on the display 60, or adjust one or more image display settings displayed on the display 60 (for example, ultrasound images, interface components, locating regions of interest).

The processor 40 includes a transmission/reception sequence control module 410, a beam synthesis module 420, an IQ demodulation module 430, and an image processing module 440.

The beam synthesizing module 420 is connected to the receiving circuit 320 to signal the signal output by the receiving circuit 320. It is used to perform beam synthesizing processing such as delay and weighted summation on the signal output by the receiving circuit 320. Because the distance between the ultrasonic receiving point in the measured tissue and the receiving array element is different Therefore, the channel data of the same receiving point output by different receiving array elements has delay differences, and delay processing is required to align the phases, and the different channel data of the same receiving point are weighted and summed to obtain the beam-combined ultrasound Image data, the ultrasound image data output by the beam synthesis module 420 is also called radio frequency data (RF data). The beam synthesis module 420 outputs the radio frequency data to the IQ demodulation module 430. In some embodiments, the beam combining module 420 may also output the radio frequency data to the memory 50 for buffering or storage, or directly output the radio frequency data to the image processing module 440 for image processing.

The IQ demodulation module 430 removes the signal carrier through IQ demodulation, extracts the organizational structure information contained in the signal, and performs filtering to remove noise. At this time, the acquired signal is called a baseband signal (IQ data pair). The IQ demodulation module 430 outputs the IQ data pair to the image processing module 440 for image processing.

In some embodiments, the IQ demodulation module 430 also buffers or saves the IQ data output to the memory 50, so that the image processing module 440 reads the data from the memory 50 for subsequent image processing.

The image processing module 440 is used to process the data output by the beam synthesis module 420 or the data output by the IQ demodulation module 430 to generate a grayscale image of signal strength changes within the scanning range, which reflects the internal anatomy of the tissue The structure is called a B image. The image processing module 440 can output the B image to the display 60 of the human-computer interaction device for display.

The human-computer interaction device is used for human-computer interaction, that is, receiving user input and outputting visual information; it can receive user input using keyboard, operation buttons, mouse, trackball, etc., or it can use touch integrated with the display Screen; its output visualized information adopts the display 60.

The memory 50 may be a flash memory card, a solid-state memory, a hard disk, and the like.

Based on the ultrasonic imaging device shown in Fig. 1, the processing method of the ultrasonic echo signal is shown in Fig. 2, including the following steps:

Step 1. The processor 40 obtains the ultrasound echo signal of the liver. The processor 40 may obtain the ultrasound echo signal of the liver from the memory 50 or an external device, or may use the ultrasound probe 20 to obtain it. In this embodiment, the ultrasound probe 20 is used as an example for description. The transmitting/receiving sequence control module 410 controls the ultrasonic probe 20 through the transmitting/receiving control circuit 30 to transmit ultrasonic waves to the liver and receive the echoes of the ultrasonic waves to obtain the echoed electrical signals. The processor 40 obtains an ultrasonic echo signal according to the echoed electrical signal.

The processing of the electrical signal obtained from the echo may include signal processing links such as analog signal gain compensation, beam synthesis, IQ demodulation, digital signal gain compensation, amplitude calculation, and image enhancement. Specifically, the above-mentioned electrical signal is subjected to front-end filtering and amplification (that is, gain compensation) through an analog circuit, and then converted into a digital signal by an analog-to-digital converter (ADC), and the channel data after the analog-to-digital conversion is further subjected to beam synthesis processing to form a scan line Data, the data processing performed before this can be collectively referred to as front-end processing. The data obtained after the completion of this stage, that is, the ultrasonic echo signal output by the beam synthesis module 50, may be referred to as radio frequency signal data, that is, RF data. After the RF data is acquired, the signal carrier is removed by IQ demodulation, the organizational structure information contained in the signal is extracted, and filtering is performed to remove noise. At this time, the acquired signal is a baseband signal (IQ data). All the processing required from the radio frequency signal processing to the baseband signal can be collectively referred to as mid-end processing. Finally, obtain the intensity of the baseband signal and pass its gray level through logarithmic compression and gray conversion to obtain an ultrasound image. The processing completed at this time can be collectively referred to as back-end processing.

The ultrasonic echo signal of the present invention is the data obtained by performing one-stage or multi-stage signal processing on the electrical signal obtained based on the ultrasonic echo, that is, the ultrasonic echo signal can be the data generated in any of the above-mentioned signal processing links. For example, the ultrasonic echo signal may be an analog or digital ultrasonic echo signal before beam synthesis, or data after beam synthesis, such as the ultrasonic echo signal output by the beam synthesis module 50, or it may be after IQ demodulation. The data, such as the ultrasound echo signal output by the IQ demodulation module 60, may also be ultrasound image data obtained by further processing based on beam-synthesized data or IQ demodulated data.

Step 2. The image processing module 440 analyzes the ultrasonic echo signal, identifies the image sign of interest contained therein, and obtains a quantitative value reflecting the degree of interest of the image sign of interest (image feature of interest) and the credibility of the quantitative value . The image sign of interest is used to reflect the properties of the liver, such as whether the liver has disease, and the type of disease (fatty liver, liver fibrosis, tumor, etc.). The image processing module 440 obtains a quantitative value reflecting the degree of interest of the image sign of interest and the credibility of the quantitative value according to the characteristics of the image of interest. The degree of interest may be the severity of the disease. Or the severity of liver fibrosis as an example.

As described above, in this embodiment, the ultrasonic echo signal may be the signal after the echoed electrical signal is beam-synthesized, and it may be the data output by the beam-synthesis module 420 or the data output by the IQ demodulation module 430. , It may also be the ultrasound image data processed by the image processing module 440. The processor 40 analyzes the ultrasound echo signal to obtain a quantitative value of the severity of fatty liver or liver fibrosis and the credibility of the quantitative value, including: processing electrical signals to obtain an ultrasound image (gray image) The signal of any signal processing link is analyzed to obtain the quantitative value of the severity of fatty liver or liver fibrosis and the reliability of the quantitative value.

As shown in FIG. 3, the image processing module 440 obtaining the quantitative value of the severity of fatty liver or liver fibrosis and the credibility of the quantitative value includes the following steps:

Step 210: The image processing module 440 automatically analyzes the ultrasound echo signal through a machine learning method to obtain a classification result of the severity of fatty liver or liver fibrosis and the probability of the classification result. Machine learning can be traditional machine learning or deep learning. For example, obtain the ultrasound echo signals corresponding to livers with different severity of fatty liver or liver fibrosis; use ultrasound echo signals as input, and classify the severity of fatty liver or liver fibrosis as labels, perform machine learning or deep learning, and train Obtain the severity classification as a model function of the feature index; subsequently, input the ultrasound echo signal obtained by the image processing module 440 into the model function, and obtain the classification result and classification of the severity of the liver fatty liver or liver fibrosis corresponding to the ultrasound echo signal Probability of outcome. The classification results include multiple categories, such as severe, moderate, minor, etc., and each category corresponds to a probability. The probability of the classification result can be generated at the same time as the classification result is generated. This is a conventional method of machine learning. However, the prior art usually uses the most probable result as the final result, which is not the case in this application. This application uses probability to determine the severity For the second calculation, see step 220 for details.

Step 220: The image processing module 440 quantitatively calculates the severity of fatty liver or liver fibrosis according to the classification result and its probability, and obtains a quantitative value reflecting the severity of fatty liver or liver fibrosis. In this embodiment, the probability is used as the weight, and at least two categories are weighted and calculated to obtain a quantitative value reflecting the severity of fatty liver or liver fibrosis. Perform weight calculation on at least two categories. Specifically, weight calculation may be performed on two or more categories with the highest probability among the classification results. For example, the classification results include severe, moderate, mild, and normal, which are represented as 3, 2, 1, 0 according to the grade. When the automatic analysis is performed by the machine learning method, the output analysis result is directly the classification result of the severity of the ultrasonic echo signal and the probability of the classification result. For example, the classification results and their probabilities obtained by the machine learning method are: severe (3), 60%, moderate (2), 20%, mild (1), 10%, normal (0), 10%; the final The quantitative value is: min(2,3)+|2-3|*(60%/(20%+60%))+0.5=3.25. In this example, the quantitative interval corresponding to severe is 3-4, the quantitative interval corresponding to medium is 2-3, the quantitative interval corresponding to slight is 1-2, and the quantitative interval corresponding to normal is 0-1. Based on the division of the above quantitative interval, in this example, the final severity of fatty liver or liver fibrosis of the patient lies within the severe quantitative interval, and the quantitative value is 3.25. The severity obtained by this method is more accurate, and the numerical display further provides doctors with a more accurate reference, which is convenient for doctors to diagnose.

Step 230: The image processing module 440 calculates the credibility of the quantitative value according to the probability of the classification result. Specifically, the credibility is divided into multiple levels, each level corresponds to a probability interval, and the probability intervals add up to 1. For example, the probability intervals corresponding to high, medium, and low credibility are: : 100%～70%, 70%～30%, 30%～0%. The image processing module 440 calculates the credibility of the quantitative value according to the probability of the classification result (for example, n classification results). According to the probability of the classification result, the first two or n-1 numerical probabilities are added together to obtain The value of the credibility, preferably, the credibility of the quantitative value is calculated based on the probability used in the calculation of the quantitative value, for example, the probabilities used in the calculation of the quantitative value are added. Continuing the example in the previous paragraph where the classification results are severe, moderate, mild, and normal, the probability of adding the first two values to calculate the reliability is: 60% + 20% = 80%, that is, high confidence. It can be seen that the present invention can not only obtain qualitative credibility, but also obtain specific numerical values. Of course, the image processing module 440 can also perform statistical analysis on the probability of at least the first two numerical values according to the magnitude of each probability, and determine that the relationship between the analysis result and the preset multiple credibility intervals (probability intervals) will be consistent. The credibility corresponding to the preset credibility interval of is used as the credibility of the quantitative value.

This embodiment specifically takes the ultrasound echo signal as an ultrasound image as an example for description, where the ultrasound image may be a three-dimensional ultrasound image, an ultrasound B image, an ultrasound C image, etc., and this embodiment takes an ultrasound B image as an example for description. In addition to obtaining the quantitative value of the severity of liver fatty liver or liver fibrosis and the credibility of the quantitative value through the above-mentioned method, the image processing module 440 can also automatically analyze the ultrasound image to obtain a reflection of fatty liver or liver. The quantitative value of the severity of fibrosis, for example, acquiring the texture parameter and the acoustic attenuation parameter of the ultrasound image, and determining the quantitative value according to the texture parameter and the acoustic attenuation parameter; and obtaining the credibility of the quantitative value according to the image quality of the ultrasound image degree. If the quality of the ultrasound image is poor, the quantitative value obtained by the automatic analysis is definitely low, and its credibility is also low, so that the credibility can be accurately obtained.

It is far from enough to obtain a quantitative value reflecting the severity of fatty liver or liver fibrosis, because doctors usually think that the quantitative value is 100% accurate, but it is actually difficult to achieve 100% accuracy. Therefore, the present invention focuses on calculation The credibility of the quantitative value enables the doctor to have a certain degree of credibility of the quantitative value.

Step 3. The image processing module 440 displays the calculated quantitative value and its credibility on the display interface of the display 50, and also displays the ultrasound image of the liver, as shown in FIG. 4, which is convenient for the doctor to observe the ultrasound image of the patient’s liver. , And understand the quantitative value and credibility of the severity of fatty liver or liver fibrosis. Wherein, the image processing module 440 may simultaneously display the quantitative value and the credibility on the display interface of the display 50; it may also display the quantitative value on the display interface of the display 50, and the human-computer interaction device receives the user After the preset instruction is input, the quantitative value and the credibility are displayed at the same time. In this embodiment, the simultaneous display of the quantitative value and its credibility is taken as an example for further description. In this embodiment, the image processing module 440 graphically displays the quantitative value and its credibility on the display interface of the display 50, and the graphical display is more intuitive. Specifically, the image processing module 440 takes the quantitative value as one dimension and the credibility as another dimension, and visually displays two-dimensional information on the display interface of the display 50. There are many kinds of two-dimensional information visualization display, which will be further explained by examples below.

In an embodiment, as shown in FIG. 5, the image processing module 440 provides a first graphic A. The first graphic A may be obtained from a memory or an external device, or may be generated by the image processing module 440; on the display interface of the display 50 The first graph A is displayed, the quantitative value is identified by the quantitative index of the first graph A, and the credibility is identified by the qualitative index of the first graph. The first image A can be various regular or irregular geometric figures, etc. In this embodiment, the first image A is a schematic diagram of the liver, which is convenient for visually showing the degree of fatty liver of the liver and its credibility. Wherein, the quantitative index includes the quantitative value and its range, and also includes at least one of the figure size, the filling area, and the number of filled tiles. As shown in FIG. 5, the quantitative index of the first figure A includes the filling area of the first image A ( The gray area in the figure), the quantitative value (2.4) and its range (0-4). The larger the filling area, the more serious the fatty liver. From a doctor's point of view, one can know that the severity of fatty liver or liver fibrosis is moderate at a glance, and the quantitative value is 2.4 (medium) by looking at the value, which is very convenient and intuitive. In addition to the filling area in Figure 5, the quantitative indicators can also use line segments to represent quantitative values, as shown in Figures 6 and 7.

Qualitative indicators include at least one of line color, filling color, filling pattern, filling block size, number of filling blocks, text, letters, and numbers; the filling color (gray) in Figure 5, the darker the gray indicates the credibility The higher the higher, Figures 5a-c show the low-reliability, medium-reliability, and high-reliability situations, which are also clear at a glance. In Fig. 6, the qualitative index is the size of the filling block, supplemented by the coordinates, it can be seen that the credibility of the qualitative value in Fig. 6 is medium.

In one embodiment, as shown in FIG. 7, the image processing module 440 displays the first graphic A on the display interface of the display 50, uses the quantitative index of the first graphic A to mark the quantitative value, and marks the credibility on the first graphic A. The value of degrees. In Figure 7, the credibility is directly displayed in the form of text, of course, the specific value of the credibility can be further displayed.

In addition to the liver diagram shown above, it can also be displayed in the form of a graph. In one embodiment, as shown in FIG. 8a, the image processing module 440 displays a chart for displaying the quantitative value and reliability on the display interface of the display 50, and the first coordinate axis of the chart is the quantitative value, and the first axis of the chart is the quantitative value. The two axis is the credibility. The chart can be a variety of geometric figures, and the coordinate axis is not limited to the conventional vertical coordinate axis. As shown in Figure 8a, the horizontal axis represents the quantitative value of the severity of fatty liver, the farther to the right the more serious the fatty liver; the vertical axis represents the reliability of the quantitative value of fatty liver, the higher the higher the reliability of the quantitative value, The quantitative value in the figure is 2.8, and the reliability is medium. As shown in Figure 8b, the horizontal axis of the pyramid represents the quantitative value of fatty liver severity, and the longitudinal axis represents the reliability of the quantitative value of fatty liver. The pyramid from left to right represents the severity of fatty liver from normal to mild to moderate to severe. (Serious); The pyramid from the bottom of the tower to the top of the tower represents the reliability of the quantitative value of fatty liver from low to high. The quantitative value in the figure is 2.6, and the reliability is high. Similarly, in order to facilitate highlighting, you can also create geometric figures in the chart according to the coordinate system, such as the rectangle in Figure 8a and the triangle in Figure 8b. The quantitative value of the geometric figure is used to identify the quantitative value, and the qualitative indicator of the geometric figure is used to identify the quantitative value. The credibility, the quantitative index and the qualitative index have been described in the above embodiments, and will not be repeated here.

Of course, it can also be displayed in the form of a first graph and a chart. As shown in FIG. 9, in an embodiment, the image processing module 440 displays the first graph A and the first coordinate axis D on the display interface of the display 50, so The qualitative index of the first graph A identifies the credibility, and the position of the first graph A corresponding to the first coordinate axis D identifies the quantitative value. The first graph A and the first coordinate axis D can be connected by a straight line to facilitate the positioning of specific quantitative values on the coordinate axis; an arrow from the first graph A can also be used to indicate to the first coordinate axis D to facilitate the Position the specific quantitative value on the coordinate axis. The first graph A has the above-mentioned qualitative index to identify the credibility. Figure 6 is actually in this form, but the first coordinate axis is attached to the schematic diagram of the liver. Of course, as shown in Figure 6, a second coordinate axis can also be set, and the second coordinate axis moves with the quantitative value. The intersection of B and the second coordinate axis identifies the credibility. As shown in FIG. 10, the first coordinate axis and the second coordinate axis may also be set on adjacent two sides of the first image A, respectively.

The above embodiment describes the solution of displaying the quantitative value and its credibility at the same time. Based on the above embodiment, when the quantitative value is displayed, the credibility is first hidden (not displayed), and the user-input preset is received in the human-computer interaction device. After the instruction, the quantitative value and its credibility are displayed at the same time, that is, the hidden credibility is displayed. The final effect is still shown in Figure 5 to Figure 10, so I will not repeat it.

In summary, the present invention aims at the severity of fatty liver or liver fibrosis. On the basis of the calculated quantitative value of fatty liver or liver fibrosis, the reliability of the quantitative value is calculated, and the quantitative value is summed up. The reliability of these two parameters is combined with two-dimensional visual display, which provides doctors with accurate and comprehensive reference information and improves the accuracy of doctors' diagnosis.

In addition, the foregoing content mentions a method for calculating the quantitative value and its reliability: acquiring the texture parameter and sound attenuation parameter of the ultrasound image, and determining the quantitative value according to the texture parameter and the sound attenuation parameter; and, according to the image quality of the ultrasound image The credibility of the quantitative value is obtained (as shown in Figure 11). The following content will explain this process in detail.

The processor 40 processes the acquired ultrasonic echo data to obtain the texture parameter and the sound attenuation parameter of the liver 10, and determines the quantitative value of the severity of fatty liver or liver fibrosis of the liver 10 according to the texture parameter and the sound attenuation parameter . Taking the ultrasound echo data as an ultrasound image as an example, the processor 40 processes the ultrasound image of the liver 10 to determine some related parameters of the liver 10 in the ultrasound image, for example, the texture parameters and sound attenuation parameters of the liver 10, etc. The quantitative value of the severity of fatty liver or liver fibrosis of the liver 10 is determined according to the texture parameter and the acoustic attenuation parameter of the liver 10, so as to intuitively quantitatively analyze the severity of fatty liver or liver fibrosis. The ultrasound image obtained by the processor 40 and related parameters of the liver 10 may be stored in the memory 50.

The method for calculating the quantitative value and its reliability in the embodiment shown in FIG. 11 of the present invention will be described in detail below.

In step 210', the processor 40 obtains the texture parameters and sound attenuation parameters of the ultrasound image.

After the processor 40 obtains the ultrasound image of the liver 10, it further obtains texture parameters and sound attenuation parameters in the ultrasound image. Among them, an optional implementation manner: determine the texture parameters of the ultrasound image according to the ultrasound image and a first preset model, where the first preset model is a model obtained by training based on historical data.

First of all, first introduce the process of establishing the first preset model. The process includes:

Step 2101: Obtain historical data.

Among them, the historical data includes analysis data of the severity of fatty liver or liver fibrosis of multiple livers. Optionally, the analysis data includes doctor diagnosis data of multiple livers and/or pathological diagnosis data of multiple livers. For example, the doctor's diagnosis data may include the diagnosis results of the multiple livers, such as the severity classification of fatty liver or liver fibrosis: normal, mild fatty liver, moderate fatty liver, severe fatty liver, etc. The pathological diagnosis data may be data obtained through pathological analysis of the liver obtained by external surgery.

Step 2102: Establish the first preset model based on historical data.

The first preset model is obtained by training based on the historical data and preset algorithms, where the preset algorithm may include algorithms such as deep learning or machine learning.

In a possible implementation manner of the present application, the processor 40 may directly process the entire ultrasound image, that is, input the ultrasound image as an input parameter into the first preset model to obtain a feature image; and then perform texture characteristic analysis on the feature image , The texture parameters of the liver 10 are obtained. Alternatively, the processor 40 inputs the ultrasound image as an input parameter into the first preset model to obtain the texture parameter of the liver 10.

In another possible implementation manner, the processor 40 determines the region to be analyzed in the ultrasound image, that is, the region of interest, where the region of interest may include the entire liver region or part of the liver region; and then the region to be analyzed The image of is input into the first preset model as an input parameter to obtain a characteristic image; then, texture characteristic analysis is performed on the characteristic image to obtain the texture parameter of the liver 10. Alternatively, the processor 40 inputs the image of the region to be analyzed as an input parameter into the first preset model to obtain the texture parameter of the liver 10.

Optionally, there are multiple ways to acquire the sound attenuation parameter of the ultrasound image in the embodiment of the present application, and the following examples illustrate:

1. Determine the sound attenuation parameter of the ultrasound image by the signal amplitude value of the ultrasonic echo in the preset depth range of the area to be analyzed.

First, determine the region to be analyzed in the ultrasound image, that is, the region of interest, and determine the sound attenuation parameter of the region to be analyzed according to the signal amplitude value of the ultrasonic echo corresponding to the region to be analyzed at a preset depth. The distance between the tissue in the analysis area and the probe. For example, the acoustic attenuation parameter may be the ratio of the signal amplitude value of the ultrasonic echo at the first depth of the area to be analyzed to the signal amplitude value of the ultrasonic echo at the second depth of the area to be analyzed, where the first depth It can be the near field depth, the second depth can be the far field depth, or the first depth is the far field depth and the second depth is the near field depth, which is not specifically limited here.

2. Determine the sound attenuation parameter of the ultrasound image according to the gray value corresponding to the image of the area to be analyzed in the preset depth range.

First, determine the region to be analyzed in the ultrasound image, that is, the region of interest, where the region of interest can be determined automatically by the system or manually input by the user, according to the corresponding image of the region to be analyzed within the preset depth range To determine the sound attenuation parameter of the area to be analyzed, the depth is the distance between the tissue in the area to be analyzed and the probe. For example, the sound attenuation parameter may be the ratio of the gray value corresponding to the image of the area to be analyzed at the first depth to the gray value of the image of the area to be analyzed at the second depth.

In step 220', the processor 40 determines the fatty liver quantitative parameter of the liver 10 according to the texture parameter and the sound attenuation parameter.

Optionally, the processor 40 determines the fatty liver quantitative parameter of the liver 10 according to the texture parameter and the sound attenuation parameter.

Specifically, the processor determines the quantitative value of the liver 10 according to the texture parameter, the sound attenuation parameter, and the second preset model. The second preset model may be a model trained according to algorithms such as deep learning or machine learning, and the texture parameter and the sound attenuation parameter are used as input to the second preset model to obtain the quantitative value of the liver 10 . Optionally, the second preset model may also be a functional relationship. For example, the functional relationship is a weight relationship, and the weight relationship includes a weight coefficient, and the weight coefficient may be system default or user-defined. There is no limit. For example, if the texture parameter is A, the sound attenuation parameter is B, and the weight coefficient is 4:6, the quantitative value is A*0.4+B*0.6. Optionally, the processor 40 may also average the texture parameter and the sound attenuation parameter to obtain the quantitative value of the liver 10, for example, the texture parameter is A, the sound attenuation parameter is B, that is, the weight coefficient is 1:1, Then the quantitative value is A*0.5+B*0.5.

In an embodiment of the present application, while the quantitative value and its credibility are displayed above, the ultrasound image and the corresponding sound attenuation parameter and texture parameter are also displayed.

Exemplarily, as shown in Fig. 12, the ultrasound image 701, the regions to be analyzed 702 and 703 are displayed on the display; the region to be analyzed 702 is distinguished and displayed by means of shadow, color, or frame. 703 is the quantitative value and Its credibility is shown in Figure 5 to Figure 10.

In step 230', the processor 40 obtains the credibility of the quantitative value according to the image quality of the ultrasound image. The image quality can be evaluated based on the overall brightness and artifacts of the ultrasound image. For example, the ultrasound image is matched with the preset standard image information library to obtain the matching degree with the standard image in the standard image information library; the matching degree reflects the image quality, and the higher the matching degree, the higher the image quality. The higher the credibility.

Of course, in some embodiments, data other than the ultrasound image in the ultrasound echo data can also be used to calculate the quantitative value, for example, the quantitative value is calculated based on the data output by the receiving circuit 320, and the calculation is based on the data output by the beam synthesis module 420. Quantitative value, or calculation of quantitative value based on the data output by IQ demodulation module 430, in other words, the above embodiment of calculating quantitative value based on ultrasound image can be extended to calculate quantitative value based on ultrasound echo data, the steps are shown in Figure 13 Shown. Since the specific process of calculating the quantitative value and its credibility based on the ultrasound echo data is the same as the above-mentioned calculation process based on the ultrasound image, it will not be repeated here.

Those skilled in the art can understand that all or part of the functions of the various methods in the above-mentioned embodiments can be realized by hardware or by computer programs. When all or part of the functions in the above embodiments are realized by a computer program, the program may be stored in a computer-readable storage medium. The storage medium may include: read-only memory, random access memory, magnetic disk, optical disk, hard disk, etc. The computer executes the program to realize the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above functions can be realized. In addition, when all or part of the functions in the above embodiments are implemented by a computer program, the program can also be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a mobile hard disk, and saved by downloading or copying. In the memory of the local device, or update the version of the system of the local device, when the program in the memory is executed by the processor, all or part of the functions in the foregoing embodiments can be realized.

This document is described with reference to various exemplary embodiments. However, those skilled in the art will recognize that changes and modifications can be made to the exemplary embodiments without departing from the scope of this document. For example, various operation steps and components used to perform the operation steps can be implemented in different ways according to a specific application or considering any number of cost functions associated with the operation of the system (for example, one or more steps can be deleted, Modify or incorporate into other steps).

In addition, as understood by those skilled in the art, the principles herein can be reflected in a computer program product on a computer-readable storage medium, which is pre-installed with computer-readable program code. Any tangible, non-transitory computer-readable storage medium can be used, including magnetic storage devices (hard disks, floppy disks, etc.), optical storage devices (CD-ROM, DVD, Blu Ray disks, etc.), flash memory and/or the like . These computer program instructions can be loaded on a general-purpose computer, a special-purpose computer, or other programmable data processing equipment to form a machine, so that these instructions executed on the computer or other programmable data processing device can generate a device that realizes the specified function. These computer program instructions can also be stored in a computer-readable memory, which can instruct a computer or other programmable data processing equipment to operate in a specific manner, so that the instructions stored in the computer-readable memory can form a piece of Manufactured products, including realizing devices that realize designated functions. Computer program instructions can also be loaded on a computer or other programmable data processing equipment, thereby executing a series of operation steps on the computer or other programmable equipment to produce a computer-implemented process, so that the execution of the computer or other programmable equipment Instructions can provide steps for implementing specified functions.

Although the principles herein have been shown in various embodiments, many modifications to the structure, arrangement, proportions, elements, materials, and components that are particularly suitable for specific environments and operating requirements can be made without departing from the principles and scope of this disclosure. use. The above modifications and other changes or amendments will be included in the scope of this article.

The foregoing detailed description has been described with reference to various embodiments. However, those skilled in the art will recognize that various modifications and changes can be made without departing from the scope of this disclosure. Therefore, the consideration of this disclosure will be in an illustrative rather than restrictive sense, and all these modifications will be included in its scope. Likewise, the advantages, other advantages, and solutions to problems of the various embodiments have been described above. However, benefits, advantages, solutions to problems, and any solutions that can produce these or make them more specific should not be construed as critical, necessary, or necessary. The term "including" and any other variants thereof used in this article are non-exclusive inclusions. Such a process, method, article or device that includes a list of elements not only includes these elements, but also includes those that are not explicitly listed or are not part of the process. , Methods, systems, articles or other elements of equipment. In addition, the term "coupled" and any other variations thereof used herein refer to physical connection, electrical connection, magnetic connection, optical connection, communication connection, functional connection and/or any other connection.

Those skilled in the art will recognize that many changes can be made to the details of the above-described embodiments without departing from the basic principles of the present invention. Therefore, the scope of the present invention should be determined according to the following claims.

Claims (31)

1. An ultrasonic imaging equipment, characterized in that it comprises:

   An ultrasonic probe for transmitting ultrasonic waves to a target area and receiving echoes of the ultrasonic waves to obtain electrical signals of the echoes;

   A transmitting/receiving control circuit for controlling the ultrasonic probe to transmit ultrasonic waves to a target area and receive echoes of the ultrasonic waves;

   Display, used to output visual information;

   Processor for:

   Obtain an ultrasonic echo signal according to the electrical signal, analyze the ultrasonic echo signal to obtain a quantitative value of the severity of liver fatty liver or liver fibrosis and the reliability of the quantitative value; and

   Provide a schematic diagram of the liver, mark the quantitative value as an indicator of the schematic diagram of the liver, and mark the reliability as another indicator of the schematic diagram of the liver. Reliability is displayed visually.
2. The ultrasonic imaging device according to claim 1, wherein the processor visually displaying the quantitative value and the credibility through the marked schematic diagram of the liver on the display interface of the display comprises:

   The schematic diagram of the liver is displayed on the display interface of the display, the quantitative value is identified by the quantitative index of the schematic liver diagram, and the credibility is identified by the qualitative index of the schematic liver diagram.
3. The ultrasonic imaging device according to claim 1, wherein the processor visually displaying the quantitative value and the credibility through the marked schematic diagram of the liver on the display interface of the display comprises:

   The schematic diagram of the liver is displayed on the display interface of the display, the quantitative value is identified by the quantitative index of the schematic diagram of the liver, and the credibility value is identified on the schematic diagram of the liver.
4. The ultrasonic imaging device according to claim 2 or 3, wherein the quantitative index includes the quantitative value, and further includes at least one of a size, a filling area, and the number of filled tiles.
5. The ultrasonic imaging device according to claim 2, wherein the qualitative index includes at least one of line color, filling color, filling pattern, filling block size, filling block number, text, letters, and numbers.
6. The ultrasonic imaging device according to claim 1, wherein the processor visually displaying the quantitative value and the credibility through the marked schematic diagram of the liver on the display interface of the display comprises:

   The schematic diagram of the liver is displayed on the display interface of the display, the quantitative value is identified by the fill area of the schematic liver, and the credibility is identified by the fill color of the schematic liver.
7. An ultrasonic imaging equipment, characterized in that it comprises:

   An ultrasonic probe for transmitting ultrasonic waves to a target area and receiving echoes of the ultrasonic waves to obtain electrical signals of the echoes;

   The transmitting/receiving control circuit is used to control the ultrasonic probe to transmit ultrasonic waves to the target area and receive echoes of the ultrasonic waves;

   Display, used to output visual information;

   Processor for:

   Obtain an ultrasonic echo signal according to the electrical signal, analyze the ultrasonic echo signal to obtain a quantitative value reflecting the severity of liver attribute analysis and the credibility of the quantitative value; and

   The quantitative value and the credibility are displayed on the display interface of the display.
8. 8. The ultrasonic imaging device of claim 7, wherein the processor displaying the quantitative value and the credibility on a display interface of a display comprises:

   Simultaneously display the quantitative value and the credibility on the display interface of the display; or,

   The quantitative value is displayed on the display interface of the display, and the quantitative value and the credibility are displayed simultaneously after receiving the preset instruction input by the user.
9. 8. The ultrasonic imaging device of claim 7, wherein the processor displaying the quantitative value and the credibility on a display interface of a display comprises:

   The quantitative value and the credibility are displayed graphically on the display interface of the display.
10. 8. The ultrasonic imaging device of claim 7, wherein the processor displaying the quantitative value and the credibility on a display interface of a display comprises:

    Taking the quantitative value as one dimension and the credibility as another dimension, it is visually displayed on the display interface of the display.
11. The ultrasound imaging device of claim 10, wherein the processor uses the quantitative value as one dimension and the reliability as another dimension, and performing visual display on the display interface of the display comprises:

    Displaying a first graphic on the display interface of the display, using a quantitative indicator of the first graphic to identify the quantitative value, and using a qualitative indicator of the first graphic to identify the credibility;

    Or, displaying a first graphic on the display interface of the display, marking the quantitative value with a quantitative index of the first graphic, and marking the credibility value on the first graphic.
12. The ultrasound imaging device according to claim 11, wherein the quantitative index includes the quantitative value, and further includes at least one of a size, a filling area, and the number of filled tiles, and the qualitative index includes line color, At least one of filling color, filling pattern, filling block size, number of filling blocks, text, letters, and numbers.
13. The ultrasound imaging device of claim 11, wherein the first figure is a schematic diagram of a liver.
14. The ultrasound imaging device of claim 10, wherein the processor uses the quantitative value as one dimension and the reliability as another dimension, and performing visual display on the display interface of the display comprises:

    A chart for displaying the quantitative value and reliability is displayed on the display interface of the display, the first coordinate axis of the chart is the quantitative value, and the second coordinate axis is the reliability.
15. The ultrasound imaging device according to claim 10, wherein the processor uses the quantitative value as one dimension and the reliability as another dimension, and performing visual display on the display interface of the display comprises:

    A first graph and a first coordinate axis are displayed on the display interface of the display, the qualitative index of the first graph identifies the credibility, and the position of the first graph corresponding to the first coordinate axis identifies the quantitative value.
16. 8. The ultrasound imaging device of claim 7, wherein the liver attribute analysis includes fatty liver or liver fibrosis.
17. The ultrasound imaging device according to claim 1 or 16, wherein the processor analyzes the ultrasound echo signal to obtain a quantitative value of the severity of liver fatty liver or liver fibrosis and a quantitative value of the quantitative value. Credibility includes:

    Automatically analyze the ultrasound echo signal by a machine learning method to obtain a classification result of the severity of fatty liver or liver fibrosis and the probability of the classification result;

    According to the classification result and its probability, quantitatively calculate the severity of fatty liver or liver fibrosis to obtain a quantitative value reflecting the severity of fatty liver or liver fibrosis;

    The reliability of the quantitative value is calculated according to the probability of the classification result.
18. The ultrasound imaging device according to claim 1 or 16, wherein the ultrasound echo signal is an ultrasound image; the processor processes the ultrasound echo signal to obtain the severity of fatty liver or liver fibrosis The quantitative value of and the credibility of the quantitative value include:

    The ultrasound image is automatically analyzed to obtain a quantitative value reflecting the severity of fatty liver or liver fibrosis, and the credibility of the quantitative value is obtained according to the image quality of the ultrasound image.
19. 8. The ultrasound imaging device according to claim 1 or 7, wherein the processor displays the quantitative value and the credibility on the display interface of the display, and at the same time also displays the ultrasound image of the liver.
20. The ultrasound imaging device according to claim 17, wherein the classification result includes a plurality of classifications, each of which corresponds to a probability; and the processor determines the fatty liver or liver fiber according to the classification result and its probability. The severity of liver fibrosis is quantitatively calculated, and the quantitative values that reflect the severity of fatty liver or liver fibrosis include:

    The probability is used as a weight, and at least two classifications are weighted and calculated to obtain a quantitative value reflecting the severity of fatty liver or liver fibrosis.
21. The ultrasound imaging device of claim 17, wherein the processor calculating the credibility of the quantitative value according to the probability of the classification result comprises:

    According to the magnitude of each probability, at least the first two numerical probabilities are added together to obtain the reliability value;

    Or, according to the magnitude of each probability, at least the first two numerical probabilities are statistically analyzed, and the relationship between the analysis result and the preset multiple credibility intervals is judged, and the corresponding preset credibility interval is corresponding to the reliability interval. Reliability, as the credibility of the quantitative value.
22. The ultrasonic imaging device according to claim 17, wherein the processor is further configured to perform signal processing on the electrical signal to obtain the ultrasonic echo signal, and the signal processing includes one or more of the following : Gain compensation, analog-to-digital conversion, beam synthesis, quadrature demodulation, baseband signal strength calculation and gray-scale logarithmic compression.
23. A processing method for ultrasonic echo signals, which is characterized in that it includes:

    Obtain the ultrasound echo signal of the liver;

    Analyze the ultrasonic echo signal, identify the image sign of interest contained therein, and obtain a quantitative value reflecting the degree of interest of the image sign of interest and the credibility of the quantitative value; and

    Taking the quantitative value as one dimension and the credibility as another dimension, the degree of interest in the image of interest is displayed in association on the display interface.
24. 22. The method of claim 23, wherein using the quantitative value as one dimension and the credibility as another dimension, and performing an associated display on a display comprises:

    Displaying a first graphic on the display interface of the display, using a quantitative indicator of the first graphic to identify the quantitative value, and using a qualitative indicator of the first graphic to identify the credibility;

    Or the first graph is displayed on the display interface of the display, the quantitative value is identified by the quantitative index of the first graph, and the credibility value is displayed on the first graph.
25. The method according to claim 24, wherein the quantitative index comprises the quantitative value, and further comprises at least one of size, filling area, and number of filling tiles;

    And/or, the qualitative index includes at least one of line color, filling color, filling pattern, filling block size, number of filling blocks, text, letters, and numbers.
26. The method of claim 24, wherein the first graphic is a schematic diagram of a liver.
27. 22. The method of claim 23, wherein using the quantitative value as one dimension and the credibility as another dimension, and performing an associated display on a display interface comprises:

    A graph for displaying the quantitative value and the credibility is displayed on the display interface, the first coordinate axis of the graph is the quantitative value, and the second coordinate axis is the credibility.
28. 22. The method of claim 23, wherein using the quantitative value as one dimension and the credibility as another dimension, and performing an associated display on a display interface comprises:

    A first graph and a first coordinate axis are displayed on the display interface of the display, the qualitative index of the first graph identifies the credibility, and the position of the first graph corresponding to the first coordinate axis identifies the quantitative value.
29. The method of claim 23, wherein identifying the image feature of interest contained therein, and obtaining a quantitative value reflecting the degree of interest of the image feature of interest and the credibility of the quantitative value comprises:

    Classify the recognized image signs of interest by a machine learning method, and obtain a classification result of the degree of interest of the image signs of interest and the probability of the classification result;

    According to the classification result and its probability, quantitatively calculate the degree of interest of the image sign of interest to obtain a quantitative value reflecting the degree of interest of the image sign of interest; calculate the quantitative value according to the probability of the classification result Credibility.
30. The method according to claim 23, wherein the ultrasound echo signal is an ultrasound image; the image sign of interest contained therein is identified, and the quantitative value reflecting the degree of interest of the image sign of interest and the The credibility of quantitative values includes:

    The ultrasound image is processed to obtain a quantitative value reflecting the degree of interest of the image feature of interest, and the credibility of the quantitative value is obtained according to the image quality of the ultrasound image.
31. The method of claim 29, wherein calculating the credibility of the quantitative value according to the probability of the classification result comprises:

    According to the magnitude of each probability, at least the first two numerical probabilities are added together to obtain the reliability value;

    Or, according to the magnitude of each probability, at least the first two numerical probabilities are statistically analyzed, and the relationship between the analysis result and the preset multiple credibility intervals is judged, and the corresponding preset credibility interval is corresponding to the reliability interval. Reliability, as the credibility of the quantitative value.

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