High-definition ultrasonic blood flow imaging method based on phase fluctuation

Abstract

The invention discloses a high-definition blood flow ultrasonic imaging method based on phase fluctuation, which is used for fully reflecting blood vessel structures with different flow velocities, particularly small blood vessel structures with slow blood flow, greatly improving blood flow sensitivity by using phase fluctuation and obtaining a real-time high-definition blood flow ultrasonic imaging result. The method specifically comprises the following steps: a preprocessing module M1 used for removing background tissue interference in an acquired high-frame-rate ultrasonic echo IQ complex signal and constructing a matrix X1 through complex modular operation; the color Doppler imaging module M2 is used for obtaining a phase diagram sequence Y1 and averaging the Y1 to obtain an image Y2; the phase time sequence construction module M3 is used for calculating a phase-time sequence Rk of each pixel point in the Y2; the mask calculation module M4 is used for carrying out binary classification on the variation degree seat features of the phase-time sequence of each pixel point to obtain a mask M with noise removed; and the result output module M5 is used for obtaining a real-time high-definition power Doppler imaging result and a real-time high-definition color Doppler blood flow imaging result.

Description

Technical Field

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

[0002] The vascular system is essential for the normal function of organs. Vascular dysfunction directly or indirectly leads to a variety of pathological conditions, causing significant morbidity and mortality. Unfortunately, however, traditional ultrasound blood flow imaging methods can generally only clearly observe small blood vessels with a diameter of 100 μm, and the blood flow sensitivity is very poor for smaller blood vessels. The main clinical solution at present is the power threshold mask strategy (abbreviated as PoM). Although the PoM strategy can effectively remove shallow low-power noise in power Doppler imaging and color Doppler imaging, it filters out small blood flows with low power and slow flow together with the noise. Although the overall image quality seems to be improved, in fact, many small blood flow signals are lost, which seriously affects clinical judgment.

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

[0004] In order to solve the above technical problems, the present invention discloses an imaging method, electronic equipment, device, system and computer storage medium for high-definition ultrasonic blood flow imaging based on phase fluctuation.

[0005] Specifically, the imaging method of high-definition ultrasonic blood flow imaging based on phase fluctuation comprises the following steps: Step 10, the collected high frame rate ultrasonic echo IQ complex signals from the previous N frames to the current frame are subjected to space-time matrix decomposition to obtain a complex space-time matrix Z of N frames after wall filtering; wherein, the higher the ultrasonic imaging frame rate, the more it can ensure that the imaging part is quasi-static; preferably, N is not less than 300 frames; Step 20 is responsible for performing frame-by-frame complex modulus operations on the complex space-time matrix Z of N frames to construct a matrix X1; wherein X1 is used to obtain real-time high-definition power Doppler imaging results; Step 30 is responsible for obtaining a phase image sequence Y1 through a classical autocorrelation strategy; averaging Y1 to obtain a Y2 image; wherein Y2 is used to obtain a real-time high-definition color Doppler blood flow imaging result; Step 40: Based on each pixel position k in Y2, a phase-time series R with a length of N is constructed.k (k=1,2,…,K); where K is the total number of pixels in each frame of image Y2; Step 50: R k The degree of variation of the fluctuation Q k Use it as a feature for binary classification and obtain the mask M for removing noise; Step 60, multiply M by 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.

[0006] The space-time matrix decomposition is composed of the following steps: (1) Calculate the corresponding B-mode imaging results for the acquired high frame rate ultrasound echo IQ complex signal; (2) Perform registration or discard motion frames based on the B-mode imaging results; this is to maintain the quasi-static state of the imaging site and the validity of the spatiotemporal matrix decomposition; (3) Performing spatiotemporal matrix decomposition on the complex IQ signal of the ultrasound echo after registration or discarding the motion frame, manually or adaptively selecting the threshold for reconstruction, and obtaining the complex spatiotemporal matrix Z of N frames after wall filtering; the purpose of spatiotemporal matrix decomposition is to remove quasi-static background tissue interference.

[0007] The binary classification based on the degree of variability of the fluctuation of the phase-time series consists of the following steps: (1) A phase-time series R of length N is constructed for each pixel in Y2 k , calculate the degree of variation Q of each sequence k ; (2) According to Q k The statistical features are used to classify blood flow and noise point by point in the Y2 space; (3) Set the noise area to 0 and the blood flow area to 1 to obtain the mask M for removing noise.

[0008] The electronic device for high-definition ultrasonic blood flow imaging based on phase fluctuation includes a processor, a memory storing executable instructions, and a storage medium; wherein the processor is used to execute a computer program corresponding to the high-definition ultrasonic blood flow imaging method based on phase fluctuation; and the storage medium is responsible for storing the computer program and imaging data corresponding to the high-definition ultrasonic blood flow imaging method based on phase fluctuation.

[0009] The high-definition ultrasonic blood flow imaging device based on phase fluctuation comprises: a data acquisition module S1, used to obtain a high frame rate ultrasonic echo IQ complex signal; a preprocessing module M1, used to remove background tissue interference and construct a matrix X1; a color Doppler imaging module M2, used to obtain a phase image sequence Y1 and a color Doppler blood flow imaging result Y2; a phase time series construction module M3, used to calculate the phase-time series R of each pixel point in Y2k ; a mask calculation module M4, used to obtain a mask M for removing noise; a result output module M5, used to obtain real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

[0010] The high-definition ultrasonic blood flow imaging system based on phase fluctuation comprises: an acquisition device for executing the first method; and the electronic device or imaging device.

[0011] The computer storage medium for high-definition ultrasonic blood flow imaging based on phase fluctuation includes: a computer program and imaging data corresponding to the high-definition ultrasonic blood flow imaging method based on phase fluctuation that are used by the electronic device to execute the high-definition ultrasonic blood flow imaging method based on phase fluctuation. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of a high-definition ultrasonic blood flow imaging method based on phase fluctuation according to an exemplary embodiment of the present application.

[0013] Figure 2 It is a schematic diagram of an exemplary embodiment of the present application that collects high frame rate ultrasonic echo IQ complex signals, decomposes the space-time matrix, and obtains the complex space-time matrix Z after wall filtering.

[0014] Figure 3 An exemplary embodiment of the present application is to k The degree of variation of the fluctuation Q k A schematic diagram of a mask M for removing noise is obtained by performing binary classification as a feature.

[0015] Figure 4 It is a module schematic diagram of a high-definition ultrasonic blood flow imaging device based on phase fluctuation according to an exemplary embodiment of the present application.

[0016] Figure 5 It is an electronic device according to an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] Figure 1 The figure 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, which includes the following acquisition and calculation steps: Step 10, the collected high frame rate ultrasonic echo IQ complex signal from the previous N frames to the current frame is subjected to space-time matrix decomposition to obtain the N-frame complex space-time matrix Z after wall filtering; specifically, the collected ultrasonic echo IQ complex signal of the imaging part has a high requirement on the frame rate of the IQ complex signal in order to ensure that the imaging part remains quasi-static during the acquisition period, preferably not less than 300 Hz, and in this exemplary embodiment, the frame rate of the IQ complex signal is 500 Hz. In this step, a total of N frames of IQ complex signals are collected.

[0019] In one embodiment of the present application, the N frames of IQ complex signals collected at the imaging site can be collected by multi-angle plane wave coherent composite imaging technology and demodulated; they can also be collected based on spherical wave coherent composite ultrasound ultra-fast imaging technology and demodulated; they can also be collected based on other ultra-fast ultrasound collection methods and demodulated. In this exemplary embodiment, 7-angle plane wave coherent composite imaging technology is used to collect and demodulate to obtain 500 frames of IQ complex signals; N is 500 frames.

[0020] In an embodiment of the present application, the space-time matrix decomposition may be singular value decomposition, non-negative matrix decomposition, or TT tensor decomposition. In this exemplary embodiment, a singular value decomposition strategy is used to decompose the IQ complex signal, filter out the stationary tissue signal, and reconstruct the complex space-time matrix Z.

[0021] Step 20 is responsible for performing complex modular operations on the complex space-time matrix Z of N frames frame by frame to construct the matrix X1. In this exemplary embodiment, complex modular operations are performed on the complex space-time matrix Z of 500 frames frame by frame to construct the amplitude matrix X1.

[0022] Step 30 is responsible for obtaining a phase image sequence Y1 through a classical autocorrelation strategy; averaging Y1 to obtain a Y2 image; in this exemplary embodiment, performing image normalization and pseudo-colorization on the phase in Y1 and averaging every two frames to obtain a Y2 color Doppler blood flow image.

[0023] Step 40: Based on each pixel position k in Y2, a phase-time series R with a length of N is constructed. k (k=1,2,…,K); wherein K is the total number of pixels of each frame image in Y2; Step 50, R k The degree of variation of the fluctuation Q k The noise is removed by using the binary classification method as a feature to obtain a mask M for removing noise. In this exemplary embodiment, the time domain variance is used as a statistical feature of the phase fluctuation variation degree, the classic Otsu method is used as a binary classification method, and the noise area is set to 0 to obtain a mask M for removing noise.

[0024] Step 60, multiply M by 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.

[0025] Figure 2 It is a schematic diagram of step 10 provided by an exemplary embodiment of the present application, which collects high frame rate ultrasonic echo IQ complex signals, decomposes them into time-space matrix, and obtains the complex time-space matrix Z after wall filtering.

[0026] Step 11, for the high frame rate ultrasonic echo IQ complex signals from the previous N frames to the current frame, calculate the corresponding B-mode imaging results; specifically, perform complex analog operation on the IQ complex signals of N frames frame by frame to obtain the corresponding B-mode imaging results; in order to ensure the calculation time and the quasi-static state of the imaging part, according to experience, in this embodiment, N is 500 frames and the frame rate is 500 Hz.

[0027] Step 12, register or discard motion frames according to the B-mode imaging results; in this embodiment, for frames with motion 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 state of the imaging part and the effectiveness of the spatiotemporal matrix decomposition.

[0028] Step 13, perform spatiotemporal matrix decomposition on the complex ultrasound echo IQ signal after registration or discarding the motion frame, select a threshold manually or adaptively for reconstruction, and obtain the N-frame complex spatiotemporal matrix Z after wall filtering; the purpose of spatiotemporal matrix decomposition is to remove static background tissue interference.

[0029] In this embodiment, singular value decomposition is performed on the complex IQ signal of the ultrasound echo after the motion frame is discarded, and the background tissue signals corresponding to the first 10% of the singular values ​​are discarded to obtain the complex space-time matrix Z after wall filtering.

[0030] Figure 3 The step 50 provided by an exemplary embodiment of the present application is shown as follows: k The degree of variation of the fluctuation Q k A schematic diagram of a mask M for removing noise is obtained by performing binary classification as a feature.

[0031] Step 51, calculate the phase-time series R corresponding to each pixel point k k The degree of variation of the fluctuation Q k Specifically, the time domain variance is calculated for each phase-time series to obtain the time domain variance Q of each series. k .

[0032] Step 52: R k The degree of variation of the fluctuation Q k As a feature, and according to Q kThe statistical features of Q are used to classify blood flow and noise point by point in Y2 space; specifically, k Histogram statistics are performed, and the threshold of histogram classification is determined according to the Otsu method. Blood flow and noise are classified point by point in the Y2 space.

[0033] Step 53, according to the classification result, a mask M for removing noise is obtained; specifically, according to the classification result, the noise area is set to 0 and the blood flow area is set to 1, and finally a mask M for enhancing the blood flow signal and removing noise is obtained.

[0034] Figure 4 A schematic diagram of a module of a high-definition ultrasonic blood flow imaging device based on phase fluctuation provided by an exemplary embodiment of the present application. It includes: (1) High-speed acquisition module S1, responsible for obtaining the ultrasonic echo IQ complex signal of the imaging part; (2) Preprocessing module M1 is responsible for obtaining the N-frame complex space-time matrix Z based on the ultrasonic echo IQ complex signal from the previous N frames to the current frame by using space-time matrix decomposition, and performing complex modulus operation on Z to obtain the matrix X1; (3) Color Doppler imaging module M2, which is responsible for obtaining the phase image sequence Y1 based on Z and the classical autocorrelation strategy, and further averaging Y1 to obtain Y2; (4) Phase-time series construction module M3 is responsible for constructing a phase-time series R with a length of N based on the position k of each pixel in Y2. k (k=1,2,…,K); (5) Mask calculation module M4, R k The degree of variation of the fluctuation Q k Use it as a feature for binary classification and obtain the mask M for removing noise; (6) The result output module M5 multiplies M by X1 and Y2 respectively to obtain the real-time high-definition power Doppler imaging results and the real-time high-definition color Doppler blood flow imaging results.

[0035] refer to Figure 5 An electronic device according to an embodiment of the present application is described.

[0036] As shown in the figure, the electronic device 70 includes one or more processors 701 and a memory 702 .

[0037] The processor 701 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 70 to perform desired functions.

[0038] The memory 702 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache.

[0039] The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 701 may execute the program instructions to implement the high-definition ultrasonic blood flow imaging method based on phase fluctuation of each embodiment of the present application described above and / or other desired functions.

[0040] The computer storable medium may also store various contents such as ultrasonic echo IQ complex signals of the imaging site, complex space-time matrix Z after wall filtering, constructed matrix X1, phase map sequence Y1, mask M, etc.

[0041] In one example, the electronic device 70 may further include: an input device 703 and an output device 704 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0042] The input device 703 may include, for example, a keyboard, a mouse, etc.

[0043] The output device 704 can output various information to the outside, including various contents such as ultrasonic echo IQ complex signal of the imaging part, complex space-time matrix Z after wall filtering, constructed matrix X1, phase map sequence Y1, mask M, etc. The output device 704 can include, for example, a display, a speaker, a printer, a communication network and its connected remote output device, etc.

[0044] Of course, to simplify, Figure 5 Only some of the components related to the present application in the electronic device 70 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application conditions, the electronic device 70 may also include any other appropriate components.

[0045] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the high-definition ultrasonic blood flow imaging method based on phase fluctuation according to various embodiments of the present application described above in this specification.

[0046] The computer program product can be written in any combination of one or more programming languages ​​to write program codes for executing the operations of the embodiments of the present application, and the programming languages ​​include object-oriented programming languages, such as Java, C++, etc., and also include conventional procedural programming languages, such as "C" language or similar programming languages.

[0047] The program code may execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server.

[0048] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the high-definition ultrasonic blood flow imaging method based on phase fluctuation according to various embodiments of the present application described above in this specification.

[0049] The computer readable storage medium may be any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or components, or any combination thereof.

[0050] More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more conductors, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM, an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0051] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be pointed out that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required to be possessed by each embodiment of the present application.

[0052] In addition, the specific details disclosed above are only for the purpose of illustration and facilitating understanding, and are not restrictive. The above details do not limit the present application to being implemented by adopting the above specific details.

[0053] The block diagrams of devices, apparatuses, equipment, and systems involved in the present application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams.

[0054] As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, systems may be connected, arranged, configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended words, meaning "including but not limited to", and may be used interchangeably therewith, and the words "or" and "and" used herein refer to the words "and / or", and may be used interchangeably therewith, unless the context clearly indicates otherwise, and the word "such as" used herein refers to the phrase "such as but not limited to", and may be used interchangeably therewith.

[0055] It should also be pointed out that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined, and such decomposition and / or recombination should be regarded as an equivalent solution of the present application.

[0056] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0057] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize that some variations, modifications, changes, additions and sub-combinations thereof are still within the scope of protection of the technical solutions of the present invention.

Claims

1. A high-definition ultrasonic blood flow imaging method, characterized in that: The variation degree of the phase fluctuation of the ultrasonic echo IQ complex signal over time is used as a feature, and the noise is removed by using a binary classification strategy to obtain a high-definition ultrasonic blood flow imaging result; the following steps are included: (a) The acquired ultrasonic echo IQ complex signals from the previous N frames to the current frame are decomposed through a time-space matrix to obtain an N-frame complex time-space matrix Z after wall filtering; (b) For N frames Z, the matrix X1 is constructed by performing complex modulus operations frame by frame; (c) For N frames Z, the phase image sequence Y1 is obtained through the classical autocorrelation strategy; Y1 is averaged to obtain the Y2 image; (d) For each pixel position k in Y2, a phase-time series R of length N is constructed. k (k=1,2,…,K); where K is the total number of pixels in each frame of image Y2; (e) R k The degree of variation of the fluctuation Q k Use it as a feature for binary classification and obtain the mask M for removing noise; (f) Multiply M by X1 to obtain a single-frame high-definition power Doppler imaging result; (g) Multiply M by Y2 to obtain a single-frame high-definition color Doppler blood flow imaging result; (h) The real-time acquired ultrasound echo IQ complex signal is looped from (a) to (g) to obtain real-time high-definition power Doppler imaging results and real-time high-definition color Doppler blood flow imaging results.

2. A high-definition ultrasonic blood flow imaging method according to claim 1, characterized in that: The collected ultrasonic echo IQ complex signals from the previous N frames to the current frame are subjected to space-time matrix decomposition to obtain the space-time matrix Z of N frames after wall filtering; the space-time matrix decomposition is SVD or non-negative matrix decomposition or TT tensor decomposition.

3. The high-definition ultrasonic blood flow imaging method according to claim 1, characterized in that: R k The degree of variation of the fluctuation Q k Use it as a feature for binary classification and obtain the mask M for removing noise; The specific steps include: calculating R k The degree of variation Q k , further according to Q k The statistical characteristics of the blood flow and noise are classified point by point in the Y2 space; the noise area is set to 0, and the blood flow area is set to 1, and finally a mask M for removing noise is obtained; the statistical characteristics of the degree of variation of the fluctuation are the extreme value of the time domain variance or the time difference or the ratio of the main peak energy to the sidelobe energy in the frequency domain; the classification method is the Otsu law method or the classical machine learning method.

4. An electronic device, comprising a processor and a computer storage medium, wherein the computer storage medium stores instructions executable by the processor, and the processor is configured to execute the instructions to implement the method according to any one of claims 1 to 3.

5. An imaging device, characterized in that: The imaging device is used to implement the imaging method of claims 1 to 4, comprising: (1) Preprocessing module M1 is responsible for obtaining the N-frame complex space-time matrix Z based on the ultrasonic echo IQ complex signal from the previous N frames to the current frame by using space-time matrix decomposition, and constructing the matrix X1 based on Z; (2) Color Doppler imaging module M2, which is responsible for obtaining the phase image sequence Y1 based on Z and the classical autocorrelation strategy, and averaging Y1 to obtain image Y2; (3) Phase-time series construction module M3 is responsible for constructing a phase-time series R with a length of N based on the position k of each pixel in Y2. k (k=1,2,…,K); (4) Mask calculation module M4, R k The degree of variation of the fluctuation Q k Use it as a feature for binary classification and obtain the mask M for removing noise; (5) The result output module M5 multiplies M by X1 and Y2 respectively to obtain the real-time high-definition power Doppler imaging results and the real-time high-definition color Doppler blood flow imaging results.

6. An imaging system, characterized in that: include: (1) Acquisition device S1, responsible for acquiring high frame rate ultrasonic echo IQ complex signal; (2) The electronic device according to claim 4 or the imaging device according to claim 5.

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

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