Ultrasonic transducer sensitivity attenuation compensation method and system based on system optimization

Abstract

The invention relates to the technical field of ultrasonic inspection equipment, in particular to an ultrasonic transducer sensitivity attenuation compensation method and system based on system optimization, and the method comprises the steps: obtaining a first imaging sequence, and carrying out the recognition to obtain a sensitivity reference region; performing feature extraction on the sensitivity reference area, constructing an image quality score, and determining whether the sensitivity needs to be compensated according to the image quality score; searching the second imaging sequence to obtain a calibration part and generating prompt information; and moving the ultrasonic probe to the calibration part according to the prompt information, and then performing closed-loop gain adjustment to calibrate the sensitivity. Aiming at the problem that an ultrasonic calibration scheme in the prior art depends on a specific target and is inconvenient to use, a process for judging whether the image quality of a current ultrasonic image needs to be calibrated in real time is introduced, and a uniform tissue part which can be used for calibration in a real-time scanning process is screened out by combining echo information in the image, so that the calibration accuracy is improved. Calibration is carried out based on the part, and a specific process of target calibration is omitted.

Description

Technical Field

[0001] The present invention relates to the technical field of ultrasonic examination equipment, and particularly relates to a method and system for compensating for the sensitivity attenuation of an ultrasonic transducer based on system optimization. Background Art

[0002] A transducer refers to a device that converts electrical energy and acoustic energy into each other, and plays an important role in ultrasonic examination equipment. It utilizes the piezoelectric effect of materials to achieve the conversion of electrical energy and acoustic energy, so as to transmit and receive ultrasonic waves during the ultrasonic detection process. Medical ultrasonic examination (ultrasonic examination, ultrasonography) is a medical imaging diagnostic technique based on ultrasonic waves (ultrasound), which visualizes muscles and internal organs, including their size, structure, and pathological lesions. Since the transducer realizes the acoustic-electric conversion through piezoelectric materials, usually piezoelectric ceramics, the elastic modulus of the material itself will decay with the increase in the number of vibrations, which will in turn lead to a decrease in the signal transmission gain and the reception gain, affecting the related imaging process.

[0003] To solve this problem, it is usually necessary to calibrate and recalibrate the sensitivity of ultrasonic equipment in the prior art.

[0004] For example, Chinese Patent CN201610680708.5 discloses an ultrasonic calibration method and device. The ultrasonic calibration method includes: when the mobile device meets the calibration conditions, using an ultrasonic transmitter to transmit a first ultrasonic wave with a predetermined frequency according to a predetermined transmission intensity; using an ultrasonic receiver to receive the second ultrasonic wave reflected by the first ultrasonic wave, and obtaining the frequency response value of the second ultrasonic wave; calculating the absolute value of the difference between the frequency response value of the second ultrasonic wave and the standard frequency response value corresponding to the predetermined frequency; when the absolute value is greater than a predetermined difference threshold, increasing the transmission intensity of the ultrasonic wave transmitted by the ultrasonic transmitter. It solves the technical problem that the mobile device cannot automatically calibrate and adapt to the optimal ultrasonic transmission intensity in the current environment, and achieves the technical effect of being able to receive ultrasonic signals with a stable intensity in various environments.

[0005] For another example, Chinese Patent CN201811472207.3 discloses an ultrasonic probe calibration method, which includes obtaining the blind area of the ultrasonic probe at a preset detection depth; placing the ultrasonic probe in a three-dimensional magnetic field and obtaining a first imaging map obtained when the ultrasonic probe scans air and a second imaging map obtained when the acoustic lens of the ultrasonic probe touches the top of a free sensor coated with a coupling agent; respectively selecting a first area and a second area with the longest continuous color difference on the corresponding arc according to the color difference ratio, and calculating the intermediate value coordinates of the first area and the second area; calculating the two-dimensional coordinates of the top of the free sensor in the second imaging map according to the intermediate value coordinates of the first area and the second area and the blind area and converting them into the three-dimensional coordinates to be measured, and establishing a ternary equation system according to the three-dimensional coordinates to be measured and the actual three-dimensional coordinates of the free sensor receiving the magnetic field, and calculating the correction value of the ultrasonic probe in the three-dimensional magnetic field. It can effectively reduce the measurement error and improve the three-dimensional positioning accuracy.

[0006] However, in the actual implementation process, the inventor found that this type of calibration process usually needs to rely on a specific target in the application. For example, ultrasonic signals are emitted through specific markers and the echoes are collected, and calibration is performed according to relevant calibration parameters, which leads to the problem of relatively inconvenient calibration in the application process. Summary of the Invention

[0007] In view of the above problems existing in the prior art, the present invention provides a method for compensating the sensitivity attenuation of an ultrasonic transducer based on system optimization;

[0008] On the other hand, it also provides an ultrasonic transducer sensitivity attenuation compensation system for implementing this method.

[0009] The specific technical solution is as follows:

[0010] A method for compensating the sensitivity attenuation of an ultrasonic transducer based on system optimization includes:

[0011] Step S1: Obtain a first imaging sequence during the scanning process and identify the sensitivity reference area;

[0012] Step S2: Extract features from the sensitivity reference area and construct an image quality score. When it is determined according to the image quality score that sensitivity compensation is required, turn to step S3;

[0013] Step S3: Find the calibration part from the second imaging sequence and generate a prompt message;

[0014] Step S4: Move the ultrasonic probe to the calibration part according to the prompt message, and then perform closed-loop gain adjustment to calibrate the sensitivity.

[0015] On the other hand, step S1 includes:

[0016] Step S11: During the scanning process, obtain the first imaging sequence and the corresponding ultrasonic echo sequence respectively and register them;

[0017] Step S12: Screen and obtain the appearance time of bone tissue according to the echo gain of the ultrasonic echo sequence;

[0018] Step S13: Extract the bone tissue region image from the first imaging requirement according to the appearance time of the bone tissue;

[0019] Step S14: Segment the bone tissue region image and judge the image uniformity. When the image uniformity meets the uniformity condition, output the bone tissue region image as the sensitivity reference region.

[0020] On the other hand, the step S2 includes:

[0021] Step S21: Extract noise information from the sensitivity reference region and evaluate the image signal-to-noise ratio to form a first score;

[0022] Step S22: Dilate the sensitivity reference region to form a dilated region, and evaluate the edge pixel width of the sensitivity reference region in the dilated region to obtain a second score;

[0023] Step S23: Evaluate the gain value corresponding to the sensitivity reference region to obtain a third score;

[0024] Step S24: Generate the image quality score according to the first score, the second score and the third score, and compare it with the image quality threshold.

[0025] On the other hand, the step S3 includes:

[0026] Step S31: During the process of collecting the second image sequence, splice the second image sequence to construct a complete view image;

[0027] Step S32: Perform edge extraction on the complete view image to obtain a plurality of closed regions;

[0028] Step S33: Screen the image gain values of the closed regions to obtain neutral tissue regions;

[0029] Step S33: Calculate the tissue score for the image uniformity and the image edge curvature change rate of each neutral tissue region, and determine the calibration site according to the tissue score.

[0030] On the other hand, the step S4 includes:

[0031] Step S41: Display the orientation of the calibration site in the complete view image on the display device;

[0032] Step S42: After starting the acquisition, perform pre-adjustment according to the image gain value of the calibration part;

[0033] Step S43: Perform secondary adjustment of the sensitivity according to the image edge of the calibration part to make the edge clear.

[0034] An ultrasonic transducer sensitivity attenuation compensation system based on system optimization is used to implement the above ultrasonic transducer sensitivity attenuation compensation method;

[0035] The ultrasonic transducer sensitivity attenuation compensation system includes:

[0036] A first recognition module, which obtains a first imaging sequence during the scanning process and recognizes a sensitivity reference area;

[0037] An evaluation module, which is connected to the first recognition module;

[0038] The evaluation module extracts features from the sensitivity reference area and constructs an image quality score;

[0039] A second recognition module, which is connected to the evaluation module;

[0040] The second recognition module finds a calibration part from the second imaging sequence and generates a prompt message;

[0041] An adjustment module, which is connected to the second recognition module;

[0042] The adjustment module moves the ultrasonic probe to the calibration part according to the prompt message, and then performs closed-loop gain adjustment to calibrate the sensitivity.

[0043] On the other hand, the first recognition module includes:

[0044] A registration module, which respectively obtains the first imaging sequence and the corresponding ultrasonic echo sequence during the scanning process and performs registration;

[0045] A time determination module, which is connected to the registration module;

[0046] The time determination module screens out the bone tissue appearance time according to the echo gain of the ultrasonic echo sequence;

[0047] An image capture module, which is connected to the time determination module;

[0048] The image capture module extracts the bone tissue area image from the first imaging requirement according to the bone tissue appearance time;

[0049] A uniformity judgment module, the uniformity judgment module is connected to the image capture module;

[0050] The uniformity judgment module segments the bone tissue area image and judges the image uniformity. When the image uniformity meets the uniformity condition, the bone tissue area image is output as the sensitivity reference area.

[0051] On the other hand, the evaluation module includes:

[0052] A first scoring module, the first scoring module extracts noise information from the sensitivity reference area and evaluates the image signal-to-noise ratio to form a first score;

[0053] A second scoring module, the second scoring module is connected to the first scoring module;

[0054] The second scoring module dilates the sensitivity reference area to form a dilated area, and evaluates the edge pixel width of the sensitivity reference area in the dilated area to obtain a second score;

[0055] A third scoring module, the third scoring module is connected to the second scoring module;

[0056] The third scoring module evaluates the gain value corresponding to the sensitivity reference area to obtain a third score;

[0057] A score comparison module, the score comparison module is connected to the third scoring module;

[0058] The score comparison module generates the image quality score according to the first score, the second score and the third score, and compares it with the image quality threshold.

[0059] On the other hand, the second recognition module includes:

[0060] An image stitching module, during the process of collecting the second image sequence, the image stitching module stitches the second image sequence to construct a complete view image;

[0061] An edge extraction module, the edge extraction module is connected to the image stitching module;

[0062] The edge extraction module performs edge extraction on the complete view image to obtain a plurality of closed areas;

[0063] A brightness screening module, the brightness screening module is connected to the edge extraction module;

[0064] The brightness screening module screens the image gain values of the closed areas to obtain a neutral tissue area;

[0065] A part determination module, the part determination module being connected to the brightness screening module;

[0066] The part determination module calculates a tissue score for the image uniformity and the image edge curvature change rate of each of the neutral tissue region images, and determines the calibration part according to the tissue score.

[0067] On the other hand, the adjustment module includes:

[0068] An indication module, the indication module displaying the orientation of the calibration part in the full view image on the display device;

[0069] A first adjustment module, the first adjustment module being connected to the indication module;

[0070] After starting the acquisition, the first adjustment module performs pre-adjustment according to the image gain value of the calibration part;

[0071] A second adjustment module, the second adjustment module being connected to the first adjustment module;

[0072] The second adjustment module performs secondary adjustment on the sensitivity according to the image edge of the calibration part to make the edge clear.

[0073] The above technical solution has the following advantages or beneficial effects:

[0074] Regarding the problem that the existing ultrasonic calibration scheme in the prior art depends on a specific target for use and is inconvenient, a process for real-time judging whether the image quality of the current ultrasonic image needs to be calibrated is introduced, and uniform tissue parts available for calibration in the real-time scanning process are screened out in combination with the echo information in the image, and calibration is performed based on this part, eliminating the specific process of target calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] With reference to the accompanying drawings, the embodiments of the present invention are described more fully. However, the accompanying drawings are only for illustration and explanation and do not constitute a limitation on the scope of the present invention.

[0076] Figure 1 is the overall schematic diagram of the embodiment of the present invention;

[0077] Figure 2 is the schematic diagram of step S1 in the embodiment of the present invention;

[0078] Figure 3 is the schematic diagram of step S2 in the embodiment of the present invention;

[0079] Figure 4 is the schematic diagram of step S3 in the embodiment of the present invention;

[0080] Figure 5Schematic diagram of step S4 in the embodiment of the present invention;

[0081] Figure 6 Schematic diagram of the system in the embodiment of the present invention;

[0082] Figure 7 Schematic diagram of the first recognition module in the embodiment of the present invention;

[0083] Figure 8 Schematic diagram of the evaluation module in the embodiment of the present invention;

[0084] Figure 9 Schematic diagram of the second recognition module in the embodiment of the present invention;

[0085] Figure 10 Schematic diagram of the adjustment module in the embodiment of the present invention; Detailed implementation manners

[0086] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0087] Some of the block diagrams shown in the drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0088] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0089] Next, the present invention will be further described in conjunction with the accompanying drawings and specific embodiments, but it is not a limitation of the present invention.

[0090] The present invention includes:

[0091] An ultrasonic transducer sensitivity attenuation compensation method based on system optimization, as Figure 1 shown, includes:

[0092] Step S1: Obtain a first imaging sequence during the scanning process and identify a sensitivity reference area;

[0093] Step S2: Extract features from the sensitivity reference area and construct an image quality score. When it is determined according to the image quality score that sensitivity compensation is required, turn to step S3;

[0094] Step S3: Locate the calibration part from the second imaging sequence and generate a prompt message;

[0095] Step S4: Move the ultrasound probe to the calibration part according to the prompt message, and then perform closed-loop gain adjustment to calibrate the sensitivity.

[0096] Specifically, for the problem that the existing ultrasound calibration scheme in the prior art depends on a specific target and is inconvenient to use, in this embodiment, first, during the normal scanning process, the first imaging sequence is obtained and the images are recognized frame by frame to determine whether the ultrasound images reconstructed from the first imaging sequence include a specific tissue area that can be used for image sensitivity judgment and serve as a sensitivity reference area.

[0097] During the ultrasound scanning process, generally, ultrasonic waves are emitted to the patient's tissue and the echo sequence is collected, and then a real-time image reconstruction process is performed based on the echo sequence. Then, in each emission-acquisition-reconstruction cycle, a corresponding frame of image is generated. Then, the above-mentioned images are stored according to the acquisition time, and the first imaging sequence and the second imaging sequence are formed. Generally speaking, the first imaging sequence is used to refer to the sequence generated during the normal image reconstruction process, and the second imaging sequence is used to refer to the sequence that needs to be collected and cached after compensation, and they have different storage areas in terms of data.

[0098] The sensitivity reference area refers to a tissue area in the ultrasound image that has specific image features and good consistency in different images, such as bones, muscles, etc. Then, feature extraction is performed on the sensitivity reference area and an image quality score is constructed to measure the effect of the current transducer array in collecting images. There is a pre-calibrated image quality score threshold for the image quality score. When the image quality score threshold is not met, it indicates that the image quality has deteriorated significantly and sensitivity calibration is required.

[0099] Then, during the calibration process, the image sequence of the ultrasound reconstruction is synchronously obtained and stored as the second imaging sequence. Subsequently, the images in the second imaging sequence are respectively recognized to determine the part in the second imaging sequence that is more suitable for calibration as the calibration part.

[0100] Finally, move the ultrasound probe to the calibration part according to the prompt message, and then perform closed-loop gain adjustment. During the gain adjustment process, judge the change of the image quality until the requirement is met to calibrate the sensitivity.

[0101] In one embodiment, as Figure 2 shown, step S1 includes:

[0102] Step S11: Obtain the first imaging sequence and the corresponding ultrasound echo sequence respectively during the scanning process and register them;

[0103] Step S12: Screen the appearance time of bone tissue according to the echo gain of the ultrasonic echo sequence.

[0104] Step S13: Extract the bone tissue region image from the first imaging sequence according to the appearance time of bone tissue.

[0105] Step S14: Segment the bone tissue region image and judge the image uniformity. When the image uniformity meets the uniformity condition, output the bone tissue region image as the sensitivity reference region.

[0106] Specifically, to achieve a better sensitivity verification process, in this embodiment, first, during the scanning process, the first imaging sequence and the corresponding ultrasonic echo sequence are respectively acquired and registered, that is, for multiple frames of images in the first imaging sequence, the corresponding ultrasonic echo sequence is acquired and aligned in chronological order.

[0107] Among them, for the ultrasonic echo sequence, the received signal gain intensity of the corresponding ultrasonic echo signal can be directly read. Since there are obvious hardness changes in bone tissue compared with other types of tissues, there will be significantly higher signal gain in the echo gain. Screen the appearance time of bone tissue according to the echo gain of the ultrasonic echo sequence.

[0108] Then, search the first imaging sequence with reference to the appearance time of bone tissue, and the bone tissue image at the corresponding time point can be obtained.

[0109] Then, combined with the gray value in the image, edge extraction is performed to segment the bone tissue region image, thereby removing the irrelevant background part. For the segmented bone tissue region image, judge the image uniformity, including obtaining edge points according to the image edge, determining the center point of the bone tissue region image according to the set of edge points, and constructing the two longest radial lines passing through the center point from the edge points. Subsequently, read the gray values of multiple pixel points on this radial line and calculate the change rate between the gray values as the image uniformity.

[0110] In another embodiment, the exponentially weighted moving average (EWMA) model can also be used to perform a sliding image evaluation on the bone tissue region to judge the image uniformity.

[0111] For example, S_avg(t) = α·S_avg(t - 1) + (1 - α)·S_i(t);

[0112] In the formula, S_avg(t) is the uniformity parameter obtained by cutting the sliding window at time t, S_avg(t - 1) is the uniformity parameter obtained by cutting the sliding window at time t - 1, S_i(t) is the pixel mean value calculated by the sliding window at time t, and α is the adjustment factor. Judge whether the uniformity parameter changes significantly to judge the image uniformity.

[0113] Judge whether the image uniformity meets the uniformity condition. If the image uniformity meets the uniformity condition, output the bone tissue region image as the sensitivity reference region.

[0114] In one embodiment, as Figure 3 shown, step S2 includes:

[0115] Step S21: Extract noise information from the sensitivity reference region and evaluate the image signal-to-noise ratio to form a first score;

[0116] Step S22: Dilate the sensitivity reference region to form a dilated region, and evaluate the edge pixel width of the sensitivity reference region in the dilated region to obtain a second score;

[0117] Step S23: Evaluate the gain value corresponding to the sensitivity reference region to obtain a third score;

[0118] Step S24: Generate an image quality score according to the first score, the second score and the third score, and compare it with the image quality threshold.

[0119] Specifically, to achieve a better evaluation of the image quality, in this embodiment, first extract noise information from the sensitivity reference region and evaluate the image signal-to-noise ratio, and evaluate it according to the corresponding scale in combination with the image signal-to-noise ratio to form a first score;

[0120] Subsequently, dilate the sensitivity reference region to form a dilated region, which includes multiple pixel lengths. For the pixel lengths of the dilated region, calculate the contrast between two adjacent pixels in turn. When the value of the contrast is greater than the contrast threshold, it is considered that the actual edge of the sensitivity reference region is reached. At this time, determine the edge pixel width according to the number of pixels passed in the dilated region. Subsequently, evaluate the edge pixel width according to the relevant scale. The larger the edge pixel width, the more blurred the image, and a second score is obtained.

[0121] Finally, calculate the gain values for the multiple pixel points corresponding to the sensitivity reference region respectively, obtain the gain mean and standard deviation, and evaluate them according to the relevant scale to obtain a third score.

[0122] Add up the first score, the second score and the third score to generate an image quality score, and compare it with the image quality threshold to determine whether there is a problem of image degradation.

[0123] In one embodiment, as Figure 4 shown, step S3 includes:

[0124] Step S31: During the process of collecting the second image sequence, splice the second image sequence to construct a complete view image;

[0125] Step S32: Perform edge extraction on the complete view image to obtain multiple closed regions;

[0126] Step S33: Screen the image gain values of the closed regions to obtain neutral tissue regions;

[0127] Step S34: Calculate the tissue scores for the image uniformity and the change rate of the image edge curvature of each neutral tissue region, and determine the calibration site according to the tissue scores.

[0128] Specifically, to achieve a better calibration site determination process, in this embodiment, during the process of collecting the second image sequence, first splice the second image sequence, including superimposing according to the overlapping parts in the images, so as to construct a complete view image.

[0129] Subsequently, perform edge extraction on the complete view image to obtain multiple closed regions, and each closed region corresponds to a part of the tissue region respectively.

[0130] For each tissue region, due to its different tissue densities and different reflection intensities of ultrasound, the tissues are screened according to the pre-calibrated range of image gain values, so as to obtain neutral tissue regions.

[0131] Finally, calculate the tissue scores for the image uniformity and the change rate of the image edge curvature of each neutral tissue region, and determine the calibration site according to the tissue scores. The calibration site has better image uniformity and a relatively smooth edge, which is convenient for observing the calibration effect.

[0132] In one embodiment, as Figure 5 shown, step S4 includes:

[0133] Step S41: Display the orientation of the calibration site in the complete view image on the display device; Step S42: After starting the collection, perform pre-adjustment according to the image gain value of the calibration site in combination with the human reflection model;

[0134] Step S43: Perform secondary adjustment on the sensitivity according to the image edge of the calibration site to make the edge clear.

[0135] Specifically, to achieve a better calibration effect, in this embodiment, first display the orientation of the calibration site in the complete view image on the display device, and according to this displayed image, the doctor can point the probe to a specific orientation.

[0136] Subsequently, the control probe starts to collect data, generate echoes, and reconstruct images. To accurately measure the image gain value, the human body structure is calibrated before the start of data collection, and a set of tissue type-impedance compensation coefficient mapping tables are constructed.

[0137] Specifically, during the ultrasonic imaging process, it is often necessary to pass through multiple interfaces, including the coupling agent, skin layer, fat layer, muscle layer, and even the bone part. Among them, the skin layer can be simply equivalent to adipose tissue.

[0138] For the above-mentioned tissue parts, a tissue type-impedance compensation coefficient mapping table is pre-constructed.

[0139] Tissue type <![CDATA[Acoustic impedance (kg / m 2 s)]]> Compensation factor Fat 1.38×10^6 0.92 Muscle 1.70×10^6 1.05 Bone 7.80×10^6 1.28

[0140] According to the above compensation coefficient, during the data collection process, the image gain coefficient can be compensated to determine the actual image gain value on the corresponding calibration part.

[0141] Then, pre-adjustment is performed according to the image gain value so that the image gain value on the calibration part meets the set range.

[0142] Subsequently, the sensitivity is secondarily adjusted according to the image edge of the calibration part to make the edge clear, so as to realize the closed-loop adjustment process.

[0143] An ultrasonic transducer sensitivity attenuation compensation system based on system optimization is used to implement the above ultrasonic transducer sensitivity attenuation compensation method;

[0144] As Figure 6 shown, the ultrasonic transducer sensitivity attenuation compensation system includes:

[0145] The first recognition module 1, which obtains the first imaging sequence and recognizes the sensitivity reference area during the scanning process;

[0146] The evaluation module 2, which is connected to the first recognition module 1;

[0147] The evaluation module 2 extracts features from the sensitivity reference area and constructs an image quality score;

[0148] The second recognition module 3, which is connected to the evaluation module 2;

[0149] The second recognition module 3 finds the calibration part from the second imaging sequence and generates a prompt message;

[0150] The adjustment module 4, which is connected to the second recognition module 3;

[0151] The adjustment module 4 moves the ultrasonic probe to the calibration part according to the prompt message, and then performs closed-loop gain adjustment to calibrate the sensitivity.

[0152] Specifically, in view of the problem that the existing ultrasonic calibration scheme depends on a specific target and is inconvenient to use, in this embodiment, first, during the normal scanning process, the first recognition module 1 acquires the first imaging sequence and performs frame-by-frame recognition on the images to determine whether the ultrasonic images reconstructed in the first imaging sequence include a specific tissue region that can be used for image sensitivity judgment and serves as a sensitivity reference region.

[0153] During the ultrasonic scanning process, generally, ultrasonic waves are emitted to the patient's tissue and the echo sequence is collected, and then a real-time image reconstruction process is performed based on the echo sequence. Then, in each emission-acquisition-reconstruction cycle, a corresponding image is generated. Storing the above images according to the acquisition time will form the first imaging sequence and the second imaging sequence. Generally speaking, the first imaging sequence is used to refer to the sequence generated during the normal image reconstruction process, and the second imaging sequence is used to refer to the sequence that needs to be acquired and cached after compensation, and they have different storage areas in terms of data.

[0154] The sensitivity reference region refers to a tissue region in the ultrasonic image that has specific image features and good consistency in different images, such as bones, muscles, etc. Then, the evaluation module 2 extracts features from the sensitivity reference region and constructs an image quality score to measure the effect of the current transducer array in collecting images. An image quality score threshold is pre-calibrated for the image quality score. When the image quality score threshold is not met, it indicates that the image quality has deteriorated significantly and sensitivity calibration is required. <L

[0155] Then, during the calibration process, the second recognition module 3 synchronously acquires the image sequence of ultrasonic reconstruction and stores it as the second imaging sequence. Subsequently, the images in the second imaging sequence are respectively recognized to determine the part in the second imaging sequence that is more suitable for calibration as the calibration part.

[0156] Finally, the adjustment module 4 moves the ultrasonic probe to the calibration part according to the prompt information, and then performs closed-loop gain adjustment. During the gain adjustment process, by judging the change of the image quality, the sensitivity is calibrated until the requirements are met.

[0157] In one embodiment, as Figure 7 shown, the first recognition module 1 includes:

[0158] A registration module 11, which acquires the first imaging sequence and the corresponding ultrasonic echo sequence respectively during the scanning process and performs registration;

[0159] A time determination module 12, and the time determination module 12 is connected to the registration module 11;

[0160] The time determination module 12 screens out the appearance time of bone tissue according to the echo gain of the ultrasonic echo sequence;

[0161] An image capture module 13, and the image capture module 13 is connected to the time determination module 12;

[0162] The image capture module 13 extracts the bone tissue region image from the first imaging sequence according to the appearance time of bone tissue;

[0163] A uniformity judgment module 14, and the uniformity judgment module 14 is connected to the image capture module 13;

[0164] The uniformity judgment module 14 segments the bone tissue region image and judges the image uniformity. When the image uniformity meets the uniformity condition, the bone tissue region image is output as the sensitivity reference region.

[0165] Specifically, to achieve a better sensitivity verification process, in this embodiment, the registration module 11 first obtains the first imaging sequence and the corresponding ultrasonic echo sequence respectively during the scanning process and performs registration, that is, for multiple frames of images in the first imaging sequence, the corresponding ultrasonic echo sequence is obtained and aligned according to the time sequence.

[0166] Among them, for the ultrasonic echo sequence, the received signal gain intensity of the corresponding ultrasonic echo signal can be directly read. Since there are obvious hardness changes in bone tissue compared with other types of tissues, there will be significantly higher signal gains in the echo gain. The time determination module 12 screens out the appearance time of bone tissue according to the echo gain of the ultrasonic echo sequence.

[0167] Then the image capture module 13 searches the first imaging sequence with reference to the appearance time of bone tissue, and can obtain the bone tissue image at the corresponding time point.

[0168] Then, the uniformity judgment module 14 combines the gray values in the image for edge extraction, segments the bone tissue region image, thereby removing the irrelevant background part. For the segmented bone tissue region image, the image uniformity is judged, including obtaining edge points according to the image edge, determining the center point of the bone tissue region image according to the set of edge points, and constructing the two longest radial lines passing through the center point of the edge points. Subsequently, the gray values of multiple pixel points on this radial line are read and the change rate between the gray values is calculated as the image uniformity.

[0169] Judge whether the image uniformity meets the uniformity condition. If the image uniformity meets the uniformity condition, the bone tissue region image is output as the sensitivity reference region.

[0170] In one embodiment, as Figure 8 shown, the evaluation module 2 includes:

[0171] The first scoring module 21 extracts noise information from the sensitivity reference region and evaluates the image signal-to-noise ratio to form a first score.

[0172] The second scoring module 22 is connected to the first scoring module 21.

[0173] The second scoring module 22 dilates the sensitivity reference region to form a dilated region, and evaluates the edge pixel width of the sensitivity reference region in the dilated region to obtain a second score.

[0174] The third scoring module 23 is connected to the second scoring module 22.

[0175] The third scoring module 23 evaluates the gain value corresponding to the sensitivity reference region to obtain a third score.

[0176] The scoring comparison module 24 is connected to the third scoring module 23.

[0177] The scoring comparison module 24 generates an image quality score based on the first score, the second score, and the third score, and compares it with the image quality threshold.

[0178] Specifically, to achieve a better evaluation of the image quality, in this embodiment, the first scoring module 21 first extracts noise information from the sensitivity reference region and evaluates the image signal-to-noise ratio, and forms a first score by evaluating according to the corresponding scale in combination with the image signal-to-noise ratio.

[0179] Subsequently, the second scoring module 22 dilates the sensitivity reference region to form a dilated region, which includes multiple pixel lengths. For the pixel lengths of the dilated region, the contrast between two adjacent pixels is calculated in sequence. When the value of the contrast is greater than the contrast threshold, it is considered that the actual edge of the sensitivity reference region has been reached. At this time, the edge pixel width is determined according to the number of pixels passed in the dilated region. Subsequently, the edge pixel width is evaluated according to the relevant scale. The larger the edge pixel width, the more blurred the image, and a second score is obtained.

[0180] Finally, the third scoring module 23 calculates the gain values of multiple pixel points corresponding to the sensitivity reference region respectively, obtains the gain mean and standard deviation, and obtains a third score by evaluating according to the relevant scale.

[0181] The scoring comparison module 24 adds up the first score, the second score, and the third score to generate an image quality score, and compares it with the image quality threshold to determine whether there is a problem of image degradation.

[0182] In one embodiment, as Figure 9As shown, the second identification module 3 includes:

[0183] An image stitching module 31 stitches the second image sequence to construct a complete view image during the process of acquiring the second image sequence;

[0184] An edge extraction module 32 , the edge extraction module 32 is connected to the image stitching module 31 ;

[0185] The edge extraction module 32 performs edge extraction in the complete view image to obtain a plurality of closed areas;

[0186] A brightness screening module 33, the brightness screening module 33 is connected to the edge extraction module 32;

[0187] The brightness screening module 33 screens the image gain value of the closed area to obtain a neutral tissue area;

[0188] A part determination module 34, the part determination module 34 is connected to the brightness screening module 33;

[0189] The position determination module 34 calculates the image uniformity and the image edge curvature change rate of each neutral tissue region to obtain a tissue score, and determines the calibration position according to the tissue score.

[0190] Specifically, to achieve a better calibration position determination process, in this embodiment, the image stitching module 31 first stitches the second image sequence during the process of acquiring the second image sequence, including superimposing the overlapping parts in the image to construct a complete view image.

[0191] Subsequently, the edge extraction module 32 performs edge extraction in the full view image to obtain a plurality of closed regions, each of which corresponds to a portion of the tissue region.

[0192] For each tissue region, since its tissue density is different, the reflection intensity of ultrasound is also different. Therefore, the brightness screening module 33 screens the tissue according to the pre-calibrated image gain value range to obtain a neutral tissue region.

[0193] Finally, the part determination module 34 calculates the image uniformity and image edge curvature change rate of each neutral tissue area to obtain a tissue score, and determines the calibration part according to the tissue score. The calibration part has good image uniformity and relatively smooth edges, which is convenient for observing the calibration effect.

[0194] In one embodiment, Figure 10 As shown, the adjustment module 4 includes:

[0195] an indication module 41 , the indication module 41 displays the position of the calibration part in the full view image on a display device;

[0196] The first adjustment module 42, and the first adjustment module 42 is connected to the indication module 41;

[0197] After starting the acquisition, the first adjustment module 42 performs pre-adjustment in combination with the human reflection model according to the image gain value of the calibration part;

[0198] The second adjustment module 43, and the second adjustment module 43 is connected to the first adjustment module 42;

[0199] The second adjustment module 43 performs secondary adjustment on the sensitivity according to the image edge of the calibration part to make the edge clear.

[0200] Specifically, to achieve a better calibration effect, in this embodiment, the indication module 41 first displays the orientation of the calibration part in the full-view image on the display device, and according to this display image, the doctor can point the probe to a specific orientation.

[0201] Subsequently, the first adjustment module 42 controls the probe to start acquisition, generates echoes and reconstructs to obtain an image. According to the reconstructed image, first perform pre-adjustment according to the image gain value of the calibration part to make the image gain value of the calibration part meet the expectation.

[0202] Subsequently, the second adjustment module 43 performs secondary adjustment on the sensitivity according to the image edge of the calibration part to make the edge clear, so as to achieve a closed-loop adjustment process.

[0203] Those of ordinary skill in the art will understand that various aspects of the present invention, or possible implementations of various aspects, can be specifically implemented as a system, method, or computer program product. Therefore, various aspects of the present invention, or possible implementations of various aspects, can adopt the form of a complete hardware embodiment, a complete software embodiment (including firmware, resident software, etc.), or a form combining software and hardware embodiments, which are collectively referred to as "circuits", "modules", or "systems" here. In addition, various aspects of the present invention, or possible implementations of various aspects, can adopt the form of a computer program product, and a computer program product refers to computer instructions stored in a memory.

[0204] The memory can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium includes, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or apparatuses, or any suitable combination of the foregoing, such as random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable read-only memory (CD-ROM).

[0205] A processor in a computer reads computer instructions stored in a memory, enabling the processor to perform functional actions specified in each step, or combinations of steps, in a flowchart; and generates means for implementing the functional actions specified in each block, or combinations of blocks, in a block diagram.

[0206] It should be understood that the processor in the computer can be understood as being implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components for executing the aforementioned computer instructions.

[0207] The computer instructions can be executed entirely on the user's local computer, partially on the user's local computer, as a separate software package, partially on the user's local computer and partially on a remote computer, or entirely on a remote computer or server. It should also be noted that in some alternative embodiments, the functions noted in each step in the flowchart, or each block in the block diagram, may not occur in the order noted in the figure. For example, depending on the functions involved, two consecutive steps, or two blocks shown in succession, may actually be executed substantially simultaneously, or these blocks may sometimes be executed in the reverse order.

[0208] Of course, in actual applications, the various components in a computer system are coupled together through a bus system. It can be understood that the bus system is used to achieve connection and communication between these components. In addition to a data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0209] The above are only preferred embodiments of the present invention, and do not limit the implementation manners and protection scope of the present invention. For those skilled in the art, it should be realized that any equivalent replacements and obvious changes made by using the description and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. An ultrasonic transducer sensitivity attenuation compensation method based on system optimization, characterized in that Including: Step S1: Obtain a first imaging sequence during the scanning process and identify a sensitivity reference region; Step S2: Extract features from the sensitivity reference region and construct an image quality score. When it is determined according to the image quality score that sensitivity compensation is required, proceed to Step S3; Step S3: Locate a calibration site from the second imaging sequence and generate a prompt message; Step S4: Move the ultrasonic probe to the calibration site according to the prompt message, and then perform closed-loop gain adjustment to calibrate the sensitivity.

2. The method for compensating the sensitivity attenuation of an ultrasonic transducer according to claim 1, wherein, The said Step S1 includes: Step S11: Obtain the first imaging sequence and the corresponding ultrasonic echo sequence respectively during the scanning process and register them; Step S12: Screen the bone tissue appearance time according to the echo gain of the ultrasonic echo sequence; Step S13: Extract the bone tissue region image from the first imaging sequence according to the bone tissue appearance time; Step S14: Segment the bone tissue region image and judge the image uniformity. When the image uniformity meets the uniformity condition, output the bone tissue region image as the sensitivity reference region.

3. The method for compensating the sensitivity attenuation of an ultrasonic transducer according to claim 1, characterized in that, The said Step S2 includes: Step S21: Extract noise information from the sensitivity reference region and evaluate the image signal-to-noise ratio to form a first score; Step S22: Dilate the sensitivity reference region to form a dilated region, and evaluate the edge pixel width of the sensitivity reference region in the dilated region to obtain a second score; Step S23: Evaluate the gain value corresponding to the sensitivity reference region to obtain a third score; Step S24: Generate the image quality score according to the first score, the second score and the third score, and compare it with the image quality threshold.

4. The ultrasonic transducer sensitivity attenuation compensation method according to claim 1, characterized in that, The said Step S3 includes: Step S31: During the process of collecting the second image sequence, splice the second image sequence to construct a complete view image; Step S32: Perform edge extraction on the complete view image to obtain a plurality of closed regions; Step S33: Screen the image gain values of the closed regions to obtain a neutral tissue region; Step S34: Calculate the tissue score for the image uniformity and the image edge curvature change rate of each neutral tissue region, and determine the calibration site according to the tissue score.

5. The method for compensating for the sensitivity attenuation of the ultrasonic transducer according to claim 4, characterized in that, The said Step S4 includes: Step S41: Display the orientation of the calibration site in the complete view image on the display device; Step S42: After starting the acquisition, perform pre-adjustment according to the image gain value of the calibration site in combination with the human body reflection model; Step S43: Perform secondary adjustment on the sensitivity according to the image edge of the calibration site to make the edge clear.

6. An ultrasonic transducer sensitivity attenuation compensation system based on system optimization, characterized in that, For implementing the ultrasonic transducer sensitivity attenuation compensation method according to any one of claims 1-5; The ultrasonic transducer sensitivity attenuation compensation system includes: A first identification module, which obtains a first imaging sequence during the scanning process and identifies a sensitivity reference region; An evaluation module, the evaluation module is connected to the first identification module; The evaluation module extracts features from the sensitivity reference region and constructs an image quality score; A second recognition module, the second recognition module being connected to the evaluation module; The second recognition module finds a calibration part from the second imaging sequence and generates a prompt message; An adjustment module, the adjustment module being connected to the second recognition module; The adjustment module moves the ultrasonic probe to the calibration part according to the prompt message, and then performs closed-loop gain adjustment to calibrate the sensitivity.

7. The ultrasonic transducer sensitivity attenuation compensation system according to claim 6, wherein The first recognition module includes: A registration module, the registration module respectively acquiring the first imaging sequence and the corresponding ultrasonic echo sequence during the scanning process and performing registration; A time determination module, the time determination module being connected to the registration module; The time determination module screens out the bone tissue appearance time according to the echo gain of the ultrasonic echo sequence; An image extraction module, the image extraction module being connected to the time determination module; The image extraction module extracts the bone tissue region image from the first imaging sequence according to the bone tissue appearance time; A uniformity judgment module, the uniformity judgment module being connected to the image extraction module; The uniformity judgment module segments the bone tissue region image and judges the image uniformity. When the image uniformity meets the uniformity condition, the bone tissue region image is output as the sensitivity reference region.

8. The ultrasonic transducer sensitivity attenuation compensation system according to claim 6, wherein The evaluation module includes: A first scoring module, the first scoring module extracting noise information from the sensitivity reference region and evaluating the image signal-to-noise ratio to form a first score; A second scoring module, the second scoring module being connected to the first scoring module; The second scoring module dilates the sensitivity reference region to form a dilated region, and evaluates the edge pixel width of the sensitivity reference region in the dilated region to obtain a second score; A third scoring module, the third scoring module being connected to the second scoring module; The third scoring module evaluates the gain value corresponding to the sensitivity reference region to obtain a third score; A score comparison module, the score comparison module being connected to the third scoring module; The score comparison module generates the image quality score according to the first score, the second score and the third score, and compares it with the image quality threshold.

9. The ultrasonic transducer sensitivity attenuation compensation system according to claim 6, wherein The second recognition module includes: An image stitching module, the image stitching module stitching the second image sequence during the process of collecting the second image sequence to construct a complete view image; An edge extraction module, the edge extraction module being connected to the image stitching module; The edge extraction module performs edge extraction on the complete view image to obtain a plurality of closed regions; A brightness screening module, the brightness screening module being connected to the edge extraction module; The brightness screening module screens the image gain values of the closed regions to obtain a neutral tissue region; A part determination module, the part determination module being connected to the brightness screening module; The part determination module calculates the tissue score for the image uniformity and the image edge curvature change rate of each neutral tissue region, and determines the calibration part according to the tissue score.

10. The ultrasonic transducer sensitivity attenuation compensation system according to claim 9, characterized in that The adjustment module includes: An indication module that displays the orientation of the calibration part in the full-view image on the display device; A first adjustment module, the first adjustment module being connected to the indication module; After starting the acquisition, the first adjustment module performs pre-adjustment in combination with the human body reflection model according to the image gain value of the calibration part; A second adjustment module, the second adjustment module being connected to the first adjustment module; The second adjustment module performs secondary adjustment on the sensitivity according to the image edge of the calibration part to make the edge clear.

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