A medical ultrasound image intelligent processing method and system

Abstract

This embodiment relates to an intelligent medical ultrasound image processing method and system. The target's output alternating voltage waveform is determined by invoking the cycle length and duty cycle of output PWM data. By inputting the target's output alternating voltage waveform into the steady-state function of a MOS transistor assembly, the induced electric field applied to the piezoelectric material can be determined. The piezoelectric material emits ultrasonic waves, which contact the target object, generating an abnormal wave. This abnormal wave, acting as a mechanical wave in the environment, can superimpose with the output mechanical wave to form an echo. The output mechanical wave and the received superimposed echo are analyzed. The echo data analysis identifies the abnormal wave, which is a characteristic echo. An ultrasound image is generated based on the characteristic echo-to-image function. The steady-state function of the MOS transistor assembly is used to analyze the induced electric field deformation during the startup and steady-state processes of the field-effect transistor, thereby reducing the blurriness of the ultrasound image.

Description

Technical Field

[0001] The present application relates to the field of medical device technology, and in particular to a method and system for intelligent processing of medical ultrasound images. Background Art

[0002] Ultrasonic technology uses high-frequency oscillations in a circuit to apply an alternating voltage to a piezoelectric material, causing it to generate high-frequency mechanical vibrations, thereby producing ultrasonic waves. Piezoelectric materials convert electrical energy into mechanical energy. When the ultrasonic wave strikes the object being measured, it generates an echo. The echo receiving circuit receives this echo and generates a digital signal. A processor processes this digital signal to generate an ultrasonic image.

[0003] Because traditional circuit high-frequency oscillation generators use field-effect transistors as their core oscillator, the startup and steady-state processes of the field-effect transistors affect the blurriness of ultrasound images. Therefore, it is necessary to propose an intelligent medical ultrasound image processing method and system to address the drawback of the relatively blurry imaging results of traditional ultrasound images. Summary of the Invention

[0004] Based on this, it is necessary to propose an intelligent processing method and system for medical ultrasound images to address the defect that traditional ultrasound imaging results are relatively fuzzy.

[0005] This application provides a method for intelligent processing of medical ultrasound images, comprising:

[0006] Call the cycle length and duty cycle of the output PWM data;

[0007] Based on the steady-state function of the MOS tube set, the wave function of the output ultrasonic wave is determined;

[0008] Receive echo data;

[0009] According to the echo data analysis function, the characteristic echo to be cleaned is obtained;

[0010] Based on the ultrasonic wave function, the fuzzy parameters of the characteristic echo to be cleaned are fitted;

[0011] Obtain characteristic echo;

[0012] An ultrasound image is formed based on a characteristic echo-to-image function.

[0013] The present application also provides a medical ultrasound image intelligent processing system.

[0014] A medical ultrasound image intelligent processing system, comprising:

[0015] A processor, configured to execute the medical ultrasound image intelligent processing method;

[0016] a mechanical wave circuit electrically connected to the processor;

[0017] A display is electrically connected to the processor.

[0018] This application relates to an intelligent medical ultrasound image processing method and system. The target's output alternating voltage waveform is determined by invoking the cycle length and duty cycle of output PWM data. By inputting the target's output alternating voltage waveform into the steady-state function of a MOS transistor assembly, the induced electric field applied to the piezoelectric material can be determined. The piezoelectric material emits ultrasonic waves, which contact the target object, generating an abnormal wave. This abnormal wave, acting as a mechanical wave in the environment, can superimpose with the output mechanical wave to form an echo. The output mechanical wave and the received superimposed echo are analyzed. The echo data analysis identifies the abnormal wave. This abnormal wave is the characteristic echo, and an ultrasound image is formed based on the characteristic echo-to-image function. When ultrasound waves propagate from one material to another with a different acoustic impedance, two things occur. Some of the ultrasound waves continue to enter the second material, but slightly deviate from their original direction. When ultrasound waves propagate from one material to another with a different acoustic impedance, this bending is called refraction.

[0019] In addition, some of the sound waves are reflected back to the probe. The amount of reflection depends on the difference in acoustic impedance between the two materials; the greater the difference, the stronger the reflection. These reflected waves are crucial because only the reflected waves can reach the detector and provide the information needed to display the image.

[0020] As ultrasound waves travel from one tissue to the next, each tissue having a different acoustic impedance, some of the waves are reflected back at each intersection. As a result, multiple reflected waves return to the probe, and the machine uses this information to create an image showing the different tissues.

[0021] Compressing the wave into a smaller length means that the wave's oscillations between high and low pressure areas become more concentrated. As the wave is compressed, it has more oscillations (high and low pressure areas) per second than before (i.e., its frequency increases). The waves reflected by an object moving toward the probe have a higher frequency than the waves that were emitted.

[0022] The Doppler effect also occurs when an object moves away from the transmitting probe. Again, there's a difference between the frequencies of the transmitted and returning waves. However, this time, the frequency of the returning waves is lower than the frequency of the transmitted waves. The faster the object moves, the greater the frequency difference. The reason for this drop in frequency is the opposite of the explanation given previously. In this case, the moving object "stretches" the waves. This stretching reduces the number of oscillations per second.

[0023] By using the steady-state function of the MOS tube set to analyze the induced electric field deformation during the startup process and steady-state process of the field effect transistor, the ambiguity of the ultrasound image can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings constituting a part of this application are used to provide a further understanding of this application and make other features, purposes and advantages of this application more apparent. The drawings and descriptions of the exemplary embodiments of this application are used to explain this application and do not constitute an improper limitation on this application.

[0025] Figure 1 A flowchart of a method for intelligent processing of medical ultrasound images provided in one embodiment of the present application.

[0026] Figure 2 This is a structural connection diagram of a medical ultrasound image intelligent processing system provided in one embodiment of the present application.

[0027] Reference numerals:

[0028] 100-processor; 200-mechanical wave circuit; 300-display. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0030] The present application provides a method for intelligent processing of medical ultrasound images.

[0031] like Figure 1 As shown, in one embodiment of the present application, a medical ultrasound image intelligent processing method includes:

[0032] S100, calling the cycle length and duty cycle of the output PWM data.

[0033] S200 , determining a wave function of output ultrasonic waves based on a steady-state function of the MOS tube set.

[0034] S300, receiving echo data.

[0035] S400 , obtaining characteristic echoes to be cleaned according to an echo data analysis function.

[0036] S500: fitting fuzzy parameters of the characteristic echo to be cleaned based on the ultrasonic wave function.

[0037] S600: Acquire a characteristic echo.

[0038] S700 , forming an ultrasound image based on a characteristic echo-to-image function.

[0039] This embodiment relates to an intelligent medical ultrasound image processing method. The target's output alternating voltage waveform is determined by invoking the cycle length and duty cycle of output PWM data. By inputting the target's output alternating voltage waveform into the steady-state function of a MOS transistor assembly, the induced electric field applied to the piezoelectric material can be determined. The piezoelectric material emits ultrasonic waves, which contact the target object, generating an abnormal wave. This abnormal wave, acting as a mechanical wave in the environment, can superimpose with the output mechanical wave to form an echo. The output mechanical wave and the received superimposed echo are analyzed. The echo data analysis identifies the abnormal wave. This abnormal wave is the characteristic echo, and an ultrasound image is generated based on the characteristic echo-to-image function. Using the steady-state function of the MOS transistor assembly, the induced electric field deformation during the startup and steady-state processes of the field-effect transistor can be analyzed to reduce ultrasound image blur.

[0040] In one embodiment of the present application, S100 includes:

[0041] S111, determining the cycle length of the output PWM data.

[0042] S112 , determining the accumulated amount of the output PWM voltage over time in a full cycle based on the cycle length of the output PWM data and the voltage intensity of the output PWM data.

[0043] S113, based on the duty cycle of the output PWM data.

[0044] S114, storing the output PWM data including the accumulated amount of the output PWM voltage over time.

[0045] S115 , defining the output PWM data to include the accumulated amount of the voltage for outputting the PWM over time as the accumulated amount of voltage.

[0046] Specifically, multiplying the PWM signal increases the frequency of the PWM signal, but does not change the duty cycle. If the multiplied PWM frequency is greater than the resolution of the processor I / O, the piezoelectric material will default to analog input and can be input to the analog I / O.

[0047] Typically, the PWM duty cycle is calculated by converting the accumulated voltage over time, which is used to output PWM data. A program is written in the processor to measure the duration of the PWM signal's high level, thereby calculating the accumulated voltage corresponding to the duty cycle.

[0048] In one embodiment of the present application:

[0049] S121, determining the cycle length of the output PWM data.

[0050] S122 , determining the accumulated amount of the output PWM current over time in a full cycle based on the cycle length of the output PWM data and the current intensity of the output PWM data.

[0051] S123, based on the duty cycle of output PWM data.

[0052] S124, storing the output PWM data including the accumulated amount of the output PWM current over time.

[0053] S125 , defining the accumulated amount of the current for outputting the PWM data over time as the accumulated current.

[0054] Specifically, the accumulated current over time, which is used to output PWM data, can be used to multiply the PWM signal, increasing its frequency without changing its duty cycle. If the multiplied PWM frequency exceeds the resolution of processor I / O, the piezoelectric material will automatically interpret it as an analog quantity and thus input it into analog I / O.

[0055] Generally speaking, for milliampere currents, PWM frequency multiplication technology can be used to achieve a frequency greater than the resolution of processor I0 after PWM frequency multiplication, so that the piezoelectric material defaults to the I0 output end as an analog quantity, which can be input into the analog quantity I / 0.

[0056] In one embodiment of the present application, S100 further includes:

[0057] S131 , determining a target voltage fluctuation function based on the voltage accumulation amount and the cycle length of the output PWM data.

[0058] S132: Determine a target current fluctuation function based on the current accumulation amount and the cycle length of the output PWM data.

[0059] Specifically, the GP8101 is an electrical component that takes a 0%-100% duty cycle PWM signal Q input and linearly converts it into a 0-5V or 0-10V analog voltage output. The GP8101M takes a 0%-100% duty cycle high-frequency modulated PWM signal input and linearly converts it into a 0-5V or 0-10V analog voltage output. This chip should be used in conjunction with a high-frequency modulation APC chip (GP9301M, GP9303M, etc.) for capacitive or transformer isolation of analog signals. The input signal range is 0%-100%. The input PWM signal high level is 3.0V-5.5V, the output voltage error is <1% (0.5%), and the output voltage linearity error is <0.5% (0.2%). The power supply voltage is 10V-15V, the power consumption is <2mA, the startup time is <2ms, and the operating temperature range is -40°C to 85°C.

[0060] In one embodiment of the present application, S200 includes:

[0061]

[0062] Among them, E p is the induced electric field, V' is the starting voltage, is the deformed magnetic field, r is the basic magnetic field width, that is, the equivalent width of the electrical device, and r' is the distance between the target area and the basic magnetic field.

[0063] The changing induced magnetic field can be measured by a magnetic field sensor.

[0064] As you can understand, when a conductive medium is present, the electric field induced by the time-varying magnetic field of the quasistatic field generates an induced current in the conductive medium. This induced current is equal to the conduction current generated by the excitation source (and its magnitude is not negligible), generating a magnetic field. The distribution of the electric field around conductors in a quasistatic system has important engineering implications. For example, the insulation of power transformer windings relies on the quasistatic electric field.

[0065] In a magnetoquasistatic system, it is assumed that the conductor is a good conductor (approximately a perfectly pure conductor), and the surrounding insulating material is a linear dielectric. Because the charge relaxation time in a good conductor is much shorter than the timescales used in engineering, there is no space charge density within the conductor. Furthermore, the charge relaxation time in insulating materials (including lossy dielectrics) is very long, but for a uniform linear dielectric, there is no free charge density within the dielectric either.

[0066] Therefore, an induced current will be generated in a high-frequency electric field, and this induced current will generate a parasitic magnetic field. The electromagnetic environment such as the induced electric field and the parasitic magnetic field will affect the blurriness of the ultrasound image.

[0067] S210 , incorporating the target voltage fluctuation function into Formula 1.

[0068] S220, obtaining a fluctuation function of the output voltage.

[0069] S310, defining the waveform of the output mechanical wave to be the same as the waveform of the wave function of the output voltage.

[0070] Specifically, the mechanical wave pattern is the same as the wave pattern of the output voltage fluctuation function, and the cycle length and duty cycle of the output PWM data are linked to the output voltage fluctuation function, effectively reducing the blurriness of the image.

[0071] In one embodiment of the present application, S200 further includes:

[0072]

[0073] Among them, F(T) is the echo after superposition, F(t1) is the mechanical wave after contact with the environment, F(t2) is the output mechanical wave, q is the environmental adjustment constant, C1 is the amplitude of the mechanical wave after contact with the environment, ω1 is the inverse of the frequency of the mechanical wave after contact with the environment, C2 is the amplitude of the output mechanical wave, ω2 is the inverse of the frequency of the output mechanical wave, and ζ is the superposition damping.

[0074] Specifically, superimposed damping is related to the attenuation rate of vibration, and the attenuation rate is often expressed as Calculated by the method.

[0075] The relationship between superimposed damping and the vibration attenuation rate is linear with a constant coefficient. When using the fuzzy algorithm, this embodiment ignores the constant coefficient, thereby improving the effectiveness of mechanical wave analysis in complex environments.

[0076] In fact, when working with large amounts of monitoring data, due to the superposition of mechanical waves, the superposition damping is small and approaches zero, so the superposition damping can take a non-zero constant. When the superposition damping takes a constant less than 1, it can adjust the high-frequency mechanical waves in the strong environment.

[0077] When the superimposed damping takes a constant greater than 1, the low-frequency mechanical waves in the fundamental mechanical waves of the weaker environment can be adjusted.

[0078] When ultrasound waves pass from one material to another with a different acoustic impedance, two things happen. Some of the ultrasound waves continue into the second material, but are slightly deflected from their original direction. This bending of ultrasound waves as they pass from one material to another with a different acoustic impedance is called refraction.

[0079] In addition, some of the sound waves are reflected back to the probe. The amount of reflection depends on the difference in acoustic impedance between the two materials; the greater the difference, the stronger the reflection. These reflected waves are crucial because only the reflected waves can reach the detector and provide the information needed to display the image.

[0080] As ultrasound waves travel from one tissue to the next, each tissue having a different acoustic impedance, some of the waves are reflected back at each intersection. As a result, multiple reflected waves return to the probe, and the machine uses this information to create an image showing the different tissues.

[0081] Compressing the wave into a smaller length means that the wave's oscillations between high and low pressure areas become more concentrated. As the wave is compressed, it has more oscillations (high and low pressure areas) per second than before (i.e., its frequency increases). The waves reflected by an object moving toward the probe have a higher frequency than the waves that were emitted.

[0082] The Doppler effect also occurs when an object moves away from the transmitting probe. Again, there's a difference between the frequencies of the transmitted and returning waves. However, this time, the frequency of the returning waves is lower than the frequency of the transmitted waves. The faster the object moves, the greater the frequency difference. The reason for this drop in frequency is the opposite of the explanation given previously. In this case, the moving object "stretches" the waves. This stretching reduces the number of oscillations per second.

[0083] In one embodiment of the present application, S700 includes:

[0084] S710: Generate a cross-platform computer vision library calling function based on the cross-platform computer vision library.

[0085] S720: Generate a connection function using the type managed by the system.

[0086] S730, incorporate the cross-platform computer vision library calling function and connection function into the feature echo-to-image function.

[0087] Specifically, OpenCV (open source computer vision library) is a cross-platform computer vision library distributed based on BSD open source, running on Linux, Windows, Android, and Mac OS operating systems. It is lightweight and efficient—composed of a series of C functions and a small number of C++ classes, it also provides interfaces for languages ​​such as Python, Ruby, and MATLAB, implementing many common algorithms for image processing and computer vision. OpenCV is written in C++, and its primary interface is also in C++, but it still retains a large number of C language interfaces. In the development of computer vision projects, OpenCV, as a relatively popular open source library, has a rich library of commonly used image processing functions. Written in C / C++, it can run on operating systems such as Linux, Windows, and Mac, and can quickly implement a number of image processing and recognition tasks. OpenCV also provides interfaces for Java, Python, CUDA, and other languages, as well as the invocation of basic machine learning algorithms.

[0088] As a part of the image recognition function, the connection function can connect the operation program of the processor and the storage calling program of the memory.

[0089] The connection function can also connect the processor's operation program and the cloud storage call program, and the connection function can connect the processor's operation program and the cloud operation program, thereby realizing the processor's high applicability in complex light wave parsing and analysis environments.

[0090] The present application provides a medical ultrasound image intelligent processing system.

[0091] like Figure 1 As shown, in one embodiment of the present application, a medical ultrasound image intelligent processing system includes:

[0092] The processor 100 is used to execute the medical ultrasound image intelligent processing method.

[0093] The mechanical wave circuit 200 is electrically connected to the processor 100 .

[0094] The display 300 is electrically connected to the processor 100 .

[0095] This embodiment relates to an intelligent medical ultrasound image processing system. The processor 100 determines the target's output alternating voltage waveform by invoking the cycle length and duty cycle of output PWM data. By inputting the target's output alternating voltage waveform into the steady-state function of a MOS transistor assembly, the induced electric field applied to the piezoelectric material of the mechanical wave circuit 200 can be determined. The piezoelectric material emits ultrasonic waves, which contact the target object, generating an abnormal wave. This abnormal wave, acting as an environmental mechanical wave, can superimpose with the output mechanical wave to form an echo. The output mechanical wave and the received superimposed echo are analyzed. The echo data analysis identifies the abnormal wave. This abnormal wave is the characteristic echo. Based on the characteristic echo-to-image function, an ultrasound image is generated and displayed on the display 300. By using the steady-state function of the MOS transistor assembly to analyze the induced electric field deformation during the startup and steady-state processes of the field-effect transistor, the blurriness of the ultrasound image can be reduced.

[0096] As you can understand, a medical ultrasound diagnostic instrument consists of two main components: the processor 100 in the main unit and the mechanical wave circuit 200 of the ultrasound probe. The main unit primarily processes and displays the signals received from the probe. The ultrasound probe transmits and receives ultrasound waves, converting electrical signals sent from the main unit into high-frequency oscillating ultrasound signals. It also converts ultrasound signals reflected from tissues and organs into electrical signals, which are then displayed on the main unit's display 300.

[0097] The various technical features of the above-described embodiments can be combined arbitrarily, and the execution order of the method steps is not restricted. In order to make the description concise, not all possible combinations of the various technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0098] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A medical ultrasound image intelligent processing method, characterized in that: include: Call the cycle length and duty cycle of the output PWM data; Based on the steady-state function of the MOS tube set, the wave function of the output ultrasonic wave is determined; Formula 1, where is the induced electric field, is the starting voltage, is the deformed magnetic field, r is the basic magnetic field width, that is, the equivalent width of the electrical device, is the distance between the target area and the basic magnetic field; Receive echo data; define the output mechanical wave pattern to be the same as the wave pattern of the output voltage fluctuation function; in, is the echo after superposition, is the mechanical wave after contacting the environment, is the output mechanical wave, is the environmental regulation constant, is the amplitude of the mechanical wave after contact with the environment, is the inverse of the frequency of the mechanical wave after contact with the environment, is the amplitude of the output mechanical wave, is the inverse of the frequency of the output mechanical wave, is the superimposed damping; According to the echo data analysis function, the characteristic echo to be cleaned is obtained; Based on the ultrasonic wave function, the fuzzy parameters of the characteristic echo to be cleaned are fitted; Obtain characteristic echo; An ultrasound image is formed based on a characteristic echo-to-image function.

2. The medical ultrasound image intelligent processing method according to claim 1, characterized in that: The calling output PWM data cycle length and duty cycle, including: Determine the cycle length of the output PWM data; Based on the cycle length of the output PWM data and the voltage intensity of the output PWM data, the accumulated amount of the output PWM voltage over time in the full cycle is determined; Based on the duty cycle of output PWM data; The output PWM data is stored in the accumulated amount of the output PWM voltage over time; The output PWM data is defined as the voltage accumulation amount of the output PWM over time.

3. The medical ultrasound image intelligent processing method according to claim 2, characterized in that: The calling of the cycle length and duty cycle of the output PWM data further includes: Determine the cycle length of the output PWM data; Based on the cycle length of the output PWM data and the current intensity of the output PWM data, the accumulated amount of the output PWM current in the full cycle is determined; Based on the duty cycle of output PWM data; The output PWM data is stored in the accumulated amount of the output PWM current over time; The output PWM data is defined as the current accumulation amount of the output PWM current over time.

4. The medical ultrasound image intelligent processing method according to claim 3, characterized in that: The calling of the cycle length and duty cycle of the output PWM data further includes: Determine the target voltage fluctuation function based on the voltage accumulation amount and the cycle length of the output PWM data; The target current fluctuation function is determined based on the current accumulation amount and the cycle length of the output PWM data.

5. The intelligent processing method for medical ultrasound images according to claim 4, characterized in that: The step of determining the wave function of the output ultrasonic wave based on the steady-state function of the MOS tube set includes: Incorporate the target voltage fluctuation function into Formula 1; Obtain the fluctuation function of the output voltage.

6. The medical ultrasound image intelligent processing method according to claim 5, characterized in that: The forming of an ultrasound image based on the characteristic echo-to-image function comprises: Generate cross-platform computer vision library call functions based on the cross-platform computer vision library; Generate connection functions using system-managed types; Incorporate cross-platform computer vision library calling functions and connection functions into the feature echo-to-image function.

7. A medical ultrasound image intelligent processing system, characterized in that: include: A processor, configured to execute the medical ultrasound image intelligent processing method according to any one of claims 1 to 6; a mechanical wave circuit electrically connected to the processor; A display is electrically connected to the processor.

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