CN116309084A - Method and device for extracting maximum frequency of spectrogram and medical equipment - Google Patents
Method and device for extracting maximum frequency of spectrogram and medical equipment Download PDFInfo
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Abstract
The invention relates to the technical field of ultrasound, in particular to a method and a device for extracting the maximum frequency of a spectrogram and medical equipment, wherein the method comprises the steps of obtaining a target frequency spectrum image; dividing the region of the target spectrum image based on the pixel value of each pixel point in the target spectrum image to determine a target region; filtering each target area based on pixel values and noise threshold values of pixel points in each target area to determine a target frequency spectrum area; an envelope of the target spectral region is extracted to determine a maximum frequency of the target spectral image. The weak noise and the weak signal can be distinguished and analyzed by carrying out region division on the pixel value of the pixel point in the target frequency spectrum image; and meanwhile, each target area is filtered to remove strong noise so as to resist the interference of noise on analysis results, and the accuracy of the extracted maximum frequency is improved.
Description
Technical Field
The invention relates to the technical field of ultrasound, in particular to a method and a device for extracting maximum frequency of a spectrogram and medical equipment.
Background
In the technical field of medical ultrasound, a method for obtaining a sonogram by using a doppler effect to measure a blood flow velocity has been rapidly developed in recent years due to its non-destructive nature. When the Doppler technology is clinically applied, firstly, spectrum analysis is carried out on the obtained blood flow signals to obtain a spectrogram, and then, the spectrogram is utilized to calculate the spectrogram parameters such as S/D, RI, PI and the like for diagnosing vascular diseases. The estimation of the maximum frequency is the basis for calculating the doppler parameter, and in order to obtain a small error, the maximum frequency curve must be extracted accurately.
To solve this problem, a related paper proposes an improved method of the percentage method, called a hybrid method. According to the method, firstly, a spectrum integral curve of a single spectral line is calculated, then the integral curve is analyzed, the intersection point of a preset straight line and the integral curve is searched by the mixing method, and the frequency corresponding to the intersection point is regarded as the maximum frequency, but the frequency is sensitive to the signal to noise ratio, and the optimal percentage is difficult to determine. Further, there is a paper for improving the mixing method, and a geometrical method is proposed, the method also comprises the steps of firstly calculating a spectrum integral curve of a single spectral line, then analyzing the integral curve, designing a straight line, calculating the distance from each point on the integral curve to the straight line, and obtaining the frequency corresponding to the point with the shortest distance as the maximum frequency. However, when the noise power is high, the noise point may be detected on the maximum frequency curve, and when the spectrum signal is weak, the estimated error is increased, so that the maximum frequency curve loses part of the blood flow signal.
However, the influence of noise on the maximum frequency extraction is large in the two modes, so that the accuracy of the extracted maximum frequency curve is low, and the maximum frequency curve loses part of blood flow signals.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a method, an apparatus, and a medical device for extracting a maximum frequency of a spectrogram, so as to solve the problem of low extraction accuracy of the maximum frequency.
According to a first aspect, an embodiment of the present invention provides a method for extracting a maximum frequency of a spectrogram, including:
acquiring a target spectrum image;
dividing the region of the target spectrum image based on the pixel value of each pixel point in the target spectrum image to determine a target region;
filtering each target area based on pixel values and noise threshold values of pixel points in each target area to determine a target frequency spectrum area;
an envelope of the target spectral region is extracted to determine a maximum frequency of the target spectral image.
According to the extraction method of the maximum frequency of the spectrogram, provided by the embodiment of the invention, the weak noise and the weak signal can be distinguished and analyzed by dividing the pixel values of the pixel points in the target frequency spectrum image; and meanwhile, each target area is filtered to remove strong noise so as to resist the interference of noise on analysis results, and the accuracy of the extracted maximum frequency is improved.
With reference to the first aspect, in a first implementation manner of the first aspect, the determining, by performing region division on the target spectrum image based on pixel values of each pixel point in the target spectrum image, a target region includes:
acquiring the number of the target areas and a pixel threshold corresponding to the target areas;
and comparing the pixel value of each pixel point in the target spectrum image with each pixel threshold value, dividing each pixel point, and determining the target area.
According to the extraction method of the maximum frequency of the spectrogram, corresponding pixel thresholds are determined for each target area, so that the pixel points are accurately divided, and the reliability of the divided target areas is guaranteed.
With reference to the first implementation manner of the first aspect, in a second implementation manner of the first aspect, comparing a pixel value of each pixel point in the target spectrum image with each pixel threshold value, dividing each pixel point, and determining the target area includes:
and determining the pixel point with the pixel value smaller than the minimum pixel threshold value as a noise pixel point, and removing the noise pixel point to determine the target area.
According to the extraction method of the maximum frequency of the spectrogram, provided by the embodiment of the invention, the pixel points with the pixel values smaller than the minimum pixel threshold value are removed, so that the purpose of signal-to-noise separation is achieved.
With reference to the first aspect, in a third implementation manner of the first aspect, the filtering the target areas based on a relationship between a pixel value of a pixel point in each target area and a corresponding threshold value, determining a target spectrum area, and determining a target spectrum area includes:
determining all connected areas in the target area based on the pixel values of the pixel points in each target area and the pixel values of the adjacent pixel points;
acquiring the scanning speed of the target spectrum image to determine the area threshold of the noise area;
and filtering the communication areas based on the size relation between the area of each communication area and the area threshold of the noise area, and determining the target frequency spectrum area.
According to the extraction method of the maximum frequency of the spectrogram, the communication area is determined, and then the communication area is filtered, wherein the communication area with the too small area is considered as noise, and the communication area with the too small area is removed, so that the effect of removing relatively strong independent speckle noise is achieved.
With reference to the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the acquiring a scanning speed of acquiring the target spectrum image to determine an area threshold of the noise area includes:
acquiring an initial threshold value of a noise area at a preset scanning speed;
determining an adjustment coefficient based on the magnitude relation between the scanning speed and the preset scanning speed;
and determining an area threshold of the noise area based on the adjustment coefficient and the initial threshold.
According to the extraction method of the maximum frequency of the spectrogram, when the scanning speed is low, the frequency spectrum is scattered, the noise signal can be stretched, and the area is large; when the scanning speed is high, the frequency spectrum is concentrated, the noise signal can be compressed, and the area is small. Therefore, based on the replacement relation between the scanning speed and the preset scanning speed, the area threshold value of the noise area is adjusted, and the accuracy of noise filtering can be ensured.
With reference to the first aspect, in a fifth implementation manner of the first aspect, the extracting an envelope of the target spectrum area to determine a maximum frequency of the target spectrum image includes:
acquiring a baseline in the target spectrum image;
determining the number of the target spectrum regions above and below the base line by utilizing the position relation between the base line and the target spectrum regions;
determining target spectrum regions corresponding to an upper envelope and a lower envelope based on the number of the target spectrum regions above and below the base line;
and respectively extracting the upper envelope curve and the lower envelope curve based on the target frequency spectrum region corresponding to the upper envelope curve and the lower envelope curve so as to determine the maximum frequency of the target frequency spectrum image.
According to the extraction method of the maximum frequency of the spectrogram, when the number of the target frequency spectrum areas above or below the base line is larger than 1, the occurrence of aliasing phenomenon is indicated, and under the condition that the base line is unchanged, the target frequency spectrum areas corresponding to the upper envelope line and the lower envelope line are determined, so that the self-adaptive extraction of the maximum frequency can be realized.
With reference to the fifth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the extracting the upper envelope and the lower envelope based on the target spectrum regions corresponding to the upper envelope and the lower envelope to determine the maximum frequency of the target spectrum image includes:
determining a target line from a region between two of the target spectral regions on the same side of the baseline when the two of the target spectral regions are present on the same side of the baseline;
and carrying out envelope extraction based on the target line and the corresponding target frequency region, and determining the maximum frequency of the target frequency spectrum image.
According to the extraction method of the maximum frequency of the spectrogram, the target line is determined in the area between the two target frequency spectrum areas on the same side, so that the upper envelope and the lower envelope on the same side are distinguished, and automatic simultaneous extraction of the upper envelope and the lower envelope is ensured.
According to a second aspect, an embodiment of the present invention further provides an apparatus for extracting a maximum frequency of a spectrogram, including:
the acquisition module is used for acquiring a target frequency spectrum image;
the dividing module is used for dividing the region of the target spectrum image based on the pixel value of each pixel point in the target spectrum image to determine a target region;
the filtering module is used for filtering each target area based on the pixel values and the noise threshold values of the pixel points in each target area and determining a target frequency spectrum area;
and the extraction module is used for extracting the envelope of the target spectrum area so as to determine the maximum frequency of the target spectrum image.
According to the extraction device of the maximum frequency of the spectrogram, provided by the embodiment of the invention, the weak noise and the weak signal can be distinguished and analyzed by dividing the pixel values of the pixel points in the target frequency spectrum image; and meanwhile, each target area is filtered to remove strong noise so as to resist the interference of noise on analysis results, and the accuracy of the extracted maximum frequency is improved.
According to a third aspect, an embodiment of the present invention provides a medical device comprising: the device comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions so as to execute the method for extracting the maximum frequency of the spectrogram in the first aspect or any implementation manner of the first aspect.
According to a fourth aspect, an embodiment of the present invention provides a computer readable storage medium storing computer instructions for causing the computer to perform the method for extracting a maximum frequency of a spectrogram according to the first aspect or any implementation manner of the first aspect.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic representation of a maximum frequency curve extracted by a prior art method;
FIG. 2 is a flow chart of a method of extracting maximum frequency of a spectrogram according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method of extracting maximum frequency of a spectrogram according to an embodiment of the present invention;
FIGS. 4 a-4 b are schematic illustrations of determining a communication area according to embodiments of the present invention;
FIG. 5 is a flow chart of a method of extracting maximum frequency of a spectrogram according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a spectrogram maximum frequency plot according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a spectrogram maximum frequency plot according to an embodiment of the present invention;
fig. 8 is a block diagram of a structure of an apparatus for extracting a maximum frequency of a spectrogram according to an embodiment of the present invention;
fig. 9 is a schematic hardware structure of a medical device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the existing extraction method of the maximum spectrum of the spectrogram, the spectrum is extracted through integration, and the integration is the accumulation of noise, so that the extraction method is sensitive to the noise, and the final extraction result is affected by the existence of any noise. Based on the above, according to the extraction method of the maximum frequency of the spectrogram provided by the embodiment of the invention, the target frequency image is divided into the regions, and the weak noise is filtered to obtain each target region; filtering the target area on the basis, determining the target frequency spectrum area to remove strong noise, obtaining the target frequency spectrum area, and extracting the envelope on the target frequency spectrum area, so that the influence of noise on the extracted maximum frequency can be avoided.
Further, existing extraction methods, whether percentage method, threshold method, geometric method, etc., must be processed on a suitable spectrogram. If the baseline of the spectrogram itself is improperly adjusted and frequency aliasing occurs, an envelope identification error as shown in fig. 1 may occur. Therefore, in the prior art, if the correct envelope is to be obtained, the baseline position of the spectrogram must be adjusted first, then the upper envelope is identified, the lower envelope is identified simultaneously, and then the envelope is detected by using a corresponding method. In order to solve the problem, in the embodiment of the invention, the number of the connected areas on the same side of the base line is counted, and if 2 connected areas exist on the same side of the base line, the occurrence of aliasing is indicated. If the 2 connected areas are located above the base line, an upper envelope is obtained for a frequency spectrum above the base line, which is close to the base line, and a lower envelope is obtained for a frequency spectrum above the base line, which is far from the base line; if the 2 connected areas are positioned below the base line, a lower envelope is obtained for the frequency spectrum which is close to the base line below the base line, and an upper envelope is obtained for the frequency spectrum which is far from the base line below the base line, so that the effect of extracting the envelope by one key is achieved, and the base line is prevented from being adjusted when frequency spectrum aliasing occurs.
According to an embodiment of the present invention, there is provided an embodiment of a method for extracting a maximum frequency of a spectrogram, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer-executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different from that herein.
In this embodiment, a method for extracting a maximum frequency of a spectrogram is provided, which may be used in medical equipment, such as an ultrasound device, and fig. 2 is a flowchart of a method for extracting a maximum frequency of a spectrogram according to an embodiment of the present invention, as shown in fig. 2, where the flowchart includes the following steps:
s11, acquiring a target spectrum image.
The target spectrum image may be obtained by the medical device through collecting spectrum data, or may be obtained by the medical device from other devices, and the method for obtaining the target spectrum image by the medical device is not limited at all, and may be set according to actual requirements. Taking the medical equipment as an example for collecting frequency spectrum data, the medical equipment collects a Doppler signal which changes along with time, filters low-frequency information through a filter, and then performs Fourier change on the filtered data segment to obtain frequency spectrum data so as to obtain a target frequency spectrum image.
S12, dividing the region of the target spectrum image based on the pixel values of all the pixel points in the target spectrum image to determine a target region.
After the medical equipment acquires the target spectrum image, the pixel value of each pixel point can be obtained. Based on the pixel values of each pixel point, cluster analysis can be carried out, and region division is carried out on the target spectrum image; the method can also be used for dividing the areas of the pixel points of the target frequency spectrum image by using the Ojin method to obtain a plurality of target areas.
Specifically, the medical device may define a pixel value range corresponding to each target area in advance, and the medical device matches each pixel point into each target area, thereby performing area division on the target spectrum image. The pixel value range corresponding to each target area can be determined according to an empirical value, can be obtained through optimization analysis, and the like. The medical device can identify the region corresponding to the weak noise by dividing the region of the target spectrum image, and then filter the region.
This step will be described in detail later in detail.
And S13, filtering each target area based on the pixel values and the noise threshold values of the pixel points in each target area to determine a target frequency spectrum area.
For a target spectral image, it includes not only weak noise but also strong noise, and for strong noise, it may last for a period of time, and reflect onto the target spectral image as a continuous spectral region. But the area of the continuous spectral region is relatively small compared to the area of the signal region. Therefore, the medical equipment can determine the connected region in the target region based on the pixel values of the pixel points in each target region, and then the area of the connected region is compared with the corresponding noise threshold value, so that the filtering of strong noise can be realized, and the target frequency spectrum region is determined.
Alternatively, the medical device may analyze the difference between each pixel and the adjacent pixel. If the difference is too large, the pixel point can be considered as an abnormal pixel point, and the abnormal pixel point can be taken out to determine a target frequency spectrum region.
This step will be described in detail later in detail.
S14, extracting the envelope of the target spectrum area to determine the maximum frequency of the target spectrum image.
After determining the target spectral region, the medical device may extract the envelope in the target spectral region. As described above, it is possible to determine whether the upper envelope or the lower envelope is to be extracted, depending on the number of target spectral regions on the same side of the baseline. The extracted envelope curve is the maximum frequency curve of the target spectrum image.
The analysis of the blood flow signal based on the maximum frequency curve may be performed later, or other applications may be performed, and the application based on the extracted maximum frequency curve is not limited at all, and may be set according to actual requirements.
This step will be described in detail later in detail.
According to the extraction method of the maximum frequency of the spectrogram, the weak noise and the weak signal can be distinguished and analyzed through dividing the pixel values of the pixel points in the target spectrum image into areas; and meanwhile, each target area is filtered to remove strong noise so as to resist the interference of noise on analysis results, and the accuracy of the extracted maximum frequency is improved.
In this embodiment, a method for extracting a maximum frequency of a spectrogram is provided, which may be used in medical equipment, such as an ultrasound device, and fig. 3 is a flowchart of a method for extracting a maximum frequency of a spectrogram according to an embodiment of the present invention, and as shown in fig. 3, the flowchart includes the following steps:
s21, acquiring a target spectrum image.
Please refer to the description of S11 in the embodiment shown in fig. 2 in detail, which is not repeated here.
S22, dividing the region of the target spectrum image based on the pixel values of all the pixel points in the target spectrum image to determine a target region.
Specifically, the step S22 includes:
s221, the number of the target areas and the pixel threshold value corresponding to the target areas are obtained.
If m target areas exist in the target spectrum image, m-1 thresholds are needed to distinguish the target areas, wherein the thresholds are k respectively 1 ，…，k n ，…，k m-1 . Wherein, the pixel points in each target area can be expressed as: c (C) 0 ＝{0,1,...,k 1 }，…，C m ＝{k m+1 ,k m+2 ,...,k m+N The variance of these target regions is:
σ BC ＝ω 0 (μ 0 -μ r ) 2 +...+ω n (μ n -μ r ) 2 +...+ω m-1 (μ m-1 -μ r ) 2
wherein, the liquid crystal display device comprises a liquid crystal display device,
P i is pixel iThe proportion of omega i Is the proportion of the ith target area, mu i Is the pixel mean, mu, of the ith target area T Is the total average of all target areas. The medical device will be sigma BC The set of thresholds that take the maximum value is the pixel threshold corresponding to each target region.
S222, comparing the pixel value of each pixel point in the target spectrum image with each pixel threshold value, dividing each pixel point, and determining a target area.
After the medical equipment determines the pixel threshold value of each target area, each pixel point in the target spectrum image is matched with each pixel threshold value, each pixel point is divided, and each pixel point can be classified into the corresponding target area. Further, a pixel point with a pixel value smaller than the minimum pixel threshold value is determined as a noise pixel point, and the noise pixel point is removed. And removing the pixel points with the pixel values smaller than the minimum pixel threshold value, so as to achieve the purpose of signal-to-noise separation.
S23, filtering each target area based on the pixel values and the noise threshold values of the pixel points in each target area to determine a target frequency spectrum area.
Specifically, the step S23 includes:
s231, determining the connected areas in all the target areas based on the pixel values of the pixel points in each target area and the pixel values of the adjacent pixel points.
For all target areas, the smallest unit is a pixel, with 8 contiguous pixels around each pixel. Two common adjacencies are two, namely 4 adjacencies and 8 adjacencies, and 4 adjacencies have 4 points in total, namely up, down, left and right, as shown in fig. 4 a; the 8 contiguous points are a total of 8, including the diagonally located points, as shown in fig. 4 b. The medical equipment can determine the communication area in the target area by analyzing the 4 adjacent or 8 adjacent pixel points in the target area.
Of course, the medical device may analyze each target area in other manners to determine the connected area in the target area.
S232, acquiring the scanning speed of the acquisition target frequency spectrum image to determine the area threshold value of the noise area.
The scanning speed determines the area of the acquired spectrum data in unit time, and the faster the scanning speed is, the smaller the area of the spectrum data in unit time is; the slower the scan speed, the larger the area of spectral data per unit time. Based on this, it is necessary to acquire a scanning speed at which the target spectrum image is acquired, and an area threshold of the noise region is determined based on the scanning speed. The faster the scanning speed, the smaller the area threshold of the noise region; the slower the scan speed, the greater the area threshold of the noise region.
In some optional implementations of this embodiment, the step S232 may include:
(1) And acquiring an initial threshold value of a noise area at a preset scanning speed.
(2) And determining an adjustment coefficient based on the magnitude relation between the scanning speed and the preset scanning speed.
(3) An area threshold for the noise region is determined based on the adjustment coefficient and the initial threshold.
Specifically, assuming that the noise threshold under the normal scanning speed is thre, when the scanning speed is small, the whole screen spectrum is scattered, the noise signal is stretched, and the area is large, so that the area threshold of the noise area is set to be 1.4 x thre; on the contrary, when the scanning speed is high, the whole screen spectrum is concentrated, the noise signal is compressed and the area is small, so that the area threshold of the noise area is set to be 0.6 x thre.
Of course, the above adjustment coefficients of 1.4 and 0.6 are merely examples, and may be specifically adjusted according to actual requirements, which are not limited in any way.
When the scanning speed is small, the frequency spectrum is scattered, noise signals can be stretched, and the area is large; when the scanning speed is high, the frequency spectrum is concentrated, the noise signal can be compressed, and the area is small. Therefore, based on the replacement relation between the scanning speed and the preset scanning speed, the area threshold value of the noise area is adjusted, and the accuracy of noise filtering can be ensured.
S233, filtering the connected regions based on the size relation between the area of each connected region and the area threshold of the noise region, and determining the target frequency spectrum region.
The medical equipment compares the area of each communication area with the area threshold value of the noise area, and then whether each communication area is a strong noise area or not can be determined. And if the certain connected region is a region with strong noise, filtering the connected region, so as to determine a target frequency spectrum region for subsequent envelope extraction.
S24, extracting the envelope of the target spectrum area to determine the maximum frequency of the target spectrum image.
Please refer to the description of S14 in the embodiment shown in fig. 2 in detail, which is not repeated here.
According to the extraction method of the maximum frequency of the spectrogram, corresponding pixel thresholds are determined for each target area, so that pixel points are accurately divided, and the reliability of the divided target areas is guaranteed. And determining the communication area, and filtering the communication area, wherein the communication area with the too small area is regarded as noise, and the communication area with the too small area is removed, so that the effect of removing relatively strong independent speckle noise is achieved.
In this embodiment, a method for extracting a maximum frequency of a spectrogram is provided, which may be used in medical equipment, such as an ultrasound device, and fig. 5 is a flowchart of a method for extracting a maximum frequency of a spectrogram according to an embodiment of the present invention, as shown in fig. 5, where the flowchart includes the following steps:
s31, acquiring a target spectrum image.
Please refer to the description of S11 in the embodiment shown in fig. 2 in detail, which is not repeated here.
S32, dividing the region of the target spectrum image based on the pixel values of all the pixel points in the target spectrum image to determine a target region.
Please refer to the description of S22 in the embodiment shown in fig. 3 in detail, which is not repeated here.
S33, filtering each target area based on the pixel values and the noise threshold values of the pixel points in each target area to determine a target frequency spectrum area.
Please refer to the description of S23 in the embodiment shown in fig. 3 in detail, which is not repeated here.
S34, extracting the envelope of the target spectrum area to determine the maximum frequency of the target spectrum image.
Specifically, the step S34 includes:
s341, acquiring a baseline in the target spectrum image.
S342, determining the number of target frequency spectrum regions above and below the base line by utilizing the position relation between the base line and the target frequency spectrum regions.
The medical device may record location information for each target spectral region, and compare the location information to the location of the baseline to determine whether the target spectral region is above the baseline or below the baseline, and the number of target spectral regions on the same side of the baseline.
S343, determining the target spectrum regions corresponding to the upper envelope and the lower envelope based on the number of target spectrum regions above and below the base line.
The medical device first determines the number of connected regions, i.e., the number of target spectral regions, remaining after denoising above the base line. If there is only one connected region above the base line, i.e., region a, and there is also only one connected region below the base line, i.e., region B, this indicates that no aliasing of the spectrum occurs, as shown in fig. 6, which is a general case where an upper envelope is found for the spectrum above the base line and a lower envelope is found for the spectrum below the base line. If two connected areas are reserved above the base line, namely an area A and an area B, and only one connected area is reserved below the base line, namely an area C, the base line is not at the optimal position, and the spectrum has the aliasing phenomenon, as shown in fig. 7, in the prior art, the base line needs to be adjusted to be at a proper position, and then the envelope is obtained. However, the method provided by the embodiment is to calculate the upper envelope of the frequency spectrum above the base line, which is closer to the base line, calculate the lower envelope of the frequency spectrum above the base line, which is farther from the base line, and is different from the existing method which needs to adjust the base line and then calculate the lower envelope. If two connected areas are reserved above the base line, namely an area A and an area B, and two connected areas are reserved below the base line, namely an area C and an area D, which indicate that the upper frequency spectrum and the lower frequency spectrum have aliasing, the problem cannot be solved in the prior art, and the method provided by the implementation obtains a lower envelope for the frequency spectrum above the base line and further away from the base line, and obtains an upper envelope for the frequency spectrum below the base line and further away from the base line, so that the effect of extracting the envelopes by one key is achieved.
S344, based on the target spectrum regions corresponding to the upper envelope and the lower envelope, the upper envelope and the lower envelope are extracted respectively to determine the maximum frequency of the target spectrum image.
After the medical equipment determines the target frequency spectrum region corresponding to the upper envelope and the lower envelope, the medical equipment can extract the envelope. Specifically, firstly, determining the topmost line L of a target frequency spectrum region, and then calculating points, which are continuously larger than a preset threshold value, of single spectral lines in the target frequency spectrum region from the L-th line to a base line, wherein the points are the maximum frequency points of the spectral lines, and the maximum frequency points on all the spectral lines connected with the target frequency spectrum region form a maximum frequency curve.
In some optional implementations of this embodiment, S344 may include:
(1) When two target spectral regions exist on the same side of the baseline, a target line is determined from the region between the two target spectral regions on the same side.
(2) And carrying out envelope extraction based on the target line and the corresponding target frequency region, and determining the maximum frequency of the target frequency spectrum image.
As shown in fig. 7, there are two target spectrum regions above the base line, the target spectrum region above the base line close to the base line is referred to as region a, and the target spectrum region above the base line far from the base line is referred to as region B. The medical equipment determines a target line from a blank area between the area A and the area B, namely the topmost row L, and extracts an upper envelope line by utilizing a target spectrum area between the topmost row L and a base line; the extraction of the lower envelope is performed using the target spectrum region between the boundary line of the topmost line L and the region B.
And determining target lines in the region between the two target spectrum regions on the same side, so as to distinguish the upper envelope from the lower envelope on the same side, and ensuring the automatic simultaneous extraction of the upper envelope and the lower envelope.
According to the extraction method of the maximum frequency of the spectrogram, when the number of the target frequency spectrum areas above or below the base line is larger than 1, the occurrence of aliasing phenomenon is indicated, and under the condition that the base line is unchanged, the target frequency spectrum areas corresponding to the upper envelope line and the lower envelope line are determined, so that the self-adaptive extraction of the maximum frequency can be realized. Specifically, in this embodiment, the target spectrum image is preprocessed by using a region segmentation method or the like, two regions with the largest area are extracted, the upper spectrum envelope is calculated by using a region above the base line, which is close to the base line, and the lower envelope is calculated by using a region above the base line, which is far from the base line, or below the base line. The method can accurately obtain the maximum frequency curve of the spectrum data under strong noise and weak noise, and is not influenced by the baseline position. The method can resist interference of noise on results under the condition of strong noise, can effectively detect weak blood flow signals under the condition of weak noise, avoids signal loss, and has the advantages of self-adaption, real-time processing, strong practicability and the like.
In this embodiment, an apparatus for extracting a maximum frequency of a spectrogram is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, which have been described and will not be repeated. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides an apparatus for extracting a maximum frequency of a spectrogram, as shown in fig. 8, including:
an acquisition module 41 for acquiring a target spectrum image;
a dividing module 42, configured to determine a target region by performing region division on the target spectrum image based on pixel values of each pixel point in the target spectrum image;
the filtering module 43 is configured to filter each target area based on a pixel value and a noise threshold value of a pixel point in each target area, and determine a target spectrum area;
an extraction module 44 is configured to extract an envelope of the target spectral region to determine a maximum frequency of the target spectral image.
According to the extraction device of the maximum frequency of the spectrogram, the weak noise and the weak signal can be distinguished and analyzed through dividing the pixel values of the pixel points in the target frequency spectrum image; and meanwhile, each target area is filtered to remove strong noise so as to resist the interference of noise on analysis results, and the accuracy of the extracted maximum frequency is improved.
The means for extracting the maximum frequency of the spectrogram in this embodiment is presented in the form of functional units, where the units refer to ASIC circuits, processors and memories executing one or more software or fixed programs, and/or other devices that can provide the above described functionality.
Further functional descriptions of the above respective modules are the same as those of the above corresponding embodiments, and are not repeated here.
The embodiment of the invention also provides medical equipment, which is provided with the extraction device of the maximum frequency of the spectrogram shown in the figure 8.
Referring to fig. 9, fig. 9 is a schematic structural diagram of a medical device according to an alternative embodiment of the present invention, and as shown in fig. 9, the medical device may include: at least one processor 51, such as a CPU (Central Processing Unit ), at least one communication interface 53, a memory 54, at least one communication bus 52. Wherein the communication bus 52 is used to enable connected communication between these components. The communication interface 53 may include a Display screen (Display) and a Keyboard (Keyboard), and the selectable communication interface 53 may further include a standard wired interface and a wireless interface. The memory 54 may be a high-speed RAM memory (Random Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 54 may alternatively be at least one memory device located remotely from the aforementioned processor 51. Wherein the processor 51 may be in conjunction with the apparatus described in fig. 8, the memory 54 stores an application program, and the processor 51 invokes the program code stored in the memory 54 for performing any of the method steps described above.
The communication bus 52 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The communication bus 52 may be classified as a resist bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 9, but not only one bus or one type of bus.
Wherein the memory 54 may include volatile memory (english) such as random-access memory (RAM); the memory may also include a nonvolatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviated as HDD) or a solid state disk (english: solid-state drive, abbreviated as SSD); memory 54 may also include a combination of the types of memory described above.
The processor 51 may be a central processor (English: central processing unit, abbreviated: CPU), a network processor (English: network processor, abbreviated: NP) or a combination of CPU and NP.
The processor 51 may further include a hardware chip, among others. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof (English: programmable logic device). The PLD may be a complex programmable logic device (English: complex programmable logic device, abbreviated: CPLD), a field programmable gate array (English: field-programmable gate array, abbreviated: FPGA), a general-purpose array logic (English: generic array logic, abbreviated: GAL), or any combination thereof.
Optionally, the memory 54 is also used for storing program instructions. The processor 51 may invoke program instructions to implement the method of extracting the maximum frequency of the spectrogram as shown in any of the embodiments of the present application.
The embodiment of the invention also provides a non-transitory computer storage medium, which stores computer executable instructions, and the computer executable instructions can execute the extraction method of the maximum frequency of the spectrogram in any of the method embodiments. Wherein the storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. The method for extracting the maximum frequency of the spectrogram is characterized by comprising the following steps of:
acquiring a target spectrum image;
dividing the region of the target spectrum image based on the pixel value of each pixel point in the target spectrum image to determine a target region;
filtering each target area based on pixel values and noise threshold values of pixel points in each target area to determine a target frequency spectrum area;
an envelope of the target spectral region is extracted to determine a maximum frequency of the target spectral image.
2. The method according to claim 1, wherein the determining the target region by region-dividing the target spectrum image based on the pixel values of the respective pixels in the target spectrum image includes:
acquiring the number of the target areas and a pixel threshold corresponding to the target areas;
and comparing the pixel value of each pixel point in the target spectrum image with each pixel threshold value, dividing each pixel point, and determining the target area.
3. The method of claim 2, wherein comparing the pixel value of each pixel point in the target spectrum image with each pixel threshold value, dividing each pixel point, and determining the target region comprises:
and determining the pixel point with the pixel value smaller than the minimum pixel threshold value as a noise pixel point, and removing the noise pixel point to determine the target area.
4. The method of claim 1, wherein the filtering each of the target regions to determine a target spectral region based on a relationship between pixel values of pixel points within each of the target regions and corresponding thresholds, comprises:
determining all connected areas in the target area based on the pixel values of the pixel points in each target area and the pixel values of the adjacent pixel points;
acquiring the scanning speed of the target spectrum image to determine the area threshold of the noise area;
and filtering the communication areas based on the size relation between the area of each communication area and the area threshold of the noise area, and determining the target frequency spectrum area.
5. The method of claim 4, wherein the acquiring a scan speed at which the target spectral image is acquired to determine an area threshold for a noise region comprises:
acquiring an initial threshold value of a noise area at a preset scanning speed;
determining an adjustment coefficient based on the magnitude relation between the scanning speed and the preset scanning speed;
and determining an area threshold of the noise area based on the adjustment coefficient and the initial threshold.
6. The method of claim 1, wherein the extracting the envelope of the target spectral region to determine the maximum frequency of the target spectral image comprises:
acquiring a baseline in the target spectrum image;
determining the number of the target spectrum regions above and below the base line by utilizing the position relation between the base line and the target spectrum regions;
determining target spectrum regions corresponding to an upper envelope and a lower envelope based on the number of the target spectrum regions above and below the base line;
and respectively extracting the upper envelope curve and the lower envelope curve based on the target frequency spectrum region corresponding to the upper envelope curve and the lower envelope curve so as to determine the maximum frequency of the target frequency spectrum image.
7. The method of claim 6, wherein the extracting the upper envelope and the lower envelope to determine the maximum frequency of the target spectral image based on the target spectral region corresponding to the upper envelope and the lower envelope, respectively, comprises:
determining a target line from a region between two of the target spectral regions on the same side of the baseline when the two of the target spectral regions are present on the same side of the baseline;
and carrying out envelope extraction based on the target line and the corresponding target frequency region, and determining the maximum frequency of the target frequency spectrum image.
8. An apparatus for extracting a maximum frequency of a spectrogram, comprising:
the acquisition module is used for acquiring a target frequency spectrum image;
the dividing module is used for dividing the region of the target spectrum image based on the pixel value of each pixel point in the target spectrum image to determine a target region;
the filtering module is used for filtering each target area based on the pixel values and the noise threshold values of the pixel points in each target area and determining a target frequency spectrum area;
and the extraction module is used for extracting the envelope of the target spectrum area so as to determine the maximum frequency of the target spectrum image.
9. A medical device, comprising:
the device comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, so as to execute the method for extracting the maximum frequency of the spectrogram according to any one of claims 1-7.
10. A computer-readable storage medium storing computer instructions for causing a computer to execute the method of extracting a maximum frequency of a spectrogram according to any one of claims 1 to 7.
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