CN116549018B - Three-dimensional ultrasonic super-resolution method based on nano liquid drops - Google Patents
Three-dimensional ultrasonic super-resolution method based on nano liquid drops Download PDFInfo
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Abstract
The invention discloses a three-dimensional ultrasonic super-resolution method based on nano liquid drops, which comprises the steps of preprocessing nano liquid drops, activating the nano liquid drops, performing three-dimensional motion compensation by adopting two nonlinear optimization methods of affine transformation image registration and B-spline free deformation registration, removing background signals, and realizing the positioning of contrast signals by adopting a three-dimensional cross-correlation method. The invention utilizes the large-scale spatial activation of the two-dimensional ultrasonic probe and the multi-angle three-dimensional imaging, can definitely target the imaging and activation mechanism of the nano liquid drop under the three-dimensional ultrasonic, and obviously shortens the acquisition and reconstruction time of the three-dimensional ultrasonic super-resolution image, thereby realizing the rapid three-dimensional micro-vessel imaging with large depth and micron level and promoting the application of the three-dimensional micro-vessel imaging in the aspect of early and accurate diagnosis of diseases.
Description
Technical Field
The invention belongs to the technical field of ultrasonic detection and ultrasonic imaging, and particularly relates to a three-dimensional ultrasonic super-resolution method based on nano liquid drops.
Background
The ultrasonic super-resolution imaging obtains a high-resolution ultrasonic micro-blood flow image with large depth and breaking through diffraction limit by tracking the position of the injected contrast microbubbles, so that the imaging of micro-blood vessels in a tumor area is realized. With the development of materials and synthetic biotechnology, microparticles such as drug-loaded microbubbles, bacteria and cells can be used as ultrasound contrast agents to realize visualization of deep microvessels. The Mickaael Tanter team of French institute in 2015 provides an ultrasonic positioning microscopic imaging technology (ULM) for the first time, which acquires the motion information of microbubbles in blood vessels by a super-high-speed plane wave acquisition method, extracts the signals of flowing microbubbles in static tissues by using a continuous image difference algorithm, positions the centers of mass of the microbubbles by using a deconvolution point spread function, and breaks through the ultrasonic diffraction limit to realize the 10 mu m resolution of microvascular imaging of the rat brain. In addition, the university of Qinghai Luo Jian teaching team provides a fast and high-robustness microbubble positioning method based on deep learning, but the method can achieve good positioning accuracy only under the condition of high microbubble concentration.
However, the microbubble contrast agent currently used clinically is used as a blood pool contrast agent, and it takes up to several minutes to perform complete perfusion in the microvascular network, thereby resulting in an increase in data acquisition and image reconstruction time. The microbubble contrast agent is relatively unstable in the living body, and can be metabolized out of the human body through the pulmonary circulation after 3-5 minutes, so that the contrast signal is sharply reduced. Moreover, artifacts due to tissue or organ motion have been a bottleneck limiting the quality of ultrasound super-resolution imaging.
Therefore, a three-dimensional ultrasonic super-resolution method based on nano liquid drops for accelerating the data acquisition and image reconstruction time of three-dimensional ultrasonic super-resolution imaging is needed to be proposed.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a three-dimensional ultrasonic super-resolution method based on nano liquid drops.
In order to solve the technical problems, the invention provides the following technical scheme:
the invention provides a three-dimensional ultrasonic super-resolution method based on nano liquid drops, which comprises the following steps:
s1, preprocessing nano-liquid drops: filtering the nano droplets by adopting a polytetrafluoroethylene film to obtain a monodisperse nano droplet solution;
s2, activating nano liquid drops, namely firstly, activating the nano liquid drops in a target area in a holographic field mode by adopting a two-dimensional area array; then, scanning a target area by adopting three-dimensional plane waves with different angles, transmitting m three-dimensional plane waves within T1ms, and performing multi-angle compounding on the acquired echo signals to complete the activation and imaging of nano liquid drops once; finally, repeatedly activating and imaging the nano liquid drops to obtain time sequence images of a plurality of groups of contrast modes;
s3, performing three-dimensional motion compensation on the ultrasonic contrast image obtained in the step S2 by adopting two nonlinear optimization methods of affine transformation image registration and B-sp line-based free deformation registration, so as to obtain a registered ultrasonic image sequence;
s4, filtering background signals from the registered ultrasonic image sequence obtained in the step S3 by using a time-space domain singular value decomposition filtering algorithm, wherein the ultrasonic image sequence is expressed as a matrix S (n) x ,n y ,n z ,n t ) Wherein n is x ，n y ，n z Represents the number of sampling points in the three-dimensional space, n t Representing the number of samples along the time dimension, reconstruct this matrix into a two-dimensional casorai matrix S (n x ×n y ×n z ,n t ) And the processed time-space domain singular value decomposition filtering algorithm is expressed as:
wherein, th1 and th2 respectively represent singular value critical points for distinguishing background signals, contrast signals and noise signals, the algorithm adopts an adaptive threshold selection method, namely, the threshold th1 is determined by the position with the maximum curvature of a singular value energy curve, the th2 is determined by the position of an inflection point with gentle curve, and lambda before i=th1 and after i=th2 are determined i =0 to extract contrast signals and suppress clutter signals;
s5, positioning of contrast signals is achieved by adopting a three-dimensional cross-correlation method, and the method comprises the following steps:
s51, carrying out Gaussian fitting on a calibrated ultrasonic imaging point spread function to obtain a template Gaussian kernel, and carrying out normalized three-dimensional cross-correlation on the template Gaussian kernel and an extracted contrast agent image sequence:
wherein f represents the contrast agent image, t 1 Representing the template gaussian kernel image,representing the mean value of a template gaussian kernel image, c representing the cross-correlation coefficient, x, y, z representing the three-dimensional spatial position, f (x, y, z) representing the pixel values at the (x, y, z) coordinates in the contrast agent image, u, v, w representing the amount of translation of the contrast agent template image in the contrast agent image along the x, y, z axes, respectively,/->Representing an average value of pixels of the contrast agent image in the covered region as the template gaussian kernel image translates in the contrast agent image;
s52, setting a threshold value to remove a part with a lower correlation coefficient, and then taking the coordinate of the local maximum value of the phase relation number as the center coordinate of the contrast agent to realize the positioning of the three-dimensional space contrast signal; finally accumulating the positioned points in the frame to obtain a final super-resolution image; comparing the resolution of the final image with the theoretical limit resolution to verify the effectiveness of the positioning method;
s53, after extracting the central coordinates of each frame of contrast signals, pairing the contrast signals with the nearest adjacent two frames by using a Kuhn-Munkres algorithm, taking the distance between each microbubble of the adjacent two frames as a weight, constructing a bipartite graph with weight, initializing a pairing matrix M with n being the number of nodes based on the weight of the bipartite graph, setting M (i, j) as 1 for any element M (i, j) in the pairing matrix M if an augmented path exists between the nodes, and indicating that the nodes are paired; otherwise, set M (i, j) to 0, indicating that the node and the node are unpaired; and continuously updating the pairing matrix to minimize the total weight, and finally removing the matching of overlarge distance and zero distance by setting a threshold value to realize the tracking of the three-dimensional space contrast signal.
Preferably, the nano-droplets in step S1 are prepared by first generating microbubbles, and then condensing the microbubbles into nano-droplets by reducing the temperature and increasing the pressure of the microbubbles, and the preparation method specifically comprises the following steps:
s11, dissolving normal saline, propylene glycol and glycerol in DPPC and DSPE-PEG-2000, and then adding distearoyl phosphatidyl acetamide-polyethylene di-2000-folic acid into the mixture to prepare folic acid lipid solution so as to prepare lipid shells of nano-droplets;
s12, adding the folic acid lipid solution obtained in the step S11 into a glass bottle, exhausting air in the glass bottle by adopting an exhaust method, injecting perfluorobutane, then putting the glass bottle into a stirrer to shake the glass bottle sufficiently, and then putting the glass bottle into a saline solution mixture at the temperature of minus 10 ℃ to condense the glass bottle, thus finally obtaining nano droplets.
Preferably, in the step S11, the molar ratio of DPPC to DSPE-PEG-2000 is 9:1, the volume ratio of normal saline, propylene glycol and glycerin is 16:3:1, the molar ratio of DPPC, DSPE-PEG-2000 and distearoyl phosphatidyl acetamide-polyethylene di-2000-folic acid is 9:0.8:0.2, and the total lipid concentration of the folic acid lipid solution is 1mg/mL.
Preferably, in the preparation of the nanodrop in step S1, after the nanodrop is gasified into microbubbles, the gas phase needs to be kept in equilibrium with the interface of water, so the total pressure P in the gas phase g Vapor pressure P of nanodrop vap,PFC (T s,PFC ) And steam pressure of waterThe sum is that:
total pressure P outside the microbubble surface 0 Is the gas phase pressure P g And Laplaex pressureThe difference is that:
wherein γ is the surface tension between the nanodrop and water, and R (t) is the distance from the center of the nanodrop to the surface;
the vapor pressure of the nanodrop core and water can be described by empirical equations:
wherein A is 1 B, C, D and E are constants, T s The temperature corresponding to different vapor pressures.
Preferably, the pressure and temperature required to activate the nanodroplets in step S2 are derived from the antoni vapor pressure equation derived from the clausius-clappelone equation:
wherein P is i Is the ambient pressure, T, required to activate the nanodrop 1 Is the ambient temperature around the nanodrop, F, G, H is a constant measured experimentally;
the laplace pressure required to excite a single nano-droplet is predicted by the particle size of the single nano-droplet according to an ideal gas state equation:
wherein ρ is i Is the density of nano-droplets, R is the ideal gas constant, T 2 Is the temperature, r l Is the radius of the nano-droplet, m is the molar mass of the ideal gas, r g Is the radius of the microbubbles after excitation, P is the Laplaex pressure, and γ is the interfacial free energy.
Preferably, the activation of the nanodrop in step S2 is also affected by the acoustic field pressure in the complex medium, and the activation threshold is:
P ∞ ＝P atm +ρ w gh+A 2 sinωt 2
wherein P is ∞ Is total pressure, P atm Represents atmospheric pressure ρ w gh represents hydrostatic pressure, asinωt represents local sound pressure change generated by sound field, h is the position of nano droplet below water surface, ρ w Is the density of water, g is the gravitational acceleration, A 2 Is the magnitude of the sound wave, ω is the angular velocity, t 2 Is time.
Preferably, the step S3 performs three-dimensional motion compensation by adopting two nonlinear optimization methods of affine transformation image registration and B-spline based free deformation registration, and specifically includes the following steps:
s31, representing the affine transformation of the image in the three-dimensional space as:
wherein θ 11 、θ 12 、θ 13 、θ 14 、θ 21 、θ 22 、θ 23 、θ 24 、θ 31 、θ 32 、θ 33 、θ 34 Representing 12 degrees of freedom of affine transformation;
s32, dividing the moving image obtained in the step S31 into a plurality of 3D matrix lattices, calculating each individual pixel to obtain a B spline control node of each 3D matrix, and supposing that the B spline control node is along S=UDV * Is s=udv respectively * Together s=udv * A control node, then the free deformation registrationThe problem becomes a compound containing s=udv * Nonlinear optimization problem of degrees of freedom, i.e. the generation contains an unknown of all degrees of freedom s=udv * The method comprises the steps of carrying out a first treatment on the surface of the Interpolation is carried out on each pixel point on the moving image, and the position of each pixel point after deformation is calculated by utilizing a B-spline function, so that nonlinear deformation of the moving image is realized, smooth processing of control points is realized, and the registration accuracy of the image is improved; wherein the free deformation is expressed as a three-dimensional tensor product of a one-dimensional cubic B-spline:
wherein, [X，Y，Z]representing the image size;
the ith cubic B-spline basis function, written as Bi (u), and therefore, the cubic B-spline basis function B l (u)、B m (v) B (B) n The expression (w) is:
B 0 (u)＝(1-u) 3 /6
B 1 (u)＝(3u 3 -6u 2 +4)/6
B 2 (u)＝(-3u 3 +3u 2 +3u+1)/6
B 3 (u)＝u 3 /6
comparing the moved image with the reference image, evaluating the registration accuracy by calculating registration errors, and introducing a cost function C (theta, phi) to optimize the image registration effect, wherein the expression is as follows:
C(θ，ψ)＝-C similarity (I(t 0 )，T(I(t)))+λC smooth (T)
wherein C is similarity Representing mutual information of globally transformed images, C smooth Penalty function representing local transformation, λ representing weighting parameters, t and t0 representing two time nodes in resolution, I representing the imageThe image intensity of the midpoint, T, represents the function gradient;
finally, by finding the parameters theta and phi that minimize the cost function, accurate registration of the three-dimensional ultrasound image is achieved.
Compared with the prior art, the invention has the following beneficial effects:
(1) The invention utilizes the targeting and drug carrying capability of nano liquid drops, can realize rapid activation and accurate control, enables the nano liquid drops to be selectively activated in time and space to provide ultrasonic contrast signals, develops microbubbles through three-dimensional plane waves, realizes tumor microvascular ultrasonic super-resolution imaging, and determines tumor structures and boundaries. Therefore, by combining with the ultrasonic super-resolution imaging technology, the nano liquid drops are precisely activated and super-resolution imaged in the tumor area, the distribution and characteristics of micro blood vessels in the tumor are displayed, the application of the nano liquid drops in front biomedical aspects such as early diagnosis of breast cancer, targeted drug delivery, precise treatment and the like is promoted, and the nano liquid drops have important scientific significance and application value. The ultrasonic super-resolution imaging has very high space-time resolution, but the use of microbubbles requires low contrast agent concentration and long acquisition time, and the space-time distribution of the microbubbles can not be controlled almost, compared with the microbubble contrast agent, the nano liquid drops have excellent chemical medicine carrying and physical cavitation characteristics, and the ultrasonic super-resolution imaging accelerating technology has unique advantages.
(2) The preparation of the monodisperse nano liquid drops can enable the activation and imaging efficiency of the nano liquid drops to be more stable and uniform, and flexible and rapid three-dimensional ultrasonic super-resolution imaging can be realized under a low flow environment. Acoustic activation and deactivation of nanodroplets has unique functions not possessed by other non-invasive imaging modalities that can avoid problems in perfusion imaging, i.e., contrast agent dynamics modeling may be affected by variable transmission delays or fitting errors. Two adjacent droplets may be broken down into microbubbles due to slow flow in the microvasculature, but the uniqueness of the nanodroplets and their low spatiotemporal nature with other scatterers may allow them to separate very slow or stationary nanodroplet signals from tissue and fluids.
(3) The invention compensates the motion in the three-dimensional space by using two nonlinear optimization methods of two-stage image registration and B-spline free deformation registration, and minimizes the influence of the motion on the ultrasonic super-resolution imaging quality so as to break through the bottleneck of restricting the ultrasonic super-resolution imaging quality due to artifacts caused by the motion. And the three-dimensional ultrasonic super-resolution imaging based on the two-dimensional area array is adopted, so that the imaging quality is ensured and the acquisition speed of the three-dimensional ultrasonic super-resolution imaging data is improved.
(4) The invention utilizes the large-scale spatial activation of the two-dimensional ultrasonic probe and the multi-angle three-dimensional imaging, can definitely target the imaging and activation mechanism of the nano liquid drop under the three-dimensional ultrasonic, and obviously shortens the acquisition and reconstruction time of the three-dimensional ultrasonic super-resolution image, thereby realizing the rapid three-dimensional micro-vessel imaging with large depth and micron level and promoting the application of the three-dimensional micro-vessel imaging in the aspect of early and accurate diagnosis of diseases.
Drawings
FIG. 1 is a flow chart of a three-dimensional ultrasonic super-resolution method based on nano-droplets of the invention;
FIG. 2 is a schematic diagram showing particle size and concentration analysis of contrast agent in nanodroplets in example 1 of the present invention;
fig. 3 is a schematic diagram of a three-dimensional fast image acquisition algorithm for holographic field activated nanodroplets at multiple focal points in space.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention. Embodiments 1 to 5 of the present invention implement three-dimensional ultrasonic super resolution based on nano droplets according to a flowchart as shown in fig. 1.
Example 1: and (3) preparing nano liquid drops.
The embodiment prepares the monodisperse folic acid targeted nano-droplets with targeting to the breast cancer folic acid receptor through the steps of dissolving, ventilating, oscillating, condensing, filtering and the like of lipid powder; then, the physical and chemical properties and the acoustic properties of the prepared folic acid targeted nano liquid drop contrast agent are detected and analyzed, and parameters such as particle size, concentration, zeta potential, activation range and depth of nano liquid drops and the like are included, so that the optimal effect of ultrasonic super-resolution imaging can be achieved through the activation of the nano liquid drops. The particle size and concentration analysis of the contrast agent of the nano-droplets is shown in fig. 2.
(1) Nanodroplets were prepared by dissolving 9:1 molar ratio of DPPC and DSPE-PEG-2000 in 16:3:1 volume ratio of physiological saline, propylene glycol and glycerol to achieve a total lipid concentration of 1mg/mL. Then distearoyl phosphatidyl acetamide-polyethylenimine-2000-folate (DSPE-PEG-2000-fonate) was added to the mixture, and DPPC was maintained at a molar ratio of DSPE-PEG-2000 to DSPE-PEG-2000-fonate of 9:0.8:0.2, thereby making a folic acid lipid solution. 1mL of the lipid solution was placed in a 2mL glass bottle, and the air in the glass bottle was vented by degassing and perfluorobutane was injected. The vial was then placed in a stirrer and shaken for one minute to allow full shaking. And then placing the glass bottle into a saline water mixture at the temperature of minus 10 ℃ to condense the saline water mixture, and finally obtaining the nano liquid drops. The nano droplets are filtered by adopting a 200nm polytetrafluoroethylene film to obtain a monodisperse nano droplet solution with the average particle size of 200 nm. The preparation of monodisperse nano-droplets can enable the activation and imaging efficiency of nano-droplets to be more stable and uniform. The nano liquid drops are prepared by firstly generating microbubbles, and then condensing the microbubbles into the nano liquid drops by reducing the temperature and increasing the pressure of the microbubbles.
(2) In the preparation process of the nano-droplets, after the nano-droplets are gasified into microbubbles, the gas phase needs to be kept in balance with the interface of water, so the total pressure P in the gas phase g Vapor pressure P of nanodrop vap,PFC (T s,PFC ) And steam pressure of waterThe sum is that:
total pressure P outside the microbubble surface 0 Is the gas phase pressure P g And Laplaex pressureThe difference is that:
wherein γ is the surface tension between the nanodrop and water, and R (t) is the distance from the center of the nanodrop to the surface;
the vapor pressure of the nanodrop core and water can be described by empirical equations:
wherein A is 1 B, C, D and E are constants, T s Corresponding to different vapor pressures
(3) The pressure and temperature required to activate the nanodroplets were derived from the antoni vapor pressure equation derived from the clausius-clappelone equation:
where P is the ambient pressure required to activate the nanodrop, T is the ambient temperature around the nanodrop, A, B, C is the experimentally measured constant; the laplace pressure required to excite a single nano-droplet is predicted by the particle size of the single nano-droplet according to an ideal gas state equation:
wherein ρ is i Is the density of nano-droplets, R is the ideal gas constant, T is the temperature, R l Is the radius of the nano-droplet, m is the molar mass, r g Is the radius of the microbubbles after excitation, P is the Laplaex pressure, and γ is the interfacial free energy.
(4) The activation of nanodroplets is also affected by acoustic field pressure in complex media, which is activated by the threshold:
P ∞ ＝P atm +ρ w gh+A 2 sinωt 2
wherein P is ∞ Is total pressure, P atm Represents atmospheric pressure ρ w gh represents hydrostatic pressure, asinωt represents local sound pressure change generated by sound field, h is the position of nano droplet below water surface, ρ w Is the density of water, g is the gravitational acceleration, A 2 Is the magnitude of the sound wave, ω is the angular velocity, t 2 Is time.
Example 2: and establishing a mouse breast cancer xenograft model.
Selecting a mouse triple negative breast cancer cell strain 4T1, culturing with a RMPI-1640 culture medium containing 10% fetal bovine serum, adding 100U/L penicillin and 10mg/ml streptomycin into the culture medium, culturing in a constant temperature incubator with the volume fraction of CO2 of 5% at 37 ℃, observing the cell wall adhesion condition the next day, and changing the liquid. Breast cancer cells with good adherent growth are digested by 0.25% trypsin, and cells in logarithmic growth phase are selected for experiment. 8 female BALB/c mice of SPF grade 7-8 weeks old are selected, the weight is 20-25g, 4T1 cells are washed 3 times with sterile physiological saline and diluted appropriately, tumor cell suspension with the concentration of 1X 107/ml is prepared according to 1X 106 cells/mouse, the cell suspension is inoculated on fat pads near the 4 th and 5 th pair of nipples of the mice by subcutaneous injection, the tumor size is measured by calipers every day, and when the tumor diameter reaches 6-8mm, the mice are randomly grouped for experiments.
And obtaining a time intensity curve through an ultrasonic contrast image, and verifying the ultrasonic development effect of the folic acid targeted nano-droplets in the mouse body according to the analyzed kinetic parameters. According to the relation between the activation efficiency and the activation range of single-focus sound fields with different intensities on nano liquid drops in a three-dimensional space, holographic sound field optimization parameters (the number of focuses, the distance, the intensity and the like) of multi-focus distribution in the space and the optimal time sequence combination of a holographic sound field excitation sequence and a three-dimensional plane wave acquisition sequence are determined, so that the development activation of the high-efficiency phase-change micro-foaming of the nano liquid drops is realized to the maximum extent.
Example 3: the nanodroplets are activated.
Activating nano liquid drops in a target area in a holographic field mode by adopting a 32 multiplied by 32 two-dimensional area array; then, scanning a target area by adopting three-dimensional plane waves with different angles, transmitting m three-dimensional plane waves within T1ms, and performing multi-angle compounding (frame rate 100 fps) on the acquired echo signals to complete the activation and imaging of nano liquid drops at one time; finally, by repeatedly activating and imaging the nano-droplets (as shown in fig. 3), singular value decomposition filtering processing is performed on the obtained multiple groups of time-series images to obtain super-resolution images. The influence of different excitation times T1 on the ultrasonic super-resolution image quality is studied, and meanwhile, the excitation time T1 is optimally determined in consideration of the system data throughput.
After the nano liquid drops are activated, the generated microbubble contrast signals are acquired by adopting multi-angle three-dimensional plane waves, and the data acquisition time is shortened by optimizing the parameters of the emission sequence through the corresponding relation between the optimal activation efficiency of the nano liquid drops under different concentrations and the intensity and activation frequency of an activation sound field, so that the imaging quality is ensured and the acquisition speed of three-dimensional ultrasonic super-resolution imaging data is improved.
Example 4: three-dimensional motion compensation.
Artifacts caused by motion have been the bottleneck limiting the quality of ultrasound super-resolution imaging. Three-dimensional ultrasound super-resolution imaging requires more complex algorithms to compensate for motion in three-dimensional space relative to two-dimensional ultrasound super-resolution imaging. According to the invention, three-dimensional motion compensation is performed by two nonlinear optimization methods, namely affine transformation-based image registration and B-spline-based free deformation registration, namely, the influence of global motion is eliminated by affine transformation, and then the influence on the positioning accuracy of contrast signals caused by image distortion is compensated by free deformation registration, so that the accurate registration of three-dimensional images is finally realized, and a registered ultrasonic image sequence is obtained. The method specifically comprises the following steps:
s31, representing the affine transformation of the image in the three-dimensional space as:
wherein θ 11 、θ 12 、θ 13 、θ 14 、θ 21 、θ 22 、θ 23 、θ 24 、θ 31 、θ 32 、θ 33 、θ 34 Representing 12 degrees of freedom of affine transformation;
s32, dividing the moving image obtained in the step S31 into a plurality of 3D matrix lattices, calculating each individual pixel to obtain a B spline control node of each 3D matrix, and supposing that the B spline control node is along S=UDV * Is s=udv respectively * Together s=udv * A control node, the free deformation registration problem becomes a control node containing s=udv * Nonlinear optimization problem of degrees of freedom, i.e. the generation contains an unknown of all degrees of freedom s=udv * The method comprises the steps of carrying out a first treatment on the surface of the Interpolation is carried out on each pixel point on the moving image, and the position of each pixel point after deformation is calculated by utilizing a B-spline function, so that nonlinear deformation of the moving image is realized, smooth processing of control points is realized, and the registration accuracy of the image is improved; wherein the free deformation is expressed as a three-dimensional tensor product of a one-dimensional cubic B-spline:
wherein, [X，Y，Z]representing the image size;
the ith cubic B-spline basis function, written as Bi (u), and therefore, the cubic B-spline basis function B l (u)、B m (v) B (B) n The expression (w) is:
B 0 (u)＝(1-u) 3 /6
B 1 (u)＝(3u 3 -6u 2 +4)/6
B 2 (u)＝(-3u 3 +3u 2 +3u+1)/6
B 3 (u)＝u 3 /6
comparing the moved image with the reference image, evaluating the registration accuracy by calculating registration errors, and introducing a cost function C (theta, phi) to optimize the image registration effect, wherein the expression is as follows:
C(θ，ψ)＝-C similarity (I(t 0 )，T(I(t)))+λC smooth (T)
wherein C is similarity Representing mutual information of globally transformed images, C smooth A penalty function representing local transformation, lambda represents a weighting parameter, T and T0 represent two time nodes in a distinguishing mode, I represents image intensity of points in an image, and T represents a function gradient;
finally, by finding the parameters theta and phi that minimize the cost function, accurate registration of the three-dimensional ultrasound image is achieved.
Example 5: and removing the background signal, extracting the contrast signal and realizing tracking of the contrast signal.
And carrying out decorrelation processing on the background signal and the contrast signal according to the space-time characteristics of the signal based on a three-dimensional filtering algorithm of singular value decomposition, and removing the background signal by rejecting low-order singular values with larger energy occupation in the singular value decomposition so as to extract the flowing contrast signal. After the contrast signals are extracted, a three-dimensional cross-correlation algorithm is adopted, normalized cross-correlation processing is carried out on the contrast signals in each frame and the calibrated point spread function signals, the local maximum value position of the cross-correlation coefficient is extracted as the center coordinates of the contrast signals, and the centers of the contrast signals in each frame are accumulated to obtain a final super-resolution image. And, the motion of the adjacent interframe contrast signals is tracked by using a Kuhn-Munkres pairing algorithm, so that a micro blood flow velocity image is further obtained.
(1) Filtering background signals from the obtained registered ultrasonic image sequence by using a time-space domain singular value decomposition filtering algorithm, wherein the ultrasonic image sequence is expressed as a matrix S (n x ,n y ,n z ,n t ) Wherein n is x ，n y ，n z Represents the number of sampling points in the three-dimensional space, n t Representing the number of samples along the time dimension, reconstructing the matrix into twoVitamin casorai matrix S (n x ×n y ×n z ,n t ) After being processed by a time-space domain singular value decomposition filtering algorithm, the data are expressed as follows:
wherein, th1 and th2 respectively represent singular value critical points for distinguishing background signals, contrast signals and noise signals, the algorithm adopts an adaptive threshold selection method, namely, the threshold th1 is determined by the position with the maximum curvature of a singular value energy curve, the th2 is determined by the position of an inflection point with gentle curve, and lambda before i=th1 and after i=th2 are determined i =0 to extract contrast signal and suppress clutter signal.
(2) The method for realizing the positioning of the contrast signal by adopting the three-dimensional cross-correlation comprises the following steps:
s51, carrying out Gaussian fitting on a calibrated ultrasonic imaging point spread function to obtain a template Gaussian kernel, and carrying out normalized three-dimensional cross-correlation on the template Gaussian kernel and an extracted contrast agent image sequence:
wherein f represents the contrast agent image, t 1 Representing the template gaussian kernel image,representing the mean value of a template Gaussian kernel image, c representing the cross-correlation coefficient, x, y, z representing the three-dimensional spatial position, f (x, y, z) representing the pixel values at the (x, y, z) coordinates in the contrast agent image, u, v, w representing the amount of translation of the contrast agent template image in the contrast agent image along the x, y, z axes, respectively,/->Representing the average value of pixels of the contrast agent image in the covered region as the template Gaussian kernel image translates in the contrast agent image；
S52, setting a threshold value to remove a part with a lower correlation coefficient, and then taking the coordinate of the local maximum value of the phase relation number as the center coordinate of the contrast agent to realize the positioning of the three-dimensional space contrast signal; finally accumulating the positioned points in the frame to obtain a final super-resolution image; comparing the resolution of the final image with the theoretical limit resolution to verify the effectiveness of the positioning method;
s53, after extracting the central coordinates of each frame of contrast signals, pairing the contrast signals with the nearest adjacent two frames by using a Kuhn-Munkres algorithm, taking the distance between each microbubble of the adjacent two frames as a weight, constructing a bipartite graph with weight, initializing a pairing matrix M with n being the number of nodes based on the weight of the bipartite graph, setting M (i, j) as 1 for any element M (i, j) in the pairing matrix M if an augmented path exists between the nodes, and indicating that the nodes are paired; otherwise, set M (i, j) to 0, indicating that the node and the node are unpaired; and continuously updating the pairing matrix to minimize the total weight, and finally removing the matching of overlarge distance and zero distance by setting a threshold value to realize the tracking of the three-dimensional space contrast signal.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The three-dimensional ultrasonic super-resolution method based on the nano liquid drops is characterized by comprising the following steps of:
s1, preprocessing nano-liquid drops: filtering the nano droplets by adopting a polytetrafluoroethylene film to obtain a monodisperse nano droplet solution;
s2, activating nano liquid drops, namely firstly, activating the nano liquid drops in a target area in a holographic field mode by adopting a two-dimensional area array; then, scanning a target area by adopting three-dimensional plane waves with different angles, transmitting m three-dimensional plane waves within T1ms, and performing multi-angle compounding on the acquired echo signals to complete the activation and imaging of nano liquid drops once; finally, repeatedly activating and imaging the nano liquid drops to obtain time sequence images of a plurality of groups of contrast modes;
s3, performing three-dimensional motion compensation on the ultrasonic contrast image obtained in the step S2 by adopting two nonlinear optimization methods of affine transformation image registration and B-spline-based free deformation registration, so as to obtain a registered ultrasonic image sequence;
s4, filtering background signals from the registered ultrasonic image sequence obtained in the step S3 by using a time-space domain singular value decomposition filtering algorithm, wherein the ultrasonic image sequence is expressed as a matrix S (n) x ,n y ,n z ,n t ) Wherein n is x ，n y ，n z Represents the number of sampling points in the three-dimensional space, n t Representing the number of samples along the time dimension, reconstruct this matrix into a two-dimensional casorai matrix S (n x ×n y ×n z ,n t ) And the processed time-space domain singular value decomposition filtering algorithm is expressed as:
wherein, th1 and th2 respectively represent singular value critical points for distinguishing background signals, contrast signals and noise signals, the algorithm adopts an adaptive threshold selection method, namely, the threshold th1 is determined by the position with the maximum curvature of a singular value energy curve, the th2 is determined by the position of an inflection point with gentle curve, and lambda before i=th1 and after i=th2 are determined i =0 to extract contrast signals and suppress clutter signals;
s5, positioning of contrast signals is achieved by adopting a three-dimensional cross-correlation method, and the method comprises the following steps:
s51, carrying out Gaussian fitting on a calibrated ultrasonic imaging point spread function to obtain a template Gaussian kernel, and carrying out normalized three-dimensional cross-correlation on the template Gaussian kernel and an extracted contrast agent image sequence:
wherein f represents the contrast agent image, t 1 Representing the template gaussian kernel image, +.>Representing the mean value of the template gaussian kernel image, c representing the cross-correlation coefficient, x, y, z representing the three-dimensional spatial position, f (x, y, z) representing the pixel values at the (x, y, z) coordinates in the contrast agent image, u, v, w representing the amount of translation of the contrast agent template image in the contrast agent image along the x, y, z axes, respectively>Representing an average value of pixels of the contrast agent image in the covered region as the template gaussian kernel image translates in the contrast agent image;
s52, setting a threshold value to remove a part with a lower correlation coefficient, and then taking the coordinate of the local maximum value of the phase relation number as the center coordinate of the contrast agent to realize the positioning of the three-dimensional space contrast signal; finally accumulating the positioned points in the frame to obtain a final super-resolution image; comparing the resolution of the final image with the theoretical limit resolution to verify the effectiveness of the positioning method;
s53, after extracting the central coordinates of each frame of contrast signals, pairing the contrast signals with the nearest adjacent two frames by using a Kuhn-Munkres algorithm, taking the distance between each microbubble of the adjacent two frames as a weight, constructing a bipartite graph with weight, initializing a pairing matrix M with n being the number of nodes based on the weight of the bipartite graph, setting M (i, j) as 1 for any element M (i, j) in the pairing matrix M if an augmented path exists between the nodes, and indicating that the nodes are paired; otherwise, set M (i, j) to 0, indicating that the node and the node are unpaired; and continuously updating the pairing matrix to minimize the total weight, and finally removing the matching of overlarge distance and zero distance by setting a threshold value to realize the tracking of the three-dimensional space contrast signal.
2. The three-dimensional ultrasonic super-resolution method based on nano liquid drops according to claim 1, wherein the nano liquid drops in the step S1 are prepared by firstly generating microbubbles, and then condensing the microbubbles into nano liquid drops by reducing the temperature and increasing the pressure of the microbubbles, and the preparation method specifically comprises the following steps:
s11, dissolving normal saline, propylene glycol and glycerol in DPPC and DSPE-PEG-2000, and then adding distearoyl phosphatidyl acetamide-polyethylene di-2000-folic acid into the mixture to prepare folic acid lipid solution so as to prepare lipid shells of nano-droplets;
s12, adding the folic acid lipid solution obtained in the step S11 into a glass bottle, exhausting air in the glass bottle by adopting an exhaust method, injecting perfluorobutane, then putting the glass bottle into a stirrer to shake the glass bottle sufficiently, and then putting the glass bottle into a saline solution mixture at the temperature of minus 10 ℃ to condense the glass bottle, thus finally obtaining nano droplets.
3. The three-dimensional ultrasonic super-resolution method based on nano-droplets according to claim 2, wherein in the step S11, the molar ratio of DPPC to DSPE-PEG-2000 is 9:1, the volume ratio of physiological saline, propylene glycol and glycerin is 16:3:1, the molar ratio of DPPC, DSPE-PEG-2000 and distearoyl phosphatidyl acetamide-polyethylene-2000-folic acid is 9:0.8:0.2, and the total lipid concentration of folic acid lipid solution is 1mg/mL.
4. The three-dimensional ultrasonic super-resolution method based on nano-droplets according to claim 1, wherein in the preparation process of the nano-droplets in step S1, after the nano-droplets are gasified into microbubbles, the gas phase needs to be kept in equilibrium with the interface of water, so that the total pressure P in the gas phase g Vapor pressure P of nanodrop vap , PFC (T s,PFC ) And steam pressure of waterThe sum is that:
total pressure P outside the microbubble surface 0 Is the gas phase pressure P g And Laplaex pressureThe difference is that:
wherein γ is the surface tension between the nanodrop and water, and R (t) is the distance from the center of the nanodrop to the surface;
the vapor pressure of the nanodrop core and water can be described by empirical equations:
wherein A is 1 B, C, D and E are constants, T s The temperature corresponding to different vapor pressures.
5. The three-dimensional ultrasonic super-resolution method based on nano-droplets according to claim 1, wherein the pressure and temperature required for activating the nano-droplets in step S2 are obtained according to the antoni vapor pressure equation derived from the clausius-clappelone equation:
wherein P is i Is the ambient pressure, T, required to activate the nanodrop 1 Is the ambient temperature around the nano-droplet, F, G, H is the result of experimentsA measured constant;
the laplace pressure required to excite a single nano-droplet is predicted by the particle size of the single nano-droplet according to an ideal gas state equation:
wherein ρ is i Is the density of nano-droplets, R is the ideal gas constant, T 2 Is the temperature, r l Is the radius of the nano-droplet, m is the molar mass of the ideal gas, r g Is the radius of the microbubbles after excitation, P is the Laplaex pressure, and γ is the interfacial free energy.
6. The three-dimensional ultrasonic super-resolution method based on nano-droplets according to claim 1, wherein the activation of nano-droplets in step S2 is further affected by the acoustic field pressure in the complex medium, and the activation threshold is:
P ∞ ＝P atm +ρ w gh+A 2 sinωt 2
wherein P is ∞ Is total pressure, P atm Represents atmospheric pressure ρ w gh represents hydrostatic pressure, asinωt represents local sound pressure change generated by sound field, h is the position of nano droplet below water surface, ρ w Is the density of water, g is the gravitational acceleration, A 2 Is the magnitude of the sound wave, ω is the angular velocity, t 2 Is time.
7. The three-dimensional ultrasonic super-resolution method based on nano liquid drops according to claim 1, wherein the step S3 adopts two nonlinear optimization methods of affine transformation image registration and B-spline based free deformation registration for three-dimensional motion compensation, and specifically comprises the following steps:
s31, representing the affine transformation of the image in the three-dimensional space as:
wherein θ 11 、θ 12 、θ 13 、θ 14 、θ 21 、θ 22 、θ 23 、θ 24 、θ 31 、θ 32 、θ 33 、θ 34 Representing 12 degrees of freedom of affine transformation;
s32, dividing the moving image obtained in the step S31 into a plurality of 3D matrix lattices, calculating each individual pixel to obtain a B spline control node of each 3D matrix, and supposing that the B spline control node is along S=UDV * Is s=udv respectively * Together s=udv * A control node, the free deformation registration problem becomes a control node containing s=udv * Nonlinear optimization problem of degrees of freedom, i.e. the generation contains an unknown of all degrees of freedom s=udv * The method comprises the steps of carrying out a first treatment on the surface of the Interpolation is carried out on each pixel point on the moving image, and the position of each pixel point after deformation is calculated by utilizing a B-spline function, so that nonlinear deformation of the moving image is realized, smooth processing of control points is realized, and the registration accuracy of the image is improved; wherein the free deformation is expressed as a three-dimensional tensor product of a one-dimensional cubic B-spline:
wherein, [X，Y，Z]representing the image size;
the ith cubic B-spline basis function, written as Bi (u), and therefore, the cubic B-spline basis function B l (u)、B m (v) B (B) n The expression (w) is:
B 0 (u)＝(1-u) 3 /6
B 1 (u)＝(3u 3 -6u 2 +4)/6
B 2 (u)＝(-3u 3 +3u 2 +3u+1)/6
B 3 (u)＝u 3 /6
comparing the moved image with the reference image, evaluating the registration accuracy by calculating registration errors, and introducing a cost function C (theta, phi) to optimize the image registration effect, wherein the expression is as follows:
C(θ,ψ)＝-C similarity (I(t 0 ),T(I(t)))+λC smooth (T)
wherein C is similarity Representing mutual information of globally transformed images, C smooth A penalty function representing local transformation, lambda represents a weighting parameter, T and T0 represent two time nodes in a distinguishing mode, I represents image intensity of points in an image, and T represents a function gradient;
finally, by finding the parameters theta and phi that minimize the cost function, accurate registration of the three-dimensional ultrasound image is achieved.
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| CN110772285A (en) * | 2019-10-31 | 2020-02-11 | 南京景瑞康分子医药科技有限公司 | Ultrasonic super-resolution imaging method |
| CN112450983A (en) * | 2020-11-19 | 2021-03-09 | 深圳先进技术研究院 | Super-resolution imaging method and system |
| WO2023039353A2 (en) * | 2021-09-08 | 2023-03-16 | The Board Of Trustees Of The University Of Illinois | Real-time super-resolution ultrasound microvessel imaging and velocimetry |
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