Ultrasonic signal compounding method, device, ultrasonic equipment and storage medium

Abstract

The present application discloses an ultrasonic signal compounding method, apparatus, an ultrasonic device, and a computer-readable storage medium. The method comprises: collecting ultrasonic echo signals and determining signal segments corresponding to different depths in the ultrasonic echo signals; determining a target diagnostic site, and based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, determining a transformation range of a dynamic range change curve corresponding to each depth, performing dynamic range changes on the signal segments at the corresponding depths, and obtaining a dynamic range change result corresponding to each depth; wherein the transformation range includes the energy range corresponding to all tissue organs except noise; and summing the dynamic range change results corresponding to all depths to obtain a composite ultrasonic signal. It can be seen that the ultrasonic signal compounding method provided by the present application improves the efficiency of ultrasonic signal compounding and achieves the purpose of suppressing noise.

Description

Technical Field

[0001] The present application relates to the field of ultrasound technology, and more specifically, to an ultrasound signal compounding method and apparatus, an ultrasound device, and a computer-readable storage medium. Background Art

[0002] In related technologies, the compounding of ultrasonic signals can be done by spatial compounding, frequency compounding, or line compounding. In the process of spatial compounding, the probe is scanned at different angles, the image is corrected according to the spatial position of the echo signal, and the ultrasonic signals scanned at multiple angles are superimposed. Since spatial compounding requires multiple scans, the time resolution of the image is low. Frequency compounding is to demodulate a group of echo signals using different frequencies, and superimpose multiple demodulation results, which easily introduces noise. The process of line compounding is to transmit ultrasonic waves multiple times at the same spatial position and superimpose the echo signals transmitted multiple times. However, line compounding is heavily dependent on hardware equipment and requires a very powerful computing chip and a large data storage space.

[0003] Therefore, how to improve the efficiency of ultrasonic signal recombination and suppress noise is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of this application is to provide an ultrasonic signal compounding method, an apparatus, an ultrasonic device and a computer-readable storage medium, which improve the efficiency of ultrasonic signal compounding and achieve the purpose of suppressing noise.

[0005] To achieve the above objectives, the present application provides an ultrasonic signal compounding method, comprising:

[0006] collecting ultrasonic echo signals, and determining signal segments corresponding to different depths in the ultrasonic echo signals;

[0007] Determine a target diagnostic site, and determine a transformation range of a dynamic range change curve corresponding to each depth based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, perform dynamic range changes on the signal segments at the corresponding depths, and obtain a dynamic range change result corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissue organs except noise;

[0008] The dynamic range change results corresponding to all the depths are summed to obtain a composite ultrasonic signal.

[0009] The step of determining the transformation range of the dynamic range change curve corresponding to each depth based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, performing dynamic range changes on the signal segments at the corresponding depths, and obtaining the dynamic range change results corresponding to each depth includes:

[0010] Determining the transformation ranges of multiple dynamic range change curves based on the energy ranges corresponding to different tissue organs at each depth of the target diagnostic site, performing dynamic range changes on the signal segments at the corresponding depths, and obtaining multiple dynamic range change results corresponding to each signal segment; wherein each transformation range corresponds one-to-one to the energy range corresponding to each tissue organ;

[0011] A plurality of dynamic range change results corresponding to the same signal segment are weighted and composited to obtain a dynamic range change result corresponding to each depth.

[0012] Wherein, the tissue organ includes a lesion, and at the same depth, the weighted coefficient of the dynamic range change curve corresponding to the lesion is greater than the weighted coefficients of the dynamic range change curves corresponding to other tissue organs.

[0013] The average energy in the energy range is negatively correlated with the average depth in the depth range.

[0014] Among them, also include:

[0015] The energy range corresponding to different tissue organs at each depth of each diagnosis site is determined.

[0016] The step of determining the energy range corresponding to different tissues and organs at each depth at each diagnostic site includes:

[0017] Acquire a plurality of training ultrasound signals corresponding to each of the diagnosis parts, and determine training signal segments corresponding to different depths in the training ultrasound signals;

[0018] determining an energy statistical map of each of the diagnosis parts at each of the depths based on the training signal segments;

[0019] The energy ranges of different tissue organs at different depths are determined based on the energy statistical map.

[0020] The energy statistics graph includes energy statistics corresponding to any one or several of blood vessels, noise, tumors, tissues and stones in order of energy from low to high.

[0021] After summing the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal, the method further includes:

[0022] A demodulation operation is performed on the composite ultrasonic signal to obtain a demodulated signal, and an ultrasonic image is output based on the demodulated signal.

[0023] To achieve the above objectives, the present application provides an ultrasonic signal compounding device, comprising:

[0024] an acquisition module, configured to acquire ultrasonic echo signals and determine signal segments corresponding to different depths in the ultrasonic echo signals;

[0025] A dynamic range change module is used to determine the target diagnostic site, and based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, determine the transformation range of the dynamic range change curve corresponding to each depth, and perform dynamic range changes on the signal segments at the corresponding depths to obtain the dynamic range change results corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissue organs except noise;

[0026] The compound module is used to sum the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal.

[0027] To achieve the above objectives, the present application provides an ultrasonic device, comprising:

[0028] memory for storing computer programs;

[0029] A processor is used to implement the steps of the above-mentioned ultrasonic signal compounding method when executing the computer program.

[0030] To achieve the above objectives, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned ultrasonic signal compounding method are implemented.

[0031] It can be seen from the above scheme that the present application provides an ultrasonic signal compounding method, including: collecting ultrasonic echo signals and determining the signal segments corresponding to different depths in the ultrasonic echo signals; determining the target diagnostic part, and based on the energy range corresponding to different tissue organs at each depth of the target diagnostic part, determining the transformation range of the dynamic range change curve corresponding to each depth, and performing dynamic range changes on the signal segments at the corresponding depths to obtain the dynamic range change results corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissue organs except noise; and summing the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal.

[0032] The ultrasonic signal compounding method provided by the present application compounds the signal segments corresponding to different depths in the ultrasonic echo signal of the same scan. Compared with the spatial compounding method, it does not require multiple scans at different angles, thereby improving the efficiency of ultrasonic signal compounding. Furthermore, based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, the energy range corresponding to all tissue organs except noise at different depths is determined, and the dynamic range of the signal segments at the corresponding depths is changed respectively, and the different dynamic range change results are compounded, which can reduce the tissue echo plaque suppression noise and enhance the spatial resolution of the tissue to highlight the lesion. It can be seen that the ultrasonic signal compounding method provided by the present application, through the spatial distribution characteristics of different tissue organs and noise in the ultrasonic signal, uses different transformation ranges to change the dynamic range of the signal segments at different depths respectively, and compounds them when the signal is output, so as to achieve the purpose of highlighting the lesion and suppressing noise. The present application also discloses an ultrasonic signal compounding device, an ultrasonic device and a computer-readable storage medium, which can also achieve the above-mentioned technical effects.

[0033] It should be understood that the foregoing general description and the following detailed description are merely illustrative and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. The drawings are used to provide a further understanding of the present disclosure and constitute part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure, but do not constitute a limitation of the present disclosure. In the drawings:

[0035] Figure 1 is a flow chart of an ultrasonic signal compounding method according to an exemplary embodiment;

[0036] Figure 2 is a standard curve diagram of an echo signal according to an exemplary embodiment;

[0037] Figure 3 is a graph showing a change in the dynamic range of an echo signal according to an exemplary embodiment;

[0038] Figure 4 is a flow chart of another ultrasonic signal compounding method according to an exemplary embodiment;

[0039] Figure 5 is a flow chart of another ultrasonic signal compounding method according to an exemplary embodiment;

[0040] Figure 6 An energy statistical histogram is shown according to an exemplary embodiment;

[0041] Figure 7 is a structural diagram of an ultrasonic signal compounding device according to an exemplary embodiment;

[0042] Figure 8 The figure is a structural diagram of an ultrasonic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. In addition, in the embodiments of the present application, "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0044] The embodiment of the present application discloses an ultrasonic signal compounding method, which improves the efficiency of ultrasonic signal compounding and achieves the purpose of suppressing noise.

[0045] See also Figure 1 , according to an exemplary embodiment, a flow chart of an ultrasonic signal compounding method is shown, as shown in FIG. Figure 1 Shown, including:

[0046] S101: collecting ultrasonic echo signals and determining signal segments corresponding to different depths in the ultrasonic echo signals;

[0047] The execution subject of this embodiment is an ultrasound device, and the purpose is to compound the collected ultrasound echo signals to generate an ultrasound image. The ultrasound echo signal here can be a variety of source signals such as radio frequency signals and demodulation signals. This embodiment is not specifically limited and does not require additional hardware equipment. It can be applied to any ultrasound platform. Both the radio frequency signal and the demodulation signal are a series of echo signals in the depth direction. The radio frequency signal is the signal after signal modulation, and the signal range is in the modulation frequency band, while the demodulation signal is the signal of the radio frequency signal moved from the modulation frequency band to the baseband.

[0048] It should be noted that during tissue movement, the energy of the ultrasonic signal attenuates, while the noise signal increases. That is, the energy of the ultrasonic signal decreases with increasing depth, while the noise signal increases with increasing depth, and the signal-to-noise ratio decreases with increasing depth. Therefore, this application processes ultrasonic echo signals at different depths separately to suppress noise in the ultrasonic signal.

[0049] In this step, the ultrasonic echo signal is divided into several signal segments according to depth, that is, the signal segments corresponding to different depths in the ultrasonic echo signal are determined. This embodiment does not limit the span between adjacent depths, and the spans between adjacent depths can be the same or different.

[0050] S102: Determine a target diagnostic site, and determine a transformation range of a dynamic range change curve corresponding to each depth based on the energy range corresponding to different tissues and organs at each depth of the target diagnostic site, perform dynamic range changes on the signal segments at the corresponding depths, and obtain a dynamic range change result corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissues and organs except noise;

[0051] The purpose of this step is to change the dynamic range of the ultrasound signal. The principle of dynamic range change is to change the range of the original data by means of logarithmic compression. The significance of dynamic range change is to increase or decrease a certain special signal. It is understandable that since there is generally noise interference in the echo signal and the energy corresponding to the noise is small, therefore, changing the dynamic range of the ultrasound signal to a certain extent can reduce the noise signal and achieve the purpose of suppressing noise, thereby improving the brightness of the tissue and lesion image. For example, Figure 2 This is the standard curve of the echo signal. The horizontal axis represents energy in dB, ranging from 0 to 90 dB, corresponding to the linear change of the grayscale signal from 0 to 255, which is the signal seen by the human eye. The vertical axis represents the signal amplitude. Figure 3 As shown in FIG, the energy range of the echo signal 20-70dB corresponds to the linear change of the grayscale signal 0-255. Signals with energy below 20dB are considered as noise signals, thus achieving the purpose of noise suppression.

[0052] Because the signal-to-noise ratio of ultrasound signals decreases with depth, it is necessary to use different transformation ranges for signal segments at different depths to achieve dynamic range changes. That is, different depths correspond to different transformation ranges. As depth increases, the energy of the lesion and tissue gradually decreases, and the energy range should also be appropriately shifted downward. That is, the average energy within the energy range is negatively correlated with the average depth at that depth. For example, at 2 cm, a 40-90 dB energy range can be used for dynamic range changes, while at 10 cm, a 20-70 dB energy range can be used for dynamic range changes.

[0053] Furthermore, the tissue composition of different diagnostic sites on the human body varies, which in turn leads to different ultrasonic echo signal components collected at different sites. Although the human body is complex, most structures are known and determined on ultrasound. For example, the abdomen is mainly composed of tissue components and tumors, while the heart contains a large number of echo-free areas. The ultrasound signals collected at different diagnostic sites need to have dynamic range changes based on different energy ranges, that is, different diagnostic sites correspond to different energy ranges. Therefore, in this step, the user needs to select the target diagnostic site on the ultrasound device.

[0054] In a specific implementation, for a signal segment at a specific depth, the energy ranges of the different tissues and organs corresponding to the target diagnostic site at that depth are first determined. Then, based on the energy of the tissues and organs excluding noise, the transformation range corresponding to that depth is determined. This means that the transformation range corresponding to that depth encompasses the energy ranges corresponding to all tissues and organs excluding noise. Finally, a dynamic range shift is performed on the signal segment based on this transformation range to obtain the dynamic range shift result for that signal segment. This process is repeated for signal segments at all depths, resulting in dynamic range shift results corresponding to all depths.

[0055] S103: Sum the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal.

[0056] The purpose of this step is to composite the dynamic range change results. In a specific implementation, the dynamic range change results corresponding to all depths are summed to obtain a composite ultrasonic signal. Preferably, the dynamic range change results corresponding to all depths can be weighted and composited to obtain a composite ultrasonic signal, i.e., different depths are assigned different weights, which can be flexibly set based on actual conditions.

[0057] As a preferred embodiment, after this step, the method further includes: performing a demodulation operation on the composite ultrasonic signal to obtain a demodulated signal, and outputting an ultrasonic image based on the demodulated signal. It is understood that since the composite ultrasonic signal is a radio frequency signal, it needs to be demodulated to obtain a demodulated signal, and the demodulated signal is then subjected to other operation processes to output an ultrasonic image.

[0058] The ultrasonic signal compounding method provided in the embodiment of the present application compounds the signal segments corresponding to different depths in the ultrasonic echo signal of the same scan. Compared with the spatial compounding method, it does not require multiple scans at different angles, thereby improving the efficiency of ultrasonic signal compounding. Furthermore, based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, the energy range corresponding to all tissue organs except noise at different depths is determined, and the dynamic range of the signal segments at the corresponding depths is changed respectively, and the different dynamic range change results are compounded, which can reduce the tissue echo plaque suppression noise and enhance the spatial resolution of the tissue to highlight the lesions. It can be seen that the ultrasonic signal compounding method provided in the embodiment of the present application, through the spatial distribution characteristics of different tissue organs and noise in the ultrasonic signal, uses different transformation ranges to change the dynamic range of the signal segments at different depths respectively, and compounds them when the signal is output, so as to achieve the purpose of highlighting the lesions and suppressing the noise.

[0059] The embodiment of this application discloses a method for combining ultrasonic signals. Compared with the previous embodiment, this embodiment further illustrates and optimizes the technical solution. Specifically:

[0060] See also Figure 4 , a flow chart of another ultrasonic signal compounding method according to an exemplary embodiment is shown, as Figure 4 Shown, including:

[0061] S201: collecting ultrasonic echo signals and determining signal segments corresponding to different depths in the ultrasonic echo signals;

[0062] S202: Determine a target diagnostic site, and determine transformation ranges of multiple dynamic range change curves based on energy ranges corresponding to different tissues and organs at each depth of the target diagnostic site, perform dynamic range changes on signal segments at corresponding depths, and obtain multiple dynamic range change results corresponding to each signal segment; wherein each transformation range corresponds to an energy range corresponding to each tissue and organ;

[0063] It's understandable that different tissues and organs have varying echo intensities. For example, stones are high-intensity echoes, tissue is hyperechoic, tumors are hypoechoic, noise is sub-hypoechoic, and blood vessels are anechoic. Because of this, dynamic range changes are required for the same signal segment using different energy ranges to suppress noise and highlight key areas. For example, separate energy ranges can be set for tumors and stones, and dynamic range changes can be applied to each signal segment based on these energy ranges to highlight the tumor and stone.

[0064] That is to say, this embodiment comprehensively determines the energy range based on the diagnostic site, depth, and tissue organs. Therefore, it is necessary to predetermine the energy range corresponding to different tissue organs at each depth of each diagnostic site, rather than to do it in real time during ultrasound imaging. This improves the composite efficiency of the ultrasound signal and thus the imaging speed of the ultrasound image. Different diagnostic sites correspond to different energy ranges, different depths of the same diagnostic site correspond to different energy ranges, and different tissue organs at the same depth of the same diagnostic site correspond to different energy ranges. For example, the diagnostic sites include the abdomen and the heart, the depths include 2cm, 5cm, and 10cm, and the tissue organs include tumors and stones. Then, at 2cm in the abdomen, the tumor corresponds to energy range a, the stone corresponds to energy range b, at 5cm in the abdomen, the tumor corresponds to energy range c, the stone corresponds to energy range d, and at 10cm in the abdomen, the tumor corresponds to energy range e, and the stone corresponds to energy range f. When the heart is 2 cm away, the tumor corresponds to energy range g, and the stone corresponds to energy range h. When the heart is 5 cm away, the tumor corresponds to energy range i, and the stone corresponds to energy range j. When the heart is 10 cm away, the tumor corresponds to energy range k, and the stone corresponds to energy range l. Each part corresponds to 6 energy ranges.

[0065] In a specific implementation, for a signal segment at a certain depth, the energy ranges of different tissue organs corresponding to the target diagnostic site at the depth are first determined, and then the dynamic range change of the signal segment is performed based on each energy range to obtain the dynamic range change result of the signal segment. For signal segments at all depths, the above operation is used to obtain the dynamic range change results of all signal segments. In the above example, if the diagnostic site is the abdomen, the dynamic range change of the signal segment at 2 cm is performed based on energy range a and energy range b, respectively, to obtain dynamic range change results 1 and 2, respectively; the dynamic range change of the signal segment at 5 cm is performed based on energy range c and energy range d, respectively, to obtain dynamic range change results 3 and 4, respectively; the dynamic range change of the signal segment at 10 cm is performed based on energy range e and energy range f, respectively, to obtain dynamic range change results 5 and 6, respectively.

[0066] S203: performing weighted combination on multiple dynamic range change results corresponding to the same signal segment to obtain a dynamic range change result corresponding to each depth;

[0067] In practice, the dynamic range change results for the same signal segment are weighted and composited to produce a composite result corresponding to each depth. Different tissues and organs are assigned different weights, meaning that the dynamic range change results for different tissues and organs have different weights. This can be flexibly set based on actual conditions. Generally speaking, lesions such as stones and tumors are assigned larger weights, meaning that the weighting coefficient of the dynamic range change curve corresponding to the lesion at the same depth is greater than the weighting coefficients of the dynamic range change curves for other tissues and organs.

[0068] In the example given in the previous step, dynamic range change results 1 and 2 are weighted and composited to obtain the dynamic range change result corresponding to a depth of 2 cm. Dynamic range change results 3 and 4 are weighted and composited to obtain the dynamic range change result corresponding to a depth of 5 cm. Dynamic range change results 5 and 6 are weighted and composited to obtain the dynamic range change result corresponding to a depth of 10 cm.

[0069] S204: Sum the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal.

[0070] In the example given in the previous step, the dynamic range change results corresponding to depths of 2 cm, 5 cm, and 10 cm are summed to obtain the final composite ultrasonic signal.

[0071] In this embodiment, the following formula can be used to compound multiple dynamic range change results corresponding to different signal segments and dynamic range change results corresponding to different depths:

[0072]

[0073] Where α(d,k) represents the weight corresponding to depth d and tissue organ k, dyn(k) represents the energy range corresponding to tissue organ k, data(d) represents the signal segment at depth d, n is the total number of tissue organs, depth is the maximum depth, and signal represents the composite ultrasound signal.

[0074] The ultrasonic signal compounding method provided in the embodiment of the present application compounds the ultrasonic signals of the same scan. Compared with the spatial compounding method, it does not require multiple scans at different angles, thereby improving the efficiency of ultrasonic signal compounding. Furthermore, based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, the dynamic range of the signal segments at the corresponding depths is changed respectively, and the different dynamic range change results are weighted and compounded. Multiple compounding can reduce the tissue echo plaque suppression noise and enhance the spatial resolution of the tissue to highlight the lesions. It can be seen that the ultrasonic signal compounding method provided in the embodiment of the present application uses different energy ranges to perform dynamic range changes respectively through the spatial distribution characteristics of different tissue organs and noise in the ultrasonic signal, and performs weighted compounding when the signal is output, so as to achieve the purpose of highlighting the lesions and suppressing the noise.

[0075] This embodiment introduces a method for determining the energy range corresponding to different tissues and organs at each depth at each site. Specifically:

[0076] See also Figure 5 , according to an exemplary embodiment, a flow chart of another ultrasonic signal compounding method is shown, as shown in FIG. Figure 5 Shown, including:

[0077] S301: Acquire multiple training ultrasound signals corresponding to each diagnosis site, and determine training signal segments corresponding to different depths in the training ultrasound signals;

[0078] It is understandable that since different parts correspond to different energy ranges, it is necessary to collect a large amount of echo data corresponding to different parts, that is, training ultrasound signals, and divide each training ultrasound signal into several signal segments according to depth, that is, determine the signal segments corresponding to different depths in each training ultrasound signal.

[0079] S302: Determine an energy statistical map of each of the diagnosis parts at each of the depths based on the training signal segments;

[0080] In this step, energy statistics of different diagnostic parts at each depth are constructed. The energy statistics can be specifically a statistics diagram of energy and corresponding counts. For example, Figure 6 It is a histogram representation method, where the horizontal axis represents energy and the vertical axis represents count. Among them, blood vessels are echo-free signals, and their position in the histogram is generally the lowest range of the horizontal axis ( Figure 6 1 and 2), the tumor has a medium to low echo signal, and the histogram position is generally in the middle and lower position of the horizontal axis ( Figure 6 6 and 7 in the histogram), the organization is in the middle of the horizontal axis of the histogram ( Figure 6 8-16 and 19 in the figure), while stones are bright echo signals, and the histogram position is generally in the higher range of the horizontal axis ( Figure 6 17 and 18), the noise signal intensity should be between that of blood vessels and tumors ( Figure 6 3, 4 and 5). That is, the energy statistics graph may include energy statistics corresponding to blood vessels, noise, tumors, tissues and stones according to energy from low to high.

[0081] S303: Determine the energy ranges of different tissue organs at different depths based on the energy statistical graph.

[0082] In specific implementation, the distribution characteristics of the energy statistical diagram are analyzed to make the most universal and reasonable preset for the energy range of different tissues and organs.

[0083] An ultrasonic signal compounding device provided in an embodiment of the present application is introduced below. The ultrasonic signal compounding device described below and the ultrasonic signal compounding method described above can be referenced to each other.

[0084] See also Figure 7 , according to an exemplary embodiment, a structural diagram of an ultrasonic signal compounding device is shown, such as Figure 7 Shown, including:

[0085] An acquisition module 701 is configured to acquire ultrasonic echo signals and determine signal segments corresponding to different depths in the ultrasonic echo signals;

[0086] The dynamic range change module 702 is configured to determine a target diagnostic site, and based on the energy ranges corresponding to different tissues and organs at each depth of the target diagnostic site, determine a transformation range for the dynamic range change curve corresponding to each depth, and perform dynamic range changes on the signal segments at the corresponding depths to obtain a dynamic range change result corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissues and organs excluding noise;

[0087] The compound module 703 is configured to sum the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal.

[0088] The ultrasonic signal compounding device provided in the embodiment of the present application compounds the signal segments corresponding to different depths in the ultrasonic echo signal of the same scan. Compared with the spatial compounding method, it does not require multiple scans at different angles, thereby improving the efficiency of ultrasonic signal compounding. Furthermore, based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, the energy range corresponding to all tissue organs except noise at different depths is determined, and the dynamic range of the signal segments at the corresponding depths is changed respectively, and the different dynamic range change results are compounded, which can reduce the tissue echo plaque suppression noise and enhance the spatial resolution of the tissue to highlight the lesion. It can be seen that the ultrasonic signal compounding device provided in the embodiment of the present application, through the spatial distribution characteristics of different tissue organs and noise in the ultrasonic signal, uses different transformation ranges to change the dynamic range of the signal segments at different depths respectively, and compounds them when the signal is output, so as to achieve the purpose of highlighting the lesion and suppressing the noise.

[0089] Based on the above embodiment, as a preferred implementation, the dynamic range changing module 702 includes:

[0090] a dynamic range variation unit, configured to determine a target diagnostic site, and based on the energy ranges corresponding to different tissue organs at each depth of the target diagnostic site, determine the transformation ranges of a plurality of dynamic range variation curves, and perform dynamic range variation on the signal segments at the corresponding depths to obtain a plurality of dynamic range variation results corresponding to each signal segment; wherein each transformation range corresponds one-to-one to the energy range corresponding to each tissue organ;

[0091] The weighted composite unit is configured to perform weighted composite on a plurality of dynamic range change results corresponding to the same signal segment to obtain a dynamic range change result corresponding to each of the depths.

[0092] Based on the above embodiment, as a preferred implementation, the tissue organ includes a lesion, and at the same depth, the weighted coefficient of the dynamic range change curve corresponding to the lesion is greater than the weighted coefficient of the dynamic range change curve corresponding to other tissue organs.

[0093] Based on the above embodiment, as a preferred implementation manner, the average energy in the energy range is negatively correlated with the average depth in the depth range.

[0094] Based on the above embodiment, as a preferred implementation, it further includes:

[0095] The determination module is used to determine the energy range corresponding to different tissue organs at each depth of each diagnosis site.

[0096] Based on the above embodiment, as a preferred implementation, the determining module includes:

[0097] an acquiring unit, configured to acquire a plurality of training ultrasound signals corresponding to each of the diagnosis parts, and determine training signal segments corresponding to different depths in the training ultrasound signals;

[0098] a first determining unit, configured to determine an energy statistical map of each of the diagnosis parts at each of the depths based on the training signal segments;

[0099] The second determining unit is configured to determine energy ranges of different tissue organs at different depths based on the energy statistical graph.

[0100] Based on the above embodiment, as a preferred implementation manner, the energy statistics graph includes energy statistics corresponding to any one or several of blood vessels, noise, tumors, tissues and stones in order of energy from low to high.

[0101] Based on the above embodiment, as a preferred implementation, it further includes:

[0102] The output module is configured to perform a demodulation operation on the composite ultrasonic signal to obtain a demodulated signal, and output an ultrasonic image based on the demodulated signal.

[0103] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0104] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present application, the embodiment of the present application further provides an ultrasound device, Figure 8 FIG. 1 is a structural diagram of an ultrasonic device according to an exemplary embodiment. Figure 8 As shown, the ultrasound equipment includes:

[0105] Communication interface 1, capable of exchanging information with other devices such as network devices;

[0106] The processor 2 is connected to the communication interface 1 to implement information exchange with other devices and is used to execute the ultrasonic signal combination method provided by one or more technical solutions when running a computer program. The computer program is stored in the memory 3.

[0107] Of course, in actual application, the various components in the ultrasound device are coupled together through the bus system 4. It can be understood that the bus system 4 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 4 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 8 Various buses are labeled as bus system 4.

[0108] The memory 3 in the embodiment of the present application is used to store various types of data to support the operation of the ultrasound device. Examples of such data include: any computer program used to operate on the ultrasound device.

[0109] It is understood that the memory 3 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a magnetic disk memory or a magnetic tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memory 2 described in the embodiments of the present application is intended to include but is not limited to these and any other suitable types of memory.

[0110] The method disclosed in the above-mentioned embodiment of the present application can be applied to processor 2 or implemented by processor 2. Processor 2 may be an integrated circuit chip with signal processing capabilities. During the implementation process, each step of the above-mentioned method can be completed by the integrated logic circuit of the hardware in processor 2 or instructions in the form of software. The above-mentioned processor 2 can be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 2 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in memory 3. Processor 2 reads the program in memory 3 and completes the steps of the above-mentioned method in combination with its hardware.

[0111] When the processor 2 executes the program, the corresponding processes in the various methods of the embodiments of the present application are implemented. For the sake of brevity, they are not repeated here.

[0112] In an exemplary embodiment, the present application also provides a storage medium, namely, a computer storage medium, specifically a computer-readable storage medium, such as a memory 3 storing a computer program. The computer program can be executed by a processor 2 to perform the steps of the aforementioned method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0113] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: mobile storage devices, ROM, RAM, disks or optical disks, etc. Various media that can store program codes.

[0114] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling an ultrasound device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0115] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. An ultrasonic signal compounding method, characterized in that: include: Acquiring ultrasonic echo signals and determining signal segments corresponding to different depths in the ultrasonic echo signals; Determine a target diagnostic site, and determine a transformation range of a dynamic range change curve corresponding to each depth based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, perform dynamic range changes on the signal segments at the corresponding depths, and obtain a dynamic range change result corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissue organs except noise; Summing the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal; The step of determining the transformation range of the dynamic range change curve corresponding to each depth based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, performing dynamic range changes on the signal segments at the corresponding depths, and obtaining the dynamic range change results corresponding to each depth includes: Determining the transformation ranges of multiple dynamic range change curves based on the energy ranges corresponding to different tissue organs at each depth of the target diagnostic site, performing dynamic range changes on the signal segments at the corresponding depths, and obtaining multiple dynamic range change results corresponding to each signal segment; wherein each transformation range corresponds one-to-one to the energy range corresponding to each tissue organ; A plurality of dynamic range change results corresponding to the same signal segment are weighted and composited to obtain a dynamic range change result corresponding to each depth.

2. The ultrasonic signal compounding method according to claim 1, characterized in that: The tissue organ includes a lesion, and at the same depth, the weighted coefficient of the dynamic range change curve corresponding to the lesion is greater than the weighted coefficients of the dynamic range change curves corresponding to other tissue organs.

3. The ultrasonic signal compounding method according to claim 1, characterized in that: The average energy over the energy range is negatively correlated with the average depth over the depth range.

4. The ultrasonic signal compounding method according to claim 1, characterized in that: Also includes: The energy range corresponding to different tissue organs at each depth of each diagnosis site is determined.

5. The ultrasonic signal compounding method according to claim 4, characterized in that: Determining the energy range corresponding to different tissue organs at each depth at each diagnostic site includes: Acquire a plurality of training ultrasound signals corresponding to each of the diagnosis parts, and determine training signal segments corresponding to different depths in the training ultrasound signals; determining an energy statistical map of each of the diagnosis parts at each of the depths based on the training signal segments; The energy ranges of different tissue organs at different depths are determined based on the energy statistical map.

6. The ultrasonic signal compounding method according to claim 5, characterized in that: The energy statistics graph includes energy statistics corresponding to any one or several of blood vessels, noise, tumors, tissues and stones according to energy from low to high.

7. The ultrasonic signal compounding method according to claim 1, characterized in that: After summing the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal, the method further includes: A demodulation operation is performed on the composite ultrasonic signal to obtain a demodulated signal, and an ultrasonic image is output based on the demodulated signal.

8. An ultrasonic signal compounding device, characterized in that: include: an acquisition module, configured to acquire ultrasonic echo signals and determine signal segments corresponding to different depths in the ultrasonic echo signals; A dynamic range change module is used to determine the target diagnostic site, and based on the energy range corresponding to different tissue organs at each depth of the target diagnostic site, determine the transformation range of the dynamic range change curve corresponding to each depth, and perform dynamic range changes on the signal segments at the corresponding depths to obtain the dynamic range change results corresponding to each depth; wherein the transformation range includes the energy ranges corresponding to all tissue organs except noise; A compound module, configured to sum the dynamic range change results corresponding to all the depths to obtain a composite ultrasonic signal; Wherein, the dynamic range change module includes: a dynamic range variation unit, configured to determine a target diagnostic site, and based on the energy ranges corresponding to different tissue organs at each depth of the target diagnostic site, determine the transformation ranges of a plurality of dynamic range variation curves, and perform dynamic range variation on the signal segments at the corresponding depths to obtain a plurality of dynamic range variation results corresponding to each signal segment; wherein each transformation range corresponds one-to-one to the energy range corresponding to each tissue organ; The weighted composite unit is configured to perform weighted composite on a plurality of dynamic range change results corresponding to the same signal segment to obtain a dynamic range change result corresponding to each of the depths.

9. An ultrasonic device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the ultrasonic signal compounding method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the ultrasonic signal compounding method according to any one of claims 1 to 7 are implemented.

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