Ultrasonic imaging method, ultrasonic device and storage medium based on random noise signal

Abstract

The present application relates to the field of ultrasonic image processing technology, and discloses an ultrasonic imaging method, ultrasonic equipment and storage medium based on random noise signals, which are used to solve the problem that the defects of coded imaging in related technologies lead to poor ultrasonic imaging effects. First, a random noise signal of a specified pulse width is generated, and then the random noise signal is filtered based on the bandwidth of the probe to obtain an excitation signal of a target bandwidth; the excitation signal is then transmitted to the target object, and the echo signal reflected by the target object is received; and the echo signal and the decoded signal are pulse compressed to obtain a pulse compression signal; finally, an ultrasonic image of the target object is obtained based on the pulse compression signal. In summary, the embodiment of the present application generates a random noise signal by encoding, and adjusts the pulse width and bandwidth of the random noise signal, so as to improve the longitudinal resolution of the ultrasonic image while improving the penetration, and reduces the range sidelobe intensity by adjusting the bandwidth, so as to achieve better imaging effect.

Description

Technical Field

[0001] The present application relates to the field of ultrasonic imaging technology, and in particular to an ultrasonic imaging method, ultrasonic equipment, and storage medium based on random noise signals. Background Art

[0002] Currently, basic ultrasound images are obtained by transmitting and receiving ultrasound waves through a probe. The received ultrasound waves are filtered and amplified at the front end, and then beamformed to produce the original image. Narrow pulses with higher bandwidths have higher range resolution, but their penetration is limited. Compared to narrow pulses, wider pulses can improve penetration, but at the expense of reduced range resolution.

[0003] In related technologies, coded imaging methods are primarily used to address the aforementioned issues. These include Barker codes, Gray codes, frequency modulation codes, and M sequences. However, each has certain drawbacks. For example, Gray codes require two transmissions, which reduces the image frame rate. Barker codes have a limited maximum code length, resulting in a low signal-to-noise ratio (SNR) for pulse compression and high sidelobe levels. Both frequency modulation codes and M sequences have relatively large range sidelobes.

[0004] Therefore, how to improve the effect of ultrasonic imaging has become a concern in the industry. Summary of the Invention

[0005] The present application provides an ultrasound imaging method, ultrasound equipment and storage medium based on a random noise signal, so as to at least solve the problem in the related art that defects in coded imaging lead to poor ultrasound imaging effects.

[0006] The technical solution of this application is as follows:

[0007] According to a first aspect of an embodiment of the present application, a method for ultrasonic imaging based on a random noise signal is provided, the method comprising:

[0008] Generate a random noise signal with a specified pulse width;

[0009] Filtering the random noise signal based on the bandwidth of the probe to obtain an excitation signal of a target bandwidth;

[0010] transmitting an ultrasonic signal to a target object based on the excitation signal, and receiving an echo signal reflected by the target object;

[0011] Performing pulse compression processing on the echo signal and the decoded signal to obtain a pulse compression signal;

[0012] An ultrasonic image of the target object is obtained based on the pulse compression signal.

[0013] In a possible embodiment, filtering the random noise signal based on the bandwidth of the probe to obtain an excitation signal of a target bandwidth specifically includes:

[0014] Obtain the bandwidth of the probe from the specification sheet of the probe;

[0015] Based on the bandwidth of the probe, filter coefficients are determined using inverse fast Fourier transform to obtain a target filter;

[0016] The target filter is convolved with the random noise signal to obtain an excitation signal of a target bandwidth.

[0017] In a possible embodiment, the method further includes:

[0018] Based on the excitation signal, the decoded signal is determined.

[0019] In a possible embodiment, determining the decoding signal based on the excitation signal specifically includes:

[0020] The decoded signal is determined using the following formula:

[0021]

[0022] Wherein, a is a constant, S(f) is the spectrum of the excitation signal, and H(f) is the spectrum of the decoded signal.

[0023] In a possible embodiment, before performing pulse compression processing on the echo signal and the decoded signal, the method further includes:

[0024] The decoded signal is corrected using the following correction formula:

[0025] x(t)=x base (t)×e -j*2*Πf(d) *coef(d)

[0026] 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, f(d) represents the frequency attenuation corresponding to the scanning depth of d, and coef(d) represents the bandwidth of the decoded signal corresponding to the scanning depth of d.

[0027] In a possible embodiment, performing pulse compression processing on the echo signal and the decoded signal to obtain a pulse compression signal specifically includes:

[0028] The echo signal and the decoded signal are pulse compressed using the following frequency domain matched filtering method:

[0029] R corr (τ)=IFFT(FFT(X1)*CONJ(FFT(X2)))

[0030] Wherein, X1 represents the echo signal, X2 represents the decoded signal, and R corr (τ) represents the pulse compression signal, CONJ represents conjugate, FFT() represents Fourier transform, and IFFT() represents inverse Fourier transform.

[0031] In a possible embodiment, before performing pulse compression processing on the echo signal and the decoded signal, the method further includes:

[0032] A zero-padding operation is performed on the decoded signal based on the length of the echo signal.

[0033] In a possible embodiment, the target bandwidth is equal to the bandwidth of the probe.

[0034] According to a second aspect of an embodiment of the present application, there is provided an ultrasound device, comprising: a processor, a memory, a display unit, and a probe;

[0035] A probe, for transmitting ultrasonic signals;

[0036] a display unit, configured to display an ultrasound image;

[0037] The processor is connected to the probe and the display unit respectively, and is configured to execute the ultrasound imaging method based on random noise signals as described in any one of the first aspects of the embodiments of the present application.

[0038] According to the third aspect of an embodiment of the present application, an embodiment of the present application also 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 is enabled to perform the steps of the ultrasound imaging method based on random noise signals as described in any one of the first aspect of the embodiment of the present application.

[0039] According to a fourth aspect of an embodiment of the present application, a computer program product is provided. When the computer program product is run on an ultrasound device, the ultrasound device executes the steps of the ultrasound imaging method based on a random noise signal according to the first aspect of the embodiment of the present application and any one of the first aspects.

[0040] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects: First, a random noise signal of 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 pulse width and bandwidth of the random noise signal can be flexibly adjusted, and then an excitation signal with a wider bandwidth can be generated, thereby achieving effective improvement in penetration while improving the longitudinal resolution of the ultrasound image; secondly, the present application can reduce the range sidelobe intensity by adjusting the bandwidth by filtering the random noise signal. Moreover, the use of random noise for pulse compression has a significant inhibitory effect on interference signals. Therefore, the method provided by the present application is complete in design and concise in process, which overcomes the defects of coded imaging in related technologies, improves work efficiency and achieves better imaging effects.

[0041] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.

[0043] Figure 1 1 is a schematic diagram of a framework of an ultrasound device according to an exemplary embodiment;

[0044] Figure 2 FIG1 is a schematic diagram showing the principle of realizing an ultrasound image by an ultrasound device according to an exemplary embodiment;

[0045] Figure 3 is a schematic diagram showing a comparison of the processes of an ultrasound imaging method in a related art and the ultrasound imaging method provided in the present application according to an exemplary embodiment;

[0046] Figure 4 is a schematic diagram of the overall process of an ultrasound imaging method based on a random noise signal according to an exemplary embodiment;

[0047] Figure 5 is a schematic diagram of a process of filtering a random noise signal according to an exemplary embodiment;

[0048] Figure 6 is a schematic diagram comparing the processes of processing an echo signal in the related art and the present application according to an exemplary embodiment;

[0049] Figure 7 The figure is a schematic diagram of a pulse compression process according to an exemplary embodiment. DETAILED DESCRIPTION

[0050] In order to enable ordinary people in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0051] It should be noted that the terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0052] The application scenarios described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Persons skilled in the art will appreciate that, as new application scenarios emerge, the technical solutions provided by the embodiments of this application are equally applicable to similar technical problems. In the description of this application, unless otherwise specified, the meaning of "multiple" is the same.

[0053] In related technologies, Gray codes require two transmissions, resulting in a decrease in the image frame rate. Barker codes have a limited maximum code length, resulting in an insufficient signal-to-noise ratio for pulse compression and high sidelobe levels. Both linear frequency modulation signals and M sequences have relatively large range sidelobe levels. To overcome these shortcomings in related technologies, the present application provides an ultrasound imaging method based on a random noise signal.

[0054] The following describes the ultrasound device and the method for suppressing interference of ultrasound images provided in the embodiments of the present application with reference to the accompanying drawings.

[0055] See also Figure 1 , which is a structural block diagram of the ultrasound device provided in an embodiment of the present application.

[0056] It should be understood that Figure 1 The ultrasound device 100 shown is only one example, and the ultrasound device 100 may have more Figure 1 The more or less components shown in the figure can be combined with two or more components, or can have different component configurations. The various components shown in the figure can be implemented in hardware, software, or a combination of hardware and software including one or more signal processing and / or application specific integrated circuits.

[0057] Figure 1 Schematically shows a hardware configuration block diagram of the ultrasound apparatus 100 according to an exemplary embodiment.

[0058] like Figure 1 As shown, the ultrasound device 100 may include, for example: a processor 110, a memory 120, a display unit 130 and a probe 140; wherein,

[0059] Probe 140, for transmitting a random noise signal;

[0060] A display unit 130 is configured to display an ultrasound image of the target object;

[0061] The memory 120 is configured to store data required for ultrasound imaging, which may include software programs, application interface data, etc.;

[0062] The processor 110 is connected to the probe 140 , the display unit 130 and the memory 120 respectively, and is configured to execute the ultrasound imaging method based on random noise signals provided in the present application.

[0063] Figure 2 Schematic diagram of the application principle according to an embodiment of the present application. Figure 1 The implementation of some modules or functional components of the ultrasound device shown will only be described below with respect to the main components, while other components, such as memory, controller, control circuit, etc., will not be described in detail here.

[0064] like Figure 2 As shown, the application environment may include a user interface 210 , a display unit 220 for displaying the user interface, and a processor 230 .

[0065] 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 behind the display panel 221. The backlight assembly 222 may include a plurality of backlight sub-areas (not shown in the figure), each of which may emit light to illuminate the display panel 221.

[0066] 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 an ultrasonic signal and receive an ultrasonic echo signal.

[0067] The processor 230 may process the ultrasonic echo signal to determine an ultrasonic image.

[0068] The following describes the ultrasound imaging method based on random noise signals provided by the present application in conjunction with embodiments.

[0069] The inventive concept of the present application can be summarized as follows: first, a random noise signal of a specified pulse width is generated; then, the random noise signal is filtered based on the bandwidth of the probe to obtain an excitation signal of a target bandwidth; the excitation signal is then transmitted to the target object, and an echo signal reflected by the target object is received; and the echo signal and the decoded signal are pulse compressed to obtain a pulse compression signal; finally, an ultrasonic image of the target object is obtained based on the pulse compression signal. In summary, the embodiments of the present application can, under current technical conditions, first, generate a random noise signal of a specified pulse width by encoding, and adjust the bandwidth of the random noise signal to adapt to the bandwidth of the probe, so that the pulse width and bandwidth of the random noise signal can be flexibly adjusted, thereby generating an excitation signal with a wider bandwidth, thereby achieving effective improvement in penetration while improving the longitudinal resolution of the ultrasound image. Compared with the limited maximum code length of the Barker code, which leads to insufficient signal-to-noise ratio of pulse compression, the pulse width and bandwidth of the random noise signal provided by the present application are wide enough to ensure a good signal-to-noise ratio; secondly, compared with the Gray code requiring two transmissions, the present application only needs to transmit once, so it will not cause the frame rate of the image to decrease. Compared with the high range sidelobe level of the Barker code, linear frequency modulation signal and M sequence, the present application can reduce the range sidelobe intensity by filtering the random noise signal through bandwidth adjustment. Moreover, the use of random noise for pulse compression has a significant suppression effect on interference signals. Therefore, the method provided by the present application is complete in design and simple in process, overcoming the defects of coded imaging in the related art, improving work efficiency and achieving better imaging effect.

[0070] After introducing the main inventive concept of the embodiments of this application, the following describes an ultrasonic imaging method based on a random noise signal provided by the embodiments of this application. It should be noted that the embodiments described below are merely illustrative of this application and are not limiting. In specific implementations, the technical solutions provided by the embodiments of this application can be flexibly applied according to actual needs.

[0071] In some embodiments, as Figure 3 As shown, the processing flow of the ultrasonic signal link usually first excites the ultrasonic probe, that is, sends the excitation signal to the ultrasonic probe, and the excitation signal is converted from a digital signal to an analog signal through the analog-to-digital conversion (ADC) of the ultrasonic probe, so that the ultrasonic probe emits an ultrasonic wave, and then the ultrasonic wave enters the human tissue and reflects the echo signal to the ultrasonic probe. After being received by the probe, the echo signal first passes through the front-end amplification circuit, and then undergoes analog-to-digital conversion processing, and finally performs beam synthesis, orthogonal demodulation, low-pass filtering, logarithmic compression, image processing and other operations to obtain the final ultrasonic image. Compared with the related art, the present application provides an implementation of an ultrasonic imaging method based on a random noise signal, such as Figure 3 As shown in the figure, it is the framework diagram of this method. Figure 3 The contents in bold black box are the main improvements of this application. Figure 3 As shown, in this application, a random noise signal of a specified pulse width is first generated by encoding, and then the bandwidth of the random noise signal is adjusted at the transmitting end, and the random noise signal after the bandwidth adjustment is used as an excitation signal to excite the ultrasonic probe (i.e. Figure 3 The noise signal is sent to the probe in the process, and then the decoded 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, generate an ultrasound image based on the echo signal.

[0072] Based on the above description, the overall process of an ultrasound imaging method based on random noise signal provided by this application is as follows: Figure 4 As shown, it may include the following:

[0073] In step 401 , a random noise signal with a specified pulse width is generated.

[0074] In related technologies, narrow pulse width signals with higher bandwidths have higher range resolution, but lack penetration. Wider pulse widths can improve penetration, but this comes at the cost of lower bandwidth, which reduces range resolution. Therefore, related technologies are unable to provide signals with both high bandwidth and wide pulse widths. However, this application encodes and transmits the signal, giving the random noise signal a wider pulse width and a wider bandwidth, thus balancing the signal's pulse width and bandwidth, ensuring the signal has both higher range resolution and better penetration.

[0075] 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. The specified pulse width is the maximum width within the allowable range of the blind area of the random noise signal. The wider the signal pulse width, the better the signal penetration. Therefore, this application generates a random noise signal of a specified pulse width through encoding, which well ensures the penetration of the random noise signal.

[0076] In step 402 , the random noise signal is filtered based on the bandwidth of the probe to obtain an excitation signal of a target bandwidth.

[0077] After generating a random noise signal of a specified pulse width, the present application filters the random noise signal to obtain an excitation signal of a target bandwidth. The implementation process is as follows: Figure 5 As shown, it can be implemented as:

[0078] In step 501, filter coefficients are determined based on the probe bandwidth using an inverse fast Fourier transform (IFFT) to obtain a target filter. The probe bandwidth is derived from the probe specification, which contains information about the probe, including its bandwidth and power. This probe bandwidth is the frequency domain response. IFFT is performed on the frequency domain response to obtain the time domain response, which is the filter coefficient. The target filter is then determined based on the filter coefficients.

[0079] In step 502, a target filter is convolved with a random noise signal to obtain an excitation signal of a target bandwidth.

[0080] At present, there is a problem in the related art that the sidelobe level of the coded signal is relatively high. For example, in the related art, if the random Gaussian white noise is generated and the bandwidth is rectangular, the sidelobe intensity of the random noise signal is relatively large, and the width of the random noise signal bandwidth does not match the bandwidth of the signal that the ultrasonic probe can transmit. In order to solve the problem of the high sidelobe 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 higher sidelobe suppression capability. And the bandwidth of the random noise signal is adjusted according to the bandwidth of the signal transmitted by the probe recorded in the probe specification book, so that the bandwidth of the random noise signal is kept as consistent as possible with the bandwidth of the probe, so that the random noise signal can fully utilize the probe bandwidth while avoiding the probe heating caused by the bandwidth of the random noise signal being greater than the probe bandwidth, and the wider bandwidth of the random noise signal ensures that the random noise signal has a higher distance resolution.

[0081] After obtaining the excitation signal of the target bandwidth, the excitation signal is transmitted to the probe, and then the probe converts the excitation signal into an ultrasonic signal for ultrasonic scanning.

[0082] In step 403 , an ultrasonic signal is transmitted to a target object based on the excitation signal, and an echo signal reflected by the target object is received.

[0083] The probe transmits ultrasonic signals to the target object and receives echo signals reflected by the target object. It should be noted that when performing ultrasonic scanning, the ultrasonic device can set the scanning depth according to the needs, and obtain corresponding echo signals according to different depths.

[0084] After getting the echo signal, if Figure 6 As shown, the signal processing process for echo signals in the prior art typically includes beamforming, orthogonal demodulation, low-pass filtering, logarithmic compression, image processing, scan conversion, etc. To suppress interference signals, the present application adds a pulse compression step between beamforming and orthogonal demodulation, as shown in step 404.

[0085] In step 404, pulse compression processing is performed on the echo signal and the decoded signal to obtain a pulse compression signal.

[0086] In order to obtain better pulse compression results, it is necessary to design a suitable decoding signal to facilitate pulse compression with the echo signal. The generation of the decoding signal needs to take into account factors such as the probe frequency response, the attenuation of the signal at various depths of human tissue, and tissue movement. Since the characteristic of the impulse function is a special function with infinitely narrow time domain, its Fourier transform is 1, where infinitely narrow time domain is a theoretical definition. This application is to approximate the impulse function to obtain the ideal resolution. Therefore, in order to obtain a pulse compression result that is relatively close to the impulse function, this application uses the inverse filtering method to generate the decoding signal.

[0087] In order to obtain an ideal pulse compression result, the present application needs to ensure that the spectrum of the decoded signal multiplied by the spectrum of the echo signal is as constant as possible, usually 1. This filtering method is called an inverse filtering method.

[0088] In some embodiments, the present application adopts an inverse filtering method to determine a decoding signal for pulse compression based on an excitation signal. Specifically, the decoding signal can be determined using the following formula (1):

[0089]

[0090] Where a is a constant, usually set to 1, S(f) is the spectrum of the excitation signal, and H(f) is the spectrum of the decoded signal. Thus, 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):

[0091]

[0092] Where * represents the conjugate. As can be seen from the above formula, to achieve the ideal pulse compression effect, the spectrum of the excitation signal must not cross zero. Therefore, we first calculate the spectrum of the excitation signal and then take the inverse to obtain the spectrum of the decoded signal. Finally, we zero-padded the spectrum of the decoded signal and performed an inverse fast Fourier transform to obtain the decoded signal.

[0093] Since the propagation of ultrasound signals in the human body is subject to amplitude and frequency attenuation, if the same decoding signal is used, it cannot be guaranteed that the obtained ultrasound image can achieve the ideal pulse compression effect at all scanning depths. In addition, the frequency attenuation of the echo signal will cause a mismatch with the decoding signal, thereby reducing the signal-to-noise ratio gain and generating higher range sidelobes. Therefore, this application proposes a method for correcting the decoding signal with the scanning depth, which can be implemented by using the following correction formula (3) to correct the decoding signal:

[0094] x(t)=xbase (t)×e -j*2*Πf(d) *coef(d) (3)

[0095] Among them, x(t) represents the correction result of the decoded signal, x base (t) represents the basic decoding signal, that is, the decoding signal obtained according to the excitation signal. t represents the time variable. d represents the scanning depth corresponding to the echo signal, which is manually set on the ultrasonic equipment. f(d) represents the frequency attenuation corresponding to the scanning depth d. coef(d) represents the bandwidth of the decoding signal corresponding to the scanning depth d.

[0096] In some embodiments, the frequency attenuation and bandwidth changes can be calculated based on the short-time Fourier transform of the actual echo signal, or can be configured based on empirical values and set by the user according to their needs when using the ultrasound device. Ultimately, after calibrating the above parameters, the present application can determine that the decoded signals at different depths can maximize the ultimate effect of pulse compression, achieve an improvement in signal-to-noise ratio, and suppress interference signals.

[0097] After the decoded signal is obtained and corrected according to different depths, the echo signal and the decoded signal are pulse compressed.

[0098] Pulse compression can be implemented through autocorrelation, which can be divided into time domain autocorrelation and frequency domain autocorrelation. Time domain autocorrelation needs to be implemented by convolving the decoded signal with the echo signal, which is a time-consuming operation. Frequency domain autocorrelation can be used to implement pulse compression, that is, digitally executed using fast Fourier transform (FFT), which can achieve pulse compression at baseband and is a frequency domain matched filtering method. That is, the echo signal and the decoded signal are pulse compressed using the following frequency domain matched filtering method (Formula (4)):

[0099] R corr (d)=IFFT(FFT(X1)*CONJ(FFT(X2))) (4)

[0100] Among them, X1 represents the echo signal, X2 represents the decoded signal, and R corr (d) represents the pulse compression signal corresponding to the scanning depth of d, CONJ represents conjugate, FFT represents fast Fourier transform, and IFFT represents inverse fast Fourier transform.

[0101] According to the above formula (4), the schematic diagram of pulse compression in this application is as follows Figure 7As shown, the echo signal and the decoded signal are fast Fourier transformed respectively, and then the frequency domain signal of the echo signal after fast Fourier transformation is conjugated with the frequency domain signal of the decoded signal and multiplied together, and finally the multiplication result is inverse Fourier transformed to obtain the result after pulse compression.

[0102] It should be noted that before pulse compression processing is performed on the echo signal and the decoded signal, the present application pads the decoded signal with zeros 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, 896 zeros need to be padded after X2 so that their lengths are both 1024, allowing point-to-point multiplication after the fast Fourier transform.

[0103] The gain of the pulse compression implemented in this application on 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 achieve a greater gain on the signal-to-noise ratio, the larger the pulse width and bandwidth of the signal, the greater the improvement in the signal-to-noise ratio. Taking a probe with a center frequency of 7.5M and a bandwidth of 80% as an example, a satisfactory improvement in the signal-to-noise ratio can be achieved by using a pulse width of more than ten microseconds. Moreover, the interference signal cannot achieve an improvement in the signal-to-noise ratio after pulse compression with the decoded signal. Therefore, this application can very effectively suppress the interference signal.

[0104] In step 405, an ultrasonic image of the target object is obtained based on the pulse compression signal. After obtaining a relatively ideal pulse compression signal, the present application processes the pulse signal through an ultrasonic device to finally obtain an ultrasonic image of the target object and display it on a display screen of the relevant device.

[0105] In summary, under current technical conditions, the embodiments of the present application can, firstly, generate a random noise signal through encoding and adjust the pulse width and bandwidth of the random noise signal to effectively improve the penetration while improving the longitudinal resolution of the ultrasound image; secondly, the present application can reduce the range sidelobe intensity by adjusting the bandwidth. It also has a significant inhibitory effect on interference signals. Therefore, the method provided by this application is complete in design and concise in process, which overcomes the defects of coded imaging in related technologies, improves work efficiency and makes ultrasound imaging better.

[0106] In an exemplary embodiment, the present application further provides a computer-readable storage medium including instructions, such as a memory 120 including instructions, wherein the instructions can be executed by the processor 110 of the terminal device 100 to perform the above-mentioned ultrasound imaging method based on a random noise signal. Alternatively, the computer-readable storage medium can be a non-transitory computer-readable storage medium, such as a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0107] In an exemplary embodiment, a computer program product is further provided, including a computer program. When the computer program is executed by the processor 110 , the computer program implements the ultrasound imaging method based on a random noise signal as provided in the present application.

[0108] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0109] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0110] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0112] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. An ultrasonic imaging method based on random noise signal, characterized in that: The method comprises: Generate a random noise signal of a specified pulse width, wherein the specified pulse width is the maximum pulse width within an allowable range of a blind zone of the random noise signal; Filtering the random noise signal based on the bandwidth of the probe to obtain an excitation signal of 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 decoded signal to obtain a pulse compression signal; An ultrasonic image of the target object is obtained based on the pulse compression signal.

2. The method according to claim 1, characterized in that The filtering of the random noise signal based on the bandwidth of the probe to obtain an excitation signal of a target bandwidth specifically includes: Based on the bandwidth of the probe, filter coefficients are determined using inverse fast Fourier transform to obtain a target filter; The target filter is convolved with the random noise signal to obtain an excitation signal of a target bandwidth.

3. The method according to claim 1, characterized in that The method further comprises: Based on the excitation signal, the decoded signal is determined.

4. The method according to claim 3, characterized in that The determining the decoding signal based on the excitation signal specifically includes: The decoded signal is determined using the following formula: Wherein, a is a constant, S(f) is the spectrum of the excitation signal, and H(f) is the spectrum of the decoded signal.

5. The method according to claim 4, characterized in that 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, f(d) represents the frequency attenuation corresponding to the scanning depth of d, and coef(d) represents the bandwidth of the decoded signal corresponding to the scanning depth of d.

6. The method according to claim 1, characterized in that The performing pulse compression processing on the echo signal and the decoded signal to obtain a pulse compression signal specifically includes: The echo signal and the decoded signal are pulse compressed using 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, and R corr (d) represents the pulse compression signal corresponding to the scanning depth of d, CONJ represents conjugate, FFT() represents Fourier transform, and IFFT() represents inverse Fourier transform.

7. The method according to claim 6, characterized in that Before performing pulse compression processing on the echo signal and the decoded signal, the method further includes: A zero-padding operation is performed on the decoded signal based on the length of the echo signal.

8. The method according to claim 1, characterized in that The target bandwidth is equal to the bandwidth of the probe.

9. An ultrasonic device, characterized in that: include: processor, memory, display unit, and probe; A probe, for transmitting ultrasonic signals; a display unit, configured to display an ultrasound image; A processor is connected to the probe and the display unit respectively, and is configured to execute the steps of the ultrasound imaging method based on random noise signals according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of an ultrasound device, the ultrasound device is enabled to perform the steps of the ultrasound imaging method based on a random noise signal according to any one of claims 1 to 8.

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