Ultrasonic c-scan microscopic imaging method and system based on noise fluctuation optimization

Abstract

The application relates to an ultrasonic C-scan microscopic imaging method and system based on noise fluctuation optimization. The method comprises the following steps: acquiring ultrasonic echo information of an object, performing signal filtering processing on each ultrasonic echo signal of the object, and generating corresponding filtered echo signals of the object; extracting object imaging layer gate features corresponding to each filtered echo signal of the object; performing feature processing on the object imaging layer gate features by using a constructed parameterized logistic regression function; generating at least object imaging layer normalized values after the feature processing; generating pixel gray values corresponding to the current filtered echo signal of the object based on the object imaging layer normalized values; and generating an ultrasonic C-scan image corresponding to the object to be detected based on pixel gray values of all filtered echo signals of the object. The application optimizes the influence of noise fluctuation on ultrasonic imaging, and improves the signal-to-noise ratio and resolution of ultrasonic C-scan imaging.

Description

Technical Field

[0001] This invention relates to an ultrasonic C-scan microscopy method and system, and more particularly to an ultrasonic C-scan microscopy method and system optimized for noise fluctuations. Background Technology

[0002] Ultrasonic microscopy, as a non-destructive testing method, has been widely used in materials science, biomedicine, and other fields. C-scan imaging technology can achieve two-dimensional or three-dimensional imaging of the internal structure of a sample by acquiring ultrasonic echo signals at different depths within the sample. However, in practical applications, ultrasonic echo signals are susceptible to noise interference, especially under high-frequency probes and high sampling rate conditions, where noise fluctuations can significantly reduce image quality and resolution.

[0003] Traditional C-scan imaging typically employs fixed filtering parameters and simple normalization, making it difficult to adapt to variations in probe frequency and sampling rate, and its effectiveness in suppressing noise fluctuations is limited. Furthermore, existing methods often ignore the impact of noise fluctuations on peak-to-peak values ​​when processing signals within a threshold, leading to inaccurate grayscale calculations and further affecting image quality. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and provide an ultrasound C-scan microscopy imaging method and system based on noise fluctuation optimization, which optimizes the influence of noise fluctuation on ultrasound imaging and improves the signal-to-noise ratio and resolution of ultrasound C-scan imaging.

[0005] According to the technical solution provided by the present invention, an ultrasound C-scan microscopy method based on noise fluctuation optimization is provided, the ultrasound C-scan microscopy method comprising: Provides an object to be inspected and an ultrasonic probe unit adapted to the object to be inspected. The ultrasonic probe unit is used to perform ultrasonic C-scan on the object to be inspected, and ultrasonic echo information of the object is generated after the ultrasonic C-scan. The ultrasonic echo information of the object includes several ultrasonic echo signals of the object. The ultrasonic echo signal of each object is processed by signal filtering to at least filter out the high-frequency noise in the ultrasonic echo signal of each object and generate the corresponding filtered echo signal of the object. The filtering parameters used in the signal filtering process are at least based on the ultrasonic scanning state settings of the ultrasonic probe unit for ultrasonic scanning of the object under test. For each object's filtered echo signal, the corresponding object imaging layer gate feature is extracted. The constructed parameterized logistic regression function is then used to perform feature processing on the object imaging layer gate feature, generating at least a normalized value for the object imaging layer. Based on this normalized value, a pixel grayscale value corresponding to the current object's filtered echo signal is generated. The parameterized logistic regression function is generated based on at least the characteristics of the reference ultrasonic echo signal of the reference object, which is an object of the same type as the object to be inspected and without defects. Based on the pixel grayscale values ​​of the filtered echo signals of all objects, an ultrasonic C-scan image corresponding to the object to be inspected is generated.

[0006] During signal filtering, a second-order Butterworth low-pass filter is used to filter the ultrasonic echo signal of the object. The filtering parameters of the second-order Butterworth low-pass filter include at least the cutoff frequency, wherein the cutoff frequency is formed based on the ultrasonic scanning state settings of the ultrasonic probe unit when performing ultrasonic scanning on the object under test. The ultrasonic scanning status of the object includes at least the signal frequency of the ultrasonic detection signal and the sampling frequency of the ultrasonic echo signal generated from the sampled object. The ultrasonic detection signal is the ultrasonic signal emitted vertically by the ultrasonic probe unit towards the object to be inspected.

[0007] For the cutoff frequency domain of a second-order Butterworth low-pass filter, we have:

[0008] in, The cutoff frequency, The signal frequency of the ultrasonic detection signal. The sampling frequency is used to sample and generate the ultrasonic echo signal of the object.

[0009] For the constructed parameterized logistic regression function, we have:

[0010] in, For parametric logistic regression function, Features of the object imaging layer gate. The central baseline value for logistic regression, The slope of the logistic regression center; When constructing the parametric logistic regression function, the central baseline value of the logistic regression is set based on the characteristics of the reference ultrasonic echo signal of the reference object. and / or logistic regression center slope .

[0011] Based on the characteristics of the reference ultrasonic echo signal of the reference object, a logistic regression center base value is set. and logistic regression center slope Then:

[0012] in, The maximum peak-to-peak value in the echo-free region within the baseline ultrasonic echo signal. The peak-to-peak value of the reference surface segment echo signal within the reference ultrasonic echo signal. The peak-to-peak value of the reference imaging layer echo within the reference ultrasound echo signal; The reference ultrasonic echo signal is the ultrasonic echo signal generated by performing an ultrasonic A-scan on a reference object using an ultrasonic probe unit.

[0013] Extract the peak-to-peak value of the echo from the reference ultrasound layer for the reference ultrasound echo signal. Then: Identify the reference surface segment echo signal of the reference ultrasonic echo signal, and extract the surface wave reference position corresponding to the positive peak value in the reference surface segment echo signal; Based on the surface wave reference location and pre-determined surface-imaging echo parameters, the reference imaging segment echo signal is extracted from the reference ultrasonic echo signal. The surface-imaging echo parameters are determined and generated based at least on the relative positional state between the reference imaging layer within the reference object and the surface of the reference object. Based on the extracted echo signal of the reference imaging layer, the peak-to-peak value of the echo of the reference imaging layer is calculated.

[0014] For the maximum peak-to-peak value of the echo-free region within the reference ultrasonic echo signal, we have: For a reference ultrasonic echo signal, a reference echo sliding window and an echo-free identification threshold are constructed, wherein the echo-free identification threshold is set at least based on the peak-to-peak value of the reference surface segment echo signal; Following the sampling sequence of the reference ultrasonic echo signal, the reference echo sliding window is slid across the reference ultrasonic echo signal, and the peak-to-peak value of the corresponding sliding window ultrasonic echo signal within each reference echo sliding window is calculated. When the peak-to-peak value of the sliding window area is not greater than the no-echo recognition threshold, the current sliding window ultrasonic echo signal is identified as a no-echo region. Calculate the peak-to-peak value of each anechoic region, and take the maximum value among all calculated peak-to-peak values ​​of anechoic regions as the maximum peak-to-peak value of the anechoic region.

[0015] Regarding the gate features of the object's imaging layer, we have:

[0016] in, This represents the peak-to-peak value of the object imaging layer echo signal within the object's filtered echo signal. This represents the peak-to-peak value of the echo signal from the object's surface after filtering.

[0017] After generating the normalized value of the object imaging layer, multiply the normalized value of the object imaging layer by 255, and use the result of the product as the pixel gray value corresponding to the object's filtered echo signal.

[0018] An ultrasound C-scan microscopy system optimized for noise fluctuations includes an ultrasound probe unit and an imaging processing unit, wherein... For any object to be inspected, an ultrasonic probe unit is used to perform an ultrasonic C-scan on the object to generate ultrasonic echo information of the object after the ultrasonic C-scan. The imaging processing unit processes the generated ultrasonic echo signal of the object using the imaging method described above, and generates a corresponding ultrasonic C-scan image.

[0019] Advantages of this invention: Signal filtering processing is performed on the ultrasonic echo signal of the object to generate the corresponding filtered echo signal of the object after filtering out high-frequency noise in the ultrasonic echo signal of each object, so as to optimize the influence of noise fluctuation on ultrasonic imaging. The gate features of the object imaging layer are extracted from the echo signal after the object is filtered. Then, the gate features of the object imaging layer are processed using a parametric logistic regression function to obtain the normalized value of the object imaging layer. The logistic regression normalization process of the parametric logistic regression function can significantly improve the contrast and resolution of the generated ultrasound C-scan image, which is convenient for subsequent analysis and defect identification. Attached Figure Description

[0020] Figure 1 This is a flowchart of one embodiment of the ultrasonic C-scan microscopy imaging of the present invention.

[0021] Figure 2 This is a schematic diagram of an embodiment of the present invention for extracting the echo band signal of the imaging layer.

[0022] Figure 3 This is a schematic diagram of an embodiment of the echo-free region within the reference ultrasonic echo signal of the present invention.

[0023] Figure 4 This is a schematic diagram of an embodiment of the ultrasound C-scan image of the present invention. Detailed Implementation

[0024] The present invention will be further described below with reference to specific accompanying drawings and embodiments.

[0025] To optimize the impact of noise fluctuations on ultrasound imaging and improve the signal-to-noise ratio and resolution of ultrasound C-scan imaging, this invention provides an ultrasound C-scan microscopy method based on noise fluctuation optimization. The ultrasound C-scan microscopy method includes: Provides an object to be inspected and an ultrasonic probe unit adapted to the object to be inspected. The ultrasonic probe unit is used to perform ultrasonic C-scan on the object to be inspected, and ultrasonic echo information of the object is generated after the ultrasonic C-scan. The ultrasonic echo information of the object includes several ultrasonic echo signals of the object. The ultrasonic echo signal of each object is processed by signal filtering to at least filter out the high-frequency noise in the ultrasonic echo signal of each object and generate the corresponding filtered echo signal of the object. The filtering parameters used in the signal filtering process are at least based on the ultrasonic scanning state settings of the ultrasonic probe unit for ultrasonic scanning of the object under test. For each object's filtered echo signal, the corresponding object imaging layer gate feature is extracted. The constructed parameterized logistic regression function is then used to perform feature processing on the object imaging layer gate feature, generating at least a normalized value for the object imaging layer. Based on this normalized value, a pixel grayscale value corresponding to the current object's filtered echo signal is generated. The parameterized logistic regression function is generated based on at least the characteristics of the reference ultrasonic echo signal of the reference object, which is an object of the same type as the object to be inspected and without defects. Based on the pixel grayscale values ​​of the filtered echo signals of all objects, an ultrasonic C-scan image corresponding to the object to be inspected is generated.

[0026] Understandably, for ultrasound C-scan microscopy, both the object to be examined and an ultrasound probe unit are required. The object to be examined is the one to be detected using ultrasound scanning. The type of object can be selected as needed to meet the requirements of ultrasound scanning. The ultrasound probe unit can adopt commonly used forms and generally includes an ultrasound probe and an ultrasound echo acquisition device for acquiring ultrasound echo signals. The ultrasound probe unit should be compatible with the object to be examined. Specifically, compatibility means that the ultrasound probe unit can effectively perform ultrasound scanning on the object to be examined. Therefore, after determining the object to be examined, the corresponding ultrasound probe unit can be selected according to the requirements of ultrasound imaging.

[0027] After selecting a suitable ultrasonic probe unit, the object to be inspected can be subjected to ultrasonic C-scan using methods commonly used in this technical field to obtain ultrasonic echo information of the object after ultrasonic C-scan. Specifically, the ultrasonic echo information of the object includes several ultrasonic echo signals of the object. The situation of the ultrasonic echo signals of the object in the ultrasonic echo information is related to the selected ultrasonic C-scan parameters. The ultrasonic C-scan parameters may include scanning accuracy and scanning step size, etc. The situation of the ultrasonic C-scan parameters can be selected as needed to meet the requirements of ultrasonic C-scan of the object to be inspected.

[0028] It should be understood that ultrasonic images can be generated from the ultrasonic echo information of an object. Analyzing these generated ultrasonic images allows for defect analysis and inspection of the object under inspection. To improve the quality of ultrasonic imaging and thus enhance the accuracy and reliability of ultrasonic testing of the object, noise fluctuation optimization should be performed on the generated ultrasonic echo signal. Figure 1 The figure illustrates an embodiment of noise fluctuation optimization for ultrasonic echo signals of objects. As can be seen from the figure, when performing noise fluctuation optimization, signal filtering should be performed at least to filter out high-frequency noise in the ultrasonic echo signals of each object.

[0029] Specifically, during signal filtering, each ultrasonic echo signal from the object within the object's ultrasonic echo information should be filtered, and a corresponding filtered echo signal should be generated after the signal filtering process. It is understood that the filtered echo signal should contain no high-frequency noise, or only a small amount of unfiltered high-frequency noise. In other words, signal filtering effectively reduces the impact of high-frequency noise on the ultrasonic echo signal, thus improving the accuracy of subsequent ultrasonic imaging.

[0030] In order to effectively suppress high-frequency noise, in one embodiment of the present invention, the filtering parameters used are formed based at least on the ultrasonic scanning state settings of the ultrasonic probe unit for ultrasonic scanning of the object under test. The signal filtering processing method is described in detail below.

[0031] In one embodiment of the present invention, when performing signal filtering processing, a second-order Butterworth low-pass filter is used to filter the ultrasonic echo signal of the object, wherein... The filtering parameters of the second-order Butterworth low-pass filter include at least the cutoff frequency, wherein the cutoff frequency is formed based on the ultrasonic scanning state settings of the ultrasonic probe unit when performing ultrasonic scanning on the object under test. The ultrasonic scanning status of the object includes at least the signal frequency of the ultrasonic detection signal and the sampling frequency of the ultrasonic echo signal generated from the sampled object. The ultrasonic detection signal is the ultrasonic signal emitted vertically by the ultrasonic probe unit towards the object to be inspected.

[0032] It should be understood that when a second-order Butterworth low-pass filter is used to filter the ultrasonic echo signal of each object, high-frequency noise can be effectively suppressed according to the characteristics of low-pass filtering. To improve the reliability of high-frequency noise suppression and adapt to the signal frequencies and sampling frequencies of different ultrasonic probe units, the cutoff frequency of the second-order Butterworth low-pass filter of this invention can be set based on the ultrasonic scanning state of the object. Specifically, the ultrasonic scanning state of the object can include at least the signal frequency of the ultrasonic detection signal and the sampling frequency. The signal frequency of the ultrasonic detection signal specifically refers to the pulse width of the ultrasonic detection signal, and the sampling frequency specifically refers to the frequency at which the ultrasonic echo acquisition device samples the echo and generates the ultrasonic echo signal of the object.

[0033] It should be noted that when performing ultrasonic C-scan on the object under inspection, the working state of the ultrasonic probe can be set to ensure that the ultrasonic probe emits ultrasonic detection signals perpendicularly to the object under inspection, and the signal frequency corresponding to the ultrasonic detection signal can be set. Therefore, the signal frequency of the ultrasonic detection signal can be obtained by setting the working state of the ultrasonic probe. In addition, the working state of the ultrasonic echo acquisition device can also be set. The working state of the ultrasonic echo acquisition device can include at least the sampling frequency. When the sampling frequency is high, the ultrasonic echo signal of each object includes more sampling points. The sampling frequency is related to the ultrasonic echo acquisition device. Therefore, the sampling frequency can be obtained based on the working state of the ultrasonic echo acquisition device.

[0034] In one embodiment of the present invention, the cutoff frequency domain of the second-order Butterworth low-pass filter is as follows:

[0035] in, The cutoff frequency, The signal frequency of the ultrasonic detection signal. The sampling frequency is used to sample and generate the ultrasonic echo signal of the object.

[0036] Specifically, after determining the cutoff frequency of the second-order Butterworth low-pass filter using the above method, the quality factor Q of the second-order Butterworth low-pass filter should generally also be set. The value of the quality factor Q can be selected as needed, such as setting it to 0.707. It is understood that after setting the cutoff frequency and quality factor Q of the second-order Butterworth low-pass filter, it can be used to perform low-pass filtering on the ultrasonic echo signal of the object. The specific low-pass method and process are consistent with existing technology and will not be elaborated here.

[0037] Depend on Figure 1It is known that after signal filtering of the ultrasonic echo signal of each object, the filtered echo signal of the object can be generated. In order to generate an ultrasonic image, the filtered echo signal of the object should also be subjected to feature processing, which includes at least logistic regression normalization processing.

[0038] In practical implementation, this invention performs feature processing on the filtered echo signal of each object by pre-constructing a parameterized logistic regression function. When the feature processing is logistic regression normalization, a normalized value for the object imaging layer can be generated. The object imaging layer is the target scanning detection layer within the object to be inspected. Therefore, when performing ultrasonic C-scan inspection on the object to be inspected, the main focus is on detecting whether there are defects in the object imaging layer. The object imaging layer can generally be a cross-sectional layer within the object to be inspected.

[0039] In constructing the parametric logistic regression function, this invention utilizes the reference ultrasonic echo signal characteristics of a reference object. The reference object and the object under test belong to the same category of objects, and the reference object is determined to be defect-free through the means of this technical field. This means the corresponding reference imaging layer within the reference object should be defect-free. It can be understood that the reference imaging layer within the reference object and the object imaging layer of the object under test are in a positive correspondence, i.e., they belong to the same type of cross-sectional layer of material. Therefore, after determining the object imaging layer of the object under test, the reference imaging layer of the reference object can be determined. Since the reference object and the object under test belong to the same type of material, and the reference imaging layer of the reference object is defect-free, constructing the parametric logistic regression function using the reference ultrasonic echo signal characteristics of the reference object and performing feature processing using the parametric logistic regression function can achieve adaptive noise suppression and enhanced anti-interference capabilities.

[0040] Specifically, the reference ultrasonic echo signal is the ultrasonic echo signal generated by performing an ultrasonic A-scan on a reference object using an ultrasonic probe unit. Therefore, the characteristics of the reference ultrasonic echo signal of the reference object specifically refer to the characteristics of the reference ultrasonic echo signal generated by performing an ultrasonic A-scan on the reference object using the aforementioned ultrasonic probe unit. The scanning conditions for performing an ultrasonic A-scan on the reference object should be consistent with the scanning conditions for performing an ultrasonic C-scan on the object under test, so that the reference ultrasonic echo signal and the object's ultrasonic echo signal have good signal consistency. The scanning conditions include at least the aforementioned signal frequency and sampling frequency. In addition, the scanning conditions should also include necessary conditions such as scanning height. Specific scanning conditions will not be listed and explained one by one here.

[0041] The characteristics of the reference ultrasonic echo signal, and the gate characteristics of the object imaging layer in the echo signal after object filtering, will be explained in detail below.

[0042] In one embodiment of the present invention, the constructed parameterized logistic regression function has the following:

[0043] in, For parametric logistic regression function, Features of the object imaging layer gate. The central baseline value for logistic regression, The slope of the logistic regression center; When constructing the parametric logistic regression function, the central baseline value of the logistic regression is set based on the characteristics of the reference ultrasonic echo signal of the reference object. and / or logistic regression center slope .

[0044] Specifically, as can be seen from the expression of the parametric logistic regression function above, once the gate features of the object imaging layer are extracted, the parametric logistic regression function can be calculated. The value of , therefore, the parameterized logistic regression function The value is the normalized value of the object's imaging layer.

[0045] Furthermore, when constructing a parameterized logistic regression function based on the reference ultrasonic echo signal characteristics of the reference object, specifically, it refers to setting the central baseline value of the logistic regression based on the reference ultrasonic echo signal characteristics of the reference object. and / or logistic regression center slope .

[0046] In one embodiment of the present invention, a logistic regression center baseline value is set based on the reference ultrasonic echo signal characteristics of the reference object. and logistic regression center slope Then:

[0047] in, The maximum peak-to-peak value in the echo-free region within the baseline ultrasonic echo signal. The peak-to-peak value of the reference surface segment echo signal within the reference ultrasonic echo signal. The peak value of the reference imaging layer echo within the reference ultrasound echo signal.

[0048] As explained above, the logistic regression center baseline value is set based on the characteristics of the reference ultrasonic echo signal of the reference object. and logistic regression center slope At this time, it is necessary to determine the maximum peak-to-peak value of the echo-free region within the reference ultrasonic echo signal. Peak-to-peak value of the reference surface segment echo signal within the reference ultrasonic echo signal and the peak-to-peak value of the reference imaging layer echo within the reference ultrasound echo signal. In other words, the characteristics of the reference ultrasound echo signal should at least include the maximum peak-to-peak value of the unecho region within the reference ultrasound echo signal. Peak-to-peak value of echo signal on reference surface section and the peak-to-peak value of the reference imaging layer echo .

[0049] Understandably, the central baseline value of logistic regression Characterizing the echo-free region in the reference ultrasonic echo signal, and the corresponding state of the echo signals between the reference imaging layer and the reference surface segment, therefore, the imaging layer gate feature... Approaching the central base value of logistic regression If the object's imaging layer is close to the reference imaging layer, then it can be considered that the imaging layer's gate feature is similar to the reference imaging layer. Deviation from logistic regression center base value If this is the case, it can be considered that the object's imaging layer deviates significantly from the reference imaging layer. Therefore, it can be concluded that using the aforementioned logistic regression center baseline... and logistic regression center slope This can improve the gate features of the imaging layer. The maximum peak-to-peak value in the echo-free region and the peak-to-peak value of the echo in the reference imaging layer. This improves the sensitivity between the two layers, thereby enhancing the similarity between the object imaging layer and the reference imaging layer, reducing sensitivity to noise, and improving the quality of the subsequently generated ultrasound C-scan images.

[0050] It should be noted that the reference ultrasonic echo signal can be generated by performing an ultrasonic A-scan on the reference object using an ultrasonic probe unit. The area / location of the ultrasonic A-scan should be able to characterize the features of the reference imaging layer of the reference material. For example, the area / location of the ultrasonic A-scan can be the central region or a smooth region of the reference material, which can be determined according to the corresponding characteristics of the object under test and the reference object. The following is a detailed explanation of the method and process for extracting the reference ultrasonic echo signal features of the reference object.

[0051] In one embodiment of the present invention, when extracting the peak-to-peak value of the reference imaging layer echo from the reference ultrasound echo signal, the following is obtained: Identify the reference surface segment echo signal of the reference ultrasonic echo signal, and extract the surface wave reference position corresponding to the positive peak value in the reference surface segment echo signal; Based on the surface wave reference location and pre-determined surface-imaging echo parameters, the reference imaging segment echo signal is extracted from the reference ultrasonic echo signal. The surface-imaging echo parameters are determined and generated based at least on the relative positional state between the reference imaging layer within the reference object and the surface of the reference object. Based on the extracted echo signal of the reference imaging layer, the peak-to-peak value of the reference imaging layer echo is calculated.

[0052] As explained above, the reference imaging layer is generally the interior of the reference object. The reference ultrasonic echo signal can characterize the reflection state of the ultrasonic detection signal on the surface of the reference object, the reference imaging layer, or other structural layers. Therefore, the reference ultrasonic echo signal should include the echo signal of the reference surface segment and the echo signal of the reference imaging layer segment. Figure 2 An embodiment of a reference ultrasonic echo signal is shown in the figure. Figure 2 In the graph, the horizontal axis represents the sampling time, and the vertical axis represents the amplitude of the ultrasound echo. It should be understood that... Figure 2 The reference ultrasonic echo signal in the image is the truncated reference ultrasonic echo signal, which can clearly express the corresponding state of the reference surface segment echo signal and the reference imaging layer segment echo signal.

[0053] It is understandable that the reference surface segment echo signal is generally the first pulse echo within the reference ultrasonic echo signal, and generally speaking, the amplitude of the reference surface segment echo signal is the largest. Therefore, the reference surface segment echo signal within the reference ultrasonic echo signal can be identified based on the signal amplitude. Figure 2 The echo signal in the first segment on the left is the reference surface segment echo signal. After determining the reference surface segment echo signal, the peak-to-peak value of the corresponding reference surface segment echo signal can be calculated. The peak-to-peak value (Peak-to-Peak) of the reference surface segment echo signal is the difference between the positive and negative peak values ​​of the reference surface segment echo signal. Furthermore, when calculating the peak-to-peak value of the reference surface segment echo signal, the surface wave reference position corresponding to the positive peak value within the reference surface segment echo signal can also be determined. The surface wave reference position corresponding to the positive peak value should generally be the corresponding sampling time within the reference ultrasonic echo signal.

[0054] After obtaining the surface wave reference position, the reference imaging layer echo signal can be extracted from the reference ultrasonic echo signal based on pre-determined surface-imaging echo parameters. The reference imaging layer echo signal is the echo signal formed by the reflection of the ultrasonic detection signal by the reference imaging layer. Specifically, the surface-imaging echo parameters are determined at least based on the relative position between the reference imaging layer within the reference object and the surface of the reference object. The relative position may include the relative distance between the reference imaging layer and the surface of the reference object. Based on the relative position, the delay time of the reference imaging layer echo signal relative to the reference surface segment echo signal can generally be determined. Based on the determined delay time, the reference imaging layer echo signal can be extracted. Figure 2 The area marked with the data gate is the echo signal of the reference imaging segment.

[0055] It is understandable that after extracting the echo signal of the reference imaging layer, the peak-to-peak value of the reference imaging layer echo can be calculated using the above method. For the specific calculation method and process, please refer to the corresponding instructions above, which will not be repeated here.

[0056] In one embodiment of the present invention, the maximum peak-to-peak value of the echo-free region within the reference ultrasonic echo signal is: For a reference ultrasonic echo signal, a reference echo sliding window and an echo-free identification threshold are constructed, wherein the echo-free identification threshold is set at least based on the peak-to-peak value of the reference surface segment echo signal; Following the sampling sequence of the reference ultrasonic echo signal, the reference echo sliding window is slid across the reference ultrasonic echo signal, and the peak-to-peak value of the corresponding sliding window ultrasonic echo signal within each reference echo sliding window is calculated. When the peak-to-peak value of the sliding window area is not greater than the no-echo recognition threshold, the current sliding window ultrasonic echo signal is identified as a no-echo region. Calculate the peak-to-peak value of each anechoic region, and take the maximum value among all calculated peak-to-peak values ​​of anechoic regions as the maximum peak-to-peak value of the anechoic region.

[0057] Understandably, when counting the number of echo-free peak-to-peak values ​​within a reference ultrasound echo signal, the number of echo-free regions within the reference ultrasound echo signal should be counted first. Figure 3 The diagram illustrates one embodiment of an echo-free region within a reference ultrasonic echo signal. To statistically determine the echo-free region within the reference ultrasonic echo signal, a reference echo sliding window and an echo-free identification threshold should be set. The echo-free identification threshold can be set based on the peak-to-peak value of the echo signal from the reference surface segment; for example, the echo-free identification threshold could be 0.1* Of course, the no-echo recognition threshold can also be set to other conditions, depending on whether it can effectively identify no-echo areas.

[0058] A reference echo sliding window is used to slide along the reference ultrasonic echo signal. The sliding direction generally follows the sampling sequence that generated the reference ultrasonic echo signal. It can be understood that the sampling sequence corresponds to the sampling time; for example, the sampling sequence should be... Figure 2 and Figure 3 The order is from left to right. When the reference echo sliding window slides on the reference ultrasonic echo signal, there can be a sampling interval between two adjacent reference echo sliding windows. After determining the position of the reference echo sliding window, the sliding window ultrasonic echo signal corresponding to the reference echo sliding window can be obtained. Then, the peak-to-peak value of the sliding window ultrasonic echo signal can be calculated.

[0059] In practical implementation, the ultrasonic reflection characteristics of the reference object are used to configure the window size of the reference echo sliding window. Based on the configured window size (time length), the window size of the reference echo sliding window can be the signal frequency of the ultrasonic detection signal. The corresponding period is twice the value of the time frame. When the calculated peak-to-peak value of the sliding window region is not greater than the no-echo recognition threshold, the current sliding window ultrasonic echo signal is identified as a no-echo region.

[0060] The above sampling method involves sliding a reference echo window across the reference ultrasonic echo signal until it reaches its endpoint. Afterward, the peak-to-peak value of each anechoic region is calculated, and the maximum value of all calculated anechoic regions is designated as the maximum peak-to-peak value for that region. Alternatively, other methods can be used to determine the number of maximum peak-to-peak values ​​for each anechoic region, depending on what meets the maximum peak-to-peak value requirement for that region; these methods will not be elaborated upon here.

[0061] In one embodiment of the present invention, the gate feature of the object imaging layer has the following characteristics:

[0062] in, This represents the peak-to-peak value of the object imaging layer echo signal within the object's filtered echo signal. This represents the peak-to-peak value of the echo signal from the object's surface after filtering.

[0063] Specifically, since the substance to be tested and the reference substance belong to the same type of substance, the methods for obtaining the peak-to-peak value of the reference imaging layer echo and the peak-to-peak value of the object surface echo can be referred to the above-mentioned explanations, and will not be repeated here.

[0064] It should be noted that the peak-to-peak value of the object imaging layer is used. This reflects the magnitude of the reflected energy of the echo at the object's imaging layer within the filtered echo signal. When there are defects or delamination at the object's imaging layer, the reflected energy is smaller compared to when there are no defects or delamination. Since the surface echo has the largest amplitude, and the total energy of the filtered echo signal for each object is fixed, the peak-to-peak value of the object's imaging layer echo is... Divide by the peak-to-peak value of the echo on the object surface When used as a gate feature of the object imaging layer, it can play the role of "relative surface echo energy magnitude", which can realize the normalization of the object imaging layer echo energy relative to the surface wave energy.

[0065] In one embodiment of the present invention, after generating the normalized value of the object imaging layer, the normalized value of the object imaging layer is multiplied by 255, and the result of the product is used as the pixel grayscale value corresponding to the object's filtered echo signal.

[0066] Specifically, after obtaining the above-mentioned gate features of the object imaging layer from the ultrasonic echo signal of the object, the normalized value of the object imaging layer can be calculated using the above-mentioned parametric logistic regression function. The normalized value of the object imaging layer is then multiplied by 255, and the product is the pixel gray value corresponding to the current object's filtered echo signal.

[0067] It is understandable that, using the obtained pixel grayscale values, commonly used techniques in this technical field can be employed to obtain an ultrasonic C-scan image of the object under inspection after ultrasonic C-scanning. Figure 4 An embodiment of an ultrasonic C-scan image of an object to be inspected is shown in the figure.

[0068] From the above description, an ultrasonic C-scan microscopy imaging system based on noise fluctuation optimization can be obtained. In one embodiment of the present invention, it includes an ultrasonic probe unit and an imaging processing unit, wherein... For any object to be inspected, an ultrasonic probe unit is used to perform an ultrasonic C-scan on the object to generate ultrasonic echo information of the object after the ultrasonic C-scan. The imaging processing unit processes the generated ultrasonic echo signal of the object using the imaging method described above, and generates a corresponding ultrasonic C-scan image.

[0069] Specifically, the ultrasonic probe unit can be referred to the above description. The ultrasonic probe unit can be used to acquire ultrasonic echo information of the object. The imaging processing unit can use existing computer terminal equipment. The imaging processing unit should be able to complete the above-mentioned processing of the ultrasonic echo signal of the object, that is, it should be able to perform the above-mentioned signal filtering processing, feature processing and generation of ultrasonic C-scan images. For details, please refer to the above description, which will not be repeated here.

Claims

1. An ultrasound C-scan microscopy method based on noise fluctuation optimization, characterized in that, The ultrasound C-scan microscopy imaging method includes: Provides an object to be inspected and an ultrasonic probe unit adapted to the object to be inspected. The ultrasonic probe unit is used to perform ultrasonic C-scan on the object to be inspected, and ultrasonic echo information of the object is generated after the ultrasonic C-scan. The ultrasonic echo information of the object includes several ultrasonic echo signals of the object. The ultrasonic echo signal of each object is processed by signal filtering to at least filter out the high-frequency noise in the ultrasonic echo signal of each object and generate the corresponding filtered echo signal of the object. The filtering parameters used in the signal filtering process are at least based on the ultrasonic scanning state settings of the ultrasonic probe unit for ultrasonic scanning of the object under test. For each object's filtered echo signal, the corresponding object imaging layer gate feature is extracted. The constructed parameterized logistic regression function is then used to perform feature processing on the object imaging layer gate feature, generating at least a normalized value for the object imaging layer. Based on this normalized value, a pixel grayscale value corresponding to the current object's filtered echo signal is generated. The parameterized logistic regression function is generated based on at least the characteristics of the reference ultrasonic echo signal of the reference object, which is an object of the same type as the object to be inspected and without defects. Based on the pixel grayscale values ​​of the filtered echo signals of all objects, an ultrasonic C-scan image corresponding to the object to be inspected is generated. For the constructed parameterized logistic regression function, we have: in, For parametric logistic regression function, Features of the object imaging layer gate. The central baseline value for logistic regression, The slope of the logistic regression center; When constructing the parametric logistic regression function, the central baseline value of the logistic regression is set based on the characteristics of the reference ultrasonic echo signal of the reference object. and / or logistic regression center slope ; Based on the characteristics of the reference ultrasonic echo signal of the reference object, a logistic regression center base value is set. and logistic regression center slope Then: in, The maximum peak-to-peak value in the echo-free region within the reference ultrasonic echo signal. The peak-to-peak value of the reference surface segment echo signal within the reference ultrasonic echo signal. The peak-to-peak value of the reference imaging layer echo within the reference ultrasound echo signal; The reference ultrasonic echo signal is the ultrasonic echo signal generated by performing an ultrasonic A-scan on the reference object using an ultrasonic probe unit. When extracting the peak-to-peak value of the echo from the reference imaging layer for the reference ultrasound echo signal, we have: Identify the reference surface segment echo signal of the reference ultrasonic echo signal, and extract the surface wave reference position corresponding to the positive peak value in the reference surface segment echo signal; Based on the surface wave reference location and pre-determined surface-imaging echo parameters, the reference imaging segment echo signal is extracted from the reference ultrasonic echo signal. The surface-imaging echo parameters are determined and generated based at least on the relative positional state between the reference imaging layer within the reference object and the surface of the reference object. Based on the extracted echo signal of the reference imaging layer, the peak-to-peak value of the reference imaging layer echo is calculated.

2. The ultrasound C-scan microscopy method based on noise fluctuation optimization according to claim 1, characterized in that: [the method is implemented...] During signal filtering, a second-order Butterworth low-pass filter is used to filter the ultrasonic echo signal of the object. The filtering parameters of the second-order Butterworth low-pass filter include at least the cutoff frequency, wherein the cutoff frequency is formed based on the ultrasonic scanning state settings of the ultrasonic probe unit when performing ultrasonic scanning on the object under test. The ultrasonic scanning status of the object includes at least the signal frequency of the ultrasonic detection signal and the sampling frequency of the sampled ultrasonic echo signal of the object. The ultrasonic detection signal is the ultrasonic signal emitted vertically by the ultrasonic probe unit towards the object to be inspected.

3. The ultrasonic C-scan microscopy method based on noise fluctuation optimization according to claim 2, characterized in that, For the cutoff frequency domain of a second-order Butterworth low-pass filter, we have: in, The cutoff frequency, The signal frequency of the ultrasonic detection signal. The sampling frequency is used to sample and generate the ultrasonic echo signal of the object.

4. The ultrasound C-scan microscopy method based on noise fluctuation optimization according to claim 1, characterized in that, For the maximum peak-to-peak value of the echo-free region within the reference ultrasonic echo signal, we have: For a reference ultrasonic echo signal, a reference echo sliding window and an echo-free identification threshold are constructed, wherein the echo-free identification threshold is set at least based on the peak-to-peak value of the reference surface segment echo signal; Following the sampling sequence of the reference ultrasonic echo signal, the reference echo sliding window is slid across the reference ultrasonic echo signal, and the peak-to-peak value of the corresponding sliding window ultrasonic echo signal within each reference echo sliding window is calculated. When the peak-to-peak value of the sliding window area is not greater than the no-echo recognition threshold, the current sliding window ultrasonic echo signal is identified as a no-echo region. Calculate the peak-to-peak value of each anechoic region, and take the maximum value among all calculated peak-to-peak values ​​of anechoic regions as the maximum peak-to-peak value of the anechoic region.

5. The ultrasonic C-scan microscopy method based on noise fluctuation optimization according to claim 1, characterized in that, Regarding the gate features of the object's imaging layer, we have: in, This represents the peak-to-peak value of the object imaging layer echo signal within the object's filtered echo signal. This represents the peak-to-peak value of the echo signal from the object's surface after filtering.

6. The ultrasound C-scan microscopy method based on noise fluctuation optimization according to any one of claims 1 to 5, characterized in that, After generating the normalized value of the object imaging layer, multiply the normalized value of the object imaging layer by 255, and use the result of the product as the pixel gray value corresponding to the object's filtered echo signal.

7. An ultrasonic C-scan microscopic imaging system based on noise fluctuation optimization, characterized in that, It includes an ultrasound probe unit and an imaging processing unit, wherein, For any object to be inspected, an ultrasonic probe unit is used to perform an ultrasonic C-scan on the object to generate ultrasonic echo information of the object after the ultrasonic C-scan. The imaging processing unit processes the generated ultrasonic echo signal of the object using the imaging method described in any one of claims 1 to 6, and generates a corresponding ultrasonic C-scan image.

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