Method for inhibiting moving tissue noise in blood flow image and ultrasonic equipment

Abstract

The invention provides a method for inhibiting moving tissue noise in a blood flow image and ultrasonic equipment. The method is used for filtering blood flow image motion tissue noise. Comprising the steps that based on a variance image component and an energy image component in a blood flow image, first identifications of all pixel points in the blood flow image are determined, and the first identifications are used for representing whether the pixel points are pixel points with motion features or not; obtaining a target image block based on a first identifier of each pixel point in a plurality of image blocks obtained by subpackaging the blood flow image; for any target image block, according to the speed of each pixel point in the target image block, the speed distribution interval of each pixel point in the target image block is determined, and the speed of any pixel point is obtained based on the speed image component; determining a target speed distribution interval through each speed in the speed distribution interval; and filtering each pixel point of which the speed is in the target speed distribution interval and the first identifier is the motion identifier in the target image block to obtain a blood flow image after noise suppression.

Description

Background Art

[0002] Ultrasonic blood flow imaging mainly uses the Doppler effect to track and detect various parameters of human blood flow signals in real time. Under ideal conditions, the relative displacement of the blood flow signal to the probe causes the Doppler frequency shift generated by the ultrasound to be received by the probe again to obtain the blood flow signal information.

[0003] However, in the actual detection process, the inevitable heartbeat, breathing movement and probe movement will cause the muscle tissue to move relative to the probe, causing the received blood flow signal to mix with the moving tissue signal, which will interfere with the blood flow signal, resulting in lower quality of the obtained ultrasound blood flow image and reduce the accuracy of clinical diagnosis. Summary of the invention

[0004] In an exemplary embodiment of the present disclosure, a method and an ultrasound device are provided for suppressing moving tissue noise in a blood flow image, which are used to filter out moving tissue noise in a blood flow image, improve the quality of the blood flow image, and further improve the accuracy of clinical diagnosis.

[0005] A first aspect of the present disclosure provides a method for suppressing moving tissue noise in a blood flow image, the method comprising:

[0006] Acquire a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component;

[0007] Determining a first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, wherein the first identifier is used to characterize whether the pixel is a pixel with motion characteristics;

[0008] performing packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image;

[0009] Based on the first identifier of each pixel in each image block, a target image block is obtained;

[0010] for any target image block, determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, wherein the speed of any pixel is obtained based on the speed image component; and

[0011] Determining a target speed distribution interval by using the speeds in the at least one speed distribution interval;

[0012] Filtering each pixel point in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel point has a motion feature;

[0013] A blood flow image with noise suppressed is obtained according to each filtered target image block.

[0014] In this embodiment, the first identifier of each pixel in the blood flow image is determined based on the variance image component and the energy image component of the blood flow image. The first identifier is used to characterize whether the pixel is a pixel with motion characteristics, and the image blocks are filtered according to the first identifiers of each pixel in the multiple image blocks of the blood flow image obtained after the blood flow image is subpacked to obtain the target image block. Then, for any target image block, at least one speed distribution interval of each pixel in the target image block is determined according to the speed of each pixel in the target image block. The target speed distribution interval is determined by each speed in the at least one speed distribution interval; and the pixel points in the target image block whose speed is in the target speed distribution interval and whose first identifier is a motion identifier are filtered to obtain the filtered target image block, and the blood flow image after noise suppression is obtained according to the filtered target image blocks. Therefore, in the embodiment of the present application, pixel points with motion characteristics are first identified based on the variance image component and energy image of the blood flow image, and then the velocity distribution interval of each pixel point of the image block corresponding to the pixel point with motion characteristics is analyzed to obtain the location of the motion tissue noise in the blood flow image and filter it to obtain the blood flow image after noise suppression.

[0015] In one embodiment, determining the first identification of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image includes:

[0016] For any pixel point in the blood flow image, obtain the variance component of the pixel point according to the variance image component, and obtain the energy component of the pixel point according to the energy image component;

[0017] If the energy component of the pixel point is greater than a first specified threshold, and the variance component of the pixel point is less than a second specified threshold, determining the first identifier of the pixel point as the motion identifier;

[0018] Otherwise, it is determined that the first identifier of the pixel point is the static identifier, wherein the static identifier is used to indicate that the pixel point does not have a motion feature.

[0019] In this embodiment, the first identification of the pixel point is determined by combining the variance component and the energy component of each pixel point, so as to ensure the accuracy of the determined first identification of the pixel point.

[0020] In one embodiment, the subpackaging of the blood flow image to obtain a plurality of image blocks of the blood flow image includes:

[0021] According to the total number of receiving lines in the blood flow image and the preset number of beams, the number of sub-packets of the blood flow image is obtained, wherein the receiving line is a line formed by each pixel point in the blood flow image in the longitudinal direction;

[0022] Using the subpacket quantity and the length of the blood flow image, the length of each image block is obtained;

[0023] The blood flow image is packetized based on the length of each image block to obtain a plurality of image blocks of the blood flow image.

[0024] In this embodiment, the number of subpackets of the blood flow image is obtained by the total number of receiving lines in the blood flow image and the preset number of beams, and the blood flow image is subpacketized based on the number of subpackets to ensure the accuracy of multiple image blocks of the obtained blood flow image.

[0025] In one embodiment, obtaining the number of subpackets of the blood flow image according to the total number of receiving lines in the blood flow image and the preset number of beams includes:

[0026] Determine the receiving time of any receiving line by using the acquired receiving line depth and sound velocity;

[0027] Based on the receiving time of any one of the receiving lines, the preset pulse repetition frequency and the preset number of repetitions of any one of the receiving lines in the short-time direction, obtaining the number of transmissions of any one of the receiving lines in the sub-packet;

[0028] The first ratio is divided by the number of beams to obtain the number of subpackets of the blood flow image, wherein the first ratio is obtained by dividing the total number of receiving lines by the number of transmissions of the receiving lines in any subpacket.

[0029] In one embodiment, determining the receiving time of any receiving line by using the acquired depth and sound velocity of the receiving line includes:

[0030] The receiving time of any receiving line is obtained by the following formula:

[0031]

[0032] Where prt is the receiving time of any receiving line, d is the depth of the receiving line, v声 is the speed of sound;

[0033] The obtaining the number of transmissions of any receiving line in a sub-packet based on the receiving time of any receiving line, a preset pulse repetition frequency and a preset number of repetitions of any receiving line in a short-time direction comprises:

[0034] The number of transmissions of the receiving line in any sub-packet is obtained by the following formula:

[0035]

[0036] Wherein, I is the number of transmissions of the receiving line in any one of the sub-packets, prt is the receiving time of any one of the receiving lines, PRF is the pulse repetition frequency, N 发 is the number of repetitions in the short-time direction of any receiving line.

[0037] In one embodiment, obtaining the target image block based on the first identifier of each pixel in each image block includes:

[0038] For any image block, counting a first number of pixels in the image block whose first identifier is a motion identifier;

[0039] Dividing the first number by the total number of pixels in the image block to obtain a third ratio;

[0040] An image block whose third ratio is not less than a third specified threshold is determined as the target image block.

[0041] In this embodiment, the target image block is determined by comparing a third ratio obtained by dividing the first number of pixels in the image block that are first identified as motion identifiers by the total number of pixels in the image block with a third specified threshold, thereby ensuring the accuracy of the determined target image block.

[0042] In one embodiment, determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block includes:

[0043] According to the speed of each pixel point in the target image block, the number of pixel points corresponding to each speed is obtained;

[0044] For any speed, if the number of pixel points corresponding to the speed is greater than a specified number, the speed is determined as the target speed;

[0045] Sorting the target speeds in a specified order, adding two target speeds that are adjacent in position and have a difference of a specified value among the sorted target speeds to the same speed distribution set, to obtain at least one speed distribution set;

[0046] Based on the at least one speed distribution set, the at least one speed distribution interval is obtained.

[0047] In one embodiment, determining the target speed distribution interval by using the speeds in the at least one speed distribution interval includes:

[0048] If the number of the speed distribution intervals is one and a fourth ratio of the speed distribution interval is greater than a fourth specified threshold, the speed distribution interval is determined as the target speed distribution interval, wherein the fourth ratio is obtained by dividing the number of pixel points in the target image block whose speed is within the speed distribution interval and whose first identifier is a motion identifier by the total number of pixel points in the target image block whose first identifier is a motion identifier;

[0049] If there are multiple speed distribution intervals, the speed distribution interval in which the speed standard deviation is greater than the fifth specified threshold and the speed distribution interval with the largest speed standard deviation is determined as the target speed distribution interval, wherein the speed standard deviation in any speed distribution interval is obtained based on each speed in the speed division interval.

[0050] A second aspect of the present disclosure provides an ultrasound device, comprising a memory and a processor, wherein the processor and the memory are connected via a bus;

[0051] The memory stores a computer program, and the processor is configured to perform the following operations based on the computer program:

[0052] Acquire a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component;

[0053] Determining a first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, wherein the first identifier is used to characterize whether the pixel is a pixel with motion characteristics;

[0054] performing packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image;

[0055] Based on the first identifier of each pixel in each image block, a target image block is obtained;

[0056] for any target image block, determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, wherein the speed of any pixel is obtained based on the speed image component; and

[0057] Determining a target speed distribution interval by using the speeds in the at least one speed distribution interval;

[0058] Filtering each pixel point in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel point has a motion feature;

[0059] A blood flow image with noise suppressed is obtained according to each filtered target image block.

[0060] In one embodiment, the processor executes the determination of the first identification of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, and is specifically configured as follows:

[0061] For any pixel point in the blood flow image, obtain the variance component of the pixel point according to the variance image component, and obtain the energy component of the pixel point according to the energy image component;

[0062] If the energy component of the pixel point is greater than a first specified threshold, and the variance component of the pixel point is less than a second specified threshold, determining the first identifier of the pixel point as the motion identifier;

[0063] Otherwise, it is determined that the first identifier of the pixel point is the static identifier, wherein the static identifier is used to indicate that the pixel point does not have a motion feature.

[0064] In one embodiment, the processor performs the packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image, including:

[0065] According to the total number of receiving lines in the blood flow image and the preset number of beams, the number of sub-packets of the blood flow image is obtained, wherein the receiving line is a line formed by each pixel point in the blood flow image in the longitudinal direction;

[0066] Using the subpacket quantity and the length of the blood flow image, the length of each image block is obtained;

[0067] The blood flow image is packetized based on the length of each image block to obtain a plurality of image blocks of the blood flow image.

[0068] In one embodiment, the processor executes the step of obtaining the number of subpackets of the blood flow image according to the total number of receiving lines in the blood flow image and the preset number of beams, and is specifically configured as follows:

[0069] Determine the receiving time of any receiving line by using the acquired receiving line depth and sound velocity;

[0070] Based on the receiving time of any one of the receiving lines, the preset pulse repetition frequency and the preset number of repetitions of any one of the receiving lines in the short-time direction, obtaining the number of transmissions of any one of the receiving lines in the sub-packet;

[0071] The first ratio is divided by the number of beams to obtain the number of subpackets of the blood flow image, wherein the first ratio is obtained by dividing the total number of receiving lines by the number of transmissions of the receiving lines in any subpacket.

[0072] In one embodiment, the processor performs the step of determining the receiving time of any receiving line by using the acquired depth and sound velocity of the receiving line, and is specifically configured as follows:

[0073] The receiving time of any receiving line is obtained by the following formula:

[0074]

[0075] Where prt is the receiving time of any receiving line, d is the depth of the receiving line, v 声 is the speed of sound;

[0076] The obtaining the number of transmissions of any receiving line in a sub-packet based on the receiving time of any receiving line, a preset pulse repetition frequency and a preset number of repetitions of any receiving line in a short-time direction comprises:

[0077] The number of transmissions of the receiving line in any sub-packet is obtained by the following formula:

[0078]

[0079] Wherein, I is the number of transmissions of the receiving line in any one of the sub-packets, prt is the receiving time of any one of the receiving lines, PRF is the pulse repetition frequency, N 发 is the number of repetitions in the short-time direction of any receiving line.

[0080] In one embodiment, the processor performs the first identification based on each pixel in each image block to obtain the target image block, which is specifically configured as follows:

[0081] For any image block, counting a first number of pixels in the image block whose first identifier is a motion identifier;

[0082] Dividing the first number by the total number of pixels in the image block to obtain a third ratio;

[0083] An image block whose third ratio is not less than a third specified threshold is determined as the target image block.

[0084] In one embodiment, the processor performs the step of determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, and is specifically configured as follows:

[0085] According to the speed of each pixel point in the target image block, the number of pixel points corresponding to each speed is obtained;

[0086] For any speed, if the number of pixel points corresponding to the speed is greater than a specified number, the speed is determined as the target speed;

[0087] Sorting the target speeds in a specified order, adding two target speeds that are adjacent in position and have a difference of a specified value among the sorted target speeds to the same speed distribution set, to obtain at least one speed distribution set;

[0088] Based on the at least one speed distribution set, the at least one speed distribution interval is obtained.

[0089] In one embodiment, the processor performs the step of determining the target speed distribution interval by passing each speed in the at least one speed distribution interval, and is specifically configured as follows:

[0090] If the number of the speed distribution intervals is one and a fourth ratio of the speed distribution interval is greater than a fourth specified threshold, the speed distribution interval is determined as the target speed distribution interval, wherein the fourth ratio is obtained by dividing the number of pixel points in the target image block whose speed is within the speed distribution interval and whose first identifier is a motion identifier by the total number of pixel points in the target image block whose first identifier is a motion identifier;

[0091] If there are multiple speed distribution intervals, the speed distribution interval in which the speed standard deviation is greater than the fifth specified threshold and the speed distribution interval with the largest speed standard deviation is determined as the target speed distribution interval, wherein the speed standard deviation in any speed distribution interval is obtained based on each speed in the speed division interval.

[0092] According to a third aspect provided by an embodiment of the present disclosure, a computer storage medium is provided, wherein the computer storage medium stores a computer program, and the computer program is used to execute the method as described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0094] Figure 1 A schematic diagram of an applicable scenario in an embodiment of the present disclosure;

[0095] Figure 2 This is one of the flowchart diagrams of a method for suppressing moving tissue noise in a blood flow image according to an embodiment of the present disclosure;

[0096] Figure 3 It is a schematic diagram of a process of determining a first identifier of each pixel point in a blood flow image according to an embodiment of the present disclosure;

[0097] Figure 4 A schematic diagram of a process for determining multiple image blocks of a blood flow image according to an embodiment of the present disclosure;

[0098] Figure 5 is a schematic diagram of each receiving line in a blood flow image according to an embodiment of the present disclosure;

[0099] Figure 6 It is a schematic diagram of a process of determining the number of subpackaging of a blood flow image according to an embodiment of the present disclosure;

[0100] Figure 7 A schematic diagram of packaging a blood flow image according to an embodiment of the present disclosure;

[0101] Figure 8 A schematic diagram of a process for determining a velocity distribution interval of each pixel in a target image block according to an embodiment of the present disclosure;

[0102] Fig. 9 It is a schematic diagram of the corresponding relationship between speed and the number of pixels according to an embodiment of the present disclosure;

[0103] Fig.10 The second flowchart of the method for suppressing moving tissue noise in a blood flow image according to an embodiment of the present disclosure;

[0104] Fig.11 A device for suppressing moving tissue noise in a blood flow image according to an embodiment of the present disclosure;

[0105] Fig.12 It is a schematic structural diagram of an ultrasonic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0106] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0107] In the embodiments of the present disclosure, the term "and / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0108] The application scenarios described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. It is known to those skilled in the art that with the emergence of new application scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems. In the description of the present disclosure, unless otherwise specified, the meaning of "multiple" is two or more.

[0109] In the prior art, during the actual detection process, the inevitable heartbeat, breathing movement and probe movement will cause the muscle tissue to move relative to the probe, causing the received blood flow signal to mix with the tissue signal, causing interference to the blood flow signal, resulting in low quality of the obtained ultrasonic blood flow image, which will reduce the accuracy of clinical diagnosis.

[0110] Therefore, the present disclosure provides a method for suppressing motion tissue noise in a blood flow image, by determining the first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, the first identifier being used to characterize whether the pixel is a pixel with motion characteristics, and filtering the image blocks according to the first identifier of each pixel in a plurality of image blocks of the blood flow image obtained after the blood flow image is subpacked, to obtain a target image block. Then, for any target image block, according to the speed of each pixel in the target image block, at least one speed distribution interval of each pixel in the target image block is determined. The target speed distribution interval is determined by each speed in the at least one speed distribution interval; and each pixel in the target image block whose speed is in the target speed distribution interval and whose first identifier is a motion identifier is filtered to obtain a filtered target image block, and a blood flow image with noise suppressed is obtained according to each filtered target image block. Therefore, in the embodiment of the present application, the pixel points with motion characteristics are first identified based on the variance image component and energy image of the blood flow image, and then the speed distribution interval of each pixel point of the image block corresponding to the pixel point with motion characteristics is analyzed to obtain the location of the motion tissue noise in the blood flow image and filter it to obtain the blood flow image after noise suppression. Below, the scheme of the present disclosure is described in detail with reference to the accompanying drawings.

[0111] like Figure 1 As shown, an application scenario of a method for suppressing moving tissue noise in a blood flow image includes an ultrasound device 110 and a terminal device 120.

[0112] In a possible application scenario, the ultrasound device 110 obtains a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component; and based on the variance image component and the energy image component of the blood flow image, determines a first identifier of each pixel in the blood flow image, wherein the first identifier is used to characterize whether the pixel is a pixel with motion characteristics; then the ultrasound device 110 performs packet processing on the blood flow image to obtain multiple image blocks of the blood flow image; and based on the first identifier of each pixel in each image block, obtains a target image block; then the ultrasound device 110, for any target image block, according to the target image According to the speed of each pixel in the image block, at least one speed distribution interval of each pixel in the target image block is determined, wherein the speed of any pixel is obtained based on the speed image component; and the target speed distribution interval is determined through each speed in the at least one speed distribution interval; and each pixel in the target image block whose speed is in the target speed distribution interval and whose first identifier is a motion identifier is filtered to obtain a filtered target image block, wherein the motion identifier is used to characterize that the pixel has a motion feature; finally, the ultrasound device 110 obtains a blood flow image after noise suppression according to the filtered target image blocks, and displays the blood flow image after noise suppression through the terminal device 120.

[0113] in, Figure 1 The ultrasound device 110 and the terminal device 120 may exchange information via a communication network, wherein the communication mode adopted by the communication network may be divided into a wireless communication mode or a wired communication mode.

[0114] Exemplarily, the ultrasound device 110 can access the network through cellular mobile communication technology to communicate with the terminal device 120, wherein the cellular mobile communication technology, for example, includes the fifth generation mobile communication (5th Generation Mobile Networks, 5G) technology.

[0115] Optionally, the ultrasound device 110 may access the network and communicate with the terminal device 120 via short-range wireless communication, wherein the short-range wireless communication method, for example, includes Wireless Fidelity (Wi-Fi) technology.

[0116] Among them, only a single ultrasound device 110 and a single terminal device 120 are described in detail in the description of this application, but those skilled in the art should understand that the ultrasound device 110 and the terminal device 120 shown are intended to represent the operation of the ultrasound device 110 and the terminal device 120 involved in the technical solution of this application. It does not imply any limitation on the number, type or location of the ultrasound device 110 and the terminal device 120. It should be noted that if additional modules are added to the illustrated environment or individual modules are removed therefrom, the underlying concept of the exemplary embodiment of this application will not be changed.

[0117] It should be noted that the method for suppressing moving tissue noise in blood flow images proposed in this application is not only applicable to Figure 1 The application scenario shown is also applicable to any device capable of suppressing motion tissue noise in blood flow images.

[0118] In combination with the application scenarios described above, the following describes a method for suppressing moving tissue noise in a blood flow image according to an exemplary embodiment of the present application with reference to the accompanying drawings. It should be noted that the above application scenarios are only shown to facilitate understanding of the methods and principles of the present application, and the embodiments of the present application are not limited in this respect.

[0119] like Figure 2 FIG. 1 is a flow chart of a method for suppressing moving tissue noise in a blood flow image disclosed in the present invention, which may include the following steps:

[0120] Step 201: obtaining a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component and an energy image component;

[0121] In the embodiment of the present application, the velocity image component includes the velocity of each pixel in the blood flow image, the energy image component includes the blood flow energy of each pixel in the blood flow image, and the variance image component includes the energy variance of each pixel in the blood flow image.

[0122] Step 202: determining a first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, wherein the first identifier is used to indicate whether the pixel is a pixel with motion characteristics;

[0123] Next, the method for determining the first identification of each pixel in the blood flow image in step 202 is described in detail. Figure 3 As shown, it is a schematic diagram of a process of determining a first identifier of each pixel point in a blood flow image, which may include the following steps:

[0124] Step 301: for any pixel in the blood flow image, obtaining a variance component of the pixel according to the variance image component, and obtaining an energy component of the pixel according to the energy image component;

[0125] In one embodiment, step 301 can be specifically implemented as follows: for any pixel point in the variance image component, obtaining the variance component of the pixel point from the variance image component, and obtaining the energy component of the pixel point in the energy image component based on the position of the pixel point in the variance image component, wherein the position of any pixel point in the variance image component is the same as the position in the energy image component.

[0126] Step 302: Determine whether the energy component of the pixel is greater than a first specified threshold; if so, execute step 303; if not, execute step 305;

[0127] Step 303: determine whether the variance component of the pixel point is less than a second specified threshold, if so, execute step 304, if not, execute step 305;

[0128] Step 304: Determine the first identifier of the pixel point as the motion identifier;

[0129] Step 305: Determine that the first identifier of the pixel point is the static identifier, wherein the static identifier is used to indicate that the pixel point does not have motion characteristics.

[0130] It should be noted that the first specified threshold and the second specified threshold in the embodiment of the present application can be set according to actual conditions, and the embodiment of the present application does not limit the specific values ​​of the first specified threshold and the second specified threshold.

[0131] Step 203: performing packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image;

[0132] Next, the multiple image blocks of the blood flow image obtained in step 203 are described in detail. Figure 4 As shown, it is a schematic diagram of a process for determining multiple image blocks of a blood flow image, which may include the following steps:

[0133] Step 401: obtaining the number of sub-packets of the blood flow image according to the total number of receiving lines in the blood flow image and the preset number of beams, wherein the receiving line is a line formed by each pixel point in the blood flow image in the longitudinal direction;

[0134] like Figure 5As shown in FIG. 1 , it is a schematic diagram of each receiving line in the blood flow image. It can be seen from the figure that the line composed of pixels in the blood flow image in the longitudinal direction is the receiving line. That is, straight line AB, straight line CD, straight line EF, straight line MN, and straight line PQ are all receiving lines of the blood flow image.

[0135] like Figure 6 As shown, a flow chart for determining the number of subpackaging of a blood flow image may include the following steps:

[0136] Step 601: Determine the receiving time of any receiving line using the acquired receiving line depth and sound velocity;

[0137] In the embodiment of the present application, the depth of the receiving line can be directly obtained. The receiving time of any receiving line can be obtained by formula (1):

[0138]

[0139] Where prt is the receiving time of any receiving line, d is the depth of the receiving line, v 声 is the speed of sound.

[0140] Step 602: Based on the receiving time of any one receiving line, the preset pulse repetition frequency and the preset number of repetitions of any one receiving line in the short-time direction, the number of transmissions of any one receiving line in the sub-packet is obtained; wherein the number of transmissions of any one receiving line in the sub-packet can be obtained by formula (2):

[0141]

[0142] Wherein, I is the number of transmissions of the receiving line in any one of the sub-packets, prt is the receiving time of any one of the receiving lines, PRF is the pulse repetition frequency, N 发 is the number of repetitions in the short-time direction of any receiving line.

[0143] Step 603: Divide the first ratio by the number of beams to obtain the number of subpackets of the blood flow image, wherein the first ratio is obtained by dividing the total number of receiving lines by the number of transmissions of the receiving lines in any subpacket. The number of subpackets can be obtained by formula (3):

[0144]

[0145] Among them, Bag is the number of sub-packages, N line is the total number of receiving lines, I is the number of transmissions of any receiving line, N p is the number of beams.

[0146] Step 402: using the number of subpackets and the length of the blood flow image, obtaining the length of each image block;

[0147] In one embodiment, step 402 may be specifically implemented as follows: dividing the length of the blood flow image by the number of subpackets to obtain the length of each image block.

[0148] Step 403: Packetizing the blood flow image based on the length of each image block to obtain a plurality of image blocks of the blood flow image.

[0149] In one embodiment, step 403 may be specifically implemented as follows: segmenting the blood flow image according to the length of each image block to obtain a plurality of image blocks of the blood flow image.

[0150] For example, Figure 7 As shown, the description is made by taking the number of subpackets as 3 as an example. Since the length of each image block in the embodiment of the present application is obtained by equally dividing the length of the blood flow image, Figure 7 It can be seen from FIG. 1 that the multiple image blocks of the segmented blood flow image include three image blocks.

[0151] Step 204: obtaining a target image block based on the first identifier of each pixel in each image block;

[0152] In one embodiment, step 204 can be specifically implemented as follows: for any image block, counting a first number of pixels in the image block whose first identifier is a motion identifier; dividing the first number by the total number of pixels in the image block to obtain a third ratio; and determining an image block whose third ratio is not less than a third specified threshold as the target image block.

[0153] It should be noted that the third specified threshold in the embodiment of the present application can be set according to actual conditions, and the embodiment of the present application does not limit the third specified threshold.

[0154] Step 205: for any target image block, determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, wherein the speed of any pixel is obtained based on the speed image component;

[0155] Next, the method for determining the velocity distribution interval in the target image block in step 205 is described in detail. Figure 8 As shown, it is a schematic diagram of a process for determining the velocity distribution interval of each pixel in the target image block, which may include the following steps:

[0156] Step 801: according to the speed of each pixel point in the target image block, obtaining the number of pixel points corresponding to each speed;

[0157] For example, the target image block includes pixel a, pixel b, pixel c, pixel d, pixel e, pixel f, pixel g, pixel h, pixel i, and pixel k. If the speed of pixel a is v1, the speed of pixel b is v2, the speed of pixel c is v2, the speed of pixel d is v3, the speed of pixel e is v1, the speed of pixel f is v1, the speed of pixel g is v1, the speed of pixel h is v4, the speed of pixel i is v5, and the speed of pixel k is v4. Then it can be obtained that the number of pixels corresponding to speed v1 is 4. The number of pixels corresponding to speed v2 is 2. The speed of pixels corresponding to speed v3 is 1. The number of pixels corresponding to speed v4 is 2. The number of pixels corresponding to speed v5 is 1.

[0158] Step 802: for any speed, if the number of pixel points corresponding to the speed is greater than a specified number, the speed is determined as a target speed;

[0159] It should be noted that the specified number in the embodiments of the present application can be set according to actual conditions, and the embodiments of the present application do not limit the specific value of the specified number.

[0160] Step 803: sorting the target speeds in a specified order, adding two target speeds that are adjacent in position and have a difference of a specified value among the sorted target speeds to the same speed distribution set, to obtain at least one speed distribution set;

[0161] The specified order in the embodiment of the present application may be the order of the numerical values ​​from large to small, or the order of the numerical values ​​from small to large. The specified order in the embodiment of the present application may be set according to actual conditions, but the embodiment of the present application does not limit the specified order here. The specified numerical value in the embodiment of the present application may be 1 or 0.1. The specific value of the specified numerical value may be set according to actual conditions, and the embodiment of the present application does not limit the specific value of the specified numerical value here.

[0162] For example, if the target speed includes 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, then the speed distribution sets (1, 2, 3, 4, 5) and (8, 9, 10, 11, 12) are obtained. If the target speed includes 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, then the speed distribution set is (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12).

[0163] Step 804: Based on the at least one speed distribution set, obtain the at least one speed distribution interval.

[0164] For example, taking the above as an example, if the speed distribution sets are (1, 2, 3, 4, 5) and (8, 9, 10, 11, 12), two speed distribution intervals are obtained, namely, the speed distribution intervals are [1, 5] and [8, 12]. If the speed distribution set is (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12), the speed distribution interval is [1, 12].

[0165] like Fig. 9 As shown in the figure, it is a schematic diagram of the corresponding relationship between speed and the number of pixels, where the specified number is a. Fig. 9 It can be seen that the velocity distribution interval greater than the specified number a is [v a , v b ], and [v m , v n ].

[0166] Step 206: determining a target speed distribution interval by using the speeds in the at least one speed distribution interval;

[0167] In one embodiment, step 206 can be specifically implemented in the following two ways:

[0168] Method 1: If the number of the speed distribution intervals is one and the fourth ratio of the speed distribution interval is greater than a fourth specified threshold, the speed distribution interval is determined as the target speed distribution interval, wherein the fourth ratio is obtained by dividing the number of pixel points in the target image block whose speed is within the speed distribution interval and whose first identifier is a motion identifier by the total number of pixel points in the target image block whose first identifier is a motion identifier.

[0169] Method 2: If there are multiple speed distribution intervals, the speed distribution interval in which the speed standard deviation is greater than the fifth specified threshold and the speed distribution interval with the largest speed standard deviation value is determined as the target speed distribution interval, wherein the speed standard deviation in any speed distribution interval is obtained based on each speed in the speed division interval.

[0170] It should be noted that the fourth specified threshold and the fifth specified threshold in the embodiment of the present application can be set according to actual conditions, and the embodiment of the present application does not limit the fourth specified threshold and the fifth specified threshold.

[0171] Step 207: filtering the pixels in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel has a motion feature;

[0172] Step 208: Obtain a blood flow image after noise suppression according to the filtered target image blocks.

[0173] In one embodiment, step 208 may be specifically implemented as follows: fusing the filtered target image blocks and other image blocks of the multiple image blocks of the blood flow image except the target image blocks to obtain the blood flow image after noise suppression.

[0174] In order to further understand the technical solution of the present disclosure, Fig.10 A detailed description may include the following steps:

[0175] Step 1001: obtaining a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component and an energy image component;

[0176] Step 1002: for any pixel in the blood flow image, obtaining a variance component of the pixel according to the variance image component, and obtaining an energy component of the pixel according to the energy image component;

[0177] Step 1003: Determine whether the energy component of the pixel is greater than a first specified threshold, and whether the variance component of the pixel is less than a second specified threshold, if yes, execute step 1004, if no, execute step 1005;

[0178] Step 1004: Determine that the first identifier of the pixel point is the motion identifier, wherein the first identifier is used to indicate whether the pixel point is a pixel point with motion characteristics;

[0179] Step 1005: Determine that the first identifier of the pixel point is the static identifier;

[0180] Step 1006: Obtaining the number of subpackets of the blood flow image according to the total number of receiving lines in the blood flow image and the preset number of beams, wherein the receiving line is a line formed by each pixel point in the blood flow image in the longitudinal direction;

[0181] Step 1007: using the sub-packet quantity and the length of the blood flow image, obtaining the length of each image block;

[0182] Step 1008: performing packet processing on the blood flow image based on the length of each image block to obtain a plurality of image blocks of the blood flow image;

[0183] Step 1009: for any image block, counting a first number of pixels in the image block whose first identifier is a motion identifier;

[0184] Step 1010: Divide the first number by the total number of pixels in the image block to obtain a third ratio;

[0185] Step 1011: determining an image block whose third ratio is not less than a third specified threshold as the target image block;

[0186] Step 1012: according to the speed of each pixel point in the target image block, obtaining the number of pixel points corresponding to each speed;

[0187] Step 1013: for any speed, if the number of pixel points corresponding to the speed is greater than a specified number, the speed is determined as a target speed;

[0188] Step 1014: sorting the target speeds in a specified order, adding two target speeds that are adjacent in position and have a difference of a specified value among the sorted target speeds to the same speed distribution set, to obtain at least one speed distribution set;

[0189] Step 1015: obtaining the at least one speed distribution interval based on the at least one speed distribution set;

[0190] Step 1016: determining a target speed distribution interval by using the speeds in the at least one speed distribution interval;

[0191] Step 1017: filtering the pixels in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel has motion characteristics;

[0192] Step 1018: Obtain a blood flow image after noise suppression based on the filtered target image blocks.

[0193] Based on the same disclosed concept, the method for suppressing moving tissue noise in a blood flow image as described above can also be implemented by a device for suppressing moving tissue noise in a blood flow image. The effect of the device for suppressing moving tissue noise in a blood flow image is similar to that of the aforementioned method, and will not be described in detail here.

[0194] Fig.11 The figure is a schematic diagram of the structure of a device for suppressing moving tissue noise in a blood flow image according to an embodiment of the present disclosure.

[0195] like Fig.11As shown, the device 1100 for suppressing moving tissue noise in a blood flow image disclosed in the present invention may include a blood flow image acquisition module 1110, a pixel point identification determination module 1120, a packetization module 1130, a target image block determination module 1140, a velocity distribution interval determination module 1150, a target velocity distribution interval determination module 1160, a filtering module 1170 and an image processing module 1180.

[0196] A blood flow image acquisition module 1110, used to acquire a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component and an energy image component;

[0197] A pixel identification determination module 1120, configured to determine a first identification of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, wherein the first identification is used to characterize whether the pixel is a pixel with motion characteristics;

[0198] A subpackaging module 1130, configured to perform subpackaging processing on the blood flow image to obtain a plurality of image blocks of the blood flow image;

[0199] A target image block determination module 1140, configured to obtain a target image block based on a first identifier of each pixel in each image block;

[0200] a speed distribution interval determining module 1150, configured to determine, for any target image block, at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, wherein the speed of any pixel is obtained based on the speed image component; and

[0201] A target speed distribution interval determination module 1160, configured to determine a target speed distribution interval by using the speeds in the at least one speed distribution interval;

[0202] A filtering module 1170 is used to filter each pixel in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier, to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel has a motion feature;

[0203] The image processing module 1180 is used to obtain a blood flow image after noise suppression according to the filtered target image blocks.

[0204] In one embodiment, the pixel point identification determination module 1120 is specifically configured to:

[0205] For any pixel point in the blood flow image, obtain the variance component of the pixel point according to the variance image component, and obtain the energy component of the pixel point according to the energy image component;

[0206] If the energy component of the pixel point is greater than a first specified threshold, and the variance component of the pixel point is less than a second specified threshold, determining the first identifier of the pixel point as the motion identifier;

[0207] Otherwise, it is determined that the first identifier of the pixel point is the static identifier, wherein the static identifier is used to indicate that the pixel point does not have a motion feature.

[0208] In one embodiment, the subpackaging module 1130 is specifically used to:

[0209] According to the total number of receiving lines in the blood flow image and the preset number of beams, the number of sub-packets of the blood flow image is obtained, wherein the receiving line is a line formed by each pixel point in the blood flow image in the longitudinal direction;

[0210] Using the subpacket quantity and the length of the blood flow image, the length of each image block is obtained;

[0211] The blood flow image is packetized based on the length of each image block to obtain a plurality of image blocks of the blood flow image.

[0212] In one embodiment, the subpackaging module 1130 is further used to:

[0213] Determine the receiving time of any receiving line by using the acquired receiving line depth and sound velocity;

[0214] Based on the receiving time of any one of the receiving lines, the preset pulse repetition frequency and the preset number of repetitions of any one of the receiving lines in the short-time direction, obtaining the number of transmissions of any one of the receiving lines in the sub-packet;

[0215] The first ratio is divided by the number of beams to obtain the number of subpackets of the blood flow image, wherein the first ratio is obtained by dividing the total number of receiving lines by the number of transmissions of the receiving lines in any subpacket.

[0216] In one embodiment, the subpackaging module 1130 is further used to:

[0217] The receiving time of any receiving line is obtained by the following formula:

[0218]

[0219] Where prt is the receiving time of any receiving line, d is the depth of the receiving line, v 声is the speed of sound;

[0220] The obtaining the number of transmissions of any receiving line in a sub-packet based on the receiving time of any receiving line, a preset pulse repetition frequency and a preset number of repetitions of any receiving line in a short-time direction comprises:

[0221] The number of transmissions of the receiving line in any sub-packet is obtained by the following formula:

[0222]

[0223] Wherein, I is the number of transmissions of the receiving line in any one of the sub-packets, prt is the receiving time of any one of the receiving lines, PRF is the pulse repetition frequency, N 发 is the number of repetitions in the short-time direction of any receiving line.

[0224] In one embodiment, the target image block determination module 1140 is specifically configured to:

[0225] For any image block, counting a first number of pixels in the image block whose first identifier is a motion identifier;

[0226] Dividing the first number by the total number of pixels in the image block to obtain a third ratio;

[0227] An image block whose third ratio is not less than a third specified threshold is determined as the target image block.

[0228] In one embodiment, the speed distribution interval determination module 1150 is specifically used to:

[0229] According to the speed of each pixel point in the target image block, the number of pixel points corresponding to each speed is obtained;

[0230] For any speed, if the number of pixel points corresponding to the speed is greater than a specified number, the speed is determined as the target speed;

[0231] Sorting the target speeds in a specified order, adding two target speeds that are adjacent in position and have a difference of a specified value among the sorted target speeds to the same speed distribution set, to obtain at least one speed distribution set;

[0232] Based on the at least one speed distribution set, the at least one speed distribution interval is obtained.

[0233] In one embodiment, the target speed distribution interval determination module 1160 is specifically configured to:

[0234] If the number of the speed distribution intervals is one and a fourth ratio of the speed distribution interval is greater than a fourth specified threshold, the speed distribution interval is determined as the target speed distribution interval, wherein the fourth ratio is obtained by dividing the number of pixel points in the target image block whose speed is within the speed distribution interval and whose first identifier is a motion identifier by the total number of pixel points in the target image block whose first identifier is a motion identifier;

[0235] If there are multiple speed distribution intervals, the speed distribution interval in which the speed standard deviation is greater than the fifth specified threshold and the speed distribution interval with the largest speed standard deviation is determined as the target speed distribution interval, wherein the speed standard deviation in any speed distribution interval is obtained based on each speed in the speed division interval.

[0236] After introducing a method and apparatus for suppressing moving tissue noise in a blood flow image according to an exemplary embodiment of the present disclosure, next, an ultrasound device according to another exemplary embodiment of the present disclosure is introduced.

[0237] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0238] In some possible implementations, the ultrasound device according to the present disclosure may include at least one processor and at least one computer storage medium. The computer storage medium stores program code, and when the program code is executed by the processor, the processor executes the steps of the method for suppressing moving tissue noise in a blood flow image according to various exemplary embodiments of the present disclosure described above in this specification. For example, the processor may execute the following steps: Figure 2 Steps 201-208 shown in .

[0239] like Fig.12As shown, it is a schematic diagram of the ultrasound device provided in the present application. The ultrasound device 1200 includes: a processor 1202, a communication interface 1203, and a memory 1201. Optionally, the ultrasound device 1200 may also include a communication line 1204. Among them, the communication interface 1203, the processor 1202 and the memory 1201 may be interconnected through the communication line 1204; the communication line 1204 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication line 1204 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.12 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0240] Processor 1202 may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0241] The communication interface 1203 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), wired access networks, etc.

[0242] The memory 1201 may be a ROM or other types of static storage devices that can store static information and instructions, a RAM or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory may exist independently and be connected to the processor via a communication line 1204. The memory may also be integrated with the processor.

[0243] The memory 1201 is used to store computer-executable instructions for executing the solution of the present application, and the execution is controlled by the processor 1202. The processor 1202 is used to execute the computer-executable instructions stored in the memory 1201, thereby realizing the method for suppressing moving tissue noise in blood flow images provided in the above embodiment of the present application.

[0244] Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application code, which is not specifically limited in the embodiments of the present application.

[0245] In some possible embodiments, various aspects of a method for suppressing moving tissue noise in a blood flow image provided by the present disclosure may also be implemented in the form of a program product, which includes program code. When the program product is run on a computer device, the program code is used to enable the computer device to execute the steps of the method for suppressing moving tissue noise in a blood flow image according to various exemplary embodiments of the present disclosure described above in this specification.

[0246] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access computer storage medium (RAM), a read-only computer storage medium (ROM), an erasable programmable read-only computer storage medium (EPROM or flash memory), an optical fiber, a portable compact disk read-only computer storage medium (CD-ROM), an optical computer storage medium, a magnetic computer storage medium, or any suitable combination of the above.

[0247] The program product for suppressing moving tissue noise in a blood flow image of an embodiment of the present disclosure may adopt a portable compact disk read-only computer storage medium (CD-ROM) and include program code, and may be run on an ultrasound device. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus, or device.

[0248] The readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, wherein the readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0249] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0250] Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user ultrasound device, partially on the user device, as a separate software package, partially on the user ultrasound device and partially on a remote ultrasound device, or entirely on a remote ultrasound device or server. In the case of a remote ultrasound device, the remote ultrasound device may be connected to the user ultrasound device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external ultrasound device (e.g., via the Internet using an Internet service provider).

[0251] It should be noted that although several modules of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules to be embodied.

[0252] In addition, although the operations of the disclosed method are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0253] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk computer storage media, CD-ROM, optical computer storage media, etc.) containing computer-usable program codes.

[0254] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0255] These computer program instructions may also be stored in a computer-readable computer storage medium that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable computer storage medium produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0256] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0257] Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A method for suppressing moving tissue noise in a blood flow image, characterized in that: The method comprises: Acquire a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component; Determining a first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, wherein the first identifier is used to characterize whether the pixel is a pixel with motion characteristics; performing packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image; Based on the first identifier of each pixel in each image block, a target image block is obtained; for any target image block, determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, wherein the speed of any pixel is obtained based on the speed image component; and Determining a target speed distribution interval by using the speeds in the at least one speed distribution interval; Filtering each pixel point in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel point has a motion feature; A blood flow image with noise suppressed is obtained according to each filtered target image block.

2. The method according to claim 1, characterized in that The step of determining a first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image includes: For any pixel point in the blood flow image, obtain the variance component of the pixel point according to the variance image component, and obtain the energy component of the pixel point according to the energy image component; If the energy component of the pixel point is greater than a first specified threshold, and the variance component of the pixel point is less than a second specified threshold, determining the first identifier of the pixel point as the motion identifier; Otherwise, it is determined that the first identifier of the pixel point is the static identifier, wherein the static identifier is used to indicate that the pixel point does not have a motion feature.

3. The method according to claim 1, characterized in that The step of performing packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image includes: According to the total number of receiving lines in the blood flow image and the preset number of beams, the number of sub-packets of the blood flow image is obtained, wherein the receiving line is a line formed by each pixel point in the blood flow image in the longitudinal direction; Using the subpacket quantity and the length of the blood flow image, the length of each image block is obtained; The blood flow image is packetized based on the length of each image block to obtain a plurality of image blocks of the blood flow image.

4. The method according to claim 3, characterized in that The obtaining the number of subpackets of the blood flow image according to the total number of receiving lines in the blood flow image and the preset number of beams includes: Determine the receiving time of any receiving line by using the acquired receiving line depth and sound velocity; Based on the receiving time of any one of the receiving lines, the preset pulse repetition frequency and the preset number of repetitions of any one of the receiving lines in the short-time direction, obtaining the number of transmissions of any one of the receiving lines in the sub-packet; The first ratio is divided by the number of beams to obtain the number of subpackets of the blood flow image, wherein the first ratio is obtained by dividing the total number of receiving lines by the number of transmissions of the receiving lines in any subpacket.

5. The method according to claim 4, characterized in that The method of determining the receiving time of any receiving line by using the acquired receiving line depth and sound velocity includes: The receiving time of any receiving line is obtained by the following formula: Where prt is the receiving time of any receiving line, d is the depth of the receiving line, v 声 is the speed of sound; The obtaining the number of transmissions of any receiving line in a sub-packet based on the receiving time of any receiving line, a preset pulse repetition frequency and a preset number of repetitions of any receiving line in a short-time direction comprises: The number of transmissions of the receiving line in any sub-packet is obtained by the following formula: Wherein, I is the number of transmissions of the receiving line in any one of the sub-packets, prt is the receiving time of any one of the receiving lines, PRF is the pulse repetition frequency, N 发 is the number of repetitions in the short-time direction of any receiving line.

6. The method according to claim 1, characterized in that The step of obtaining a target image block based on the first identifier of each pixel in each image block includes: For any image block, counting a first number of pixels in the image block whose first identifier is a motion identifier; Dividing the first number by the total number of pixels in the image block to obtain a third ratio; An image block whose third ratio is not less than a third specified threshold is determined as the target image block.

7. The method according to claim 1, characterized in that The determining, according to the speed of each pixel in the target image block, at least one speed distribution interval of each pixel in the target image block comprises: According to the speed of each pixel point in the target image block, the number of pixel points corresponding to each speed is obtained; For any speed, if the number of pixel points corresponding to the speed is greater than a specified number, the speed is determined as the target speed; Sorting the target speeds in a specified order, adding two target speeds that are adjacent in position and have a difference of a specified value among the sorted target speeds to the same speed distribution set, to obtain at least one speed distribution set; Based on the at least one speed distribution set, the at least one speed distribution interval is obtained.

8. The method according to claim 1, characterized in that The step of determining a target speed distribution interval by using each speed in the at least one speed distribution interval comprises: If the number of the speed distribution intervals is one and a fourth ratio of the speed distribution interval is greater than a fourth specified threshold, the speed distribution interval is determined as the target speed distribution interval, wherein the fourth ratio is obtained by dividing the number of pixel points in the target image block whose speed is within the speed distribution interval and whose first identifier is a motion identifier by the total number of pixel points in the target image block whose first identifier is a motion identifier; If there are multiple speed distribution intervals, the speed distribution interval in which the speed standard deviation is greater than the fifth specified threshold and the speed distribution interval with the largest speed standard deviation is determined as the target speed distribution interval, wherein the speed standard deviation in any speed distribution interval is obtained based on each speed in the speed division interval.

9. An ultrasonic device, characterized in that: The method comprises a memory and a processor, wherein the processor and the memory are connected via a bus; The memory stores a computer program, and the processor is configured to perform the following operations based on the computer program: Acquire a blood flow image at the current moment after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component; Determining a first identifier of each pixel in the blood flow image based on the variance image component and the energy image component of the blood flow image, wherein the first identifier is used to characterize whether the pixel is a pixel with motion characteristics; performing packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image; Based on the first identifier of each pixel in each image block, a target image block is obtained; for any target image block, determining at least one speed distribution interval of each pixel in the target image block according to the speed of each pixel in the target image block, wherein the speed of any pixel is obtained based on the speed image component; and Determining a target speed distribution interval by using the speeds in the at least one speed distribution interval; Filtering each pixel point in the target image block whose speed is within the target speed distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to indicate that the pixel point has a motion feature; A blood flow image with noise suppressed is obtained according to each filtered target image block.

10. The ultrasonic device according to claim 9, characterized in that The processor executes the variance image component and the energy image component based on the blood flow image to determine the first identifier of each pixel in the blood flow image, and is specifically configured as follows: For any pixel point in the blood flow image, obtain the variance component of the pixel point according to the variance image component, and obtain the energy component of the pixel point according to the energy image component; If the energy component of the pixel point is greater than a first specified threshold, and the variance component of the pixel point is less than a second specified threshold, determining the first identifier of the pixel point as the motion identifier; Otherwise, it is determined that the first identifier of the pixel point is the static identifier, wherein the static identifier is used to indicate that the pixel point does not have a motion feature.

Images