CN114680933A - Ultrasonic imaging method based on random noise signal, ultrasonic device and storage medium - Google Patents

Abstract

The present application relates to the technical field of ultrasonic image processing, and discloses an ultrasonic imaging method, ultrasonic equipment and storage medium based on random noise signals, which are used to solve the problem of poor ultrasonic imaging effect caused by defects in coded imaging in the related art. First, generate a random noise signal with a specified pulse width, then filter the random noise signal based on the bandwidth of the probe to obtain an excitation signal with the target bandwidth; then transmit the excitation signal to the target object, and receive the echo signal reflected by the target object; and The echo signal and the decoded signal are subjected to pulse compression processing to obtain a pulse compressed signal; finally, based on the pulse compressed signal, an ultrasonic image of the target object is obtained. To sum up, the embodiment of the present application generates a random noise signal by coding, and adjusts the pulse width and bandwidth of the random noise signal, so as to improve the longitudinal resolution of the ultrasound image while improving the penetrating power, and reduce the distance side lobe intensity through bandwidth adjustment. , which makes the imaging effect better.

Description

Ultrasound imaging method, ultrasound equipment and storage medium based on random noise signal

technical field

The present application relates to the technical field of ultrasonic imaging, and in particular, to an ultrasonic imaging method, ultrasonic device and storage medium based on random noise signals.

Background technique

At present, the basic ultrasound image is obtained by transmitting and receiving ultrasound by the probe. The received ultrasound is filtered and amplified at the front end and then the original image can be obtained by beam synthesis. Narrow pulses with higher bandwidths have higher range resolution but are less penetrating. Compared with narrow pulses, wider pulses can bring about improved penetration, but at the cost of reduced range resolution.

In the related art, coding and imaging methods are mainly used to solve the above problems, and the coding methods include Barker codes, Gray codes, FM codes and M-sequences. However, each of them has certain defects. For example, the Gray code requires two transmissions, so the frame rate of the image will decrease. The longest code length of the Barker code is limited, so the signal-to-noise ratio of pulse compression is insufficient, and the side lobe level is high. Frequency modulation The range side lobe levels of the coded and M sequences are both too large.

Therefore, how to improve the effect of ultrasound imaging has become a concern of the industry.

SUMMARY OF THE INVENTION

The present application provides an ultrasonic imaging method, ultrasonic device and storage medium based on random noise signals, so as to at least solve the problem of poor ultrasonic imaging effect caused by defects in coded imaging in the related art.

The technical solution of this application is as follows:

According to a first aspect of the embodiments of the present application, an ultrasonic imaging method based on random noise signals is provided, and the method includes:

Generate random noise signal with specified pulse width;

Filter the random noise signal based on the bandwidth of the probe to obtain the excitation signal of the target bandwidth;

Based on the excitation signal, transmit an ultrasonic signal to a target object, and receive an echo signal reflected by the target object;

performing pulse compression processing on the echo signal and the decoded signal to obtain a pulse compression signal;

Based on the pulse compressed signal, an ultrasound image of the target object is obtained.

In a possible embodiment, the random noise signal is filtered based on the bandwidth of the probe to obtain the excitation signal of the target bandwidth, which specifically includes:

Obtain the bandwidth of the probe from the specification of the probe;

Based on the bandwidth of the probe, use inverse fast Fourier transform to determine filter coefficients to obtain the target filter;

The target filter is used to perform a convolution operation with the random noise signal to obtain an excitation signal with a target bandwidth.

In a possible embodiment, the method further includes:

Based on the excitation signal, the decoded signal is determined.

In a possible embodiment, the determining the decoded signal based on the excitation signal specifically includes:

The decoded signal is determined using the following formula:

where a is a constant, S(f) is the spectrum of the excitation signal, and H(f) is the spectrum of the decoded signal.

In a possible embodiment, before performing pulse compression processing on the echo signal and the decoded signal, the method further includes:

The decoded signal is corrected using the following correction formula:

x(t)=x _base (t)×e ^-j*2*Πf(d) *coef(d)

Among them, x(t) represents the correction result of the decoded signal, x _base (t) represents the decoded signal, t represents the time variable, d represents the scanning depth corresponding to the echo signal, and f(d) represents the corresponding scanning depth of d The frequency attenuation of , coef(d) represents the bandwidth of the decoded signal corresponding to the d scan depth.

In a possible embodiment, performing pulse compression processing on the echo signal and the decoded signal to obtain a pulse compressed signal specifically includes:

The echo signal and the decoded signal are subjected to pulse compression processing using the matched filtering method in the following frequency domain:

R _corr (τ)=IFFT(FFT(X1)*CONJ(FFT(X2)))

Wherein, X1 represents the echo signal, X2 represents the decoded signal, R _corr (τ) represents the pulse compression signal, CONJ represents the conjugate, FFT() represents the Fourier transform, and IFFT() represents the Fourier transform Inverse transform.

In a possible embodiment, before performing pulse compression processing on the echo signal and the decoded signal, the method further includes:

The decoded signal is complemented with 0s based on the length of the echo signal.

In a possible embodiment, the target bandwidth is equal to the bandwidth of the probe.

According to a second aspect of the embodiments of the present application, there is provided an ultrasound apparatus, including: a processor, a memory, a display unit, and a probe;

Probe for transmitting ultrasonic signals;

a display unit for displaying ultrasound images;

A processor, which is respectively connected to the probe and the display unit, is configured to execute the ultrasonic imaging method based on a random noise signal according to any one of the first aspect of the embodiments of the present application.

According to a third aspect of the embodiments of the present application, an embodiment of the present application further provides a computer-readable storage medium, when the instructions in the computer-readable storage medium are executed by the processor of the ultrasound device, the ultrasound device can The steps of the ultrasonic imaging method based on random noise signal according to any one of the first aspect of the embodiments of the present application are performed.

According to a fourth aspect of the embodiments of the present application, a computer program product is provided, which, when the computer program product runs on an ultrasound device, enables the ultrasound device to execute the first aspect and the first aspect of the embodiments of the present application. The steps of any one of the ultrasonic imaging methods based on random noise signals.

The technical solutions provided by the embodiments of the present application bring at least the following beneficial effects: first, a random noise signal with a specified pulse width is generated by encoding, and the bandwidth of the random noise signal is adjusted to adapt to the bandwidth of the probe, so that the random noise signal has a Both the pulse width and the bandwidth can be flexibly adjusted, so that a wider bandwidth excitation signal can be generated, so as to effectively improve the penetrating power while improving the longitudinal resolution of the ultrasound image; secondly, the present application can filter the random noise signal by filtering the random noise signal. The range side lobe intensity can be reduced by adjusting the bandwidth. Moreover, the use of random noise for pulse compression has a significant suppressing effect on interfering signals. Therefore, the method provided by the present application has a complete design and a simple process, overcomes the defects of the coding imaging in the related art, improves the work efficiency, and has a better imaging effect.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not limiting of the present application.

Description of drawings

The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the description, serve to explain the principles of the present application, and do not constitute an improper limitation of the present application.

FIG. 1 is a schematic diagram of a frame of an ultrasonic device according to an exemplary embodiment;

FIG. 2 is a schematic diagram showing the principle of implementing an ultrasound image by an ultrasound device according to an exemplary embodiment;

FIG. 3 is a schematic diagram illustrating a flow comparison between an ultrasonic imaging method in the related art and an ultrasonic imaging method provided by the present application according to an exemplary embodiment;

FIG. 4 is a schematic overall flowchart of an ultrasonic imaging method based on random noise signals according to an exemplary embodiment;

5 is a schematic flowchart of filtering a random noise signal according to an exemplary embodiment;

FIG. 6 is a schematic diagram showing the comparison of the flow of processing echo signals in the related art and the present application according to an exemplary embodiment;

FIG. 7 is a schematic flowchart of pulse compression according to an exemplary embodiment.

Detailed ways

In order to make those skilled in the art better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings.

It should be noted that the terms "first", "second", etc. in the description and claims of the present application and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that data so used may be interchanged under appropriate circumstances so that the embodiments of the application described herein can be practiced in sequences other than those illustrated or described herein. The implementations described in the illustrative examples below are not intended to represent all implementations consistent with this application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as recited in the appended claims.

The application scenarios described in the embodiments of the present application are for the purpose of illustrating the technical solutions of the embodiments of the present application more clearly, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. It appears that the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems. Wherein, in the description of the present application, unless otherwise specified, the meaning of "plurality".

In the related art, the Gray code needs to be transmitted twice, so the frame rate of the image will decrease. The longest code length of the Barker code is limited, so the signal-to-noise ratio of the pulse compression is insufficient, and the side lobe level is high. The linear frequency modulation signal and the M sequence The distance side lobe level is too large. In order to overcome the defects in the related art, the present application provides an ultrasonic imaging method based on random noise signals.

The ultrasonic device and the method for suppressing the interference of ultrasonic images provided by the embodiments of the present application will be described below with reference to the accompanying drawings.

Referring to FIG. 1 , it is a structural block diagram of an ultrasonic device provided in an embodiment of the present application.

It should be understood that the ultrasound device 100 shown in FIG. 1 is only an example, and that the ultrasound device 100 may have more or fewer components than those shown in FIG. 1 , two or more components may be combined, or Different component configurations are possible. The various components shown in the figures may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.

FIG. 1 exemplarily shows a block diagram of a hardware configuration of an ultrasound apparatus 100 according to an exemplary embodiment.

As shown in FIG. 1 , the ultrasound apparatus 100 may include, for example, a processor 110, a memory 120, a display unit 130 and a probe 140; wherein,

a probe 140 for transmitting random noise signals;

a display unit 130, configured to display the ultrasound image of the target object;

The memory 120 is configured to store data required for ultrasound imaging, which may include software programs, application interface data, etc.;

The processor 110, which is respectively connected with the probe 140, the display unit 130 and the memory 120, is configured to execute the ultrasonic imaging method based on random noise signals provided by the present application.

FIG. 2 is a schematic diagram of an application principle according to an embodiment of the present application. Among them, this part can be realized by some modules or functional components of the ultrasound equipment shown in FIG. 1 , and only the main components will be described below, and other components, such as memory, controller, control circuit, etc., will not be described here.

As shown in FIG. 2 , the application environment may include a user interface 210 , a display unit 220 for displaying the user interface, and a processor 230 .

The display unit 220 may include a display panel 221 and a backlight assembly 222 . The display panel 221 is configured to display ultrasound images, and the backlight assembly 222 is located on the back of the display panel 221. The backlight assembly 222 may include a plurality of backlight sub-regions (not shown in the figure), and each backlight sub-region can emit light to light up the display. Panel 221.

The processor 230 may be configured to control the brightness of the backlight source of each backlight partition in the backlight assembly 222, and to control the probe to transmit ultrasonic signals and receive ultrasonic echo signals.

The processor 230 may process the ultrasonic echo signal to determine an ultrasonic image.

The ultrasonic imaging method based on random noise signals provided by the present application will be introduced below with reference to the embodiments.

The inventive concept of the present application can be summarized as follows: first, generate a random noise signal with a specified pulse width; then, filter the random noise signal based on the bandwidth of the probe to obtain an excitation signal with a target bandwidth; then transmit the excitation signal to the target object, receive The echo signal reflected by the target object; the echo signal and the decoded signal are subjected to pulse compression processing to obtain a pulse compressed signal; finally, based on the pulse compressed signal, an ultrasonic image of the target object is obtained. To sum up, under the current technical conditions, the embodiment of the present application can firstly generate a random noise signal with a specified pulse width through coding, and adjust the bandwidth of the random noise signal to adapt to the bandwidth of the probe, so that the pulse of the random noise signal is Both the width and the bandwidth can be flexibly adjusted, so that a wider bandwidth excitation signal can be generated, so as to effectively improve the penetration power while improving the longitudinal resolution of the ultrasound image. Compared with the limited longest code length of the Barker code, pulse compression is caused The signal-to-noise ratio is insufficient, and the pulse width and bandwidth of the random noise signal provided by this application are wide enough to ensure a good signal-to-noise ratio; secondly, compared with the Gray code that requires two transmissions, this application only needs to transmit once, so it will not As a result, the frame rate of the image is reduced. Compared with the Barker code, the linear frequency modulation signal and the M sequence, the range side lobe level is higher. The present application can reduce the range side lobe intensity through bandwidth adjustment by filtering the random noise signal. Moreover, the use of random noise for pulse compression has a significant suppressing effect on interfering signals. Therefore, the method provided by the present application has a complete design and a simple process, overcomes the defects of the coding imaging in the related art, improves the work efficiency, and has a better imaging effect.

After the main inventive idea of the embodiments of the present application is introduced, an ultrasonic imaging method based on random noise signals provided by the embodiments of the present application will be introduced below. It should be noted that the embodiments introduced below are only used to illustrate the present application. rather than limiting. During specific implementation, the technical solutions provided by the embodiments of the present application may be flexibly applied according to actual needs.

In some embodiments, as shown in FIG. 3 , the processing flow of the ultrasonic signal chain usually firstly excites the ultrasonic probe, that is, the excitation signal is sent to the ultrasonic probe, and the excitation signal is subjected to analog-to-digital conversion (analogue-to-digital conversion) of the ultrasonic probe. , ADC) processing converts the digital signal into an analog signal, so that the ultrasonic probe emits ultrasonic waves, and then the ultrasonic waves enter the human tissue and reflect the echo signals to the ultrasonic probe. After the echo signal is received by the probe, it first goes through the front-end amplifying circuit, and then undergoes analog-to-digital conversion processing, and then performs beamforming, quadrature demodulation, low-pass filtering, logarithmic compression, image processing and other operations to obtain the final ultrasound image. Compared with the related art, the implementation of an ultrasonic imaging method based on random noise signals provided by the present application is shown in FIG. Major improvements. As shown in FIG. 3 , in this application, a random noise signal with a specified pulse width is first encoded and generated, and then the bandwidth of the random noise signal is adjusted at the transmitting end, and the random noise signal after the adjusted bandwidth is used as an excitation signal to excite the ultrasonic probe ( That is, the noise signal is sent to the probe in Figure 3), after that, the decoding signal is used at the receiving end to perform pulse compression processing on the echo signal after analog-to-digital conversion, so as to obtain the original echo signal with improved signal-to-noise ratio, and finally , an ultrasound image is generated based on the echo signals.

Based on the above description, the overall flow of an ultrasonic imaging method based on random noise signals provided by the present application is shown in FIG. 4 , which may include the following contents:

In step 401, a random noise signal with a specified pulse width is generated.

In the related art, the narrow pulse width signal with higher bandwidth has higher distance resolution, but the penetrating power is insufficient; the wider pulse width can improve the penetrating power, but the bandwidth of the signal is higher. Low results in a decrease in range resolution. Therefore, the related art cannot provide a signal with a high bandwidth and a wide pulse width. In the present application, by encoding and transmitting the signal, the random noise signal has a wider pulse width, and at the same time, the random noise signal has a wider bandwidth, taking into account the pulse width and bandwidth of the signal, and ensuring that the signal has a higher distance resolution and better penetration.

This application uses software such as matlab to generate a random noise signal, and sets the pulse width of the random noise signal to a specified pulse width during the encoding process, and the specified pulse width is the maximum width within the allowable range of the blind zone of the random noise signal. The wider the pulse width, the better the penetrating power of the signal. Therefore, the present application generates a random noise signal with a specified pulse width through coding, which well guarantees the penetrating power of the random noise signal.

In step 402, the random noise signal is filtered based on the bandwidth of the probe to obtain the excitation signal of the target bandwidth.

After generating a random noise signal with a specified pulse width, the present application filters the random noise signal to obtain an excitation signal with a target bandwidth. The implementation process is shown in Figure 5, which can be implemented as follows:

In step 501, based on the bandwidth of the probe, inverse fast Fourier transform is used to determine filter coefficients to obtain a target filter. The bandwidth of the above probe comes from the probe specification, and the probe specification records relevant information about the probe, and the relevant information includes the bandwidth, power, and the like of the probe. The probe bandwidth is the frequency domain response, and the time domain response can be obtained by performing inverse Fourier transform on the frequency domain response. The time domain response is the filter coefficient, and the target filter is determined based on the filter coefficient.

In step 502, a target filter is used to perform a convolution operation with a random noise signal to obtain an excitation signal with a target bandwidth.

At present, there is a problem that the side lobe level of the encoded signal is relatively high in the related art. For example, random Gaussian white noise is generated in the related art. If the bandwidth is rectangular, the side lobe intensity of the random noise signal is relatively large, and the width of the random noise signal bandwidth is large. It does not match the bandwidth of the signal that the ultrasound probe can transmit. In order to solve the problem of high side lobe level of the coded signal in the related art, the present application adjusts the shape of the bandwidth to be non-rectangular, so that the random noise signal after adjusting the bandwidth has a high side lobe suppression capability. And adjust the bandwidth of the random noise signal according to the bandwidth of the signal emitted by the probe recorded in the probe specification, so that the bandwidth of the random noise signal is as consistent as possible with the bandwidth of the probe, so that the random noise signal can make full use of the probe bandwidth and at the same time. The probe heating caused by the bandwidth of the random noise signal being larger than the probe bandwidth can be avoided, and the wider bandwidth of the random noise signal ensures that the random noise signal has a higher distance resolution.

After obtaining the excitation signal of the target bandwidth, the excitation signal is transmitted to the probe, and then the excitation signal is converted into an ultrasonic signal for ultrasonic scanning through the probe.

In step 403, an ultrasonic wave signal is transmitted to the target object based on the excitation signal, and an echo signal reflected by the target object is received.

The probe transmits the ultrasonic signal to the target object and receives the echo signal reflected by the target object. It should be noted that, when the ultrasonic device performs ultrasonic scanning, the scanning depth can be set according to requirements, and corresponding echo signals can be obtained according to different depths.

After the echo signal is obtained, as shown in FIG. 6 , the signal processing flow of the echo signal in the prior art is usually beamforming, quadrature demodulation, low-pass filtering, logarithmic compression, image processing, scan conversion, and the like. In order to suppress interference signals, the present application adds a pulse compression step between beamforming and quadrature demodulation. Step 404 is as follows.

In step 404, pulse compression processing is performed on the echo signal and the decoded signal to obtain a pulse compressed signal.

In order to obtain better pulse compression results, it is necessary to design a suitable decoded signal to facilitate pulse compression with the echo signal. The generation of the decoded signal needs to consider the frequency response of the probe, the attenuation of the signal at various depths of the human tissue, and the tissue motion. Since the characteristic of the impulse function is a special function with infinitely narrow time domain, its Fourier transform is 1, and the infinitely narrow time domain is a theoretical definition. resolution. Therefore, in order to obtain a pulse compression result that is relatively close to the impulse function, the present application adopts an inverse filtering method to generate a decoded signal.

In order to obtain an ideal pulse compression result, the present application needs to ensure that the spectrum of the decoded signal and the spectrum of the echo signal are multiplied as a constant as much as possible, usually the constant is 1, and this filtering method is called an inverse filtering method.

In some embodiments, the present application adopts the method of inverse filtering to determine the decoded signal for pulse compression based on the excitation signal. Specifically, the following formula (1) can be used to determine the decoded signal:

Among them, a is a constant, usually taken as 1, S(f) is the spectrum of the excitation signal, and H(f) is the spectrum of the decoded signal. Therefore, the present application can obtain a pulse compression result that is relatively close to the impulse function. The derivation process of the above formula (1) is shown in the following formula (2):

Among them, * is to take the conjugate. It can be seen from the above formula that in order to obtain the ideal pulse compression effect, the frequency spectrum of the excitation signal must not exceed the zero point. Therefore, first obtain the spectrum of the excitation signal, then take the reciprocal to obtain the spectrum of the decoded signal, and finally perform zero-filling on the spectrum of the decoded signal and obtain the inverse fast Fourier transform to obtain the decoded signal.

Because the propagation of ultrasonic signals in the human body has attenuation of amplitude and frequency, if the same decoding signal is used, it cannot guarantee that the obtained ultrasonic images can achieve the ideal pulse compression effect at each scanning depth, and the frequency of the echo signal is attenuated. This results in a mismatch with the decoded signal that reduces SNR gain and produces higher range side lobes. Therefore, the present application proposes a method for calibrating the decoded signal with the scanning depth, which can be implemented as the following correction formula (3) to correct the decoded signal:

x(t)=x _base (t)×e ^-j*2*Πf(d) *coef(d) (3)

Among them, x(t) represents the correction result of the decoded signal, x _base (t) represents the base decoded signal, that is, the decoded signal obtained from the excitation signal, t represents the time variable, d represents the scanning depth corresponding to the echo signal, and the depth It is set manually on the ultrasound equipment, f(d) represents the frequency attenuation corresponding to the d scanning depth, and coef(d) represents the bandwidth of the decoded signal corresponding to the d scanning depth.

In some embodiments, the frequency attenuation and bandwidth changes can be obtained according to the short-time Fourier transform of the actual echo signal, or can be configured through empirical values, which can be set by the user according to requirements when using the ultrasonic device. Finally, after the calibration of the above parameters, the present application can determine that the decoded signals at different depths can ensure the final effect of pulse compression to the greatest extent, and realize the improvement of the signal-to-noise ratio and the suppression of interference signals.

After the decoded signal is obtained and the decoded signal is corrected according to different depths, the echo signal and the decoded signal are subjected to pulse compression processing.

The implementation of pulse compression can be performed by means of autocorrelation, and its implementation is further divided into time domain autocorrelation and frequency domain autocorrelation. Time-domain autocorrelation requires convolution of the decoded signal with the echo signal, which is time-consuming. Frequency domain autocorrelation can be used to realize pulse compression, that is, fast Fourier transform (fast Fourier transform, FFT) is used for digital execution, and pulse compression can be realized in baseband, which is a matched filtering method in frequency domain. That is, the following frequency domain matched filtering method (formula (4)) is used to perform pulse compression processing on the echo signal and the decoded signal:

R _corr (d)=IFFT(FFT(X1)*CONJ(FFT(X2))) (4)

Among them, X1 represents the echo signal, X2 represents the decoded signal, R _corr (d) represents the pulse compressed signal corresponding to the d scanning depth, CONJ represents the conjugate, FFT represents the fast Fourier transform, and IFFT represents the inverse fast Fourier transform.

According to the above formula (4), the schematic diagram of pulse compression in the present application is shown in FIG. 7 , the echo signal and the decoded signal are respectively subjected to fast Fourier transform, and then the frequency domain of the echo signal after the fast Fourier transform is The signal and the frequency domain signal of the decoded signal are conjugated and then multiplied, and finally the multiplied result is subjected to inverse Fourier transform, and the result after pulse compression can be obtained.

It should be noted that, before performing pulse compression processing on the echo signal and the decoded signal, the present application will perform a zero-filling operation on the decoded signal based on the length of the echo signal. For example, assuming that the length of the echo signal X1 is 1024 and the length of the decoded signal X2 is 128, in order to ensure that they can be multiplied point-to-point in the frequency domain, it is necessary to add 896 zeros after X2, so that their lengths are all 1024, thus Point-to-point multiplication is possible after fast Fourier transform.

The gain of the pulse compression implemented in the present application to the signal-to-noise ratio is T*B, where T is the pulse width of the signal, and B is the bandwidth of the signal. In order to increase the gain of the signal-to-noise ratio, the pulse width and bandwidth of the signal are made larger, so that the improvement of the signal-to-noise ratio is larger. Taking a probe with a center frequency of 7.5M and a bandwidth of 80% as an example, a satisfactory signal-to-noise ratio improvement can be obtained with a pulse width of more than ten microseconds. Moreover, the signal-to-noise ratio cannot be improved after the interference signal is compressed with the decoded signal. Therefore, the present application can very effectively suppress the interference signal.

In step 405, an ultrasound image of the target object is obtained based on the pulse compressed signal. After an ideal pulse compression signal is obtained in the present application, the pulse signal is processed by an ultrasonic device to finally obtain an ultrasonic image of the target object, which is displayed on the display screen of the related device.

To sum up, under the current technical conditions, the embodiments of the present application can firstly generate a random noise signal by encoding, and adjust the pulse width and bandwidth of the random noise signal, so as to improve the longitudinal resolution of ultrasonic images and at the same time effectively Improve the penetration force; secondly, the present application can reduce the distance side lobe intensity by adjusting the bandwidth. And it has a significant inhibitory effect on interference signals. Therefore, the method provided by the present application has a complete design and a simple process, overcomes the defects of the coding imaging in the related art, improves the work efficiency and makes the ultrasound imaging effect better.

In an exemplary embodiment, the present application also provides a computer-readable storage medium including instructions, for example, a memory 120 including instructions, and the above-mentioned instructions can be executed by the processor 110 of the terminal device 100 to complete the above-mentioned random noise signal-based ultrasound imaging method. Alternatively, the computer-readable storage medium may be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk and optical data storage devices, etc.

In an exemplary embodiment, a computer program product is also provided, including a computer program that, when executed by the processor 110, implements the random noise signal-based ultrasound imaging method as provided in the present application.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims (10)

1. A method of ultrasound imaging based on random noise signals, the method comprising:

generating a random noise signal of a specified pulse width;

filtering the random noise signal based on the bandwidth of the probe to obtain an excitation signal with a target bandwidth;

transmitting an ultrasonic signal to a target object based on the excitation signal and receiving an echo signal reflected by the target object;

performing pulse compression processing on the echo signal and the decoding signal to obtain a pulse compression signal;

and obtaining an ultrasonic image of the target object based on the pulse compression signal.

2. The method according to claim 1, wherein the filtering the random noise signal based on a bandwidth of the probe to obtain an excitation signal with a target bandwidth comprises:

determining a filter coefficient by utilizing inverse fast Fourier transform based on the bandwidth of the probe to obtain a target filter;

and performing convolution operation on the target filter and the random noise signal to obtain an excitation signal with a target bandwidth.

3. The method of claim 1, further comprising:

determining the decoded signal based on the excitation signal.

4. The method according to claim 3, wherein said determining the decoded signal based on the excitation signal comprises:

determining the decoded signal using the following equation:

where a is a constant, s (f) is the frequency spectrum of the excitation signal, and h (f) is the frequency spectrum of the decoded signal.

5. The method of claim 4, wherein prior to pulse compressing the echo signal and the decoded signal, the method further comprises:

correcting the decoded signal using the following correction formula:

x(t)＝x_base(t)×e^-j*2*Πf(d)*coef(d)

wherein x (t) represents the correction result of the decoded signal, x_base(t) represents the decoded signal, t represents a time variable, d represents a scan depth corresponding to the echo signal, f (d) represents a frequency attenuation amount corresponding to the d scan depth, and coef (d) represents a bandwidth of the decoded signal corresponding to the d scan depth.

6. The method according to claim 1, wherein the performing the pulse compression processing on the echo signal and the decoded signal to obtain a pulse compressed signal specifically includes:

and performing pulse compression processing on the echo signal and the decoded signal by adopting the following frequency domain matched filtering method:

R_corr(d)＝IFFT(FFT(X1)*CONJ(FFT(X2)))

wherein X1 represents the echo signal, X2 represents the decoded signal, R_corr(d) Represents the pulse compression signal corresponding to d scan depth, CONJ represents conjugate, FFT () represents fourier transform, IFFT () represents inverse fourier transform.

7. The method of claim 6, wherein prior to pulse compressing the echo signal with the decoded signal, the method further comprises:

and performing 0 complementing operation on the decoding signal based on the length of the echo signal.

8. The method of claim 1, wherein the target bandwidth is equal to a bandwidth of the probe.

9. An ultrasound device, comprising: a processor, a memory, a display unit and a probe;

a probe for emitting an ultrasound signal;

a display unit for displaying an ultrasound image;

a processor, connected with the probe and the display unit, respectively, configured to perform the steps of the random noise signal based ultrasound imaging method according to any of claims 1-8.

10. A computer readable storage medium, wherein instructions in the computer readable storage medium, when executed by a processor of an ultrasound device, enable the ultrasound device to perform the steps of the random noise signal based ultrasound imaging method of any of claims 1-8.

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