Method of suppressing motion tissue noise in blood flow images and ultrasound device

Abstract

The present disclosure provides a method and an ultrasound device for suppressing motion tissue noise in a blood flow image. The method for filtering motion tissue noise in a blood flow image includes: determining a first identifier of each pixel point in the blood flow image based on a variance image component and an energy image component in the blood flow image, wherein the first identifier is used to represent whether the pixel point is a pixel point with motion characteristics; obtaining a target image block based on the first identifier of each pixel point in a plurality of image blocks obtained by dividing the blood flow image; determining a velocity distribution interval of each pixel point in the target image block according to the velocity of each pixel point in the target image block, wherein the velocity of any pixel point is obtained based on a velocity image component; determining a target velocity distribution interval through each velocity in the velocity distribution interval; and filtering each pixel point in the target image block whose velocity is in the target velocity distribution interval and whose first identifier is a motion identifier to obtain a blood flow image with suppressed noise.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, in particular to a method for suppressing motion tissue noise in blood flow images and an ultrasound device. BACKGROUND

[0002] The ultrasound blood flow image mainly tracks and detects various index parameters of human body blood flow signals in real time by using the Doppler effect. In an ideal case, the relative displacement of the blood flow signal to the probe causes the Doppler frequency shift of the ultrasound wave to be received by the probe again to obtain the information of the blood flow signal.

[0003] However, in the actual detection process, the heart beating, breathing movement, and probe movement, which cannot be avoided, will also cause the relative motion of the muscle tissue to the probe. The received blood flow signal and the motion tissue signal are mixed together, which will interfere with the blood flow signal and result in a low quality of the obtained ultrasound blood flow image, thereby reducing the accuracy of clinical diagnosis. SUMMARY

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

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

[0006] obtaining a blood flow image at a current time after wall filtering, wherein the blood flow image comprises a velocity image component, a variance image component, and an energy image component;

[0007] determining a first identifier of each pixel point 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 represent whether the pixel point is a pixel point with motion characteristics;

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

[0009] obtaining a target image block based on the first identifier of each pixel point in each image block;

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

[0011] determining a target velocity distribution interval through each velocity in the at least one velocity distribution interval.

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

[0013] obtaining a blood flow image after noise suppression according to the filtered target image blocks.

[0014] In the embodiment, the first identifier of each pixel point in the blood flow image is determined based on a variance image component and an energy image component of the blood flow image, the first identifier is used to represent whether the pixel point is a pixel point having a motion feature, and each image block of the blood flow image obtained after the blood flow image is divided into packets is filtered according to the first identifier of each pixel point in the image block, to obtain a target image block. Then, for any one target image block, at least one speed distribution interval of each pixel point in the target image block is determined according to the speed of each pixel point in the target image block. Each speed in the at least one speed distribution interval is used to determine a target speed distribution interval, and each pixel point in the target image block whose speed is in the target speed distribution interval and whose first identifier is the motion identifier is filtered, to obtain a filtered target image block. A blood flow image after noise suppression is obtained according to the filtered target image blocks. Thus, in the embodiment, the pixel points having a motion feature are first identified based on the variance image component and the energy image component of the blood flow image, and then the speed distribution interval of each pixel point of the image block corresponding to the pixel point having a motion feature is analyzed, to obtain the part where the motion tissue noise in the blood flow image is located and to filter, to obtain the blood flow image after noise suppression.

[0015] In one embodiment, the first identifier of each pixel point in the blood flow image is determined based on the variance image component and the energy image component of the blood flow image, including:

[0016] for any one pixel point in the blood flow image, obtaining a variance component of the pixel point according to the variance image component, and obtaining an 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 value and the variance component of the pixel point is less than a second specified threshold value, then the first identifier of the pixel point is determined as the motion identifier;

[0018] otherwise, the first identifier of the pixel point is determined as the still identifier, wherein the still identifier is used to represent that the pixel point does not have a motion feature.

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

[0020] In one embodiment, the blood flow image is divided into a plurality of image blocks by the following steps.

[0021] The number of the divided packages of the blood flow image is obtained according to the total number of the receiving lines in the blood flow image and the preset number of beams, wherein the receiving line is a line composed of each pixel point in the blood flow image in the longitudinal direction.

[0022] The length of each image block is obtained by using the number of the divided packages and the length of the blood flow image.

[0023] The blood flow image is divided into a plurality of image blocks based on the length of each image block.

[0024] In the embodiment, the number of the divided packages of the blood flow image is obtained according to the total number of the receiving lines in the blood flow image and the preset number of beams, and the blood flow image is divided into a plurality of image blocks based on the number of the divided packages, so as to ensure the accuracy of the obtained plurality of image blocks of the blood flow image.

[0025] In one embodiment, the number of the divided packages of the blood flow image is obtained according to the total number of the receiving lines in the blood flow image and the preset number of beams, and the blood flow image is divided into a plurality of image blocks based on the number of the divided packages, so as to ensure the accuracy of the obtained plurality of image blocks of the blood flow image.

[0026] The receiving time of any one receiving line is determined by using the obtained depth and speed of the receiving line.

[0027] The number of transmissions of the receiving line in any one divided package is obtained based on the receiving time of any one receiving line, the preset pulse repetition frequency and the preset number of repetitions of the short-time direction of any one receiving line.

[0028] The number of the divided packages of the blood flow image is obtained by dividing the first ratio by the number of beams, wherein the first ratio is obtained by dividing the total number of the receiving lines by the number of transmissions of the receiving line in any one divided package.

[0029] In one embodiment, the receiving time of any one receiving line is determined by using the obtained depth and speed of the receiving line.

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

[0031]

[0032] wherein prt is the receiving time of any one receiving line, d is the depth of the receiving line, and v is the speed of the receiving line.声 is the sound speed;

[0033] The transmission number of the receiving line in the arbitrary sub-packet is obtained based on the receiving time of the arbitrary receiving line, the preset pulse repetition frequency, and the preset repetition number of the short-time direction of the arbitrary receiving line, and includes:

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

[0035]

[0036] wherein I is the transmission number of the receiving line in the arbitrary sub-packet, prt is the receiving time of the arbitrary receiving line, PRF is the pulse repetition frequency, N 发 is the repetition number of the short-time direction of the arbitrary receiving line.

[0037] In an embodiment, the target image block is obtained based on the first identifiers of the pixel points in each image block, and includes:

[0038] For any image block, the first number of the pixel points with the first identifier as the motion identifier in the image block is counted.

[0039] The third ratio value is obtained by dividing the first number by the total number of the pixel points in the image block.

[0040] The image block with the third ratio value not less than the third specified threshold value is determined as the target image block.

[0041] In this embodiment, the target image block is determined by comparing the third ratio value obtained by dividing the first number of the pixel points with the first identifier as the motion identifier in the image block by the total number of the pixel points in the image block with the third specified threshold value, which ensures the accuracy of the determined target image block.

[0042] In an embodiment, at least one speed distribution interval of the pixel points in the target image block is determined according to the speeds of the pixel points in the target image block, and includes:

[0043] The number of the pixel points corresponding to each speed is obtained according to the speeds of the pixel points in the target image block.

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

[0045] The target speeds are sorted in a specified order, two target speeds with adjacent positions and a specified difference value in the sorted target speeds are added to the same speed distribution set, and at least one speed distribution set is obtained.

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

[0047] In one embodiment, the target velocity distribution interval is determined by each velocity in the at least one velocity distribution interval, comprising:

[0048] If the number of the velocity distribution intervals is one, and a fourth ratio of the velocity distribution interval is greater than a fourth specified threshold, the velocity distribution interval is determined as the target velocity distribution interval, wherein the fourth ratio is obtained by dividing the number of each pixel point in the target image block with velocity in the velocity distribution interval and the first identification as the motion identification by the total number of each pixel point in the target image block with the first identification as the motion identification;

[0049] If the number of the velocity distribution intervals is more than one, the velocity distribution interval with the largest value of velocity standard deviation greater than a fifth specified threshold is determined as the target velocity distribution interval, wherein the velocity standard deviation in any one velocity distribution interval is obtained based on each velocity in the velocity distribution interval.

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

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

[0052] Obtain a blood flow image of a current time after wall filtering, wherein the blood flow image comprises a velocity image component, a variance image component and an energy image component;

[0053] Based on the variance image component and the energy image component of the blood flow image, determine a first identification of each pixel point in the blood flow image, wherein the first identification is used to represent whether the pixel point is a pixel point with motion characteristics;

[0054] The blood flow image is processed to obtain a plurality of image blocks of the blood flow image;

[0055] Based on the first identification of each pixel point in each image block, obtain a target image block;

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

[0057] determining a target velocity distribution interval by each velocity in the at least one velocity distribution interval;

[0058] filtering each pixel point in the target image block with a velocity in the target velocity distribution interval and a first identifier being a motion identifier, to obtain a filtered target image block, wherein the motion identifier is used to represent that the pixel point has a motion feature;

[0059] obtaining a blood flow image after noise suppression according to the filtered target image blocks.

[0060] In one embodiment, the processor performing the determining of the first identifier of each pixel point in the blood flow image based on the variance image component and the energy image component of the blood flow image is specifically configured to:

[0061] for any one pixel point in the blood flow image, obtaining a variance component of the pixel point according to the variance image component, and obtaining an 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 value and the variance component of the pixel point is less than a second specified threshold value, determining that the first identifier of the pixel point is the motion identifier;

[0063] otherwise, determining that the first identifier of the pixel point is a still identifier, wherein the still identifier is used to represent that the pixel point does not have a motion feature.

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

[0065] obtaining a packet number of the blood flow image according to a total number of receiving lines in the blood flow image and a preset beam number, wherein the receiving line is a line composed of each pixel point in the blood flow image in a longitudinal direction;

[0066] obtaining a length of each image block by using the packet number and a length of the blood flow image;

[0067] 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.

[0068] In one embodiment, the processor performing the obtaining of the packet number of the blood flow image according to the total number of receiving lines in the blood flow image and the preset beam number is specifically configured to:

[0069] determining a receiving time of any one receiving line by using the obtained depth of the receiving line and the sound speed.

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

[0071] dividing the first ratio by the number of beams to obtain the number of sub-packets 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 line in the arbitrary one sub-packet.

[0072] In one embodiment, the processor performing the determination of the receiving time of the arbitrary one receiving line based on the obtained depth of the receiving line and the sound speed is specifically configured to:

[0073] obtaining the receiving time of the arbitrary one receiving line by the following formula:

[0074]

[0075] wherein prt is the receiving time of the arbitrary one receiving line, d is the depth of the receiving line, v 声 is the sound speed;

[0076] obtaining the number of transmissions of the receiving line in the arbitrary one sub-packet based on the receiving time of the arbitrary one receiving line, the preset pulse repetition frequency, and the preset number of repetitions of the short-time direction of the arbitrary one receiving line, includes:

[0077] obtaining the number of transmissions of the receiving line in the arbitrary one sub-packet by the following formula:

[0078]

[0079] wherein I is the number of transmissions of the receiving line in the arbitrary one sub-packet, prt is the receiving time of the arbitrary one receiving line, PRF is the pulse repetition frequency, and N 发 is the number of repetitions of the short-time direction of the arbitrary one receiving line.

[0080] In one embodiment, the processor performing the obtaining of the target image block based on the first identifiers of the pixel points in each image block is specifically configured to:

[0081] counting, for an arbitrary one image block, a first number of pixel points in the image block with the first identifier being a motion identifier;

[0082] dividing the first number by a total number of pixel points in the image block to obtain a third ratio;

[0083] determining, as the target image block, the image block with the third ratio being not less than a third specified threshold.

[0084] In an embodiment, the processor performing the determining the at least one velocity distribution interval according to the velocities of the pixels in the target image block is specifically configured to:

[0085] obtaining the number of the pixels corresponding to each velocity according to the velocities of the pixels in the target image block;

[0086] for any velocity, if the number of the pixels corresponding to the velocity is greater than a specified number, determining the velocity as a target velocity;

[0087] sorting the target velocities in a specified order, adding two target velocities which are adjacent in position and have a specified difference value in the sorted target velocities to a same velocity distribution set, and obtaining at least one velocity distribution set;

[0088] obtaining the at least one velocity distribution interval based on the at least one velocity distribution set.

[0089] In an embodiment, the processor performing the determining the target velocity distribution interval through the velocities in the at least one velocity distribution interval is specifically configured to:

[0090] if the number of the velocity distribution intervals is one and a fourth ratio of the velocity distribution interval is greater than a fourth specified threshold, determining the velocity distribution interval as the target velocity distribution interval, wherein the fourth ratio is obtained by dividing the number of the pixels in the target image block having a velocity in the velocity distribution interval and having a first label as a motion label by the total number of the pixels in the target image block having the first label as the motion label;

[0091] if the number of the velocity distribution intervals is multiple, determining a velocity distribution interval in which a velocity standard deviation is greater than a fifth specified threshold and has a maximum value as the target velocity distribution interval, wherein the velocity standard deviation in any velocity distribution interval is obtained based on the velocities in the velocity distribution interval.

[0092] According to a third aspect provided in an embodiment of the present disclosure, a computer storage medium is provided, which stores a computer program for executing the method according to the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0093] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and for those skilled in the art, other drawings can be obtained based on these drawings without creative labor.

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

[0095] Figure 2 A schematic diagram of a method for suppressing motion tissue noise in a blood flow image according to an embodiment of the present disclosure;

[0096] Figure 3 A schematic diagram of a method for 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 method for determining a plurality of image blocks of a blood flow image according to an embodiment of the present disclosure;

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

[0099] Figure 6 A schematic diagram of a method for determining a number of packets of a blood flow image according to an embodiment of the present disclosure;

[0100] Figure 7 A schematic diagram of a method for determining a number of packets of a blood flow image according to an embodiment of the present disclosure;

[0101] Figure 8 A schematic diagram of a method for determining a number of packets of a blood flow image according to an embodiment of the present disclosure;

[0102] Figure 9 A schematic diagram of a method for determining a number of packets of a blood flow image according to an embodiment of the present disclosure;

[0103] Figure 10 A schematic diagram of a method for suppressing motion tissue noise in a blood flow image according to an embodiment of the present disclosure;

[0104] Figure 11 A schematic diagram of a method for suppressing motion tissue noise in a blood flow image according to an embodiment of the present disclosure;

[0105] Figure 12 A schematic diagram of a method for suppressing motion tissue noise in a blood flow image according to an embodiment of the present disclosure; DETAILED DESCRIPTION

[0106] To make the purposes, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are some but not all of the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present disclosure.

[0107] The term “and / or” in the embodiments of the present disclosure describes the association relationship of the associated objects, and indicates that there can be three relationships, for example, A and / or B can indicate that A exists alone, A and B exist simultaneously, and B exists alone. The character “ / ” generally indicates that the associated objects before and after it are in an “or” relationship.

[0108] The application scenarios described in the embodiments of the present disclosure are used 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. A person of ordinary skill in the art can know that, as new application scenarios appear, 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, in the actual detection process, the heart beat, breathing movement, and probe movement and the like, which cannot be avoided, will cause the muscle tissue to also have relative movement relative to the probe. The received blood flow signal and tissue signal are mixed together, causing interference to the blood flow signal, resulting in that the quality of the obtained ultrasonic blood flow image is low, and the accuracy of clinical diagnosis is reduced.

[0110] Therefore, the present disclosure provides a method for suppressing motion tissue noise in a blood flow image. The first identifier of each pixel point 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 being used to represent whether the pixel point is a pixel point with motion characteristics, and each image block of the blood flow image obtained after the blood flow image is divided into multiple image blocks is filtered according to the first identifier of each pixel point in the image block to obtain a target image block. Then, for any one target image block, at least one velocity distribution interval of each pixel point in the target image block is determined according to the velocity of each pixel point in the target image block. The target velocity distribution interval is determined through each velocity in the at least one velocity distribution interval, and each pixel point in the target image block whose velocity is in the target velocity distribution interval and whose first identifier is a motion identifier is filtered to obtain a filtered target image block. The blood flow image after noise suppression is obtained according to each filtered target image block. Thus, in the embodiments of the present application, the pixel points with motion characteristics are first identified based on the variance image component and the energy image component of the blood flow image, and then the velocity distribution interval of each pixel point in the image block corresponding to the pixel point with motion characteristics is analyzed to obtain the position of the motion tissue noise in the blood flow image and to filter the motion tissue noise, thereby obtaining the blood flow image after noise suppression. In the following, the scheme of the present disclosure will be introduced in detail in combination with the drawings.

[0111] As shown in Figure 1 , an application scenario of a method for suppressing motion tissue noise in a blood flow image, the application scenario including an ultrasonic device 110 and a terminal device 120.

[0112] In a possible application scenario, the ultrasound device 110 acquires a wall-filtered current moment blood flow image, where the blood flow image includes a velocity image component, a variance image component, and an energy image component; and determines a first identifier of each pixel point in the blood flow image based on the variance image component and the energy image component of the blood flow image, where the first identifier is used to represent whether the pixel point is a pixel point with motion characteristics. Then the ultrasound device 110 performs packet processing on the blood flow image to obtain a plurality of image blocks of the blood flow image; and obtains a target image block based on the first identifier of each pixel point in each image block. Then the ultrasound device 110 determines at least one velocity distribution interval of each pixel point in the target image block according to the velocity of each pixel point in the target image block, where the velocity of any one pixel point is obtained based on the velocity image component; and determines a target velocity distribution interval through each velocity in the at least one velocity distribution interval; and filters each pixel point in the target image block whose velocity is in the target velocity distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, where the motion identifier is used to represent that the pixel point has motion characteristics. Finally, the ultrasound device 110 obtains a noise-suppressed blood flow image according to the filtered target image blocks, and displays the noise-suppressed blood flow image through the terminal device 120.

[0113] wherein, Figure 1 The ultrasound device 110 and the terminal device 120 can interact information through a communication network, where a communication mode adopted by the communication network can be divided into a wireless communication mode or a wired communication mode.

[0114] For example, the ultrasound device 110 can access a network through a cellular mobile communication technology and communicate with the terminal device 120, where the cellular mobile communication technology includes, for example, a 5th Generation Mobile Networks (5G) technology.

[0115] Optionally, the ultrasound device 110 can access a network through a short-range wireless communication mode and communicate with the terminal device 120, where the short-range wireless communication mode includes, for example, a Wireless Fidelity (Wi-Fi) technology.

[0116] The description in this application focuses on a single ultrasound device 110 and a single terminal device 120. However, those skilled in the art should understand that the illustrated ultrasound device 110 and terminal device 120 are intended to illustrate the operation of the ultrasound device 110 and terminal device 120 involved in the technical solutions of this application, and do not imply any limitation on the number, type, or location of the ultrasound device 110 and terminal device 120. It should be noted that adding additional modules to or removing individual modules from the illustrated environment will not change the underlying concept of the exemplary embodiments of this application.

[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 scenarios shown are also applicable to any device that can suppress noise in moving tissues in blood flow images.

[0118] The following describes an exemplary embodiment of the method for suppressing noise in moving tissues in blood flow images, in conjunction with the application scenarios described above and 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 this application, and the implementation of this application is not limited in any way in this respect.

[0119] like Figure 2 The diagram shown is a flowchart illustrating the method for suppressing noise in moving tissue images according to this disclosure, which may include the following steps:

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

[0121] In this embodiment, 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. The variance image component includes the energy variance of each pixel in the blood flow image.

[0122] Step 202: Based on the variance image component and the energy image component of the blood flow image, determine the 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;

[0123] The method for determining the first identifier of each pixel in the blood flow image in step 202 will be explained in detail below. For example... Figure 3 The diagram shown illustrates a flowchart for determining the first identifier of each pixel in a blood flow image, which may include the following steps:

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

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

[0126] Step 302: determining whether the energy component of the pixel point is greater than a first specified threshold; if yes, executing step 303, and if no, executing step 305;

[0127] Step 303: determining whether the variance component of the pixel point is less than a second specified threshold; if yes, executing step 304, and if no, executing step 305;

[0128] Step 304: determining the first identification of the pixel point as the motion identification;

[0129] Step 305: determining the first identification of the pixel point as the static identification, wherein the static identification is used to represent that the pixel point has no motion feature.

[0130] It should be noted that the first specified threshold and the second specified threshold 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 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 plurality of image blocks of the blood flow image obtained in step 203 will be described in detail, as shown in FIG. 3, which is a flow diagram for determining the plurality of image blocks of the blood flow image, and can include the following steps: Figure 4

[0133] Step 401: obtaining a packet number of the blood flow image according to a total number of receiving lines in the blood flow image and a preset beam number, wherein the receiving line is a line composed of each pixel point in the blood flow image in a longitudinal direction;

[0134] As shown in FIG. 4, which is a flow diagram for determining the packet number of the blood flow image, and can include the following steps: Figure 5 ​As shown in the blood flow image, each receiving line is a line composed of pixel points in the longitudinal direction. 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] As shown in the blood flow image, each receiving line is a line composed of pixel points in the longitudinal direction. 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. Figure 6 As shown in the blood flow image, each receiving line is a line composed of pixel points in the longitudinal direction. 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.

[0136] Step 601: determining the receiving time of any one receiving line by using the obtained depth of the receiving line and the sound speed;

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

[0138]

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

[0140] Step 602: obtaining the transmission times of the receiving lines in any one packet based on the receiving time of any one receiving line, the preset pulse repetition frequency and the preset repetition times of the short-time direction of any one receiving line; wherein the transmission times of the receiving lines in any one packet can be obtained by formula (2):

[0141]

[0142] Wherein, I is the transmission times of the receiving lines in any one packet, prt is the receiving time of any one receiving line, PRF is the pulse repetition frequency, N 发 is the repetition times of the short-time direction of any one receiving line.

[0143] Step 603: dividing the first ratio by the beam quantity to obtain the packet quantity of the blood flow image, wherein the first ratio is obtained by dividing the total number of the receiving lines by the transmission times of the receiving lines in any one packet; wherein the packet quantity can be obtained by formula (3):

[0144]

[0145] Wherein, Bag is the packet quantity, N line is the total number of the receiving lines, I is the transmission times of any one receiving line, and N p is the beam quantity.

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

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

[0148] Step 403: packet processing 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 can be implemented as: 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, as shown in FIG. 4, a packet number of 3 is taken 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, it can be seen from FIG. 4 that the plurality of image blocks of the segmented blood flow image includes three image blocks. Figure 7 Figure 7

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

[0152] In one embodiment, step 204 can be implemented as: for any one image block, counting a first number of pixel points with the first identifier of motion in the image block; dividing the first number by the total number of pixel points in the image block to obtain a third ratio; and determining the image block with the third ratio 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 one target image block, determining at least one speed distribution interval of each pixel point in the target image block according to the speed of each pixel point in the target image block, wherein the speed of any one pixel point is obtained based on the speed image component;

[0155] Next, the method of determining the speed distribution interval in the target image block in step 205 will be described in detail. As shown in FIG. 5, it is a flowchart for determining the speed distribution interval of each pixel point in the target image block, which can include the following steps: Figure 8

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

[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. The number of pixels corresponding to the speed v1 is 4. The number of pixels corresponding to the speed v2 is 2. The number of pixels corresponding to the speed v3 is 1. The number of pixels corresponding to the speed v4 is 2. The number of pixels corresponding to the speed v5 is 1.

[0158] Step 802: For any speed, if the number of pixels 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 embodiment of the present application can be set according to actual conditions, and the embodiment of the present application does not limit the specific value of the specified number.

[0160] Step 803: The target speeds are sorted in a specified order, two target speeds with adjacent positions and a specified value difference in the sorted target speeds are added to the same speed distribution set, and at least one speed distribution set is obtained.

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

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

[0163] Step 804: At least one speed distribution interval is obtained based on the at least one speed distribution set.

[0164] For example, as mentioned earlier, if the velocity distribution sets are (1, 2, 3, 4, 5) and (8, 9, 10, 11, 12), then we obtain two velocity distribution intervals, namely [1, 5] and [8, 12]. If the velocity distribution set is (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12), then the velocity distribution interval is [1, 12].

[0165] like Figure 9 The diagram shows the relationship between speed and the number of pixels, where the specified number is 'a'. Figure 9 As can be seen from this, the velocity distribution range greater than the specified quantity 'a' is [v a v b ], and [v m v n ].

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

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

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

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

[0170] It should be noted that the fourth and fifth specified thresholds in this application embodiment can be set according to the actual situation, and this application embodiment does not limit the fourth and fifth specified thresholds.

[0171] Step 207: Filter the pixels in the target image block whose velocities are within the target velocity distribution range and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to characterize that the pixel has motion features;

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

[0173] In one embodiment, step 208 can be implemented as: fusing the filtered target image blocks and image blocks other than the target image blocks in the blood flow image to obtain the blood flow image after noise suppression.

[0174] For further understanding of the technical solutions of the present disclosure, the following will be described in detail Figure 10 with reference to the accompanying drawings.

[0175] Step 1001: obtaining a blood flow image at a current time 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 point in the blood flow image, obtaining a variance component of the pixel point according to the variance image component, and obtaining an energy component of the pixel point according to the energy image component;

[0177] Step 1003: determining whether 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, if yes, executing step 1004, if not, executing step 1005;

[0178] Step 1004: determining a first identifier of the pixel point as the motion identifier, wherein the first identifier is used to represent whether the pixel point is a pixel point with motion characteristics;

[0179] Step 1005: determining the first identifier of the pixel point as the static identifier;

[0180] Step 1006: obtaining a number of sub-packets of the blood flow image according to a total number of receiving lines in the blood flow image and a preset number of beams, wherein the receiving line is a line composed of pixel points in the blood flow image in the longitudinal direction;

[0181] Step 1007: obtaining a length of each image block by using the number of sub-packets and a length of the blood flow image;

[0182] Step 1008: performing sub-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 one image block, counting a first number of pixel points with the first identifier as the motion identifier in the image block;

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

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

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

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

[0188] Step 1014: sorting the target speeds in a specified order, adding two target speeds with adjacent positions and a specified difference value in the sorted target speeds to a 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 through each speed in the at least one speed distribution interval;

[0191] Step 1017: filtering each pixel in the target image block with the speed in the target speed distribution interval and a first identifier as a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to represent that the pixel has a motion feature;

[0192] Step 1018: obtaining a blood flow image after noise suppression according to the filtered target image blocks.

[0193] Based on the same disclosure concept, the method for suppressing motion tissue noise in a blood flow image as described above can also be implemented by a device for suppressing motion tissue noise in a blood flow image. The device for suppressing motion tissue noise in a blood flow image has similar effects to the above-mentioned method, and will not be described here.

[0194] Figure 11 FIG. 1 is a structural schematic diagram of a device for suppressing motion tissue noise in a blood flow image according to an embodiment of the present disclosure.

[0195] As Figure 11As shown, the device 1100 for suppressing motion tissue noise in a blood flow image according to the present disclosure can 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] The blood flow image acquisition module 1110 is configured to acquire a blood flow image of a current time after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component.

[0197] The pixel point identification determination module 1120 is configured to determine a first identification of each pixel point 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 represent whether a pixel point is a pixel point with motion characteristics.

[0198] The packetization module 1130 is configured to perform packetization processing on the blood flow image to obtain a plurality of image blocks of the blood flow image.

[0199] The target image block determination module 1140 is configured to obtain a target image block based on the first identification of each pixel point in each image block.

[0200] The velocity distribution interval determination module 1150 is configured to, for any one target image block, determine at least one velocity distribution interval of each pixel point in the target image block according to the velocity of each pixel point in the target image block, wherein the velocity of any one pixel point is obtained based on the velocity image component.

[0201] The target velocity distribution interval determination module 1160 is configured to determine a target velocity distribution interval through each velocity in the at least one velocity distribution interval.

[0202] The filtering module 1170 is configured to filter each pixel point in the target image block whose velocity is in the target velocity distribution interval and whose first identification is a motion identification to obtain a filtered target image block, wherein the motion identification is used to represent that a pixel point has motion characteristics.

[0203] The image processing module 1180 is configured to obtain a blood flow image after noise suppression according to each filtered target image block.

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

[0205] For any one pixel point in the blood flow image, a variance component of the pixel point is obtained according to the variance image component, and an energy component of the pixel point is obtained 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, it is determined that the first identifier of the pixel point is 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 represent that the pixel point does not have motion characteristics.

[0208] In one embodiment, the packetizing module 1130 is specifically configured to:

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

[0210] The length of each image block is obtained by using the packetizing number and the length of the blood flow image;

[0211] The blood flow image is packetized based on the length of each image block, and a plurality of image blocks of the blood flow image are obtained.

[0212] In one embodiment, the packetizing module 1130 is further configured to:

[0213] The receiving time of any one receiving line is determined by using the obtained depth of the receiving line and the sound speed;

[0214] The transmission number of the receiving line in any one packet is obtained based on the receiving time of any one receiving line, a preset pulse repetition frequency, and a preset repetition number of the short-time direction of any one receiving line;

[0215] The packetizing number of the blood flow image is obtained by dividing the first ratio by the number of beams, wherein the first ratio is obtained by dividing the total number of receiving lines by the transmission number of the receiving line in any one packet.

[0216] In one embodiment, the packetizing module 1130 is further configured to:

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

[0218]

[0219] Wherein, prt is the receiving time of any one receiving line, d is the depth of the receiving line, v 声the sound velocity;

[0220] the transmission times of the receiving lines in the arbitrary sub-packet are obtained based on the receiving time of the arbitrary receiving line, the preset pulse repetition frequency, and the preset repetition number of the short-time direction of the arbitrary receiving line, and the transmission times of the receiving lines in the arbitrary sub-packet are obtained by the following formula:

[0221] the transmission times of the receiving lines in the arbitrary sub-packet are obtained based on the receiving time of the arbitrary receiving line, the preset pulse repetition frequency, and the preset repetition number of the short-time direction of the arbitrary receiving line, and the transmission times of the receiving lines in the arbitrary sub-packet are obtained by the following formula:

[0222]

[0223] wherein I represents the transmission times of the receiving lines in the arbitrary sub-packet, prt represents the receiving time of the arbitrary receiving line, PRF represents the pulse repetition frequency, N represents the repetition number of the short-time direction of the arbitrary receiving line, and I represents the transmission times of the receiving lines in the arbitrary sub-packet. 发 the repetition number of the short-time direction of the arbitrary receiving line.

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

[0225] For an arbitrary image block, a first quantity of pixel points with a first identifier of motion identifier in the image block is counted.

[0226] A third ratio is obtained by dividing the first quantity by a total quantity of pixel points in the image block.

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

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

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

[0230] For an arbitrary speed, if the quantity of pixel points corresponding to the speed is greater than a specified quantity, the speed is determined as a target speed.

[0231] The target speeds are sorted in a specified order, two target speeds with adjacent positions and a specified value difference in the sorted target speeds are added to a same speed distribution set, and at least one speed distribution set is obtained.

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

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

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

[0235] If the number of the velocity distribution intervals is more than one, a velocity distribution interval with the largest value of the velocity standard deviation greater than a fifth specified threshold is determined as the target velocity distribution interval, wherein the velocity standard deviation in any velocity distribution interval is obtained based on the velocities in the velocity distribution interval.

[0236] Having described a method and apparatus for suppressing motion tissue noise in blood flow images according to an example embodiment of the present disclosure, next, an ultrasound device according to another example embodiment of the present disclosure is described.

[0237] Those skilled in the art can understand that each aspect of the present disclosure can be implemented as a system, a method or a program product. Therefore, each aspect of the present disclosure can be embodied as a whole hardware embodiment, a whole software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system".

[0238] In some possible embodiments, the ultrasound device according to the present disclosure can include at least one processor and at least one computer storage medium. The computer storage medium stores program codes which, when executed by the processor, cause the processor to perform the steps in the method for suppressing motion tissue noise in blood flow images according to various example embodiments of the present disclosure described above in the specification. For example, the processor can perform steps 201-208 as shown in Figure 2

[0239] As shown in Figure 12 ​As shown, the ultrasound device provided by the present application is a schematic diagram of an ultrasound device. The ultrasound device 1200 comprises a processor 1202, a communication interface 1203, and a memory 1201. Optionally, the ultrasound device 1200 can further comprise a communication line 1204. The communication interface 1203, the processor 1202, and the memory 1201 can be connected to each other through the communication line 1204. The communication line 1204 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication line 1204 can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 12 Only one thick line is used in the figure to represent the buses, but it does not mean that there is only one bus or only one type of bus.

[0240] The processor 1202 can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of programs of the present application.

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

[0242] The memory 1201 can be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory can exist independently and be connected to the processor through the communication line 1204. The memory can also be integrated with the processor.

[0243] The memory 1201 is configured to store computer-executable instructions for implementing the solutions of the present application, and the processor 1202 is configured to execute the computer-executable instructions stored in the memory 1201. The processor 1202 is configured to execute the computer-executable instructions stored in the memory 1201, so as to implement the method for suppressing motion tissue noise in a blood flow image provided by the embodiments of the present application.

[0244] Optionally, the computer-executable instructions in the embodiments of the present application can also be referred to as application program codes, which are not limited in the embodiments of the present application.

[0245] In some possible implementation manners, each aspect of the method for suppressing motion tissue noise in a blood flow image provided by the present disclosure can also be implemented in the form of a program product, which includes program codes for causing a computer device to execute the steps in the method for suppressing motion tissue noise in a blood flow image according to various exemplary embodiments of the present disclosure described in the specification when the program product is run on the computer device.

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

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

[0248] The readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, in which readable program codes are borne. Such a propagated data signal can take on various forms, including but not limited to electro-magnetic signal, optical signal or any appropriate combination thereof. The readable signal medium can also be any readable medium that is not a readable storage medium and that can transmit, propagate or transport program for use by or in connection with an instruction execution system, device or apparatus.

[0249] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0250] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's ultrasound device, partially on the user's device, as a standalone software package, partially on the user's ultrasound device and partially on a remote ultrasound device, or entirely on a remote ultrasound device or server. In cases involving remote ultrasound devices, the remote ultrasound device can be connected to the user's ultrasound device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can 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 apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this 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 and embodied by multiple modules.

[0252] Furthermore, although the operations of the methods disclosed herein are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0253] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk computer storage media, CD-ROMs, optical computer storage media, etc.) containing computer-usable program code.

[0254] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for carrying out the function specified by the flowchart block or blocks.

[0255] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for carrying out the function specified by the flowchart block or blocks.

[0256] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 Figure 1 means for carrying out the function specified by the flowchart block or blocks.

[0257] Obviously, numerous modifications and variations of the present disclosure are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the disclosure can be practiced otherwise than as specifically described.

Claims

1. A method of suppressing motion tissue noise in a blood flow image, characterized by, The method comprises: acquiring a wall-filtered current moment blood flow image, wherein the blood flow image comprises a velocity image component, a variance image component and an energy image component; determining a first identifier of each pixel point 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 represent whether the pixel point is a pixel point with motion characteristics; obtaining a number of sub-packets of the blood flow image according to a total number of receiving lines in the blood flow image and a preset number of beams, specifically comprising: determining a receiving time of an arbitrary receiving line by using the depth of the acquired receiving line and the sound speed, wherein the receiving line is a line composed of each pixel point in the blood flow image in the longitudinal direction; obtaining a transmission number of receiving lines in an arbitrary sub-packet based on the receiving time of the arbitrary receiving line, a preset pulse repetition frequency and a preset repetition number of the arbitrary receiving line short-time direction; dividing a first ratio by the number of beams to obtain the number of sub-packets of the blood flow image, wherein the first ratio is obtained by dividing the total number of receiving lines by the transmission number of receiving lines in the arbitrary sub-packet; obtaining the length of each image block by using the number of sub-packets and the length of the blood flow image; performing sub-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; obtaining a target image block based on the first identifier of each pixel point in each image block; for an arbitrary target image block, determining at least one velocity distribution interval of each pixel point in the target image block according to the velocity of each pixel point in the target image block, wherein the velocity of an arbitrary pixel point is obtained based on the velocity image component; and determining a target velocity distribution interval through each velocity in the at least one velocity distribution interval; filtering each pixel point in the target image block whose velocity is in the target velocity distribution interval and whose first identifier is a motion identifier to obtain a filtered target image block, wherein the motion identifier is used to represent that the pixel point has motion characteristics; obtaining a blood flow image after noise suppression according to the filtered target image blocks.

2. The method of claim 1, wherein, The method comprises: for an arbitrary pixel point in the blood flow image, obtaining a variance component of the pixel point according to the variance image component, and obtaining an 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 that the first identifier of the pixel point is the motion identifier; otherwise, determining that the first identifier of the pixel point is a still identifier, wherein the still identifier is used to represent that the pixel point does not have motion characteristics.

3. The method of claim 1, wherein, The method comprises: obtaining the receiving time of the arbitrary receiving line by the following formula: ； wherein, is the reception time for any one receiving line, is the depth of the receiving line, is the speed of sound; The transmission times of the receiving lines in the arbitrary sub-packet are obtained based on the receiving time of the arbitrary receiving line, a preset pulse repetition frequency, and a preset repetition number of the arbitrary receiving line short-time direction, and include: The transmission times of the receiving lines in the arbitrary sub-packet are obtained by the following formula: ； wherein, is the number of transmissions for the arbitrary one subpacket, is the reception time for the arbitrary one reception line, is the pulse repetition frequency, is the number of repetitions for the arbitrary one reception line short-time direction.

4. The method of claim 1, wherein, The target image block is obtained based on the first identifiers of the pixel points in each image block, and includes: For any one image block, the first number of the pixel points with the first identifier as the motion identifier in the image block is counted; The third ratio is obtained by dividing the first number by the total number of the pixel points in the image block; The image block with the third ratio not less than a third specified threshold is determined as the target image block.

5. The method of claim 1, wherein, The at least one speed distribution interval of the pixel points in the target image block is determined according to the speeds of the pixel points in the target image block, and includes: The number of the pixel points corresponding to each speed is obtained according to the speeds of the pixel points in the target image block; For any one speed, if the number of the pixel points corresponding to the speed is greater than a specified number, the speed is determined as a target speed; The target speeds are sorted in a specified order, two target speeds with adjacent positions and a specified difference value in the sorted target speeds are added to the same speed distribution set, and at least one speed distribution set is obtained; The at least one speed distribution interval is obtained based on the at least one speed distribution set.

6. The method of claim 1, wherein, The target speed distribution interval is determined through the speeds in the at least one speed distribution interval, and includes: 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 the pixel points in the target image block with the speed in the speed distribution interval and the first identifier as the motion identifier by the total number of the pixel points in the target image block with the first identifier as the motion identifier; If the number of the speed distribution intervals is multiple, a speed distribution interval with a speed standard deviation greater than a fifth specified threshold and a maximum value of the speed standard deviation in each speed distribution interval is determined as the target speed distribution interval, wherein the speed standard deviation in any one speed distribution interval is obtained based on the speeds in the speed distribution interval.

7. An ultrasound apparatus, characterized by The device includes a memory and a processor, and the processor and the memory are connected through a bus; The memory stores a computer program, and the processor is configured to execute the following operations based on the computer program: Obtain a blood flow image at a current time after wall filtering, wherein the blood flow image includes a velocity image component, a variance image component, and an energy image component; Determine a first identifier of each pixel point 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 represent whether the pixel point is a pixel point with motion characteristics. According to the total number of receiving lines in the blood flow image and a preset number of beams, a number of sub-packets of the blood flow image is obtained, specifically configured as: determining a receiving time of an arbitrary receiving line by using the obtained depth of the receiving line and the sound speed, wherein the receiving line is a line composed of each pixel point in the blood flow image in the longitudinal direction; obtaining a number of times of transmission of a receiving line in an arbitrary sub-packet based on the receiving time of the arbitrary receiving line, a preset pulse repetition frequency, and a preset number of repetitions of the short-time direction of the arbitrary receiving line; and obtaining the number of sub-packets of the blood flow image by dividing a first ratio by the number of beams, wherein the first ratio is obtained by dividing the total number of receiving lines by the number of times of transmission of the receiving line in the arbitrary sub-packet; A length of each image block is obtained by using the number of sub-packets and a length of the blood flow image; The blood flow image is sub-packet processed based on the length of each image block to obtain a plurality of image blocks of the blood flow image; A target image block is obtained based on a first identifier of each pixel point in each image block; For an arbitrary target image block, at least one velocity distribution interval of each pixel point in the target image block is determined according to the velocity of each pixel point in the target image block, wherein the velocity of an arbitrary pixel point is obtained based on the velocity image component; and A target velocity distribution interval is determined by using the velocities in the at least one velocity distribution interval; Each pixel point in the target image block whose velocity is in the target velocity 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 represent that a pixel point has a motion feature. A blood flow image after noise suppression is obtained according to the filtered target image blocks.

8. The ultrasound device of claim 7, wherein, The processor performs the determination of the first identifier of each pixel point in the blood flow image based on the variance image component and the energy image component of the blood flow image, specifically configured as: For an arbitrary pixel point in the blood flow image, a variance component of the pixel point is obtained according to the variance image component, and an energy component of the pixel point is obtained according to the energy image component; If the energy component of the pixel point is greater than a first specified threshold value, and the variance component of the pixel point is less than a second specified threshold value, it is determined that the first identifier of the pixel point is the motion identifier; Otherwise, it is determined that the first identifier of the pixel point is a still identifier, wherein the still identifier is used to represent that a pixel point does not have a motion feature.

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