Ultrasound imaging method and ultrasound imaging system

Abstract

The application provides an ultrasonic imaging method and system, the method comprising: transmitting a plurality of groups of first ultrasonic wave sequences and a plurality of groups of second ultrasonic wave sequences to a target tissue region of a subject; receiving second echo signals of the plurality of groups of second ultrasonic wave sequences, and performing space-time wall filtering processing on echo signals of a first sequence length in the second echo signals as first echo signals to be filtered to obtain first blood flow motion signals; performing autocorrelation calculation on the first blood flow motion signals to generate a first blood flow image; transmitting at least one group of second ultrasonic wave sequences to the target tissue region of the subject and receiving third echo signals; performing space-time wall filtering processing on part of the first echo signals to be filtered and the third echo signals as second echo signals to be filtered to obtain second blood flow motion signals, the first sequence length being greater than a length of the second ultrasonic wave sequence; and performing autocorrelation calculation on the second blood flow motion signals to generate a second blood flow image.

Description

Technical Field

[0001] The present invention relates to the field of ultrasound, and more specifically, to an ultrasound imaging method and an ultrasound imaging system. Background Technology

[0002] Doppler color flow imaging is based on the Doppler effect generated by the movement of red blood cells in the blood. In actual engineering, the processing flow of Doppler flow imaging includes raw data acquisition, wall filtering, and autocorrelation techniques. However, conventional wall filters are pure time-domain filters, and they are infinite impulse response (IIR) filters with low order requirements. Usually, in the time-frequency dimension, low-speed blood flow and low-speed tissue are superimposed. Pure time-domain filters cannot distinguish between low-speed tissue and blood flow. In order to filter out tissue interference, a considerable part of the low-speed blood flow signal is also filtered out by the filter. Therefore, the low-speed blood flow signal cannot be observed, resulting in a loss of sensitivity in blood flow detection. Summary of the Invention

[0003] In a first aspect, embodiments of the present invention provide an ultrasound imaging method, the method comprising:

[0004] Multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences are emitted to the target tissue area of ​​the subject being examined, wherein each set of first ultrasound sequences is used to acquire a tissue image of the target tissue area, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue area.

[0005] Receive the first echo signals of the multiple sets of first ultrasound sequences, and acquire multiple frames of the tissue images based on the first echo signals;

[0006] Receive the second echo signals of the plurality of second ultrasonic sequences;

[0007] The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal. The first blood flow motion signal includes a first part of the blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with blood flow velocity higher than the tissue motion velocity range.

[0008] Autocorrelation calculation is performed on the first blood flow motion signal to obtain the first blood flow data, and a first blood flow image is generated based on the first blood flow data;

[0009] The first blood flow image and one frame of tissue image from the multiple frames of tissue images are superimposed to obtain the first multimodal image;

[0010] At least one set of the second ultrasound sequence is emitted toward the target tissue area of ​​the subject being examined;

[0011] Receive at least one set of third echo signals from the second ultrasonic sequence;

[0012] A portion of the echo signal from the first echo signal to be filtered and the third echo signal are used as the second echo signal to be filtered, and spatiotemporal wall filtering is applied to filter out tissue motion signals in the second echo signal to be filtered, thereby obtaining a second blood flow motion signal. The second blood flow motion signal includes a first portion of blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with blood flow velocity higher than the tissue motion velocity range. The sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence.

[0013] Autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, and a second blood flow image is generated based on the second blood flow data;

[0014] At least one set of the first ultrasound sequence is emitted toward the target tissue area of ​​the subject being examined;

[0015] Receive at least one set of fourth echo signals from the first ultrasound sequence, and acquire at least one frame of the tissue image based on the fourth echo signals;

[0016] The second blood flow image and at least one frame of the tissue image are superimposed to obtain a second multimodal image.

[0017] Secondly, embodiments of the present invention also provide an ultrasound imaging system, comprising:

[0018] Ultrasonic probe;

[0019] The transmitting circuit is used to transmit multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences to the target tissue area of ​​the subject being examined, wherein each set of first ultrasound sequences is used to acquire a tissue image of the target tissue area, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue area.

[0020] A receiving circuit is configured to receive the first echo signals of the plurality of first ultrasonic sequences and the second echo signals of the plurality of second ultrasonic sequences.

[0021] Processor, used for:

[0022] Multiple frames of the tissue image are acquired based on the first echo signal;

[0023] The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal. The first blood flow motion signal includes a first part of the blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with blood flow velocity higher than the tissue motion velocity range.

[0024] Autocorrelation calculation is performed on the first blood flow motion signal to obtain the first blood flow data, and a first blood flow image is generated based on the first blood flow data;

[0025] The first blood flow image and one frame of tissue image from the multiple frames of tissue images are superimposed to obtain the first multimodal image;

[0026] The transmitting circuit is also used to transmit at least one set of the second ultrasound sequence to the target tissue area of ​​the subject being examined, and to transmit at least one set of the first ultrasound sequence to the target tissue area of ​​the subject being examined.

[0027] The receiving circuit is further configured to receive at least one set of fourth echo signals of the first ultrasonic sequence and at least one set of third echo signals of the second ultrasonic sequence.

[0028] The processor is further configured to: perform the spatiotemporal wall filtering process on a portion of the echo signal in the first echo signal to be filtered and the third echo signal as a second echo signal to be filtered, so as to filter out the tissue motion signal in the second echo signal to be filtered, thereby obtaining a second blood flow motion signal, wherein the second blood flow motion signal includes a first portion of blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range; wherein the sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence;

[0029] Autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, and a second blood flow image is generated based on the second blood flow data;

[0030] At least one frame of the tissue image is acquired based on the fourth echo signal;

[0031] The second blood flow image and at least one frame of the tissue image are superimposed to obtain a second multimodal image.

[0032] Therefore, the ultrasound imaging method and system of the present invention, by using spatiotemporal wall filtering to process the echo signal corresponding to the second ultrasound sequence, and by making the sequence length of the echo signal to be filtered in each spatiotemporal wall filtering process greater than the length of the second ultrasound sequence, can more effectively distinguish slow-moving blood flow from slow tissue movement. While filtering out tissue movement signals, it can also retain slow-moving blood flow signals, thus improving the sensitivity of blood flow detection and providing better display of slow blood flow. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a schematic block diagram of an ultrasound imaging system;

[0035] Figure 2 This is a schematic diagram illustrating the acquisition dimensions of raw Doppler data;

[0036] Figure 3 This is a schematic diagram of the filtering effect of a conventional filter in one embodiment of this application;

[0037] Figure 4 This is a schematic flowchart of an ultrasound imaging method in one embodiment of this application;

[0038] Figure 5 This is a schematic diagram of the scanning mechanism for tissue imaging and blood flow imaging in one embodiment of this application;

[0039] Figure 6 This is a schematic diagram of the filtering effect of a spacetime wall filter in one embodiment of this application. Detailed Implementation

[0040] This invention provides an ultrasound imaging system capable of obtaining blood flow images, such as color blood flow images.

[0041] like Figure 1The diagram shows a structural block diagram of an ultrasound imaging system. The ultrasound imaging system 10 includes an ultrasound probe 110, a transmit / receive selection switch 120, a transmitting circuit 160, a receiving circuit 170, a memory 130, a processor 140, and a display 150. The transmitting circuit 160 can send excitation pulses to the ultrasound probe 110 via the transmit / receive selection switch 120 to excite the ultrasound probe 110 to emit an ultrasonic beam towards the object being examined. The receiving circuit 170 receives the ultrasonic echo of the returned ultrasonic beam through the ultrasound probe 110, obtains the ultrasonic echo signal, and sends the ultrasonic echo signal to the processor 140. The processor 140 can process the ultrasonic echo signal.

[0042] For example, an ultrasound probe 110 can be excited to emit multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences toward a target tissue region of the subject being examined. Each set of first ultrasound sequences is used to acquire a tissue image of the target tissue region, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue region, which includes blood vessels. The ultrasound probe 110 receives echo signals from the first ultrasound sequences returning from this region. The processor 140 can acquire a tissue image of the target tissue region based on the echo signals from the first ultrasound sequences. By receiving echo signals from the second ultrasound sequences returning from this region via the ultrasound probe 110, the processor 140 can acquire a blood flow image of the target tissue region, which includes blood vessels. The tissue image and the blood flow image are superimposed to obtain a multimodal image, which is then displayed.

[0043] Each second ultrasound sequence may include multiple pulses emitted toward the same target location. The processor 140 can obtain an autocorrelation function representing the blood flow signal for each pulse; synthesize the autocorrelation functions representing the blood flow signal obtained from multiple pulses to obtain a synthesized autocorrelation function; and obtain a blood flow image of the target tissue region based on the synthesized autocorrelation function.

[0044] Optionally, the display 150 in the ultrasound imaging system 10 can be a touch screen, an LCD screen, or a separate display device such as an LCD screen or a television, independent of the ultrasound imaging system 10; or the display 150 can be the screen of an electronic device such as a smartphone or tablet, etc. The number of displays 150 can be one or more.

[0045] Optionally, the memory 130 in the ultrasound imaging system 10 can be a flash memory card, solid-state memory, hard disk, etc. It can be volatile memory and / or non-volatile memory, removable memory and / or non-removable memory, etc.

[0046] Optionally, the processor 140 in the ultrasound imaging system 10 can be implemented by software, hardware, firmware, or any combination thereof. It can be implemented by circuits, one or more application-specific integrated circuits (ASICs), one or more general-purpose integrated circuits, one or more microprocessors, one or more programmable logic devices, or any combination of the foregoing circuits and / or devices, or other suitable circuits or devices, so that the processor 140 can perform the corresponding steps of the methods in the various embodiments of this specification.

[0047] It should be understood that Figure 1 The components included in the illustrated ultrasound imaging system 10 are merely illustrative and may include more or fewer components. For example, the ultrasound imaging system 10 may also include input devices such as a keyboard, mouse, scroll wheel, trackball, etc., and / or may include output devices such as a printer. The corresponding external input / output ports may be wireless communication modules, wired communication modules, or a combination of both. External input / output ports may also be implemented based on USB, bus protocols such as CAN, and / or wired network protocols. This invention is not limited in this respect.

[0048] Blood flow imaging, such as Doppler color blood flow imaging, is based on the Doppler effect generated by the movement of red blood cells in the blood. In actual engineering, the processing flow of Doppler blood flow imaging is as follows:

[0049] I. Acquisition of Raw Doppler Data

[0050] Doppler blood flow imaging is generally two-dimensional (2D) imaging, which has two spatial dimensions (including lateral and axial). In order to extract Doppler signals, the blood flow signal at the same spatial location needs to be sampled multiple times at different times (usually at fixed time intervals).

[0051] As above Figure 2As shown, the acquisition of raw Doppler data has three dimensions: slow time, lateral, and axial. Slow time is the time dimension, while lateral and axial are the two spatial dimensions. The sampling time interval in the slow time dimension is called the Pulse-Repetition Time (PRT), also known as the Flow Pulse-Repetition Time (FlowPRT). The PRT is related to the range of blood flow velocity being measured and the center frequency of the ultrasound signal. If a relatively slow blood flow is observed (e.g., flow velocity below 5 cm / s), the corresponding FlowPRT range is approximately 1–10 ms. The smaller the measured velocity range, the longer the FlowPRT time. Assuming the length of the sampling sequence in the slow time dimension is N, the frame rate of blood flow imaging is 1 / (N*FlowPRT). In order to ensure the temporal resolution of blood flow imaging, the frame rate requirement for blood flow imaging is generally more than 20 frames. Therefore, the length of the sampling sequence in the slow time dimension is generally small, about 4-16.

[0052] II. Wall Filtering

[0053] The acquired raw Doppler data contains both tissue signals (e.g., tissue motion signals) and blood flow signals (e.g., blood flow motion signals), and the signal intensity of the tissue signal is much stronger than that of the blood flow signal (e.g., the tissue signal intensity is approximately 100–1000 times stronger than the blood flow signal intensity). To more effectively extract the blood flow signal from the raw data, wall filtering is required.

[0054] Conventional Doppler wall filtering typically employs a pure time-domain high-pass filter. Taking advantage of the generally slow speed of tissue motion, it filters out low-frequency tissue components in the time-frequency domain, retaining higher-frequency blood flow signals. As mentioned earlier, to ensure the temporal resolution of blood flow imaging (generally requiring a frame rate of 20 frames or more), the sampling sequence length in the slow time dimension is typically 4–16. The filter order in the slow time dimension is also limited by this sampling sequence length. To achieve good filtering results with a low order (e.g., a narrow filter transition band), traditional Doppler blood flow generally uses 4–16 order IIR high-pass filters for wall filtering.

[0055] III. Autocorrelation techniques for obtaining mean velocity, energy, and variance of blood flow

[0056] After the acquired raw Doppler data undergoes wall filtering to remove tissue components, autocorrelation calculations can be used to extract blood flow data (such as mean flow velocity, variance, and energy). Autocorrelation calculation is an operation performed in the slow time dimension, and the length of the slow time sequence for autocorrelation calculation is proportional to the signal-to-noise ratio of the blood flow signal. The length of the autocorrelation calculation sequence for traditional Doppler blood flow is equal to the filter order of the wall filter, and also equivalent to the acquisition length of the raw Doppler signal in the slow time dimension.

[0057] The traditional Doppler flow imaging processing workflow, as described above, consists of the three steps:

[0058] Step 1: In the raw signal data acquisition stage, in order to ensure the frame rate, the sampling length Ncapture in the slow time dimension is generally 4-16.

[0059] Step 2: In the wall filtering stage, a pure time-domain IIR filter is used, with filter order Nfilter = Ncapture;

[0060] Step 3: In the autocorrelation blood flow signal detection stage, the length of the autocorrelation sequence is Ncorr = Nfilter.

[0061] However, the above-mentioned traditional Doppler blood flow imaging processing has a problem: in the time-frequency dimension, low-speed blood flow and low-speed tissue movement are superimposed, and pure time-domain filters cannot distinguish between the two. In order to filter out the interference of tissue movement signals, a considerable portion of low-speed blood flow signals will also be filtered out by the filter, so low-speed blood flow signals cannot be observed, resulting in a loss of sensitivity in blood flow detection.

[0062] In view of the above problems, this application proposes an ultrasound imaging method, such as... Figure 4 As shown, the ultrasound imaging method of this application may include:

[0063] Step S401: Transmit multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences to the target tissue area of ​​the subject, wherein each set of first ultrasound sequences is used to acquire a tissue image of the target tissue area, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue area.

[0064] Step S402: Receive the first echo signals of the multiple sets of first ultrasound sequences, and acquire multiple frames of the tissue images based on the first echo signals;

[0065] Step S403: Receive the second echo signals of the plurality of second ultrasonic sequences;

[0066] Step S404: The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal, wherein the first blood flow motion signal includes a first part of the blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with blood flow velocity higher than the tissue motion velocity range.

[0067] Step S405: Perform autocorrelation calculation on the first blood flow motion signal to obtain the first blood flow data, and generate the first blood flow image based on the first blood flow data;

[0068] Step S406: Overlay the first blood flow image and one frame of the tissue image from the multiple frames of the tissue images to obtain the first multimodal image;

[0069] Step S407: Emit at least one set of the second ultrasound sequence to the target tissue area of ​​the subject;

[0070] Step S408: Receive at least one set of third echo signals from the second ultrasonic sequence;

[0071] Step S409: A portion of the echo signal from the first echo signal to be filtered and the third echo signal are used as the second echo signal to be filtered, and subjected to the spatiotemporal wall filtering process to remove tissue motion signals from the second echo signal to be filtered, resulting in a second blood flow motion signal. The second blood flow motion signal includes a first portion of blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range. The sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence.

[0072] Step S410: Perform autocorrelation calculation on the second blood flow motion signal to obtain second blood flow data, and generate a second blood flow image based on the second blood flow data;

[0073] Step S411: Emit at least one set of the first ultrasound sequence to the target tissue area of ​​the subject being examined;

[0074] Step S412: Receive at least one set of fourth echo signals of the first ultrasound sequence, and acquire at least one frame of the tissue image based on the fourth echo signals;

[0075] Step S413: Overlay the second blood flow image and at least one frame of the tissue image to obtain a second multimodal image.

[0076] For example, the target tissue region in S401 may include a blood flow region.

[0077] For example, the ultrasonic wave in S401 can be emitted multiple times, and each emission includes multiple pulses.

[0078] For example, multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences can be emitted toward a target tissue area, such as two or more sets. Each emitted first ultrasound sequence may include one or more first pulse ultrasound waves. Each emitted first ultrasound sequence may include multiple second pulse ultrasound waves. The multiple second pulse ultrasound waves emitted and received by each emitted first ultrasound sequence form a scan packet.

[0079] like Figure 5 As shown, in this application, a single scan frame includes a B-scan (corresponding to the first ultrasound sequence) and a blood flow scan (corresponding to the second ultrasound sequence), wherein the portions of the B-scan (e.g., long arrow) and the blood flow scan (e.g., short arrow) are within... Figure 5 It is a sequential relationship, that is, B-scan is performed first and then blood flow scan is performed within each frame scan time. However, this application does not only include this sequence of B-scan first and then blood flow scan, but also includes blood flow scan first and then B-scan, as well as the case of B-scan and blood flow scan being interspersed. But regardless of the scanning form, it must meet the requirement that a complete tissue image, such as a B-image, can be acquired within each frame scan time, and the time interval between two adjacent blood flow scans is equal to the pulse repetition time (PRT). That is, the time interval between two adjacent sets of second ultrasound sequences is equal to the pulse repetition time in the slow time dimension. Similarly, the time interval between the echo signals corresponding to two adjacent sets of second ultrasound sequences is also equal to the pulse repetition time in the slow time dimension.

[0080] In some embodiments, the length of each second ultrasound sequence, Ncapture (i.e., the sampling length in the slow time dimension), is determined based on clinical frame rate requirements and the pulse repetition time in the slow time dimension. The pulse repetition time is determined based on the currently measured blood flow velocity range and the center frequency of the second ultrasound sequence. For example, the length of the second ultrasound sequence is negatively correlated with the pulse repetition time, i.e., when the pulse repetition time (PRT) is large, Ncapture is small; when the PRT is small, Ncapture can be appropriately increased. When the frame rate is low, Ncapture is large; when the frame rate is high, Ncapture is small. For example, the clinical frame rate requirement for blood flow imaging can be 20 frames or more, or 10 frames or more, or any other suitable frame rate.

[0081] Optionally, the length Ncapture of each group of second ultrasound sequences is less than or equal to 30, or further, Ncapture is less than or equal to 30 and greater than 4, or further, Ncapture is less than or equal to 30 and greater than 16, so as to meet the sampling requirements while also meeting the frame rate requirements. However, the length of each group of second ultrasound sequences mentioned above is only an example, and other suitable lengths can also be applied to this application.

[0082] It is worth mentioning that before each scan begins, the ultrasound imaging system can respond to user commands and set clinical frame rate requirements.

[0083] In some embodiments, in step S402, tissue images can be obtained by any suitable method known to those skilled in the art. For example, an ultrasound imaging system can obtain tissue images, such as B-mode ultrasound images, by processing the first echo signal of the received first ultrasound sequence through signal amplification, analog-to-digital conversion, beamforming, and other signal processing steps.

[0084] In some embodiments, in step S403, the receiving circuit of the ultrasound imaging system can receive the second echo signals corresponding to multiple sets of second ultrasound sequences.

[0085] In some embodiments, in step S404, the spatiotemporal wall filter, also known as the spatiotemporal adaptive wall filter, can more effectively distinguish slow-moving blood flow from slow tissue movement. While filtering out tissue, it can also retain the slow-moving blood flow signal, thus improving the blood flow detection sensitivity and providing better display of slow blood flow.

[0086] In the wall filtering stage of blood flow processing, a spatiotemporal adaptive wall filter is used (which can better filter out low-velocity tissue clutter and retain low-velocity blood flow signals). Its requirement for the sampling sequence length is much higher than that of a conventional pure time-domain IIR filter (for example, it can be 10 to 20 times the order of the IIR filter).

[0087] To achieve good filtering results, the spatiotemporal adaptive wall filter algorithm requires that the original Doppler signal acquisition sequence be sufficiently long in the slow time dimension (e.g., the sequence length is usually 60-200). Using the traditional Doppler blood flow imaging processing flow (Ncapture=Nfilter=Ncorr), the blood flow frame rate cannot meet clinical needs (because Ncapture is too large and the frame rate is very low). However, in this application, by making the length of the first sequence Nfilter greater than the length of each group of second ultrasound sequences Ncapture, the filtering effect of the spatiotemporal adaptive wall filter can be improved without affecting the frame rate.

[0088] Furthermore, since the length of the first sequence length Nfilter is directly related to the filtering effect of the spatiotemporal adaptive wall filter, a larger first sequence length Nfilter results in better filtering. However, an excessively large first sequence length Nfilter may lead to excessive computational load. Therefore, in some embodiments, the first sequence length Nfilter can be more than four times the length Ncapture of the second ultrasonic sequence. For example, the first sequence length Nfilter can be more than four to five times the length Ncapture of the second ultrasonic sequence. Alternatively, the first sequence length Nfilter can be four to ten times, four to eight times, or four to six times the length Ncapture of the second ultrasonic sequence. It is worth noting that the above ranges are merely examples and do not constitute a limitation.

[0089] In some embodiments, to ensure the filtering effect, the first sequence length Nfilter (i.e., the filtering order) can be greater than or equal to 60, or other suitable numerical ranges.

[0090] In some embodiments, the first sequence length is obtained by multiplying the length of the second ultrasound sequence by a first preset coefficient, or the first sequence length is a preset value.

[0091] In one embodiment, in step S404, specifically, the temporal and spatial features of the first echo signal to be filtered are extracted through spatiotemporal wall filtering, and the temporal and spatial features are analyzed to filter out tissue motion signals in the first echo signal to be filtered, thereby obtaining the first blood flow motion signal, such as... Figure 6 As shown, the first blood flow motion signal includes a first part of the blood flow motion signal (i.e., a low-speed motion signal) with a blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal (a high-speed motion signal higher than the low-speed motion signal) with a blood flow velocity higher than the tissue motion velocity range. For example, the blood flow velocity of the first part of the blood flow motion signal is below 5 cm / s.

[0092] The specific method for extracting the temporal and spatial features of the first echo signal to be filtered through spatiotemporal wall filtering and analyzing the temporal and spatial features is not specifically limited here; any suitable method can be used.

[0093] In step S405, in some embodiments, autocorrelation calculation is performed on the first blood flow motion signal to obtain first blood flow data. This includes: obtaining a blood flow motion signal of a second sequence length from the first blood flow motion signal and performing autocorrelation calculation to obtain the first blood flow data. The second sequence length Ncorr is greater than or equal to the length Ncapture of the second ultrasound sequence, and less than or equal to the length Nfilter of the first sequence. A larger Ncorr results in better blood flow sensitivity, but may weaken the dynamic range of the blood flow. The specific value of Ncorr can be determined by comprehensively considering the blood flow sensitivity and temporal resolution. In this application, the second sequence length Ncorr is greater than or equal to the length Ncapture of the second ultrasound sequence, and less than or equal to the length Nfilter of the first sequence, thereby improving the temporal resolution while satisfying the blood flow sensitivity, thus maintaining good dynamic range in the blood flow image.

[0094] Optionally, in this application, the first blood flow data includes at least one of mean blood flow velocity, variance, and energy.

[0095] Autocorrelation calculation is a common phase difference analysis algorithm that can estimate the characteristics of the Doppler effect into three physical quantities: velocity, energy, and variance. The velocity information obtained from autocorrelation calculation can be mapped to pseudo-color information, and the generated pseudo-color image can be called a Doppler color blood flow image (hereinafter referred to as a blood flow image). The energy information obtained from autocorrelation estimation can also be mapped to pseudo-color information, and the generated pseudo-color image can be called an energy image. The variance information obtained from autocorrelation estimation can also be mapped to pseudo-color information, and the generated pseudo-color image can be called a variance image. That is, the first blood flow image can include any one or more of the velocity image, energy image, and variance image.

[0096] In step S406, in some embodiments, the first blood flow image and one frame of tissue image from the multiple frames of tissue images are superimposed to obtain a first multimodal image. The one frame of tissue image from the multiple frames of tissue images can be any tissue image obtained before the first blood flow image is acquired, or it can be any tissue image obtained afterward. For example, for the first blood flow image, it can be superimposed with the obtained first frame of tissue image, or it can be superimposed with any tissue image after the first frame and before the first blood flow image is output.

[0097] The method of superimposing blood flow images and tissue images can be achieved by inputting both blood flow images and tissue images into the threshold decision module of the ultrasound imaging system to complete threshold decision and determine the image mode flag for each scanned pixel. This image mode flag, along with the tissue image and blood flow image, is then processed by a post-processing module to embed the blood flow image into the tissue image according to certain rules, thereby obtaining a first multimodal image. A display can also be used to display this first multimodal image; for example, the obtained first multimodal image can be processed by a color digital scanning converter before being displayed on the monitor. In this process, image post-processing includes two levels of processing: first, single-channel signal processing of each image channel before mixing, using methods to filter out noise points to improve image quality; second, mixing the color blood flow velocity image, energy image, or variance image output by the autocorrelation processor with the tissue image according to a certain method, i.e., threshold rules. The above superposition method is only an example; other methods that enable the superposition display of blood flow images and tissue images are also applicable to this application.

[0098] The first multimodal image can be obtained using the above method. However, during the real-time scanning and acquisition process, the acquisition of the first multimodal image may be delayed because it requires waiting for the sequence length of the echo signal used for spatiotemporal wall filtering to reach the first sequence length.

[0099] After obtaining the first multimodal image, in step S407, at least one set of the second ultrasound sequence is transmitted to the target tissue region of the examined object. The specific number of sets of the second ultrasound sequence transmitted can be reasonably set according to actual needs, for example, it can be one set, which can ensure that the frame rate of the subsequent output blood flow image is relatively small. At least one set of the first ultrasound sequence can be transmitted before or after transmitting the at least one set of the second ultrasound sequence to acquire tissue images.

[0100] Next, in step S408, at least one set of third echo signals from the second ultrasound sequence are received to acquire updated blood flow images.

[0101] Next, in step S409, a portion of the echo signal in the first echo signal to be filtered and the third echo signal are used as the second echo signal to be filtered and subjected to the spatiotemporal wall filtering process to filter out the tissue motion signal in the second echo signal to be filtered, thereby obtaining the second blood flow motion signal. That is, the second echo signal to be filtered includes both the newly obtained third echo signal and a portion of the echo signal in the previously obtained first echo signal to be filtered.

[0102] The second blood flow motion signal includes a first portion of the blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second portion of the blood flow motion signal with blood flow velocity higher than the tissue motion velocity range; wherein the sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the sequence length corresponding to the second echo signal to be filtered is also greater than the length of the second ultrasound sequence.

[0103] In one example, step S409 includes: extracting the temporal and spatial features of the second echo signal to be filtered through spatiotemporal wall filtering, and analyzing the temporal and spatial features to filter out tissue motion signals in the second echo signal to be filtered, thereby obtaining a second blood flow motion signal.

[0104] Specifically, some details of S409 can be found in the description of step S404 above, and will not be repeated here.

[0105] In one example, autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, including: obtaining a blood flow motion signal of a second sequence length from the second blood flow motion signal and performing autocorrelation calculation to obtain the second blood flow data, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the length of the first sequence.

[0106] Specifically, some details of step S410 can be found in the description of step S405 above, and will not be repeated here.

[0107] In one embodiment, steps S411 and S412 may be performed before step S407, after step S407, or interspersed. No specific limitations are made here; for further details, please refer to the descriptions of steps S401 to S402 above.

[0108] In one embodiment, step S413 superimposes the second blood flow image and one frame of tissue image from at least one of the tissue images to obtain a second multimodal image. The tissue image used for superimposing the second blood flow image can be any frame of tissue image obtained before obtaining the second blood flow image, or it can be any frame of tissue image obtained after obtaining the second blood flow image. Preferably, to reduce output latency, the tissue image used for superimposing the second blood flow image can be any frame of tissue image obtained before obtaining the second blood flow image. Specifically, the superposition method can be referred to the relevant description of step S406 above, and will not be repeated here.

[0109] In some embodiments, the second multimodal image may be displayed after it has been obtained.

[0110] Furthermore, as the scanning proceeds sequentially, the method further includes the following steps: transmitting at least one set of the second ultrasound sequences to the target tissue region of the subject; receiving the fifth echo signal of at least one set of the second ultrasound sequences; and performing spatiotemporal wall filtering on a portion of the echo signals from the second set of echo signals to be filtered and the fifth echo signal as the third set of echo signals to be filtered, thereby filtering out tissue motion signals in the third set of echo signals to be filtered, and obtaining a third blood flow motion signal, wherein the third blood flow motion signal includes a first portion of blood flow motion signal with blood flow velocity within the tissue motion velocity range and a portion of blood flow motion signal with blood flow velocity higher than the set of second ultrasound sequences. The second part of the blood flow motion signal within the tissue motion velocity range; wherein the sequence length corresponding to the third echo signal to be filtered is the same as the first sequence length; autocorrelation calculation is performed on the third blood flow motion signal to obtain third blood flow data, and a third blood flow image is generated based on the third blood flow data; at least one set of the first ultrasound sequence is transmitted to the target tissue region of the subject; a sixth echo signal of at least one set of the first ultrasound sequence is received, and at least one frame of the tissue image is obtained based on the sixth echo signal; the third blood flow image and one frame of the tissue image from the at least one frame of the tissue image are superimposed to obtain a third multimodal image.

[0111] Specifically, the details of each step can be found in the detailed descriptions of similar steps mentioned above, and will not be repeated here.

[0112] Subsequently, by continuing to execute the above-mentioned process of acquiring blood flow images and tissue images in a loop, multimodal images are obtained frame by frame for output and display.

[0113] In a specific example, as shown above Figure 5As shown, the horizontal axis is a slow time axis, the time included in a frame period is one frame of Doppler blood flow scanning time, which includes B-scanning (long arrows) and blood flow scanning (short arrows). The sequence length of blood flow scanning in slow time within one frame is Ncapture (that is, the length of each second ultrasonic sequence is Ncapture), and the blood flow signal sequence length required by the spatiotemporal adaptive wall filter (that is, the first sequence length) is Nfilter (Nfilter is greater than Ncapture). The sequence length of the blood flow signal (also referred to as blood flow motion signal in this paper) finally used for autocorrelation calculation (that is, the second sequence length) is Ncorr. Optionally, Ncapture≤Ncorr≤Nfilter, and Ncapture<Nfilter. The finally output one frame of blood flow image (that is, C image) is obtained by obtaining a blood flow motion signal after an echo signal with a length of Nfilter (that is, the aforementioned first to-be-filtered echo signal or the second to-be-filtered echo signal or the third to-be-filtered echo signal) undergoes a wall filtering operation, and then extracting the sequence with a length of the second sequence length Ncorr from the blood flow motion signal to perform an autocorrelation calculation. It can be seen that Figure 5 In the example shown, the blood flow data acquisition within one frame always ensures that the length of the acquisition sequence is Ncapture (the acquisition frame rate is constant), while windows with lengths of Nfilter and Ncorr are respectively used for subsequent spatiotemporal wall filtering processing and autocorrelation processing. Each time sliding backward by a length of Ncapture on the basis of the original blood flow data, a new frame of blood flow image C is obtained. Wherein the blood flow image Cn and the tissue image Bn are finally superimposed and paired one by one for display on the interface of the display.

[0114] upper Figure 5 As shown, one frame scanning time includes B-scanning and blood flow scanning, wherein the B-scanning (long arrow) and blood flow scanning (short arrow) parts are in sequential relationship in the above figure, but the present invention is not limited to such a sequence of B-scanning first and then blood flow scanning, also includes the sequence of blood flow scanning first and then B-scanning, and also includes the situation where B-scanning and blood flow scanning are performed alternately, as long as it is ensured that a complete frame of B image can be acquired within the scanning time, and the time between two adjacent blood flow scans is equal to the pulse repetition time (PRT).

[0115] Compared with the traditional Doppler blood flow processing strategy (that is, as described above, a pure time-domain IIR filter is adopted in the wall filtering step, and Ncapture=Nfilter=Ncorr, and this processing strategy has poor sensitivity to low-speed blood flow detection), the blood flow processing strategy proposed by the present invention adopts a spatio-temporal adaptive wall filter in the wall filtering step. The wall filter can combine the temporal and spatial information of blood flow to perform adaptive feature decomposition, and can distinguish tissue motion signals with low-speed motion from blood flow motion signals, as Figure 6 shown, so that the low-speed moving blood flow can be retained from the low-speed moving tissue clutter, and the sensitivity of low-speed blood flow detection is improved. Because the spatio-temporal adaptive filter has a relatively high requirement on the sequence length of the blood flow signal in the slow time dimension, the present invention also proposes a blood flow signal processing strategy based on the spatio-temporal adaptive wall filter, that is, the window lengths (that is, sequence lengths) of the signal acquisition stage, the wall filtering stage and the autocorrelation stage in the slow time dimension are different, and Ncapture=<Ncorr<=Nfilter, and frame-by-frame blood flow images finally displayed are obtained by means of sliding window.

[0116] The ultrasonic imaging method provided by the present invention can on the one hand ensure a frame rate comparable to that of the traditional method, and on the other hand, due to the powerful filtering performance of the spatio-temporal adaptive wall filter, it has better display of low-speed blood flow than conventional blood flow processing methods. In addition, in the present invention, the sequence length for autocorrelation calculation can be adjusted according to the display effect, which takes into account both the dynamic sense of blood flow and the sensitivity of blood flow, and can achieve a better balance between the two.

[0117] Returning now to Figure 1 the ultrasound imaging system 10 shown.

[0118] In one implementation, the transmitting circuit 160 can send excitation pulses to the ultrasound probe 110 via a transmit / receive selection switch 120 to excite the ultrasound probe 110 to transmit multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences toward a target tissue region of the subject. Each set of first ultrasound sequences is used to acquire a tissue image of the target tissue region, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue region, which includes blood vessels. The receiving circuit 170 receives first echo signals from the multiple sets of first ultrasound sequences and second echo signals from the multiple sets of second ultrasound sequences through the ultrasound probe 110, and sends the first and second echo signals to the processor 140. Each set of second ultrasound sequences includes transmitting multiple pulses toward the same target location. The processor 140 can be used to: acquire multiple frames of the tissue images based on the first echo signal; perform spatiotemporal wall filtering on the echo signal of a first sequence length in the second echo signal as a first echo signal to be filtered, so as to filter out the tissue motion signal in the first echo signal to be filtered, to obtain a first blood flow motion signal, wherein the first blood flow motion signal includes a first part of the blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range; perform autocorrelation calculation on the first blood flow motion signal to obtain first blood flow data, and generate a first blood flow image based on the first blood flow data; and superimpose the first blood flow image and one frame of the tissue images from the multiple frames to obtain a first multimodal image. A display is used to display the first multimodal image.

[0119] Furthermore, the transmitting circuit 160 is also configured to transmit at least one set of the second ultrasound sequence to the target tissue region of the subject, and to transmit at least one set of the first ultrasound sequence to the target tissue region of the subject; the receiving circuit 170 is also configured to receive at least one set of the fourth echo signal of the first ultrasound sequence, and to receive at least one set of the third echo signal of the second ultrasound sequence; the processor 140 is also configured to: perform the spatiotemporal wall filtering process on a portion of the echo signal in the first echo signal to be filtered and the third echo signal as the second echo signal to be filtered, so as to filter out the tissue motion signal in the second echo signal to be filtered, and obtain the second blood flow motion signal. The second blood flow motion signal includes a first portion of the blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second portion of the blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range; wherein the sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence; autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, and a second blood flow image is generated based on the second blood flow data; at least one frame of the tissue image is acquired based on the fourth echo signal; the second blood flow image and one frame of the tissue image from the at least one frame of the tissue image are superimposed to obtain a second multimodal image. The display 150 is used to display the second multimodal image.

[0120] In some embodiments, the transmitting circuit 160 is further configured to: transmit at least one set of the second ultrasound sequence to the target tissue region of the subject and transmit at least one set of the first ultrasound sequence to the target tissue region of the subject; the receiving circuit 170 is further configured to: receive at least one set of the fifth echo signal of the second ultrasound sequence and receive at least one set of the sixth echo signal of the first ultrasound sequence; the processor 140 is further configured to: perform the spatiotemporal wall filtering process on a portion of the echo signal to be filtered in the second echo signal and the fifth echo signal as the third echo signal to be filtered, so as to filter out the tissue motion signal in the third echo signal to be filtered, and obtain the third blood flow motion. The signal, wherein the third blood flow motion signal includes a first portion of blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with blood flow velocity higher than the tissue motion velocity range; wherein the sequence length corresponding to the third echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence; autocorrelation calculation is performed on the third blood flow motion signal to obtain third blood flow data, and a third blood flow image is generated based on the third blood flow data; at least one frame of the tissue image is acquired based on the sixth echo signal; the third blood flow image and one frame of the tissue image from the at least one frame of the tissue image are superimposed to obtain a third multimodal image. A display 150 is used to display the third multimodal image.

[0121] In some embodiments, the processor 140 is configured to perform spatiotemporal wall filtering on the echo signal of the first sequence length in the second echo signal as the first echo signal to be filtered, so as to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal. This includes: extracting the time features and spatial features of the first echo signal to be filtered through spatiotemporal wall filtering, and analyzing the time features and spatial features to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal.

[0122] In some embodiments, the processor 140 is configured to perform spatiotemporal wall filtering on a portion of the echo signal in the first echo signal to be filtered and the third echo signal as the second echo signal to be filtered, so as to filter out the tissue motion signal in the second echo signal to be filtered and obtain the second blood flow motion signal. This includes: extracting the temporal and spatial features of the second echo signal to be filtered through spatiotemporal wall filtering, and analyzing the temporal and spatial features to filter out the tissue motion signal in the second echo signal to be filtered and obtain the second blood flow motion signal.

[0123] In some embodiments, the processor 140 is configured to perform autocorrelation calculation on the first blood flow motion signal to obtain first blood flow data, including: obtaining a blood flow motion signal of a second sequence length from the first blood flow motion signal and performing autocorrelation calculation to obtain the first blood flow data, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the length of the first sequence.

[0124] In some embodiments, the processor 140 is configured to perform autocorrelation calculation on the second blood flow motion signal to obtain second blood flow data, including: obtaining a blood flow motion signal of a second sequence length from the second blood flow motion signal and performing autocorrelation calculation to obtain the second blood flow data, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the first sequence length.

[0125] In some embodiments, the length of the second ultrasound sequence is determined based on clinical frame rate requirements and pulse repetition time in the slow time dimension, wherein the pulse repetition time is determined based on the currently measured blood flow velocity range and the center frequency of the second ultrasound sequence.

[0126] In some embodiments, the length of the second ultrasound sequence is negatively correlated with the pulse repetition time.

[0127] In some embodiments, the length of the second ultrasound sequence is less than or equal to 30.

[0128] In some embodiments, the first sequence length is obtained by multiplying the length of the second ultrasound sequence by a first preset coefficient, or the first sequence length is a preset value.

[0129] In some embodiments, the length of the first sequence is greater than or equal to 60; and / or, the length of the first sequence is more than four times the length of the second ultrasound sequence.

[0130] In some embodiments, the second sequence length is obtained by multiplying the first sequence length by a second preset coefficient, or the second sequence length is a preset value.

[0131] In some embodiments, the time interval between two adjacent sets of the second ultrasound sequences is equal to the pulse repetition time in the slow time dimension.

[0132] For specific details, please refer to the relevant descriptions of the methods mentioned above, which will not be repeated here.

[0133] Therefore, the ultrasound imaging method and system of the present invention, by using spatiotemporal wall filtering to process the echo signal corresponding to the second ultrasound sequence, and by making the sequence length of the echo signal to be filtered in each spatiotemporal wall filtering process greater than the length of the second ultrasound sequence, can more effectively distinguish slow-moving blood flow from slow tissue movement. While filtering out tissue movement signals, it can also retain slow-moving blood flow signals, thus improving the sensitivity of blood flow detection and providing better display of slow blood flow.

[0134] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of the invention. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of the invention. All such changes and modifications are intended to be included within the scope of the invention as claimed in the appended claims.

[0135] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0137] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0138] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, this approach should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with fewer features than all of those in a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0139] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0140] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0141] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules in the article analysis device according to embodiments of the present invention. The present invention can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0142] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0143] The above description is merely a specific embodiment of the present invention or an explanation of that embodiment. The scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An ultrasound imaging method, characterized in that, include: Multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences are emitted to the target tissue area of ​​the subject being examined, wherein each set of first ultrasound sequences is used to acquire a tissue image of the target tissue area, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue area. Receive the first echo signals of the multiple sets of first ultrasound sequences, and acquire multiple frames of the tissue images based on the first echo signals; Receive the second echo signals of the plurality of second ultrasonic sequences; The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal. The first blood flow motion signal includes a first part of the blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with blood flow velocity higher than the tissue motion velocity range. Autocorrelation calculation is performed on the first blood flow motion signal to obtain the first blood flow data, and a first blood flow image is generated based on the first blood flow data; The first blood flow image and one frame of tissue image from the multiple frames of tissue images are superimposed to obtain the first multimodal image; At least one set of the second ultrasound sequence is emitted toward the target tissue area of ​​the subject being examined; Receive at least one set of third echo signals from the second ultrasonic sequence; A portion of the echo signal from the first echo signal to be filtered and the third echo signal are used as the second echo signal to be filtered, and spatiotemporal wall filtering is applied to filter out tissue motion signals in the second echo signal to be filtered, thereby obtaining a second blood flow motion signal. The second blood flow motion signal includes a first portion of blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with blood flow velocity higher than the tissue motion velocity range. The sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence. Autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, and a second blood flow image is generated based on the second blood flow data; At least one set of the first ultrasound sequence is emitted toward the target tissue area of ​​the subject being examined; Receive at least one set of fourth echo signals from the first ultrasound sequence, and acquire at least one frame of the tissue image based on the fourth echo signals; The second blood flow image and at least one frame of the tissue image are superimposed to obtain a second multimodal image.

2. The ultrasound imaging method as described in claim 1, characterized in that, After obtaining the second multimodal image, the method further includes: At least one set of the second ultrasound sequence is emitted toward the target tissue area of ​​the subject being examined; Receive at least one set of fifth echo signals from the second ultrasonic sequence; A portion of the echo signal from the second echo signal to be filtered and the fifth echo signal are used as the third echo signal to be filtered, and spatiotemporal wall filtering is applied to filter out tissue motion signals in the third echo signal to be filtered, resulting in a third blood flow motion signal. The third blood flow motion signal includes a first portion of blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range. The sequence length corresponding to the third echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence. Autocorrelation calculation is performed on the third blood flow motion signal to obtain third blood flow data, and a third blood flow image is generated based on the third blood flow data; At least one set of the first ultrasound sequence is emitted toward the target tissue area of ​​the subject being examined; Receive at least one set of sixth echo signals of the first ultrasound sequence, and acquire at least one frame of the tissue image based on the sixth echo signals; The third blood flow image is superimposed with at least one frame of the tissue image to obtain a third multimodal image.

3. The ultrasound imaging method as described in claim 1, characterized in that, The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out tissue motion signals in the first echo signal to be filtered and obtain the first blood flow motion signal. This includes: extracting the temporal and spatial features of the first echo signal to be filtered through spatiotemporal wall filtering, and analyzing the temporal and spatial features to filter out tissue motion signals in the first echo signal to be filtered and obtain the first blood flow motion signal.

4. The ultrasound imaging method as described in claim 1, characterized in that, A portion of the echo signal from the first echo signal to be filtered and the third echo signal are used as the second echo signal to be filtered, and then subjected to the spatiotemporal wall filtering process to remove tissue motion signals from the second echo signal to be filtered, thereby obtaining a second blood flow motion signal, including: The temporal and spatial features of the second echo signal to be filtered are extracted by spatiotemporal wall filtering, and the temporal and spatial features are analyzed to filter out tissue motion signals in the second echo signal to obtain the second blood flow motion signal.

5. The ultrasound imaging method as described in claim 1, characterized in that, Autocorrelation calculation is performed on the first blood flow motion signal to obtain the first blood flow data, including: First blood flow data is obtained by performing autocorrelation calculation on a blood flow motion signal of a second sequence length obtained from the first blood flow motion signal, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the length of the first sequence.

6. The ultrasound imaging method as described in claim 1, characterized in that, Autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, including: The second blood flow data is obtained by performing autocorrelation calculation on a blood flow motion signal of a second sequence length obtained from the second blood flow motion signal, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the length of the first sequence.

7. The ultrasound imaging method as described in claim 1, characterized in that, The length of the second ultrasound sequence is determined based on clinical frame rate requirements and pulse repetition time in the slow time dimension, wherein the pulse repetition time is determined based on the currently measured blood flow velocity range and the center frequency of the second ultrasound sequence.

8. The ultrasound imaging method as described in claim 7, characterized in that, The length of the second ultrasound sequence is negatively correlated with the pulse repetition time.

9. The ultrasound imaging method according to any one of claims 1 to 8, characterized in that, The length of the second ultrasound sequence is less than or equal to 30.

10. The ultrasound imaging method according to any one of claims 1 to 8, characterized in that, The first sequence length is obtained by multiplying the length of the second ultrasound sequence by a first preset coefficient, or the first sequence length is a preset value.

11. The ultrasound imaging method according to any one of claims 1 to 8, characterized in that, The length of the first sequence is greater than or equal to 60; and / or the length of the first sequence is more than four times the length of the second ultrasound sequence.

12. The ultrasound imaging method as described in claim 5 or 6, characterized in that, The second sequence length is obtained by multiplying the first sequence length by a second preset coefficient, or the second sequence length is a preset value.

13. The ultrasound imaging method according to any one of claims 1 to 8, characterized in that, The time interval between two adjacent sets of the second ultrasound sequences is equal to the pulse repetition time in the slow time dimension.

14. The ultrasound imaging method according to any one of claims 1 to 8, characterized in that, The method further includes: Display the first multimodal image and the second multimodal image.

15. An ultrasound imaging system, characterized in that, The system includes: Ultrasonic probe; The transmitting circuit is used to transmit multiple sets of first ultrasound sequences and multiple sets of second ultrasound sequences to the target tissue area of ​​the subject being examined, wherein each set of first ultrasound sequences is used to acquire a tissue image of the target tissue area, and each set of second ultrasound sequences is used to acquire a blood flow image of the target tissue area. A receiving circuit is configured to receive the first echo signals of the plurality of first ultrasonic sequences and the second echo signals of the plurality of second ultrasonic sequences. Processor, used for: Multiple frames of the tissue images are acquired based on the first echo signal; The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out the tissue motion signal in the first echo signal to be filtered and obtain the first blood flow motion signal. The first blood flow motion signal includes a first part of the blood flow motion signal with blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with blood flow velocity higher than the tissue motion velocity range. Autocorrelation calculation is performed on the first blood flow motion signal to obtain the first blood flow data, and a first blood flow image is generated based on the first blood flow data; The first blood flow image and one frame of tissue image from the multiple frames of tissue images are superimposed to obtain the first multimodal image; The transmitting circuit is also used to transmit at least one set of the second ultrasound sequence to the target tissue area of ​​the subject being examined, and to transmit at least one set of the first ultrasound sequence to the target tissue area of ​​the subject being examined. The receiving circuit is further configured to receive at least one set of fourth echo signals of the first ultrasonic sequence and at least one set of third echo signals of the second ultrasonic sequence. The processor is further configured to: perform the spatiotemporal wall filtering process on a portion of the echo signal in the first echo signal to be filtered and the third echo signal as a second echo signal to be filtered, so as to filter out the tissue motion signal in the second echo signal to be filtered, thereby obtaining a second blood flow motion signal, wherein the second blood flow motion signal includes a first portion of blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second portion of blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range; wherein the sequence length corresponding to the second echo signal to be filtered is the same as the first sequence length, and the first sequence length is greater than the length of the second ultrasound sequence; Autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, and a second blood flow image is generated based on the second blood flow data; At least one frame of the tissue image is acquired based on the fourth echo signal; The second blood flow image and at least one frame of the tissue image are superimposed to obtain a second multimodal image.

16. The ultrasound imaging system as described in claim 15, characterized in that, The transmitting circuit is also used to: transmit at least one set of the second ultrasound sequence to the target tissue area of ​​the subject being examined and to transmit at least one set of the first ultrasound sequence to the target tissue area of ​​the subject being examined. The receiving circuit is further configured to: receive at least one set of fifth echo signals of the second ultrasonic sequence, and receive at least one set of sixth echo signals of the first ultrasonic sequence; The processor is also used for: The second echo signal to be filtered and the fifth echo signal are used as the third echo signal to be filtered and subjected to the spatiotemporal wall filtering process to filter out the tissue motion signal in the third echo signal to be filtered, thereby obtaining the third blood flow motion signal. The third blood flow motion signal includes a first part of the blood flow motion signal with a blood flow velocity within the tissue motion velocity range and a second part of the blood flow motion signal with a blood flow velocity higher than the tissue motion velocity range. The sequence length corresponding to the third echo signal to be filtered is the same as the first sequence length. Autocorrelation calculation is performed on the third blood flow motion signal to obtain third blood flow data, and a third blood flow image is generated based on the third blood flow data; At least one frame of the tissue image is acquired based on the sixth echo signal; The third blood flow image is superimposed with at least one frame of the tissue image to obtain a third multimodal image.

17. The ultrasound imaging system as described in claim 15, characterized in that, The echo signal of the first sequence length in the second echo signal is used as the first echo signal to be filtered and subjected to spatiotemporal wall filtering to filter out tissue motion signals in the first echo signal to be filtered and obtain the first blood flow motion signal. This includes: extracting the temporal and spatial features of the first echo signal to be filtered through spatiotemporal wall filtering, and analyzing the temporal and spatial features to filter out tissue motion signals in the first echo signal to be filtered and obtain the first blood flow motion signal.

18. The ultrasound imaging system as described in claim 15, characterized in that, A portion of the echo signal from the first echo signal to be filtered and the third echo signal are used as the second echo signal to be filtered, and then subjected to the spatiotemporal wall filtering process to remove tissue motion signals from the second echo signal to be filtered, thereby obtaining a second blood flow motion signal, including: The temporal and spatial features of the second echo signal to be filtered are extracted by spatiotemporal wall filtering, and the temporal and spatial features are analyzed to filter out tissue motion signals in the second echo signal to obtain the second blood flow motion signal.

19. The ultrasound imaging system as described in claim 15, characterized in that, Autocorrelation calculation is performed on the first blood flow motion signal to obtain the first blood flow data, including: First blood flow data is obtained by performing autocorrelation calculation on a blood flow motion signal of a second sequence length obtained from the first blood flow motion signal, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the length of the first sequence.

20. The ultrasound imaging system as described in claim 15, characterized in that, Autocorrelation calculation is performed on the second blood flow motion signal to obtain second blood flow data, including: The second blood flow data is obtained by performing autocorrelation calculation on a blood flow motion signal of a second sequence length obtained from the second blood flow motion signal, wherein the second sequence length is greater than or equal to the length of the second ultrasound sequence and less than or equal to the length of the first sequence.

21. The ultrasound imaging system as described in claim 15, characterized in that, The length of the second ultrasound sequence is determined based on clinical frame rate requirements and pulse repetition time in the slow time dimension, wherein the pulse repetition time is determined based on the currently measured blood flow velocity range and the center frequency of the second ultrasound sequence.

22. The ultrasound imaging system as described in claim 21, characterized in that, The length of the second ultrasound sequence is negatively correlated with the pulse repetition time.

23. The ultrasound imaging system according to any one of claims 15 to 22, characterized in that, The length of the second ultrasound sequence is less than or equal to 30.

24. The ultrasound imaging system according to any one of claims 15 to 22, characterized in that, The first sequence length is obtained by multiplying the length of the second ultrasound sequence by a first preset coefficient, or the first sequence length is a preset value.

25. The ultrasound imaging system according to any one of claims 15 to 22, characterized in that, The length of the first sequence is greater than or equal to 60; and / or the length of the first sequence is more than four times the length of the second ultrasound sequence.

26. The ultrasound imaging system as described in claim 19 or 20, characterized in that, The second sequence length is obtained by multiplying the first sequence length by a second preset coefficient, or the second sequence length is a preset value.

27. The ultrasound imaging system according to any one of claims 15 to 22, characterized in that, The time interval between two adjacent sets of the second ultrasound sequences is equal to the pulse repetition time in the slow time dimension.

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