CN106037793B - Ultrasonic imaging system and frame averaging processing method thereof - Google Patents
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Abstract
The invention discloses an ultrasonic imaging system and a frame averaging processing method thereof, wherein the method comprises the following steps: acquiring parameters including frame average level, frame frequency, frame correlation coefficient and pixels; obtaining a frame average weight coefficient, wherein the frame average weight coefficient is related to the parameters; and carrying out frame averaging processing by using the frame averaging weight coefficient. The invention uses the parameters of frame average grade, frame frequency, frame correlation coefficient and pixel to calculate the frame average weight coefficient, realizes the frame average processing method which uses the frame average grade set by the user to control the frame average strength as the main means and simultaneously combines the frame frequency, the frame correlation coefficient and the pixel to automatically optimize the frame average strength.
Description
Technical Field
The invention belongs to the field of signal and image processing, is applied to the industry of medical instruments, and particularly relates to an ultrasonic imaging system and a frame averaging processing method thereof.
Background
Ultrasonic imaging is one of the most widely used diagnostic tools in clinical practice because of its advantages such as non-invasive, real-time, convenient operation, and low price. The ultrasonic color blood flow imaging is an important imaging mode in ultrasonic imaging, is extremely common in clinical application, and is an important basis for diagnosis of various diseases, so that the improvement of the quality of the ultrasonic color blood flow image is of great significance for diagnosis of clinicians.
Ultrasonic color flow imaging is generally based on two-dimensional tissue imaging, in which a region of interest (ROI box) is determined by a user, and then the region is subjected to flow imaging, and then a flow image is superimposed on the two-dimensional tissue image and displayed together.
Frame averaging is an important image processing method in ultrasound imaging, and plays an important role in both two-dimensional tissue imaging and color flow imaging. Frame averaging requires a user to set reasonable intensity according to an application part and an actual image, but the setting of the user is often good only under certain imaging conditions, and the effect is affected after the conditions are changed. In the prior art, no method for automatically optimizing the frame average intensity according to the change of the imaging condition is found.
In the prior art, the related frame averaging processing techniques include: (1) scanning line density, dynamic range and frame average intensity are controlled by calculating a correlation value between a new image frame and a previous image frame, and the main purpose is to optimize a plurality of ultrasonic imaging parameters through the frame correlation value, form a feedback control mechanism and not a frame average processing method; (2) the method realizes frame averaging through a hardware circuit, mainly has the effects of reducing flicker pseudo-phase and speed aliasing phenomena and achieving the purpose of improving blood flow continuity and expressive force, but the method does not realize automatic optimization of frame averaging, and the cost is increased by a hardware processing mode.
Disclosure of Invention
The invention aims to provide an ultrasonic imaging system and a frame averaging processing method thereof.
In order to achieve one of the above objects, an embodiment of the present invention provides a frame averaging processing method for an ultrasound imaging system, including:
acquiring parameters including frame average level, frame frequency, frame correlation coefficient and pixels;
obtaining a frame average weight coefficient, wherein the frame average weight coefficient is related to the parameters;
carrying out frame averaging processing by using the frame averaging weight coefficient;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents a frame average level set by a user, fr represents a frame frequency, cor represents a frame correlation coefficient, x and y represent a previous frame output pixel and a current frame input pixel respectively, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
As a further improvement of an embodiment of the present invention, the step "obtaining a frame average weighting coefficient, where the frame average weighting coefficient is related to the parameter" specifically includes:
obtaining an initial frame average weight coefficient, wherein the initial frame average weight coefficient is related to frame average level, frame frequency and frame correlation coefficient;
a frame average weight coefficient is obtained, the frame average weight coefficient being related to the initial frame average weight coefficient and the pixel.
As a further improvement of an embodiment of the present invention, a current frame output pixel is related to the frame average weight coefficient, the previous frame output pixel and the current frame input pixel.
In order to achieve one of the above objects, an embodiment of the present invention provides a frame averaging processing method for an ultrasound imaging system, including:
presetting a frame average grade parameter to obtain the frame average strength in an initial state;
acquiring other parameters, wherein the other parameters comprise frame frequency, frame correlation coefficients and pixels;
automatically adjusting the average intensity of the frame according to the parameters;
the step of automatically adjusting the frame average intensity according to the parameters specifically includes:
obtaining a frame average weight coefficient according to the frame average grade, the frame frequency, the frame correlation coefficient and the pixel;
adjusting the frame average intensity according to the frame average weight coefficient;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents a frame average level set by a user, fr represents a frame frequency, cor represents a frame correlation coefficient, x and y represent a previous frame output pixel and a current frame input pixel respectively, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
In order to achieve one of the above objects, an embodiment of the present invention provides a frame averaging processing method for an ultrasound imaging system, including:
generating a lookup table, wherein the lookup table is defined as a relation table of output pixels of a current frame and parameters, and the parameters comprise frame average level, frame frequency, frame correlation coefficient, output pixels of a previous frame and input pixels of the current frame;
acquiring the parameters;
indexing in the lookup table according to the acquired parameters to acquire corresponding current frame output pixels;
wherein the look-up table satisfies the formula:
y’＝x*μ+y*(1-μ)；
wherein, x is the output pixel of the previous frame, y is the input pixel of the current frame, mu is the average weight coefficient of the corresponding frame, and y' is the output pixel of the current frame;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents the frame average level set by a user, fr represents the frame frequency, cor represents the frame correlation coefficient, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
To achieve one of the above objects, an embodiment of the present invention provides an ultrasound imaging system including:
a parameter acquiring unit for acquiring parameters including frame average level, frame frequency, frame correlation coefficient, and pixels;
a processing unit, configured to obtain a frame average weight coefficient, and perform frame average processing by using the frame average weight coefficient, where the frame average weight coefficient is related to the parameter;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents the frame average level set by a user, fr represents the frame frequency, cor represents the frame correlation coefficient, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
Compared with the prior art, the invention has the beneficial effects that: the invention uses the parameters of frame average grade, frame frequency, frame correlation coefficient and pixel to calculate the frame average weight coefficient, realizes the frame average processing method which uses the frame average grade set by the user to control the frame average strength as the main means and simultaneously combines the frame frequency, the frame correlation coefficient and the pixel to automatically optimize the frame average strength. The invention not only satisfies the subjective control of the user on the frame average intensity, so that the user can autonomously determine the frame average intensity according to different applications and actual imaging effects, but also realizes the automatic optimization of objective factors such as frame frequency, frame correlation coefficient and pixels on the frame average intensity, ensures the continuity and dynamic sense of real-time blood flow imaging, finally achieves better ultrasonic color blood flow imaging effect, and is beneficial to the clinical diagnosis of doctors.
Drawings
FIG. 1 is a diagram of the steps of a frame averaging process for an ultrasound imaging system in accordance with one embodiment of the present invention;
FIG. 2 is a diagram of the steps of a frame averaging process for an ultrasound imaging system in accordance with another embodiment of the present invention;
FIG. 3 is a diagram of the steps of a frame averaging process for an ultrasound imaging system in accordance with yet another embodiment of the present invention;
FIG. 4 is a schematic diagram of a frame averaging processing method of an ultrasound imaging system according to yet another embodiment of the present invention;
fig. 5 is a block diagram of an ultrasound imaging system according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to specific embodiments shown in the drawings. These embodiments are not intended to limit the present invention, and structural, methodological, or functional changes made by those skilled in the art according to these embodiments are included in the scope of the present invention.
The ultrasonic color blood flow imaging is used for imaging and displaying blood flow in a blood vessel and is mainly characterized in that: (1) the blood flow changes dynamically with time under the influence of the periodic beating of the heart; (2) due to the limitation of frame frequency, the ultrasound color flow imaging cannot continuously image the blood flow change, and only limited frame images of each cardiac cycle can be acquired. For ultrasound color blood flow imaging, the continuity and dynamic feeling of blood flow are important factors influencing the imaging effect, the ideal blood flow should keep good continuity in time and space, no obvious jump and flicker can be generated between adjacent frames, and the dynamic feeling of blood flow must be considered at the same time, so that the normal blood flow speed or blood flow energy difference between adjacent frames is kept, and the dynamic feeling of blood flow is matched with the cardiac cycle. An excessively high frame average intensity may cause the blood flow image to lose dynamic sense and generate a tailing phenomenon, while an excessively low frame average intensity may cause the blood flow continuity to be deteriorated and generate a skipping sense, and a reasonable frame average intensity may achieve the optimal blood flow continuity and dynamic sense, so that frame averaging processing is required to obtain a proper frame average intensity.
The basic principle of the frame averaging process is to use the correlation between adjacent frames to take the result of weighted averaging of the pixels at the same position of the previous frame and the current frame by different weight coefficients as the output pixel of the current frame. This can be expressed as:
y’＝x*μ+y*(1-μ) (1)
wherein, x is the output pixel of the previous frame, y is the input pixel of the current frame, μ is the corresponding frame average weight coefficient, and y' is the output pixel of the current frame. The frame average intensity is determined by a frame average weight coefficient mu, the value range of mu is more than or equal to 0 and less than or equal to 1, the larger the mu is, the larger the frame average intensity is, and the frame average processing is closed when the mu is equal to 0. The proper frame averaging process can improve the signal-to-noise ratio of the image and also improve the temporal and spatial continuity, that is, the proper frame average strength, that is, the proper frame average weight coefficient μ, needs to be obtained.
The main way to adjust the frame average intensity is to set an appropriate frame average level on the user interface by the user according to the application part and the actual image, which is a subjective factor, and besides, there are some objective factors that influence the frame average intensity, mainly including frame rate, correlation between adjacent frames, and pixels. Generally, the higher the frame frequency, the smaller the change between adjacent frames, and the frame average intensity should be properly increased; the lower the frame rate, the greater the variation between adjacent frames, and the lower the frame average intensity should be. The better the correlation between adjacent frames (i.e. the larger the frame correlation coefficient), the frame average strength should be properly increased; the worse the correlation between adjacent frames (i.e., the smaller the frame correlation coefficient), the lower the frame average strength should be. The difference in pixels also affects the frame average weighting factor and thus the frame average intensity.
As shown in fig. 1, a method for frame averaging processing of an ultrasound imaging system according to an embodiment of the present invention includes:
acquiring parameters, wherein the parameters comprise a frame average level lev, a frame frequency fr, a frame correlation coefficient cor and pixels x and y;
obtaining a frame average weight coefficient mu, wherein the frame average weight coefficient mu is related to the parameters;
and carrying out frame averaging processing by using the frame averaging weight coefficient mu.
In the present embodiment, the frame average weight coefficient μ is calculated using several parameters, i.e., the frame average level lev, the frame frequency fr, the frame correlation coefficient cor, and the pixel x and y, so that a frame average processing method is realized in which the frame average level lev is set by a user as a main means to control the frame average intensity, and the frame average intensity is automatically optimized in combination with the frame frequency fr, the frame correlation coefficient cor, the pixel x, and the pixel y. The embodiment satisfies the subjective control of the user on the frame average intensity, so that the user can autonomously determine the frame average intensity according to different applications and actual imaging effects, and meanwhile, the automatic optimization of objective factors such as the frame frequency fr, the frame correlation coefficient cor, the pixel x and the pixel y on the frame average intensity is realized, the continuity and the dynamic feeling of real-time blood flow imaging are ensured, the better ultrasonic color blood flow imaging effect is finally achieved, and the clinical diagnosis of doctors is facilitated.
Specifically, according to the above formula (1), in order to adjust the frame average intensity, the frame average weight coefficient μ needs to be obtained first, and in the present embodiment, the method for calculating the frame average weight coefficient μ is simply expressed as:
μ＝fun(lev,fr,cor,x,y) (2)
wherein lev represents a frame average level set by a user, fr represents a frame frequency, cor represents a frame correlation coefficient, x and y represent a previous frame output pixel and a current frame input pixel respectively, and fun represents a function with lev, fr, cor, x and y as parameters.
For the fun function, the following condition needs to be satisfied:
(a) monotonically increases with respect to the frame average level lev, i.e. the larger the frame average level lev, the larger the frame average weight coefficient μ. Here, the calculation may be performed in two ways, one way is to directly use the frame average level lev as a parameter, and the other way is to generate a resource file in advance, and obtain the parameter in the resource file by using the frame average level lev as an index to perform the calculation, where the frame average level lev is usually an integer between 0 and 10.
(b) The frame frequency fr relative to the imaging frame is monotonically increased, i.e., the larger the frame frequency fr, the larger the frame average weight coefficient μ, and the frame frequency fr is usually an integer between 5 and 25.
(c) Monotonically increasing with respect to the frame correlation coefficient cor, i.e. the larger the frame correlation coefficient cor, the larger the frame average weight coefficient μ. The frame correlation coefficient cor can be calculated by the information of two adjacent frames of images, specifically, the frame correlation coefficient cor can be calculated by two adjacent frames of color blood flow images, and also can be calculated by two adjacent frames of two-dimensional tissue images corresponding to the color blood flow images. In the embodiment, the frame correlation coefficient cor is obtained by calculating two adjacent frames of two-dimensional tissue images, and the frame correlation coefficient cor is a decimal between 0 and 1.
(d) The following characteristics are provided with respect to pixels x and y: when the absolute value of the output pixel of the previous frame is smaller than the absolute value of the input pixel of the current frame, that is, abs (x) < abs (y), the frame average weight coefficient μ should be smaller, and in this case, the frame average weight coefficient μmay be appropriately reduced; when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, that is, abs (x) > abs (y), the frame average weight coefficient μ should be large, and in this case, the frame average weight coefficient μmay be appropriately increased. Here, taking an arterial blood flow as an example, when abs (x) < abs (y), it is considered that the arterial blood flow is in a systolic phase, at which time the heart shoots blood and the blood flow velocity increases rapidly, and in order to capture a high-speed blood flow rapidly and maintain synchronization with the cardiac cycle, a smaller frame average weight coefficient μ should be used; when abs (x) > abs (y) indicates that arterial blood flow is in diastole, the blood flow rate begins to slow, and a larger frame-averaged weight coefficient μ should be used to make the peak duration longer. The blood flow velocity pixels are typically integers between-128 and 127, and the blood flow energy pixels are typically integers between 0 and 255.
In the present embodiment, since the influence of the pixels x and y on the frame average weight coefficient μ is not easily expressed in the mathematical expression because the condition determination (i.e., the magnitude determination of abs (x) and abs (y)) is involved, the present embodiment first designs a function that satisfies the above conditions (a), (b), and (c) to obtain an initial frame average weight coefficient μ0Then averaging the weight coefficient mu through the initial frame0The relation with the pixel x, y obtains the final frame average weight coefficient mu, mu0The value range of (a) is also a decimal between 0 and 1. According to the characteristics, the exponential function is a better choice to meet the requirements, and the implementation mode selects the e exponential function to realize. The formula is as follows:
μ0＝(exp(-Const/(fr*(lev+Tiny))))(1/cor)(3)
where Tiny is set to prevent the denominator from being 0 when the frame average level lev is 0, and it is satisfactory to actually take a value less than 0.001; const is used to adjust the initial frame average weighting factor mu0A constant set for a value range, largeThe frame frequency fr is in the same order of magnitude as the frame frequency fr, and the reasonable range of the frame frequency fr is 10-60; exp denotes the e-exponential function. The above formula (3) preferably satisfies the above conditions (a), (b) and (c), and ensures the average weight coefficient μ of the initial frame0The value range is between 0 and 1. Subsequently, only the average weight coefficient mu in the initial frame is needed0On the basis, the requirement of the condition (d) can be met by performing condition judgment according to the relation of the pixels x and y and combining simple linear mapping, so that the judgment and adjustment difficulty can be greatly reduced.
In another embodiment of the present invention, as shown in fig. 2 and combined with the above embodiments, the frame averaging processing method of the ultrasound imaging system of the present embodiment includes the steps of:
presetting a frame average level lev parameter to obtain the frame average intensity in an initial state;
acquiring other parameters including a frame frequency fr, a frame correlation coefficient cor and pixels x and y;
and automatically adjusting the frame average intensity according to the parameters.
Here, the frame average intensity may be adjusted by adjusting the frame average weight coefficient μ, similarly to the previous embodiment, but may be adjusted in other ways. According to the embodiment, a user autonomously selects the frame average level lev on the interface according to an application part and an actual image to preliminarily determine the frame average intensity, and then the frame average intensity is automatically adjusted according to the actual conditions of all parameters.
In another embodiment of the present invention, as shown in fig. 3 in combination with the foregoing embodiments, the frame averaging processing method of the ultrasound imaging system of this embodiment includes the steps of:
generating a lookup table, wherein the lookup table is defined as a relation table between a current frame output pixel y' and parameters, and the parameters comprise a frame average level lev, a frame frequency fr, a frame correlation coefficient cor, a previous frame output pixel x and a current frame input pixel y;
acquiring the parameters;
and indexing the obtained parameters in the lookup table to obtain the corresponding current frame output pixel y'.
Here, the lookup table may be generated according to the foregoing equations (1) (2) (3), and thus, the calculation amount of real-time imaging may be greatly reduced.
In this embodiment, after the user sets the imaging parameters, the frame average level lev and the real-time imaging frame frequency fr are both determined values, and only the frame correlation coefficient cor and the blood flow pixels x and y are uncertain values. Therefore, according to the description of the foregoing embodiments on each parameter, the frame average look-up table established by the present embodiment is at least three-dimensional, i.e., (cor, x, y) three dimensions. Because the frame correlation coefficient cor is a decimal between 0 and 1, the frame correlation coefficient cor must be discretized when generating the lookup table, and the value range of the frame correlation coefficient cor is divided into N sections at equal intervals to reduce the storage space of the lookup table, so that the size of the lookup table calculated is N × 256.
After the lookup table is generated, the user only needs to find the corresponding current frame output pixel y' in the lookup table according to the calculated frame correlation coefficient cor, the previous frame output pixel x participating in the frame averaging processing and the current frame input pixel y in the subsequent processing. The index position in the lookup table is (floor (cor × N), x, y), where floor (cor × N) indicates that the result of cor × N is rounded.
In the embodiment, the frame rate fr is determined by imaging parameters such as depth and size of an interested region, the frame average level lev is determined by imaging parameters such as an application part considered by a user and an actual image, and when the user adjusts the imaging parameters to change any one of the two parameters of the frame average level lev and the frame rate fr, the frame average processing of the ultrasonic imaging system can be rapidly performed again only by regenerating the lookup table, so that the calculation amount of real-time imaging is further reduced, and the convenience of operation is improved.
Specifically, as shown in fig. 4, first, a frame average look-up table is obtained according to the relative relationship between the parameters, such as the frame average level lev, the frame frequency fr, the accumulated frame correlation coefficient cor, the previous frame output pixel x1, and the current frame input pixel y1, and the current frame output pixel y 1', set by the user, and is stored in the ultrasound imaging system; then, in the actual operation, obtaining a current actual frame correlation coefficient cor, a previous frame output pixel x and a current frame in-out pixel y, wherein the three parameters form (cor, x, y) indexes; then, the frame average lookup table is looked up according to the index, so that the actual current frame output pixel y' can be obtained.
The present invention also provides an ultrasound imaging system, as shown in fig. 5, the ultrasound imaging system including:
a parameter obtaining unit 10, configured to obtain parameters including a frame average level lev, a frame frequency fr, a frame correlation coefficient cor, and pixels x and y;
a processing unit 20, configured to obtain a frame average weight coefficient μ, and perform frame average processing using the frame average weight coefficient μ, where the frame average weight coefficient μ is related to the parameter.
In the present embodiment, the frame average weight coefficient μ is calculated using several parameters, i.e., the frame average level lev, the frame frequency fr, the frame correlation coefficient cor, and the pixel x and y, so that a frame average processing method is realized in which the frame average level lev is set by a user as a main means to control the frame average intensity, and the frame average intensity is automatically optimized in combination with the frame frequency fr, the frame correlation coefficient cor, the pixel x, and the pixel y. The embodiment satisfies the subjective control of the user on the frame average intensity, so that the user can autonomously determine the frame average intensity according to different applications and actual imaging effects, and meanwhile, the automatic optimization of objective factors such as the frame frequency fr, the frame correlation coefficient cor, the pixel x and the pixel y on the frame average intensity is realized, the continuity and the dynamic feeling of real-time blood flow imaging are ensured, the better ultrasonic color blood flow imaging effect is finally achieved, and the clinical diagnosis of doctors is facilitated.
For other descriptions of the ultrasound imaging system of this embodiment, reference may be made to the description of the frame averaging processing method of the ultrasound imaging system, and details are not repeated here.
It should be understood that although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description is for clarity only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can also be combined appropriately to form other embodiments understood by those skilled in the art.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.
Claims (6)
1. A frame averaging processing method for an ultrasound imaging system, comprising the steps of:
acquiring parameters including frame average level, frame frequency, frame correlation coefficient and pixels;
obtaining a frame average weight coefficient, wherein the frame average weight coefficient is related to the parameters;
carrying out frame averaging processing by using the frame averaging weight coefficient;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents a frame average level set by a user, fr represents a frame frequency, cor represents a frame correlation coefficient, x and y represent a previous frame output pixel and a current frame input pixel respectively, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
2. The method of claim 1, wherein the step of obtaining a frame average weighting factor, wherein the frame average weighting factor is related to the parameter, specifically comprises:
obtaining an initial frame average weight coefficient, wherein the initial frame average weight coefficient is related to frame average level, frame frequency and frame correlation coefficient;
a frame average weight coefficient is obtained, the frame average weight coefficient being related to the initial frame average weight coefficient and the pixel.
3. The method of claim 1, wherein a current frame output pixel is associated with the frame averaging weighting factor, the previous frame output pixel, and the current frame input pixel.
4. A frame averaging processing method for an ultrasound imaging system, comprising the steps of:
presetting a frame average grade parameter to obtain the frame average strength in an initial state;
acquiring other parameters, wherein the other parameters comprise frame frequency, frame correlation coefficients and pixels;
automatically adjusting the average intensity of the frame according to the parameters;
the step of automatically adjusting the frame average intensity according to the parameters specifically includes:
obtaining a frame average weight coefficient according to the frame average grade, the frame frequency, the frame correlation coefficient and the pixel;
adjusting the frame average intensity according to the frame average weight coefficient;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents a frame average level set by a user, fr represents a frame frequency, cor represents a frame correlation coefficient, x and y represent a previous frame output pixel and a current frame input pixel respectively, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
5. A frame averaging processing method for an ultrasound imaging system, comprising the steps of:
generating a lookup table, wherein the lookup table is defined as a relation table of output pixels of a current frame and parameters, and the parameters comprise frame average level, frame frequency, frame correlation coefficient, output pixels of a previous frame and input pixels of the current frame;
acquiring the parameters;
indexing in the lookup table according to the acquired parameters to acquire corresponding current frame output pixels;
wherein the look-up table satisfies the formula:
y’＝x*μ+y*(1-μ)；
wherein, x is the output pixel of the previous frame, y is the input pixel of the current frame, mu is the average weight coefficient of the corresponding frame, and y' is the output pixel of the current frame;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents the frame average level set by a user, fr represents the frame frequency, cor represents the frame correlation coefficient, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
6. An ultrasound imaging system, comprising:
a parameter acquiring unit for acquiring parameters including frame average level, frame frequency, frame correlation coefficient, and pixels;
a processing unit, configured to obtain a frame average weight coefficient, and perform frame average processing by using the frame average weight coefficient, where the frame average weight coefficient is related to the parameter;
the frame average weight coefficient satisfies the formula:
μ＝fun(lev,fr,cor,x,y)；
wherein lev represents the frame average level set by a user, fr represents the frame frequency, cor represents the frame correlation coefficient, and fun represents a function with lev, fr, cor, x and y as parameters;
the fun function satisfies the condition: relative to the frame average level lev, the frame frequency fr and the frame correlation coefficient cor are monotonically increased; and when the absolute value of the output pixel of the previous frame is not less than the absolute value of the input pixel of the current frame, the frame average weight coefficient is increased.
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