A high-definition ultrasonic blood flow imaging method based on phase fluctuation

Abstract

The application discloses a high-definition blood flow ultrasonic imaging method based on phase fluctuation, which is used for fully reflecting the blood vessel structure of different flow velocities, especially the micro blood vessel structure of slow blood flow, greatly improving the blood flow sensitivity by using the phase fluctuation, and obtaining real-time high-definition blood flow ultrasonic imaging results. The specific method comprises the following steps: a pretreatment module M1 is used for removing the background tissue interference in the collected high-frame-rate ultrasonic echo IQ complex signal and constructing a matrix X1 through complex module operation; a color Doppler imaging module M2 is used for obtaining a phase graph sequence Y1, and an image Y2 is obtained by averaging Y1; a phase-time sequence construction module M3 is used for calculating the phase-time sequence R of each pixel point in Y2 k ; a mask calculation module M4 is used for performing two classifications on the variation degree of the phase-time sequence of each pixel point as a feature, and obtaining a noise-removed mask M; and a result output module M5 is used for obtaining real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of ultrasonic blood flow imaging, in particular to an imaging method for high-definition ultrasonic blood flow imaging based on phase fluctuation, an electronic device, an apparatus, a system and a computer storage medium. BACKGROUND

[0002] The vascular system is essential for normal organ function, and vascular dysfunction directly or indirectly leads to a variety of pathological conditions, causing significant morbidity and mortality. Unfortunately, however, conventional ultrasonic blood flow imaging methods can generally only clearly observe small blood vessels with a diameter of 100 μm, and have poor blood flow sensitivity for even smaller blood vessels. The main solution in current clinical practice is a strategy based on a power threshold mask (referred to as PoM). The PoM strategy can effectively remove shallow low-power noise in power Doppler imaging and color Doppler imaging, but filters out small blood flow with small power and slow flow rate together with noise. Although the apparent image quality is improved, the signal of a lot of small blood flow is actually lost, which seriously affects clinical judgment.

[0003] In order to improve the blood flow sensitivity of ultrasonic blood flow imaging, previous strategies such as hardware upgrades, image denoising, and injection of ultrasonic contrast agents have been proposed, but none of them have changed the PoM strategy and cannot solve the problem of loss of small blood flow signals. Therefore, how to improve the blood flow sensitivity of ultrasonic blood flow imaging and obtain real-time high-definition ultrasonic blood flow imaging results is still an important challenge. SUMMARY

[0004] To solve the above technical problems, the application discloses an imaging method for high-definition ultrasonic blood flow imaging based on phase fluctuation, an electronic device, an apparatus, a system and a computer storage medium.

[0005] Specifically, the imaging method for high-definition ultrasonic blood flow imaging based on phase fluctuation comprises the following steps:

[0006] Step 10: The high-frame-rate ultrasonic echo IQ complex signals of the first N frames to the current frame obtained by acquisition are subjected to space-time matrix decomposition to obtain N frames of wall-filtered complex space-time matrices Z; wherein the higher the ultrasonic imaging frame rate, the better the imaging site can be kept quasi-static; preferably, N is not less than 300 frames;

[0007] Step 20: responsible for performing complex modulus operation on the N frames of complex space-time matrices Z frame by frame to construct a matrix X1; wherein X1 is used to obtain real-time high-definition power Doppler imaging results;

[0008] Step 30: responsible for obtaining a phase image sequence Y1 by a classical autocorrelation strategy, and averaging Y1 to obtain a Y2 image; wherein Y2 is used to obtain real-time high-definition color Doppler blood flow imaging results;

[0009] Step 40, based on each pixel point position k in Y2, respectively construct the phase-time sequence R of length N k (k=1,2,…,K); wherein, K is the total number of pixels of each frame image in Y2;

[0010] Step 50, multiply R k by Q k , the variation degree of the fluctuation of R k , to obtain the mask M of removing noise;

[0011] Step 60, multiply M with X1 and Y2 respectively to obtain the real-time high-definition power Doppler imaging result and the real-time high-definition color Doppler blood flow imaging result.

[0012] The space-time matrix decomposition comprises the following steps:

[0013] (1) Calculate the corresponding B-mode imaging result for the collected high-frame-rate ultrasonic echo IQ complex signal;

[0014] (2) Register or discard the motion frame according to the B-mode imaging result; this is to maintain the quasi-static of the imaging part and the effectiveness of the space-time matrix decomposition;

[0015] (3) Perform space-time matrix decomposition on the ultrasonic echo IQ complex signal after registration or discarding the motion frame, manually or adaptively select the threshold for reconstruction, and obtain the N frames of complex space-time matrix Z after wall filtering; the purpose of space-time matrix decomposition is to remove the interference of quasi-static background tissue.

[0016] The two classification based on the variation degree of the fluctuation of the phase-time sequence comprises the following steps:

[0017] (1) For each pixel point in Y2, construct the phase-time sequence R k of length N, and calculate the variation degree Q k of each sequence;

[0018] (2) According to the statistical characteristics of Q k , perform blood flow and noise two classification point by point in Y2 space;

[0019] (3) Set the noise region to 0 and the blood flow region to 1 to obtain the mask M of removing noise.

[0020] The electronic device based on the high-definition ultrasonic blood flow imaging based on phase fluctuation comprises a processor, a memory storing executable instructions, and a storage medium; wherein the processor is used to execute the computer program corresponding to the high-definition ultrasonic blood flow imaging method based on phase fluctuation; the storage medium is responsible for storing the computer program corresponding to the high-definition ultrasonic blood flow imaging method based on phase fluctuation and imaging data.

[0021] The high-definition ultrasonic blood flow imaging device based on phase fluctuation comprises a data acquisition module S1, a pre-processing module M1, a color Doppler imaging module M2, a phase-time sequence construction module M3, a mask calculation module M4 and a result output module M5. k The high-definition ultrasonic blood flow imaging device based on phase fluctuation comprises a data acquisition module S1, a pre-processing module M1, a color Doppler imaging module M2, a phase-time sequence construction module M3, a mask calculation module M4 and a result output module M5.

[0022] The high-definition ultrasonic blood flow imaging system based on phase fluctuation comprises an acquisition device for executing the first method and an electronic device or an imaging device.

[0023] The computer storage medium of the high-definition ultrasonic blood flow imaging based on phase fluctuation comprises a computer program corresponding to the high-definition ultrasonic blood flow imaging method based on phase fluctuation and imaging data, and is used for the electronic device to execute the high-definition ultrasonic blood flow imaging method based on phase fluctuation. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 FIG. 1 is a schematic diagram of a high-definition ultrasonic blood flow imaging method based on phase fluctuation according to an example embodiment of the present application.

[0025] Figure 2 FIG. 2 is a schematic diagram of acquiring high-frame-rate ultrasonic echo IQ complex signals, and obtaining a complex space-time matrix Z after wall filtering through space-time matrix decomposition according to an example embodiment of the present application.

[0026] Figure 3 FIG. 3 is a schematic diagram of performing binary classification on the variation degree Q of the fluctuation of R as a feature, and obtaining a mask M removing noise according to an example embodiment of the present application. k k

[0027] Figure 4 FIG. 5 is a module schematic diagram of a high-definition ultrasonic blood flow imaging device based on phase fluctuation according to an example embodiment of the present application.

[0028] Figure 5 FIG. 6 is an electronic device according to an example embodiment of the present application. DETAILED DESCRIPTION

[0029] ​​With reference to the drawings and the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0030] Figure 1 Fig. 1 shows a schematic diagram of a high-definition ultrasonic blood flow imaging method based on phase fluctuation provided by an exemplary embodiment of the present application. The method comprises the following acquisition and calculation steps:

[0031] Step 10: The high-frame-rate ultrasonic echo IQ complex signals of the first N frames to the current frame acquired are subjected to space-time matrix decomposition to obtain N frames of wall-filtered complex space-time matrices Z. Specifically, the ultrasonic echo IQ complex signals of the imaging site acquired are subjected to space-time matrix decomposition to obtain N frames of wall-filtered complex space-time matrices Z. In order to ensure that the imaging site remains quasi-static during the acquisition, the frame rate of the IQ complex signals is required to be high, preferably not less than 300 Hz, and in the present exemplary embodiment, the frame rate of the IQ complex signals is 500 Hz. In the present step, N frames of IQ complex signals are acquired.

[0032] In an embodiment of the present application, the N frames of IQ complex signals of the imaging site can be acquired by multi-angle plane wave coherent compound imaging technology and demodulated to obtain; can also be acquired based on spherical wave coherent compound ultrasonic superfast imaging technology and demodulated to obtain; or can be acquired based on other ultrasonic superfast acquisition modes and demodulated to obtain. In the present exemplary embodiment, 500 frames of IQ complex signals are acquired by 7-angle plane wave coherent compound imaging technology and demodulated to obtain; N is 500 frames.

[0033] In an embodiment of the present application, the space-time matrix decomposition can be singular value decomposition; can also be non-negative matrix decomposition; or can be TT tensor decomposition. In the present exemplary embodiment, singular value decomposition strategy is adopted for decomposition of the IQ complex signals, and the stationary tissue signals are filtered out, and the complex space-time matrix Z is reconstructed.

[0034] Step 20: responsible for performing complex modulus operation on the N frames of complex space-time matrices Z frame by frame to construct matrix X1; in the present exemplary embodiment, complex modulus operation is performed on the 500 frames of complex space-time matrices Z frame by frame, i.e., the amplitude matrix X1 is constructed.

[0035] Step 30: responsible for obtaining a phase map sequence Y1 by a classical autocorrelation strategy; performing averaging on Y1 to obtain Y2 image; in the present exemplary embodiment, the phase in Y1 is subjected to image normalization and pseudo-colorization, and Y2 color Doppler blood flow image is obtained by averaging every two frames.

[0036] Step 40, based on each pixel point position k in Y2, a phase-time sequence R of length N is constructed respectively k (k=1,2,…,K); wherein, K is the total number of pixels of each frame image in Y2; step 50, the variance Q of the fluctuation of R k k is taken as a feature to perform binary classification, and a noise-removed mask M is obtained; in the present exemplary embodiment, the time domain variance is taken as a statistical feature of the phase fluctuation variance, the classic Otsu method is taken as a binary classification method, and the noise region is set to 0 to obtain the noise-removed mask M.

[0037] Step 60, M is multiplied with X1 and Y2 respectively to obtain real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

[0038] Figure 2 As shown in FIG. 1, it is a schematic diagram of step 10 provided by an exemplary embodiment of the present application, high frame rate ultrasonic echo IQ complex signals are collected, and a complex space-time matrix Z after wall filtering is obtained through space-time matrix decomposition.

[0039] Step 11, the corresponding B mode imaging results are calculated for the high frame rate ultrasonic echo IQ complex signals collected from the first N frames to the current frame; specifically, complex modulus operation is performed on the IQ complex signals of the N frames frame by frame to obtain the corresponding B mode imaging results; in order to ensure the calculation time and the quasi-static of the imaging part, according to experience, N is 500 frames and the frame rate is 500 Hz in the present embodiment.

[0040] Step 12, registration or discarding of motion frames is performed according to the B mode imaging results; in the present embodiment, for the frames in which motion occurs in the B mode image, the IQ complex signals of the corresponding frames are discarded, and only the quasi-static IQ complex signals are retained. This is to maintain the quasi-static of the imaging part and the effectiveness of the space-time matrix decomposition.

[0041] Step 13, space-time matrix decomposition is performed on the ultrasonic echo IQ complex signals after registration or discarding of motion frames, a threshold is manually or adaptively selected for reconstruction, and N frames of complex space-time matrix Z after wall filtering are obtained; the purpose of the space-time matrix decomposition is to remove the interference of the static background tissue.

[0042] In the present embodiment, singular value decomposition is performed on the ultrasonic echo IQ complex signals after discarding of motion frames, and the background tissue signals corresponding to the first 10% singular values are discarded to obtain the complex space-time matrix Z after wall filtering.

[0043] Figure 3 As shown in FIG. 5, it is a schematic diagram of step 50 provided by an exemplary embodiment of the present application, the variance Q of the fluctuation of R k k is taken as a feature to perform binary classification, and a noise-removed mask M is obtained.​​

[0044] Step 51, calculate the phase-time sequence R k of each pixel point k corresponding to the variation degree Q k of the fluctuation of the phase-time sequence R k ; specifically, for each phase-time sequence, calculate the time domain variance to obtain the time domain variance Q k of each sequence.

[0045] Step 52, take the variation degree Q k of the fluctuation of the phase-time sequence R k as a feature, and perform blood flow and noise binary classification in Y2 space according to the statistical characteristics of Q k ; specifically, perform histogram statistics on Q k , and determine the threshold value of histogram classification according to the Otsu method to perform blood flow and noise binary classification in Y2 space.

[0046] Step 53, according to the classification result, obtain the mask M removing noise; specifically, according to the classification result, set the noise region to 0 and the blood flow region to 1, and finally obtain the mask M removing noise and enhancing blood flow signal.

[0047] Figure 4 The module schematic diagram of the high-definition ultrasonic blood flow imaging device based on phase fluctuation provided by an exemplary embodiment of the present application is shown. It comprises:

[0048] (1) a high-speed acquisition module S1 responsible for obtaining the ultrasonic echo IQ complex signal of the imaging part;

[0049] (2) a preprocessing module M1 responsible for obtaining N frames of complex space-time matrix Z based on the ultrasonic echo IQ complex signal of the previous N frames to the current frame, and performing complex modulus operation on Z to obtain matrix X1;

[0050] (3) a color Doppler imaging module M2 responsible for obtaining a phase map sequence Y1 based on Z and a classical autocorrelation strategy, and further averaging Y1 to obtain Y2;

[0051] (4) a phase-time sequence construction module M3 responsible for constructing a phase-time sequence R k (k=1,2,…,K) with a length of N based on each pixel point position k in Y2;

[0052] (5) a mask calculation module M4 taking the variation degree Q k of the fluctuation of the phase-time sequence R k as a feature to perform binary classification and obtain the mask M removing noise;

[0053] (6) a result output module M5 multiplying M with X1 and Y2 respectively to obtain real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

[0054] Reference Figure 5 An electronic device is described.

[0055] As shown, the electronic device 70 includes one or more processors 701 and memory 702.

[0056] The processor 701 can be a central processing unit (CPU) or other form of processing unit having data processing and / or instruction executing capabilities, and can control other components in the electronic device 70 to perform desired functions.

[0057] The memory 702 can include one or more computer program products that can include various forms of computer-readable storage media, such as volatile and / or non-volatile memory. The volatile memory, for example, can include random access memory (RAM), cache memory, and / or the like, among others.

[0058] The non-volatile memory, for example, can include read-only memory (ROM), hard disk, flash memory, and / or the like. One or more computer program instructions can be stored on the computer-readable storage media, which the processor 701 can execute to implement the phase fluctuation based high-definition ultrasound blood flow imaging method of various embodiments of the present application described above and / or other desired functions.

[0059] Various contents such as the ultrasound echo IQ complex signal of the imaging site, the wall-filtered complex space-time matrix Z, the constructed matrix X1, the phase map sequence Y1, the mask M, and the like can also be stored in the computer storage media.

[0060] In one example, the electronic device 70 can also include an input device 703 and an output device 704, which are interconnected through a bus system and / or other form of connection mechanism (not shown).

[0061] The input device 703 can include, for example, a keyboard, a mouse, and / or the like.

[0062] The output device 704 can output various information to the outside, including various contents such as the ultrasound echo IQ complex signal of the imaging site, the wall-filtered complex space-time matrix Z, the constructed matrix X1, the phase map sequence Y1, the mask M, and the like. The output device 704 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and / or the like.

[0063] Of course, in order to simplify, Figure 5Only some of the components of the electronic device 70 that are relevant to the present application are shown in FIG. 7. Components such as a bus, input / output interface, and the like have been omitted for the sake of clarity. The electronic device 70 can also include any other suitable components according to particular needs.

[0064] In addition to the methods and devices described above, embodiments of the present application can also be a computer program product including computer program instructions that, when run by a processor, cause the processor to perform steps of the phase fluctuation based high definition ultrasound blood flow imaging method according to various embodiments of the present application described above in the specification.

[0065] The computer program product can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, etc., and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

[0066] The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's device and partly on a remote computing device or entirely on the remote computing device or server.

[0067] In addition, embodiments of the present application can also be a computer readable storage medium having stored thereon computer program instructions that, when run by a processor, cause the processor to perform steps of the phase fluctuation based high definition ultrasound blood flow imaging method according to various embodiments of the present application described above in the specification.

[0068] The computer readable storage medium can be any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing.

[0069] More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0070] The above generally describes the basic principles of the application in conjunction with specific embodiments, but it should be noted that the advantages, benefits, effects and the like mentioned in the application are only examples and are not limiting, and these advantages, benefits, effects and the like cannot be considered as necessary for each embodiment of the application.

[0071] In addition, the above specific details disclosed are only for the purpose of illustration and understanding, and are not limiting, and the above details do not limit the application to necessarily adopt the above specific details for implementation.

[0072] The block diagrams of the devices, apparatuses, equipment, systems involved in the application are only illustrative examples and are not intended to require or imply the connection, arrangement, configuration shown in the block diagrams.

[0073] As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have" and the like are open-ended words, mean "including but not limited to", and can be used interchangeably, the word "or" and "and" used herein mean the word "and / or", and can be used interchangeably, unless the context clearly indicates otherwise, the word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0074] It should also be noted that in the devices, equipment and methods of the application, each component or each step can be decomposed and / or recombined, and these decompositions and / or recombinations should be considered as equivalent solutions of the application.

[0075] The above description of the disclosed aspects is provided so that any person skilled in the art can make or use the application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the application. Therefore, the application is not intended to be limited to the aspects shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0076] The above description has been given for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations of the aspects and embodiments discussed above, which are still within the scope of the inventive concept.

Claims

1. A method of high definition ultrasound blood flow imaging, characterized by, The variation degree of the phase fluctuation of the ultrasonic echo IQ complex signal over time is taken as a feature, and a binary classification strategy is used to remove noise to obtain a high-definition ultrasonic blood flow imaging result. The method comprises the following steps: a. The ultrasonic echo IQ complex signals of the first N frames to the current frame are subjected to space-time matrix decomposition to obtain N frames of complex space-time matrices Z after wall filtering; b. For the N frames of Z, a complex modulus operation is performed frame by frame to construct a matrix X1; c. For the N frames of Z, a phase graph sequence Y1 is obtained through a classical autocorrelation strategy; Y1 is averaged to obtain a Y2 image; d. For each pixel position k in Y2, a phase-time sequence Rk with a length of N is constructed, k = 1, 2, …, K; wherein K is the total number of pixels in each image in Y2; e. The variation degree Qk of the fluctuation of Rk is taken as a feature for binary classification to obtain a noise-removed mask M; f. M is multiplied by X1 to obtain a single-frame high-definition power Doppler imaging result; g. M is multiplied by Y2 to obtain a single-frame high-definition color Doppler blood flow imaging result; h. The ultrasonic echo IQ complex signals collected in real time are subjected to steps 1-7 to obtain real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

2. The method of claim 1, wherein, The ultrasonic echo IQ complex signals of the first N frames to the current frame are subjected to space-time matrix decomposition to obtain N frames of space-time matrices Z after wall filtering; the space-time matrix decomposition is SVD or non-negative matrix decomposition or TT tensor decomposition.

3. The method of claim 1, wherein, The variation degree Qk of the fluctuation of Rk is taken as a feature for binary classification to obtain a noise-removed mask M; the specific steps include: calculating the variation degree Qk of Rk, further classifying blood flow and noise point by point in the Y2 space according to the statistical features of Qk; and setting the noise region to 0 and the blood flow region to 1 to finally obtain the noise-removed mask M; the statistical features of the variation degree of the fluctuation are the time domain variance or the extreme value of the time difference or the ratio of the main peak energy to the side lobe energy in the frequency domain; the classification method is the Otsu method or a classical machine learning method.

4. An electronic device comprising a processor and a computer storage medium storing processor-executable instructions executable by the processor to implement the method of any one of claims 1 to 3.

5. An imaging device, characterized by The imaging device is used to implement the imaging method of any one of claims 1 to 3, comprising: 1) a preprocessing module M1 responsible for obtaining N frames of complex space-time matrices Z based on the ultrasonic echo IQ complex signals of the first N frames to the current frame through space-time matrix decomposition, and constructing a matrix X1 based on Z; 2) a color Doppler imaging module M2 responsible for obtaining a phase graph sequence Y1 based on Z and a classical autocorrelation strategy, and averaging Y1 to obtain an image Y2; 3) a phase-time sequence construction module M3 responsible for constructing a phase-time sequence Rk with a length of N based on each pixel position k in Y2, k = 1, 2, …, K; 4) a mask calculation module M4 taking the variation degree Qk of the fluctuation of Rk as a feature for binary classification to obtain a noise-removed mask M; 5) a result output module M5, multiplying M with X1 and Y2 respectively to obtain real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

6. An imaging system characterized by, The application relates to an imaging device and an electronic device. 1) a collection device S1 responsible for collecting high-frame-rate ultrasonic echo IQ complex signals; 2) the electronic device as claimed in claim 4 or the imaging device as claimed in claim 5.

7. A computer storage medium, characterized in that The computer storage medium is used for storing processor-executable instructions, so that the processor executes the imaging method in any one of claims 1 to 3.

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