Self-adaptive adjustment method and system for operating parameters of color ultrasonic equipment

Abstract

The invention discloses a self-adaptive adjustment method and system for operating parameters of color ultrasound equipment, and relates to the technical field of medical imagines.The method comprises the steps that in the cardiac ultrasound examination process, image feature state data information is associated with echo signal state data information, and a motion artifact evaluation coefficient Xwy is obtained; after comparison, an artifact image frame set is marked, and a gain adjustment analysis instruction is sent out; the method comprises the following steps: acquiring vascular rigidity state data information according to interference of vascular instantaneous relaxation on echo signals, and associating the vascular rigidity state data information with a corresponding motion artifact evaluation coefficient Xwy to obtain an echo signal gain degree index Zzy; through comparative analysis, whether each frame of echo signal corresponding to the current artifact image frame set needs gain compensation is judged so as to generate and execute a gain adjustment instruction of a corresponding grade, and the process optimizes the gain adjustment of the echo signal, improves the image quality, ensures the definition of ultrasonic imaging, and improves the accuracy of ultrasonic imaging. Therefore, the accuracy and the diagnosis reliability of cardiac ultrasonic examination are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical imaging, and particularly to an adaptive adjustment method and system for the operating parameters of a color ultrasound device. Background Art

[0002] Color ultrasound devices belong to the technical field of medical imaging and are one of the important tools for modern medical diagnosis. With the development of ultrasound imaging technology, their applications have expanded from traditional gray-scale ultrasound to color Doppler ultrasound, making the detection of hemodynamic analysis, cardiovascular disease diagnosis, and organ structure assessment more accurate and intuitive; among the operating parameters of color ultrasound devices, due to the attenuation of echo signals caused by the acoustic characteristics of biological tissues during the propagation of ultrasound signals, it is easy to cause motion artifacts in ultrasound images. Therefore, the echo signal gain has a direct impact on the quality of ultrasound images and the diagnostic accuracy; in order to ensure that the device can obtain the best imaging effect under different patients, different tissue types, and different usage environments, it is necessary to reasonably adjust its operating parameters to adapt to different diagnostic requirements.

[0003] However, the imaging of existing color ultrasound devices usually relies on manual adjustment of parameters by doctors, which is complex and depends on the doctor's experience, resulting in different imaging qualities for different people; in addition, due to the influence of the acoustic characteristics of biological tissues, motion artifacts, and signal attenuation factors on the propagation of ultrasound signals, fixed parameter settings often cannot take into account all situations, resulting in poor quality of some images and affecting the doctor's judgment; for example, in cardiac ultrasound examinations, if the echo signal gain is not adjusted in a timely manner or set improperly, when the instantaneous relaxation of blood vessels generated by high-speed blood flow interferes with the echo signal, the imaging of the color ultrasound device is prone to motion artifacts, resulting in the loss of diagnostic information and affecting the doctor's identification and evaluation of lesions. Therefore, there is an urgent need for an adaptive adjustment method for the operating parameters of color ultrasound devices to ensure the timeliness and accuracy of examination results under different application scenarios. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides an adaptive adjustment method and system for the operating parameters of a color ultrasound device, which solves the problems in the above background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: An adaptive adjustment method for the operating parameters of a color ultrasound device includes the following steps:

[0006] S1. Perform frame segmentation on the formed continuous ultrasound video stream, construct a color Doppler image frame set, and obtain image feature state data information. According to the echo signal reflected from the heart tissue, obtain the echo signal state data information;

[0007] S2. Correlate the image feature status data information and the echo signal status data information, fit to obtain the motion artifact evaluation coefficient Xwy for several frames. After comparison, mark the artifact image frame set and issue a gain adjustment analysis instruction;

[0008] S3. Collect the blood vessel rigidity status data information within the artifact image frame set and correlate it with the corresponding motion artifact evaluation coefficient Xwy, fit to obtain the echo signal gain degree index Zzy of the artifact image frame set;

[0009] S4. Conduct a comparison and analysis on the echo signal gain degree index Zzy of the artifact image frame set, determine whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, and generate corresponding level gain adjustment instructions for execution.

[0010] Preferably, S1 specifically includes the following steps:

[0011] S11. During cardiac ultrasound examination, use the ultrasonic probe in the color ultrasound device to emit high-frequency ultrasonic waves, receive the echo signals reflected from the cardiac tissue, use high-speed analog-to-digital conversion to convert the received echo signals into digital signals, and demodulate them through digital signal processing technology to form a continuous ultrasonic video stream;

[0012] S12. Perform frame segmentation on the image data in the ultrasonic video stream, extract the color Doppler image of each frame, construct a color Doppler image frame set, and use the histogram equalization algorithm to perform feature extraction on the color Doppler image frame set to obtain the image feature status data information. Among them, the image feature status data information includes the image brightness value Dzd of each frame;

[0013] S13. Monitor the status of the echo signals according to the echo signals reflected from the cardiac tissue, remove the noise in the non-target frequency band through band-pass filtering, and combine with Fourier transform to obtain the echo signal status data information. Among them, the echo signal status data information includes the echo signal-to-noise ratio Bxz, the echo intensity change rate Vbh, and the echo frequency offset Ppy of each frame;

[0014] S14. During cardiac ultrasound examination, keep the frame level of each frame image in the color Doppler image frame set extracted in step S12 corresponding to the frame level of each echo signal in the echo signal status data information obtained through echo signal analysis in step S13.

[0015] Preferably, S2 specifically includes the following steps:

[0016] S21. Based on the content of step S12, feature extraction is performed on the image feature status data information. By analyzing the change of the image brightness value Dzd of each frame over time, after dimensionless processing, the motion artifact change coefficient Xcd of the corresponding frame is obtained. Taking the motion artifact change coefficient Xcd of the i-th frame as an example, it is specifically obtained according to the following formula: i For example, it is specifically obtained according to the following formula:

[0017]

[0018] In the formula, Dzd i represents the image brightness value of the i-th frame, and Δt represents the time interval between two frames of images;

[0019] S22. Based on the content of step S13, feature extraction is performed on the echo signal status data information. By correlating the echo signal-to-noise ratio Bxz of each frame with the echo intensity change rate Vbh and the echo frequency offset Ppy of the corresponding frame, the echo signal quality status of each frame is analyzed. After dimensionless processing, taking the echo signal stability coefficient Xwd of the i-th frame as an example, it is specifically obtained according to the following formula: i For example, it is specifically obtained according to the following formula:

[0020]

[0021] In the formula, Bxz i represents the echo signal-to-noise ratio of the i-th frame, Vbh i represents the echo intensity change rate of the i-th frame, and Ppy i represents the echo frequency offset of the i-th frame.

[0022] Preferably, S2 specifically further includes the following steps:

[0023] S23. Based on the image feature status data information and the echo signal status data information, by performing linear normalization processing on the motion artifact change coefficient Xcd of each frame and the echo signal stability coefficient Xwd of the corresponding frame, and mapping the corresponding data values within the interval [0, 1], the motion artifact evaluation coefficient Xwy of the corresponding frame is obtained. Taking the motion artifact evaluation coefficient Xwy of the i-th frame as an example, it is specifically obtained in the following manner: i For example, it is specifically obtained in the following manner:

[0024]

[0025] In the formula, Xcd i represents the motion artifact change coefficient of the i-th frame, Xwd i represents the echo signal stability coefficient of the i-th frame, both α and β represent weight values, and A represents the first correction constant.

[0026] Preferably, S2 specifically further includes the following steps:

[0027] S24. Obtain the motion artifact evaluation coefficient Xwy of the i-th frame according to step S23 i In the above manner, obtain the motion artifact evaluation coefficients Xwy of several frames respectively, and calculate the average value of the motion artifact evaluation coefficients Xwy of several frames according to the statistical mean algorithm

[0028] S25. By comparing the motion artifact evaluation coefficients Xwy of several frames with the average value to obtain the motion artifact evaluation coefficients Xwy of the corresponding frames exceeding the average value and mark the set of color Doppler image frames where they are located as the artifact image frame set. When the number of frames in the artifact image frame set exceeds 5% of the total number of frames in the color Doppler image frame set, an instruction for gain adjustment analysis is sent out at this time

[0029] Preferably, S3 specifically further includes the following steps

[0030] S31. After receiving the gain adjustment analysis instruction, collect the data information on the vascular rigidity state in the artifact image frame set according to the interference of the instantaneous diastolic of blood vessels in the heart tissue to the echo signal, and in combination with the Canny edge detection and the statistical mean algorithm. Among them, the data information on the vascular rigidity state includes the average diastolic diameter Dsz of blood vessels in the artifact image frame set, the average systolic diameter Dss of blood vessels, the average value Pny of blood vessel pressure, and the total length Lcd of blood vessels

[0031] S32. Extract the features of the data information on the vascular rigidity state obtained in step S31, and after dimensionless processing, fit to obtain the vascular elasticity coefficient Xtx in the artifact image frame set. The specific method for obtaining it is as follows

[0032]

[0033] In the formula, Dsz represents the average diastolic diameter of blood vessels in the artifact image frame set, Dss represents the average systolic diameter of blood vessels in the artifact image frame set, Pny represents the average value of blood vessel pressure in the artifact image frame set, Lcd represents the total length of blood vessels in the artifact image frame set, and π represents the pi

[0034] Preferably, S3 specifically further includes the following steps

[0035] S33. Correlate the vascular elasticity coefficient Xtx of the artifact image frame set with the corresponding motion artifact evaluation coefficient Xwy, and after dimensionless processing, and in combination with the echo signal gain algorithm, fit to obtain the echo signal gain degree index Zzy of the artifact image frame set. The specific method for obtaining it is through the following formula

[0036]

[0037] In the formula, both ε and δ represent weight values, and B represents a second correction constant.

[0038] Preferably, the specific steps of S4 include:

[0039] S41. Preset a degree threshold Y. By comparing and analyzing the echo signal gain degree index Zzy of the artifact image frame set with the degree threshold Y, it is determined whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, so as to generate corresponding level gain adjustment instructions. The specific content is as follows:

[0040] If the echo signal gain degree index Zzy of the artifact image frame set ≥ the degree threshold Y, it means that the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, indicating that the clarity of the current artifact image frame set is not sufficient for normal cardiac ultrasound examination, and a first-level gain adjustment instruction is generated;

[0041] If the echo signal gain degree index Zzy of the artifact image frame set < the degree threshold Y, it means that the echo signals of each frame corresponding to the current artifact image frame set do not need gain compensation, indicating that the clarity of the current artifact image frame set is sufficient for normal cardiac ultrasound examination, and a second-level gain adjustment instruction is generated.

[0042] Preferably, the specific steps of S4 further include:

[0043] S42. According to the first-level gain adjustment instruction and the second-level gain adjustment instruction issued in step S41, execute the corresponding echo signal gain adjustment content. The specific execution content is as follows:

[0044] When receiving the first-level gain adjustment instruction, the adjustment content is: Based on the fact that the clarity of the current artifact image frame set is not sufficient for normal cardiac ultrasound examination, rescan the ultrasound video stream segment where the artifact image frame set is located, and use the gain controller and low-pass filter in the color ultrasound device, combined with the time-domain gain adjustment method, to amplify the echo signal intensity, simultaneously increase the image brightness, and suppress the noise brought by the amplification of the echo signal intensity;

[0045] When receiving the second-level gain adjustment instruction, the adjustment content is: Based on the fact that the clarity of the current artifact image frame set is sufficient for normal cardiac ultrasound examination, there is no need to perform gain compensation on the echo signals of each frame corresponding to the current artifact image frame set.

[0046] An adaptive adjustment system for the operating parameters of a color ultrasound device, including a data acquisition module, a motion artifact analysis module, a gain degree analysis module, and a level adjustment module;

[0047] The data acquisition module is used to perform frame segmentation on the continuous ultrasonic video stream, construct a set of color Doppler image frames, and obtain the image feature status data information. According to the echo signal reflected from the heart tissue, the echo signal status data information is obtained.

[0048] The motion artifact analysis module is used to correlate the image feature status data information and the echo signal status data information, fit and obtain the motion artifact evaluation coefficient Xwy of several frames. After comparison, the set of artifact image frames is marked, and a gain adjustment analysis instruction is issued.

[0049] The gain degree analysis module is used to collect the blood vessel rigidity status data information in the set of artifact image frames, correlate it with the corresponding motion artifact evaluation coefficient Xwy, and fit and obtain the echo signal gain degree index Zzy of the set of artifact image frames.

[0050] The level adjustment module is used to perform a comparison and analysis on the echo signal gain degree index Zzy of the set of artifact image frames, determine whether the echo signals of each frame corresponding to the current set of artifact image frames need gain compensation, and generate and execute corresponding level gain adjustment instructions.

[0051] The present invention provides a method and system for adaptively adjusting the operating parameters of a color ultrasonic device, having the following beneficial effects:

[0052] (1) By adaptively adjusting the operating parameters of the color ultrasonic device, the quality of ultrasonic imaging can be effectively improved, the interference of motion artifacts can be reduced, and the accuracy and reliability of diagnosis can be improved; this method combines key technologies such as ultrasonic video stream frame segmentation, motion artifact analysis, and echo signal gain adjustment to optimize the clarity and recognizability of ultrasonic images; compared with the traditional method of manually adjusting relying on doctors' experience, this method significantly reduces the dependence on the operator's skill level and improves the convenience and consistency of operation; at the same time, this method can perform real-time evaluation on the propagation characteristics of ultrasonic signals in tissues, combine the acoustic characteristics of biological tissues, dynamically optimize the ultrasonic gain, make the echo signal more stable, and reduce the image blurring problem caused by signal attenuation; in addition, in the application scenarios of cardiovascular diseases and hemodynamic analysis, this method can effectively reduce the interference of the instantaneous dilation of blood vessels on the ultrasonic echo signal, improve the imaging quality of the lesion area, provide more accurate image data support for doctors, and enhance the reliability of clinical diagnosis; through this adaptive adjustment method, the color ultrasonic device can operate more intelligently and efficiently in a complex clinical environment, further improving the universality and accuracy of ultrasonic diagnosis.

[0053] (2) By marking and screening the set of artifact images, the quality of ultrasonic images can be effectively improved, and the impact of artifact interference on clinical diagnosis can be reduced. During the traditional ultrasonic imaging process, artifacts are usually caused by patient tissue movement and changes in the propagation characteristics of ultrasonic signals. These artifact frames may be mixed into the normal imaging sequence, affecting doctors' observation and analysis. Existing ultrasonic devices mainly rely on doctors to manually judge and eliminate low-quality frames, but this method is greatly affected by personal experience, and the screening process is time-consuming and inaccurate. This method automatically evaluates each frame in the ultrasonic video stream through intelligent marking and screening technology, combines machine learning and image processing algorithms, and automatically identifies and marks the set of artifact images. Subsequently, through a dynamic adjustment strategy, the set of artifact images is screened to improve the clarity and stability of ultrasonic imaging. In addition, this method also adjusts the gain value of the echo signal of the ultrasonic device in real time through the analysis of the set of artifact images to reduce the generation of motion artifacts in subsequent frames, making the entire imaging process more intelligent and efficient. This screening strategy can not only improve doctors' work efficiency during the diagnosis process, but also provide more accurate input data for automatic ultrasonic image analysis, improve the accuracy of disease detection and evaluation. Especially in application scenarios with high requirements for image quality in cardiac examinations, it can significantly enhance imaging reliability and provide more powerful support for precision medicine. Description of the Drawings

[0054] Figure 1 Schematic flow chart of an adaptive adjustment method for operating parameters of a color ultrasonic device according to the present invention;

[0055] Figure 2 Block diagram of an adaptive adjustment system for operating parameters of a color ultrasonic device according to the present invention;

[0056] Figure 3 Logic thinking diagram of an adaptive adjustment method for operating parameters of a color ultrasonic device according to the present invention;

[0057] Figure 4 Line graph of the motion artifact evaluation coefficient Xwy. Detailed Embodiments

[0058] 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. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] Embodiment 1

[0060] Please refer to Figure 1 and Figure 3, the present invention provides an adaptive adjustment method for operating parameters of a color ultrasound device, including the following steps:

[0061] S1. Perform frame segmentation on the continuous ultrasound video stream to construct a color Doppler image frame set, and obtain image feature status data information. According to the echo signal reflected from the heart tissue, obtain echo signal status data information;

[0062] S2. Correlate the image feature status data information and the echo signal status data information, fit to obtain the motion artifact evaluation coefficient Xwy of several frames. After comparison, mark the artifact image frame set and issue a gain adjustment analysis instruction;

[0063] S3. Collect the blood vessel rigidity status data information in the artifact image frame set, correlate it with the corresponding motion artifact evaluation coefficient Xwy, and fit to obtain the echo signal gain degree index Zzy of the artifact image frame set;

[0064] S4. Perform comparison and analysis on the echo signal gain degree index Zzy of the artifact image frame set to determine whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, so as to generate corresponding level gain adjustment instructions and execute them.

[0065] Specific process example: During a cardiac ultrasound examination in a certain hospital, a 55-year-old male patient was arranged for an ultrasound examination due to palpitations and chest tightness;

[0066] Step 1. During the cardiac ultrasound examination, use the ultrasound probe in the color ultrasound device to emit high-frequency ultrasonic waves and receive the echo signals reflected from the heart tissue to form a continuous ultrasound video stream. The system performs frame segmentation on the video stream, constructs a color Doppler image frame set, and extracts image feature status data information through histogram equalization. The image brightness value of a certain frame is Dzd = 125; analyze the echo signal, remove non-target frequency band noise through band-pass filtering, and combine Fourier transform to extract echo signal status data information. The echo signal-to-noise ratio Bxz of a certain frame is 22 dB, the echo intensity change rate Vbh is 0.8, and the echo frequency offset Ppy is 1.5 kHz;

[0067] Step 2. Correlate the image feature status data information and the echo signal status data information, calculate the motion artifact change coefficient Xcd, and analyze multiple frames of data. It is found that the motion artifact evaluation coefficient Xwy of 10% of the frames exceeds the mean value. Mark this part of the image frame set as the artifact image frame set and trigger a gain adjustment analysis instruction;

[0068] Step 3: After receiving the gain adjustment analysis instruction, analyze that the average diastolic diameter of the blood vessels in the artifact image frame set is Dsz = 4.2 mm, the average systolic diameter is Dss = 3.8 mm, the average blood vessel pressure is Pny = 120 mmHg, and the total blood vessel length is Lcd = 50 mm. Calculate the blood vessel elasticity coefficient Xtx = 0.018, and combine it with the motion artifact evaluation coefficient Xwy for calculation to obtain the echo signal gain degree index Zzy = 0.75;

[0069] Step 4: Compare the obtained echo signal gain degree index Zzy = 0.75 with the preset degree threshold Y = 0.7, determine that the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, generate and execute a first-level gain adjustment instruction to improve the clarity and quality of the ultrasound video stream segment where the artifact image frame set is located, thereby improving the diagnostic accuracy.

[0070] In this embodiment, by adaptively adjusting the operating parameters of the color ultrasound device, the intelligent optimization of the ultrasound imaging quality is realized. Especially in cardiac ultrasound examinations, the influence of motion artifacts on imaging is effectively reduced; First, through frame segmentation and feature extraction of the ultrasound video stream, and combining Fourier transform to analyze the state of the echo signal, the dynamic changes of the cardiac tissue can be accurately perceived; Subsequently, calculate the motion artifact evaluation coefficient Xwy through relevant fitting, automatically identify and mark the artifact image frame set, providing accurate data support for subsequent gain adjustment; Further, this method combines the interference of the echo signal caused by the instantaneous diastolic of the blood vessels, collects and calculates the echo signal gain degree index Zzy of the artifact image frame set, and performs intelligent comparison and analysis through the preset degree threshold Y, so as to judge whether gain compensation is required and dynamically adjust the gain parameters of the ultrasound device; This method not only reduces the workload of manual adjustment by doctors, improves the accuracy of imaging parameter adjustment, but also can perform adaptive optimization according to the cardiovascular conditions of different patients to ensure the clarity and stability of ultrasound images; Especially for the imaging artifact problem caused by the interference of the instantaneous diastolic of the blood vessels on the echo signal, this method can accurately identify and adjust the gain in real time, ensuring the reliability of clinical diagnosis and providing more powerful technical support for the early detection and accurate evaluation of cardiovascular diseases.

[0071] Embodiment 2

[0072] Please refer to Figure 1 , specifically: S1 specifically includes the following steps:

[0073] S11. During the cardiac ultrasound examination, use the ultrasound probe in the color ultrasound device to emit high-frequency ultrasonic waves, receive the echo signals reflected from the cardiac tissue, use high-speed analog-to-digital conversion to convert the received echo signals into digital signals, and demodulate them through digital signal processing technology to form a continuous ultrasound video stream;

[0074] S12. Perform frame segmentation on the image data in the ultrasonic video stream, extract the color Doppler images of each frame, construct a color Doppler image frame set, and use the histogram equalization algorithm to extract features from the color Doppler image frame set to obtain image feature status data information. Among them, the image feature status data information includes the image brightness value Dzd of each frame;

[0075] It should be noted that the image brightness value Dzd is obtained through the probe sensor in the color ultrasonic device, and is mainly calculated by relying on the echo signal intensity after ultrasonic signal reflection. Specifically, ultrasonic waves are emitted through the probe and enter the body, and then reflect back from tissues or blood flow, and the probe then receives these reflected signals. Through analog-to-digital conversion and digital signal processing technologies, the intensity information of the echo signal is converted into image data; the image brightness value Dzd reflects the brightness information of each region in each frame of the image, representing the intensity of the echo signal and the contrast of the image; it is used to further analyze the dynamic changes of cardiac tissue and the lesion site, help doctors identify blood flow changes, cardiac wall movement and potential abnormalities, ensure the quality of ultrasonic images, and provide support for accurate diagnosis.

[0076] S13. Monitor the status of the echo signal according to the echo signal reflected from the cardiac tissue, remove the noise in the non-target frequency band through band-pass filtering, and combine with Fourier transform to obtain echo signal status data information. Among them, the echo signal status data information includes the echo signal-to-noise ratio Bxz, the echo intensity change rate Vbh, and the echo frequency offset Ppy of each frame;

[0077] It should be noted that the echo signal-to-noise ratio Bxz, the echo intensity change rate Vbh, and the echo frequency offset Ppy are obtained through the ultrasonic probe and digital signal processing system of the color ultrasonic device; first, the ultrasonic probe emits high-frequency ultrasonic waves and receives the echo signals reflected from the cardiac tissue; the echo signal-to-noise ratio Bxz represents the ratio of the effective information to the noise in the echo signal and is an important indicator to measure the signal quality; the echo intensity change rate Vbh reflects the intensity change of the echo signal at different time points; the echo frequency offset Ppy represents the offset of the echo signal frequency relative to the transmitted frequency, especially used for color Doppler imaging; it provides an important basis for the evaluation of cardiac health status and abnormal detection;

[0078] S14. During the cardiac ultrasound examination, keep the frame level of each frame image in the color Doppler image frame set extracted in step S12 in a corresponding relationship with the frame level of each echo signal in the echo signal status data information obtained through echo signal analysis in step S13.

[0079] Specifically, when the ultrasound device acquires each frame of image, it will simultaneously record the echo signal data corresponding to the time point; through the timestamp and synchronization mechanism of the digital signal processing system, it ensures that the state of each frame of image matches the echo signal data received at the same time point, so that the characteristic state data of each frame of image and the state data of the echo signal can be accurately corresponding; this synchronization method can ensure the precise pairing between the image and the signal, so as to realize the effective association and processing of the image quality and the echo signal in the subsequent analysis.

[0080] In this embodiment, during the cardiac ultrasound examination, through a series of efficient data processing steps, the accurate acquisition and intelligent analysis of the operating parameters of the color ultrasound device are realized; first, the ultrasonic probe is used to emit high-frequency ultrasonic waves, and through high-speed analog-to-digital conversion and digital signal processing technology, the received echo signal is converted into a high-precision ultrasonic video stream, laying a foundation for subsequent data analysis; then, the color Doppler image is extracted through frame segmentation, and the histogram equalization algorithm is used to extract the image characteristic state data information; in addition, the noise is removed through band-pass filtering, and the echo signal state information is obtained by combining Fourier transform, realizing the precise monitoring of the echo signal-to-noise ratio Bxz, the echo intensity change rate Vbh and the echo frequency offset Ppy, so as to be able to more comprehensively evaluate the quality of the ultrasound echo signal; it is particularly worth emphasizing that this method ensures the precise frame-level correspondence between the color Doppler image frame set and the echo signal state data information, making the image analysis and the signal analysis completely synchronized in the time dimension, providing more accurate data support for subsequent motion artifact detection and gain adaptive adjustment; this high-precision signal and image linkage analysis method not only improves the adaptability of the ultrasound device to the complex cardiac blood flow environment, but also significantly reduces the imaging instability problem caused by manual adjustment errors, providing a more reliable imaging basis for the accurate diagnosis of cardiovascular diseases.

[0081] Embodiment 3

[0082] Please refer to Figure 1 and Figure 4 , specifically: S2 specifically includes the following steps:

[0083] S21. Based on the content of step S12, feature extraction is performed on the image characteristic state data information. By analyzing the change of the image brightness value Dzd of each frame over time and after dimensionless processing, the motion artifact change coefficient Xcd of the corresponding frame is obtained. Taking the motion artifact change coefficient Xcd of the i-th frame as an example, it is specifically obtained according to the following formula: i For example, it is specifically obtained according to the following formula:

[0084]

[0085] In the formula, Dzd iThe image brightness value represented as the i-th frame, and Δt represents the time interval between two frames of images;

[0086] It should be noted that the motion artifact variation coefficient Xcd is an index used to describe the variation of artifact intensity caused by motion in color ultrasound images; by analyzing the variation of the brightness value of each frame of image over time, the variation of artifacts generated by patient body movement factors in the image is quantified; through dimensionless processing, the scale differences between different images are removed, enabling the comparison and evaluation of the variation of artifacts under a unified standard; the role of the motion artifact variation coefficient Xcd is to help identify and evaluate the motion artifacts in the image, thereby providing a key reference basis in subsequent gain adjustment and image optimization to improve the clarity and diagnostic accuracy of ultrasound images.

[0087] S22. Based on the content of step S13, feature extraction is performed on the echo signal state data information. By correlating the echo signal-to-noise ratio Bxz of each frame with the echo intensity change rate Vbh and the echo frequency offset Ppy of the corresponding frame, the quality state of the echo signal of each frame is analyzed. After dimensionless processing, taking the echo signal stability coefficient Xwd of the i-th frame i as an example, it is specifically obtained according to the following formula:

[0088]

[0089] In the formula, Bxz i represents the echo signal-to-noise ratio of the i-th frame, Vbh i represents the echo intensity change rate of the i-th frame, Ppy i represents the echo frequency offset of the i-th frame.

[0090] It should be noted that the echo signal stability coefficient Xwd is an index used to quantify the stability of the echo signal quality; by correlating the echo signal-to-noise ratio Bxz with the echo intensity change rate Vbh and the echo frequency offset Ppy of the corresponding frame, the stability of the echo signal in different frames is reflected; specifically, the echo signal stability coefficient Xwd helps to evaluate whether the echo signal in each frame of image is affected by interference or instability. Its role is to provide a reliable judgment basis for subsequent image enhancement and gain adjustment, ensuring that the image quality is effectively controlled under dynamically changing conditions, thereby improving the clarity and diagnostic effect of ultrasound images.

[0091] Specifically, S2 specifically further includes the following steps:

[0092] S23. Based on the image feature status data information and the echo signal status data information, by performing linear normalization on the motion artifact change coefficient Xcd of each frame and the echo signal stability coefficient Xwd of the corresponding frame, and mapping the corresponding data values within the interval [0, 1], the motion artifact evaluation coefficient Xwy of the corresponding frame is obtained. Taking the motion artifact evaluation coefficient Xwy of the i-th frame as an example, it is obtained in the following specific manner: i For example, it is obtained in the following specific manner:

[0093]

[0094] In the formula, Xcd i represents the motion artifact change coefficient of the i-th frame, Xwd i represents the echo signal stability coefficient of the i-th frame, both α and β represent weight values, and A represents the first correction constant.

[0095] Specifically, S2 specifically further includes the following steps:

[0096] S24. According to the method of obtaining the motion artifact evaluation coefficient Xwy of the i-th frame in step S23, the motion artifact evaluation coefficients Xwy of several frames are obtained respectively, and according to the statistical mean algorithm, the mean value of the motion artifact evaluation coefficients Xwy of several frames is calculated. i By comparing the motion artifact evaluation coefficients Xwy of several frames with the mean value

[0097] S25. By comparing the motion artifact evaluation coefficients Xwy of several frames with the mean value to obtain the motion artifact evaluation coefficients Xwy of the corresponding frames that exceed the mean value , and mark the set of color Doppler image frames where they are located as the artifact image frame set. When the number of frames in the artifact image frame set exceeds 5% of the total number of frames in the color Doppler image frame set, a gain adjustment analysis instruction is sent out at this time.

[0098] In this embodiment, through the in-depth feature analysis of color ultrasound images and echo signals, the accurate evaluation and intelligent marking of motion artifacts are realized, providing reliable data support for subsequent gain adjustment. First, by analyzing the change of image brightness over time, the motion artifact change coefficient Xcd is calculated to identify the frame images with abnormal brightness fluctuations between frames, improving the perception ability of motion artifacts. At the same time, through the joint analysis of the echo signal-to-noise ratio Bxz, the echo intensity change rate Vbh of the corresponding frame, and the echo frequency offset Ppy, the echo signal stability coefficient Xwd is calculated, enabling not only the identification of artifacts based on image features but also double verification from the perspective of signal quality, enhancing the analysis ability of artifact causes. Further, this method adopts a linear normalization strategy to map the motion artifact change coefficient Xcd and the echo signal stability coefficient Xwd, and combines weight correction to calculate the motion artifact evaluation coefficient Xwy, realizing cross-dimensional data fusion and improving the stability and generalization ability of the evaluation results. In addition, the mean value of the motion artifact evaluation coefficients Xwy of several frames is calculated using statistical methods. and the frames exceeding the mean value are selected as the artifact image frame set, enabling the adaptation to the artifact threshold under different imaging conditions instead of relying on fixed values, enhancing the flexibility and adaptability of the method. It is particularly emphasized that when the number of artifact images exceeds 5% of the total number of frames, a gain adjustment analysis instruction is automatically issued to ensure timely intervention before the artifacts significantly affect the image quality, realizing dynamic and intelligent optimization adjustment of ultrasound signals. This artifact detection method based on multi-dimensional feature correlation, statistical analysis, and intelligent discrimination significantly improves the stability and diagnostic reliability of ultrasound images, reduces diagnostic errors caused by artifacts, and provides important technical support for high-precision medical image analysis.

[0099] Example 4

[0100] Please refer to Figure 1 , specifically: S3 further includes the following steps:

[0101] S31. After receiving the gain adjustment analysis instruction, based on the interference of the instantaneous diastolic of blood vessels in the heart tissue on the echo signal, and combining the Canny edge detection and the statistical mean algorithm, collect the blood vessel rigidity state data information within the artifact image frame set, where the blood vessel rigidity state data information includes the average diameter Dsz of blood vessels in the diastolic phase, the average diameter Dss of blood vessels in the systolic phase, the average value Pny of blood vessel pressure, and the total length Lcd of blood vessels in the artifact image frame set.

[0102] It should be noted that the average diameter Dsz during the vascular diastolic phase, the average diameter Dss during the vascular systolic phase, the average value Pny of the vascular pressure, and the total length Lcd of the blood vessel are key vascular state parameters obtained by an ultrasonic device during echocardiography; these parameters are derived based on the analysis results of echo signals through the movement and echo reflection characteristics of the blood vessel wall; specifically, the average diameters during the vascular diastolic and systolic phases can be calculated by analyzing the morphological changes of the blood vessel at different time points, combining with the Canny edge detection algorithm to extract the blood vessel boundary in the image; the vascular pressure Pny is obtained by analyzing the frequency and intensity changes of the echo signal and combining with the reflection of the ultrasonic wave technology on the force of the blood vessel wall; the total length Lcd of the blood vessel is obtained from the geometric characteristics of the blood vessel in the image; these parameters are crucial for evaluating the rigidity of the blood vessel; through these data, the elasticity of the blood vessel and the interference of the movement on the echo signal can be evaluated more accurately, providing data support for optimizing the quality of the ultrasonic image and improving the diagnostic accuracy.

[0103] S32. Extract features from the vascular rigidity state data information obtained in step S31. After dimensionless processing, fit to obtain the vascular elasticity coefficient Xtx in the artifact image frame set, which is obtained in the following specific manner:

[0104]

[0105] In the formula, Dsz represents the average diameter during the vascular diastolic phase in the artifact image frame set, Dss represents the average diameter during the vascular systolic phase in the artifact image frame set, Pny represents the average value of the vascular pressure in the artifact image frame set, Lcd represents the total length of the blood vessel in the artifact image frame set, where π represents the pi.

[0106] It should be noted that the vascular elasticity coefficient Xtx reflects the response ability of the blood vessel to the echo signal, especially the influence on the echo signal during the change process of the vascular diastolic and systolic phases; when the gain adjustment of the echo signal is not timely or set improperly, the instantaneous dilation of the blood vessel caused by high-speed blood flow may interfere with the echo signal, resulting in the generation of motion artifacts; motion artifacts will affect the quality of the ultrasonic image, making the imaging blurred and even losing important diagnostic information; the vascular elasticity coefficient Xtx provides a method for quantifying the vascular rigidity by evaluating the interference degree of the blood vessel on the echo signal during the diastolic and systolic processes, which helps to adjust the gain of the echo signal more accurately, thereby reducing the influence of artifacts and ensuring the image clarity.

[0107] Specifically, S3 further includes the following steps:

[0108] S33. Associate the vascular elasticity coefficient Xtx of the artifact image frame set with the corresponding motion artifact evaluation coefficient Xwy. After dimensionless processing, and in combination with the echo signal gain algorithm, fit to obtain the echo signal gain degree index Zzy of the artifact image frame set, which is specifically obtained through the following formula;

[0109]

[0110] In the formula, both ε and δ represent weight values, and B represents the second correction constant.

[0111] In this embodiment, by comprehensively analyzing the vascular rigidity state and the degree of motion artifacts, the refined gain adjustment of the artifact image frame set is realized, providing key support for the dynamic optimization of ultrasonic imaging quality. First, based on Canny edge detection and statistical mean calculation, accurately extract the average diastolic diameter Dsz, average systolic diameter Dss, average intravascular pressure Pny, and total vascular length Lcd in the artifact image frame set, and establish the data information of the vascular rigidity state, thus breaking through the limitation of traditional gain adjustment that only relies on echo signals. Further, this method fits the vascular elasticity coefficient Xtx to quantify the elastic characteristics of blood vessels in cardiac tissue, and associates it with the motion artifact evaluation coefficient Xwy, realizing the evaluation of gain adjustment requirements from the dual perspectives of physiological structure and signal quality. Finally, in combination with the echo signal gain algorithm, calculate the echo signal gain degree index Zzy of the artifact image frame set, making the gain adjustment no longer a static adjustment based on fixed parameters, but an adaptive optimization strategy that can adapt to individual differences and dynamic changes. In particular, it is worth emphasizing that this method fuses the vascular rigidity state information with the characteristics of the motion artifact evaluation coefficient Xwy, enabling the gain compensation to accurately match the physiological characteristics in the ultrasonic image, reducing problems such as signal overcompensation and insufficiency caused by improper gain adjustment, significantly improving the clarity and reliability of ultrasonic imaging, and providing more accurate image support for cardiovascular ultrasonic diagnosis.

[0112] Embodiment 5

[0113] Please refer to Figure 1 , specifically: The specific steps of S4 include:

[0114] S41. Preset a degree threshold Y. By comparing and analyzing the echo signal gain degree index Zzy of the artifact image frame set with the degree threshold Y, determine whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, so as to generate corresponding level gain adjustment instructions. The specific content is as follows:

[0115] When the echo signal gain degree index Zzy of the artifact image frame set is greater than or equal to the degree threshold Y, it indicates that the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, which means that the clarity of the current artifact image frame set is not sufficient for normal cardiac ultrasound examination, and a first-level gain adjustment instruction is generated;

[0116] When the echo signal gain degree index Zzy of the artifact image frame set is less than the degree threshold Y, it indicates that the echo signals of each frame corresponding to the current artifact image frame set do not need gain compensation, which means that the clarity of the current artifact image frame set is sufficient for normal cardiac ultrasound examination, and a second-level gain adjustment instruction is generated.

[0117] Specifically, the specific steps of S4 also include:

[0118] S42. According to the first-level gain adjustment instruction and the second-level gain adjustment instruction issued in step S41, execute the corresponding echo signal gain adjustment content, and the specific execution content is as follows:

[0119] When receiving the first-level gain adjustment instruction, the adjustment content to be executed is: Based on the fact that the clarity of the current artifact image frame set is not sufficient for normal cardiac ultrasound examination, rescan the ultrasound video stream segment where the artifact image frame set is located, and use the gain controller and low-pass filter in the color ultrasound device, combined with the time-domain gain adjustment method, to amplify the echo signal intensity, simultaneously increase the image brightness, and suppress the noise brought by the amplification of the echo signal intensity;

[0120] It should be noted that the role of the gain controller is to amplify the echo signal, enhance the intensity of the echo signal, thereby increasing the brightness and visibility of the image; in order to prevent the influence of the noise generated after gain amplification on the image quality, a low-pass filter is added to filter the signal; the low-pass filter can effectively suppress high-frequency noise and retain low-frequency signals, which is crucial for removing the interference caused by excessive gain of the echo signal in the image; through the low-pass filter, it is ensured that the quality of the echo signal will not be overly interfered, and the image is clearer; the time-domain gain adjustment method dynamically adjusts the gain of the echo signal, based on the characteristics of the time series, to optimize the intensity of the echo signal frame by frame; through time-domain gain adjustment, the gain of each frame signal can be flexibly adjusted to ensure the stability and uniformity of the signal intensity at different time points; this not only enhances the image brightness but also avoids image distortion or noise caused by excessive enhancement; through this series of technical means, the combined effects of gain control, low-pass filtering, and time-domain adjustment significantly improve the image quality, thereby providing a clearer and more accurate image for cardiac ultrasound examination and reducing the interference of artifacts on the diagnostic results.

[0121] When receiving a secondary gain adjustment instruction, the adjustment content is as follows: Based on the clarity of the current artifact image frame set being sufficient for normal cardiac ultrasound examination, there is no need to perform gain compensation on the echo signals of each frame corresponding to the current artifact image frame set.

[0122] In this embodiment, by presetting the degree threshold Y and combining it with the echo signal gain degree index Zzy, an accurate gain compensation decision is made for the artifact image frame set, realizing dynamic adjustment and adaptive optimization in the ultrasonic imaging process; when the echo signal gain degree index Zzy of the artifact image frame set is greater than or equal to the degree threshold Y, a primary gain adjustment instruction is automatically generated, indicating that the current image clarity is insufficient and a rescan is required and the echo signal is enhanced, so as to ensure that the image quality is sufficient to support accurate cardiac ultrasound diagnosis; on the contrary, when the echo signal gain degree index Zzy is less than the degree threshold Y, a secondary gain adjustment instruction is generated to avoid unnecessary gain compensation, effectively reducing the noise impact that may be brought by excessive image enhancement, ensuring that the image clarity is moderate and meets the diagnostic requirements; this method can not only meet different image quality requirements by flexibly adjusting the gain compensation strategy, but also effectively suppress noise while improving the imaging quality, optimizing the signal processing in the ultrasonic diagnosis process, and improving the diagnostic efficiency and accuracy; through this refined gain control, the image clarity is improved, effectively avoiding the diagnostic risks brought by excessive gain or insufficient gain, and providing more reliable image support for the accurate diagnosis of diseases.

[0123] Embodiment 6

[0124] Please refer to Figure 1 and Figure 2 , specifically: An adaptive adjustment system for the operating parameters of a color ultrasonic device, including a data acquisition module, a motion artifact analysis module, a gain degree analysis module, and a level adjustment module;

[0125] The data acquisition module is used to perform frame segmentation on the continuous ultrasonic video stream to construct a color Doppler image frame set, and obtain the image feature state data information, and obtain the echo signal state data information according to the echo signal reflected from the cardiac tissue.

[0126] The motion artifact analysis module is used to correlate the image feature state data information and the echo signal state data information, fit and obtain the motion artifact evaluation coefficients Xwy of several frames, and after comparison, mark out the artifact image frame set and issue a gain adjustment analysis instruction.

[0127] The gain degree analysis module is used to collect the blood vessel rigidity state data information in the artifact image frame set, and correlate it with the corresponding motion artifact evaluation coefficient Xwy, and fit and obtain the echo signal gain degree index Zzy of the artifact image frame set.

[0128] The level adjustment module is used to compare and analyze the echo signal gain degree index Zzy of the artifact image frame set, determine whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, and generate corresponding level gain adjustment instructions for execution.

[0129] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An adaptive adjustment method for operating parameters of a color ultrasound device, characterized in that: It includes the following steps: S1. Perform frame segmentation on the formed continuous ultrasonic video stream, construct a color Doppler image frame set, and obtain image feature status data information. According to the echo signal reflected from the heart tissue, obtain echo signal status data information; S2. Correlate the image feature status data information and the echo signal status data information, fit to obtain the motion artifact evaluation coefficient Xwy of several frames. After comparison, mark the artifact image frame set and issue a gain adjustment analysis instruction; S3. Collect the blood vessel rigidity status data information in the artifact image frame set, correlate it with the corresponding motion artifact evaluation coefficient Xwy, and fit to obtain the echo signal gain degree index Zzy of the artifact image frame set; S4. Conduct a comparison analysis on the echo signal gain degree index Zzy of the artifact image frame set to determine whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, so as to generate corresponding level gain adjustment instructions and execute them.

2. The adaptive adjustment method for operating parameters of a color ultrasound device according to claim 1, characterized in that: S1 specifically includes the following steps: S11. During cardiac ultrasound examination, use the ultrasonic probe in the color ultrasound device to emit high-frequency ultrasonic waves, receive the echo signal reflected from the heart tissue, use high-speed analog-to-digital conversion to convert the received echo signal into a digital signal, and demodulate it through digital signal processing technology to form a continuous ultrasonic video stream; S12. Perform frame segmentation on the image data in the ultrasonic video stream, extract the color Doppler image of each frame, construct a color Doppler image frame set, and use the histogram equalization algorithm to extract features from the color Doppler image frame set to obtain image feature status data information. Among them, the image feature status data information includes the image brightness value Dzd of each frame; S13. Monitor the status of the echo signal according to the echo signal reflected from the heart tissue, remove the noise in the non-target frequency band through band-pass filtering, and combine with Fourier transform to obtain the echo signal status data information. Among them, the echo signal status data information includes the echo signal-to-noise ratio Bxz, the echo intensity change rate Vbh, and the echo frequency offset Ppy of each frame; S14. During cardiac ultrasound examination, keep the frame level of each frame image in the color Doppler image frame set extracted in step S12 corresponding to the frame level of each echo signal in the echo signal status data information obtained through echo signal analysis in step S13.

3. The adaptive adjustment method for operating parameters of a color ultrasound device according to claim 2, characterized in that: S2 specifically includes the following steps: S21. Based on the content of step S12, feature extraction is performed on the image feature status data information. By analyzing the change of the image brightness value Dzd of each frame over time, after dimensionless processing, the motion artifact change coefficient Xcd of the corresponding frame is obtained. Taking the motion artifact change coefficient Xcd of the i-th frame as an example, it is specifically obtained according to the following formula: i For example, it is obtained specifically according to the following formula: where Dzd i represents the image luminance value of the i-th frame, and Δt represents the time interval between two frames of images; S22. Based on the content of step S13, feature extraction is performed on the echo signal state data information. By correlating the echo signal-to-noise ratio Bxz of each frame with the echo intensity change rate Vbh and the echo frequency offset Ppy of the corresponding frame, the quality state of the echo signal of each frame is analyzed. After dimensionless processing, the echo signal stability coefficient Xwd of the i-th frame is obtained specifically according to the following formula: i For example, it is obtained specifically according to the following formula: Wherein, Bxz i represents the echo signal-to-noise ratio of the i-th frame, Vbh i represents the echo intensity change rate of the i-th frame, Ppy i represents the echo frequency offset of the i-th frame.

4. The adaptive adjustment method for operating parameters of a color ultrasound device according to claim 3, characterized in that: S2 specifically further includes the following steps: S23. Based on the image feature status data information and the echo signal status data information, by performing linear normalization on the motion artifact change coefficient Xcd of each frame and the echo signal stability coefficient Xwd of the corresponding frame, and mapping the corresponding data values within the interval [0, 1], the motion artifact evaluation coefficient Xwy of the corresponding frame is obtained. Taking the motion artifact evaluation coefficient Xwy of the i-th frame as an example, it is obtained in the following specific manner: i For example, it is obtained in the following specific manner: where Xcd i represents the motion artifact variation coefficient of the i-th frame, Xwd i represents the echo signal stability coefficient of the i-th frame, both α and β represent weight values, and A represents a first correction constant.

5. The adaptive adjustment method for operating parameters of a color ultrasound device according to claim 4, characterized in that: S2 specifically further includes the following steps: S24. Obtain the motion artifact evaluation coefficient Xwy of the i-th frame according to step S23 i In the above manner, obtain the motion artifact evaluation coefficients Xwy of several frames respectively, and calculate the mean value of the motion artifact evaluation coefficients Xwy of several frames according to the statistical mean algorithm S25. By comparing the motion artifact evaluation coefficients Xwy of several frames with the mean value in terms of magnitude, obtaining the motion artifact evaluation coefficients Xwy of the corresponding frames that exceed the mean value , and marking the set of color Doppler image frames where they are located as the artifact image frame set. When the number of frames in the artifact image frame set exceeds 5% of the total number of frames in the color Doppler image frame set, a gain adjustment analysis instruction is sent out at this time.

6. The adaptive adjustment method for the operating parameters of a color ultrasound device according to claim 5, characterized in that: S3 specifically includes the following steps: S31. After receiving the gain adjustment analysis instruction, based on the interference of the echo signal by the instantaneous diastolic of blood vessels in the heart tissue, and combining the Canny edge detection and the statistical mean algorithm, collect the blood vessel rigidity status data information in the artifact image frame set. Among them, the blood vessel rigidity status data information includes the average diameter Dsz of blood vessels in the diastolic phase, the average diameter Dss of blood vessels in the systolic phase, the average value Pny of blood vessel pressure, and the total length Lcd of blood vessels in the artifact image frame set; S32. Extract features from the vascular rigidity state data information obtained in step S31. After dimensionless processing, fit to obtain the vascular elasticity coefficient Xtx in the artifact image frameset, which is obtained specifically in the following manner: In the formula, Dsz represents the average diameter of the blood vessels in the diastolic phase in the artifact image frameset, Dss represents the average diameter of the blood vessels in the systolic phase in the artifact image frameset, Pny represents the average value of the blood pressure inside the blood vessels in the artifact image frameset, Lcd represents the total length of the blood vessels in the artifact image frameset, where π represents the pi.

7. An adaptive adjustment method for operating parameters of a color ultrasound device according to claim 6, characterized in that: S3 specifically further includes the following steps: S33. Associate the vascular elasticity coefficient Xtx of the artifact image frameset with the corresponding motion artifact evaluation coefficient Xwy. After dimensionless processing, and combined with the echo signal gain algorithm, fit to obtain the echo signal gain degree index Zzy of the artifact image frameset, which is obtained specifically through the following formula; In the formula, both ε and δ represent weight values, and B represents the second correction constant.

8. An adaptive adjustment method for operating parameters of a color ultrasound device according to claim 7, characterized in that: The specific steps of S4 include: S41. Preset the degree threshold Y. By comparing and analyzing the echo signal gain degree index Zzy of the artifact image frameset with the degree threshold Y, determine whether the echo signals of each frame corresponding to the current artifact image frameset need gain compensation, so as to generate corresponding level gain adjustment instructions. The specific content is as follows: If the echo signal gain degree index Zzy of the artifact image frameset ≥ the degree threshold Y, it means that the echo signals of each frame corresponding to the current artifact image frameset need gain compensation, indicating that the clarity of the current artifact image frameset is not sufficient for normal cardiac ultrasound examination, and generate a first-level gain adjustment instruction; If the echo signal gain degree index Zzy of the artifact image frameset < the degree threshold Y, it means that the echo signals of each frame corresponding to the current artifact image frameset do not need gain compensation, indicating that the clarity of the current artifact image frameset is sufficient for normal cardiac ultrasound examination, and generate a second-level gain adjustment instruction.

9. An adaptive adjustment method for operating parameters of a color ultrasound device according to claim 8, characterized in that: The specific steps of S4 further include: S42. According to the first-level gain adjustment instruction and the second-level gain adjustment instruction issued in step S41, execute the corresponding echo signal gain adjustment content. The specific execution content is as follows: When receiving the first-level gain adjustment instruction, the execution content is: Based on the fact that the clarity of the current artifact image frameset is not sufficient for normal cardiac ultrasound examination, rescan the ultrasound video stream segment where the artifact image frameset is located, and use the gain controller and low-pass filter in the color ultrasound device, combined with the time-domain gain adjustment method, to amplify the echo signal intensity, simultaneously increase the image brightness, and suppress the noise brought by the amplification of the echo signal intensity; When receiving the second-level gain adjustment instruction, the execution content is: Based on the fact that the clarity of the current artifact image frameset is sufficient for normal cardiac ultrasound examination, there is no need to perform gain compensation on the echo signals of each frame corresponding to the current artifact image frameset.

10. An adaptive adjustment system for operating parameters of a color ultrasound device, which is used to implement the adaptive adjustment method for operating parameters of a color ultrasound device according to any one of the above claims 1 to 9, characterized in that: Including a data acquisition module, a motion artifact analysis module, a gain degree analysis module, and a level adjustment module; The data acquisition module is used to perform frame segmentation on the continuous ultrasonic video stream, construct a color Doppler image frame set, obtain the image feature status data information, and obtain the echo signal status data information according to the echo signal reflected from the heart tissue; The motion artifact analysis module is used to correlate the image feature status data information and the echo signal status data information, fit and obtain the motion artifact evaluation coefficient Xwy of several frames. After comparison, the artifact image frame set is marked, and a gain adjustment analysis instruction is issued; The gain degree analysis module is used to collect the blood vessel rigidity status data information in the artifact image frame set, correlate it with the corresponding motion artifact evaluation coefficient Xwy, and fit and obtain the echo signal gain degree index Zzy of the artifact image frame set; The level adjustment module is used to perform a comparison analysis on the echo signal gain degree index Zzy of the artifact image frame set, determine whether the echo signals of each frame corresponding to the current artifact image frame set need gain compensation, and generate and execute corresponding level gain adjustment instructions.

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