CN114098817A - High frame rate ultrasonic image blood vessel wall motion detail tracking method, system, equipment and readable storage medium - Google Patents
High frame rate ultrasonic image blood vessel wall motion detail tracking method, system, equipment and readable storage medium Download PDFInfo
- Publication number
- CN114098817A CN114098817A CN202111372365.3A CN202111372365A CN114098817A CN 114098817 A CN114098817 A CN 114098817A CN 202111372365 A CN202111372365 A CN 202111372365A CN 114098817 A CN114098817 A CN 114098817A
- Authority
- CN
- China
- Prior art keywords
- image
- tracking
- singular
- images
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000033001 locomotion Effects 0.000 title claims abstract description 67
- 238000000034 method Methods 0.000 title claims abstract description 49
- 210000004204 blood vessel Anatomy 0.000 title claims abstract description 45
- 238000003860 storage Methods 0.000 title claims abstract description 20
- 239000011159 matrix material Substances 0.000 claims abstract description 70
- 238000001914 filtration Methods 0.000 claims abstract description 45
- 238000003384 imaging method Methods 0.000 claims abstract description 24
- 230000002792 vascular Effects 0.000 claims abstract description 20
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 18
- 238000004364 calculation method Methods 0.000 claims abstract description 13
- 238000002604 ultrasonography Methods 0.000 claims description 21
- 239000013598 vector Substances 0.000 claims description 20
- 238000004590 computer program Methods 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 11
- 230000008569 process Effects 0.000 claims description 6
- 238000012285 ultrasound imaging Methods 0.000 claims description 5
- 238000013329 compounding Methods 0.000 claims description 4
- 230000008676 import Effects 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 2
- 230000008054 signal transmission Effects 0.000 claims description 2
- 230000017531 blood circulation Effects 0.000 abstract description 2
- 230000008859 change Effects 0.000 description 10
- 238000010586 diagram Methods 0.000 description 9
- 238000004422 calculation algorithm Methods 0.000 description 7
- 230000010349 pulsation Effects 0.000 description 7
- 238000006073 displacement reaction Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 230000000747 cardiac effect Effects 0.000 description 4
- 230000000737 periodic effect Effects 0.000 description 4
- 239000002131 composite material Substances 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 210000001715 carotid artery Anatomy 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000008520 organization Effects 0.000 description 2
- 201000001320 Atherosclerosis Diseases 0.000 description 1
- 208000034189 Sclerosis Diseases 0.000 description 1
- 208000007536 Thrombosis Diseases 0.000 description 1
- 210000001367 artery Anatomy 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 235000006694 eating habits Nutrition 0.000 description 1
- 238000002592 echocardiography Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012805 post-processing Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 208000019553 vascular disease Diseases 0.000 description 1
- 230000006439 vascular pathology Effects 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
- A61B8/0891—Detecting organic movements or changes, e.g. tumours, cysts, swellings for diagnosis of blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/02—Measuring pulse or heart rate
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/48—Diagnostic techniques
- A61B8/485—Diagnostic techniques involving measuring strain or elastic properties
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Surgery (AREA)
- Pathology (AREA)
- Radiology & Medical Imaging (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Physics & Mathematics (AREA)
- Molecular Biology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Vascular Medicine (AREA)
- Cardiology (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
Abstract
The invention discloses a method, a system, equipment and a readable storage medium for tracking the details of the vascular wall motion of a high frame rate ultrasonic image, wherein the method comprises the steps of carrying out high frame rate ultrasonic imaging on the vascular wall to form a cluster of images, carrying out filtering based on singular value decomposition on the cluster of images, recombining the images into a multi-dimensional matrix describing information of each frame, and recovering the multi-dimensional matrix into a cluster of images; initializing an image, selecting a point on a blood vessel wall on a first frame image as a central point of a tracking block, defining the size of the tracking block, and selecting the point with the largest cross-correlation value as a tracking result through cross-correlation calculation to obtain a matched central point and a corresponding image block; and analyzing the horizontal and vertical coordinates of the central point of the image of the tracking result to analyze the heart rate or the elasticity of the blood vessel or dynamically playing the tracking result, and observing the image information. With high frame rate imaging, the motion detail information of the tracking record is increased. The difference between tissue and blood flow components in the ultrasonic image and random noise is combined, and the accuracy of motion tracking is effectively improved.
Description
Technical Field
The invention belongs to the technical field of vascular wall motion tracking in ultrasonic vascular imaging, and particularly belongs to a high frame rate ultrasonic image vascular wall motion detail tracking method, system, equipment and readable storage medium.
Background
With the change of life style and eating habits of people, more and more people will generate blood vessel related diseases, such as thrombus, blood vessel plaque, blood vessel atherosclerosis and the like. If the corresponding vascular pathology occurs in an artery, it will have more serious consequences. The same clinical manifestations of these diseases are the changes in vascular elasticity, i.e. the arterial vessel becomes weak with the pulsation of the heart ejection, and the displacement of the vessel wall will be small with one pulsation.
In the existing clinical imaging technology, a B-mode ultrasonic image is used as a traditional ultrasonic imaging mode, and can image a blood vessel to reflect a clear blood vessel wall. Based on the real-time characteristic of ultrasonic imaging, the blood vessel in the B-mode ultrasonic image is regularly pulsating, and the elasticity of the blood vessel can be determined through the displacement of pulsation of the blood vessel wall, so that the degree of vascular diseases such as plaque, sclerosis and the like can be reflected.
The method for tracking the motion of the ultrasound image can be roughly classified into a logical algorithm and a non-logical algorithm. The logic algorithm calculates the similarity of partial areas in two adjacent frames of images by analyzing the image pixels so as to carry out quantitative judgment. The non-logic algorithm refers to a machine learning-based method, and features related to image similarity are extracted by analyzing and analyzing a large number of images, so that prediction of image tracking is achieved. In practical applications, the logic algorithm is gradually replaced by the non-logic algorithm, because speckle and non-linear signals exist in the ultrasound image, which are noise signals for similarity calculation of the ultrasound image, and the quantitative analysis of the similarity is seriously affected. Furthermore, another problem faced by the current stage of vessel wall motion tracking is that the frame rate of the ultrasound image acquired by line scan is only about 40Hz, which is not enough to reflect the motion details of the vessel wall.
Therefore, it is desirable to filter out random noise signals in the image by designing a filtering method so as to make the motion tracking more accurate, and to design the acquisition mode to record the details of the vessel wall motion.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method, a system, a device and a readable storage medium for tracking the details of the vessel wall motion of a high frame rate ultrasonic image, which increase the motion details information of tracking record through high frame rate imaging. The difference between tissue and blood flow components in the ultrasonic image and random noise is combined, and the accuracy of motion tracking is effectively improved.
In order to achieve the purpose, the invention provides the following technical scheme:
a high frame rate ultrasonic image blood vessel wall movement detail tracking method comprises the following processes,
carrying out high frame rate ultrasonic imaging on the vascular wall to form a cluster of images, carrying out filtering based on singular value decomposition on the cluster of images, recombining the images into a multi-dimensional matrix describing information of each frame, and recovering the multi-dimensional matrix into a cluster of images;
initializing an image, selecting a point on a blood vessel wall on a first frame image as a central point of a tracking block, defining the size of the tracking block, and selecting the point with the largest cross-correlation value as a tracking result through cross-correlation calculation to obtain a matched central point and a corresponding image block;
and analyzing the horizontal and vertical coordinates of the central point of the image of the tracking result to analyze the heart rate or the elasticity of the blood vessel or dynamically playing the tracking result, and observing the image information.
Preferably, plane waves are used for high frame rate ultrasound imaging of the vessel wall.
Preferably, the high frame rate ultrasound imaging of the vessel wall comprises in particular the following procedures,
firstly, ultrasonic signal transmission is carried out on a blood vessel wall, and the transmission signal is a plane wave ultrasonic signal; then, receiving ultrasonic signals, wherein all array elements of the ultrasonic transducer participate in receiving in a full-aperture receiving mode; transmitting at a plurality of angles, and receiving echo waves at each angle; finally, processing the received signals to obtain ultrasonic images; and performing beam forming on the echo of the transmitting signal at each angle, and performing multi-angle compounding to obtain an ultrasonic image.
Preferably, the filtering based on singular value decomposition specifically comprises the following procedure,
converting a cluster of images into a three-dimensional matrix, and reconstructing the three-dimensional matrix into a two-dimensional space-time matrix according to a time sequence; and decomposing the singular values of the space-time matrix, arranging the singular values and the singular vectors according to the sequence of the singular values from large to small, carrying out singular value zeroing and carrying out random noise filtering.
A high frame rate ultrasonic image vascular wall motion detail tracking system comprises an image import module, a singular space-time filtering module, a motion tracking module and a result analysis module;
the image importing module is used for importing a blood vessel wall image and integrating the image to form a three-dimensional matrix;
the singular space-time filtering module is used for filtering the three-dimensional matrix based on singular value decomposition, recombining the three-dimensional matrix into a multi-dimensional matrix describing each frame of information and recovering the multi-dimensional matrix into a cluster of images;
the motion tracking module is used for initializing, selecting a point on a blood vessel wall on a first frame image as a central point of a tracking block, defining the size of the tracking block, and selecting the point with the largest cross-correlation value as a tracking result through cross-correlation calculation;
the result analysis module is used for analyzing the horizontal and vertical coordinates of the central point of each image obtained by tracking to analyze the heart rate or the elasticity of blood vessels or dynamically playing the tracking result and observing the image information.
Preferably, the singular space-time filtering module includes: the image reconstruction module, the singular value decomposition module, the space-time filtering module and the image inverse reconstruction module;
the image reconstruction module is used for reconstructing a three-dimensional matrix obtained by integrating a cluster of images into a two-dimensional space-time matrix according to a time sequence;
the singular value decomposition module is used for decomposing the singular values of the space-time matrix and arranging the singular values and the singular vectors according to the sequence of the singular values from large to small;
the space-time filtering module is used for filtering a space-time matrix represented by singular values and singular vectors;
and the image inverse reconstruction module is used for recombining the filtered singular values and singular vectors into a two-dimensional space-time matrix, recombining the two-dimensional space-time matrix into a three-dimensional matrix and recovering the three-dimensional matrix into a cluster of images.
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of a high frame rate ultrasound image vessel wall motion detail tracking method as claimed in any one of the above.
A computer readable storage medium storing a computer program which when executed by a processor implements the steps of a high frame rate ultrasound image vessel wall motion detail tracking method as claimed in any one of the above.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention provides a method for tracking details of vascular wall motion of an ultrasonic image with a high frame rate, which adopts plane wave imaging and combines a multi-angle composite imaging method, thereby improving the frame rate of ultrasonic imaging, shortening the time interval of two adjacent images, recording more detailed vascular wall motion information, and simultaneously ensuring the signal-to-noise ratio of the images by the multi-angle composite method. Compared with the traditional ultrasonic line scanning mode, the method can record more detailed vessel wall motion and can capture short-time sudden motion of the vessel wall. And a cluster of images are reconstructed into a two-dimensional space-time matrix, and then filtering processing is carried out, so that the time consumption is very short. A filtering method based on singular value decomposition is adopted, the size of a singular value is used for representing related components in an image cluster, filtering is achieved through the zeroing of the singular value, and the filtering method is simple and easy to operate.
The size of the tracking image block can be set in the motion tracking of the invention, the size of the image block determines the time required by the tracking, and the execution is more flexible. The motion tracking is expanded by the central point of the image block, and the horizontal and vertical coordinates of the central point can be directly used for subsequent result analysis without further processing. When the candidate center point is calculated, the motion tracking algorithm selects according to the maximum displacement of the blood vessel wall in the frame interval, so that the problem of large time complexity of global calculation is avoided. The tracking operation and realization are simpler, and the use is very convenient. The tracking result can be saved, and repeated analysis of the result or corresponding post-processing research can be realized.
Drawings
FIG. 1 is a flowchart of an overall method for tracking details of vessel wall motion in an ultrasound image with a high frame rate;
FIG. 2 is a detail view of high frame rate ultrasound imaging;
FIG. 3 is a schematic view of image reconstruction;
FIG. 4 is a schematic diagram of a vessel wall motion tracking calculation process;
FIG. 5 is a user control interface for completion of tracking by the high frame rate ultrasound image vessel wall motion detail tracking system;
FIG. 6 is a graph of the movement tracking of the carotid vessel wall along the abscissa and the ordinate with time in the embodiment;
FIG. 7 shows the heart rate of the subject measured by the clinical ultrasound device in the example.
Detailed Description
The present invention will now be described in further detail with reference to specific examples, which are intended to be illustrative, but not limiting, of the invention.
The invention provides a high frame rate ultrasonic image vascular wall motion detail tracking method, which comprises the following processes:
high frame rate ultrasonic imaging, using plane wave imaging to improve the imaging frame rate;
reconstructing an image, wherein a cluster of images are converted into a two-dimensional space-time matrix;
singular space-time filtering, namely performing singular value decomposition on the space-time matrix to obtain different components of the image, and realizing random noise filtering by zeroing a singular value;
performing inverse reconstruction on the image, reconstructing the image into a multi-dimensional matrix describing information of each frame, and recovering the image into a cluster of images;
tracking initialization, wherein an image block around a blood vessel wall is selected from a first frame of image;
and (3) tracking the motion of the blood vessel wall, namely selecting the maximum cross-correlation value by calculating the cross-correlation of the image blocks to realize the tracking of the motion of the blood vessel wall.
And analyzing the tracking result, wherein parameters such as a cardiac cycle, a heart rate, blood vessel pulsation intensity and the like can be obtained by analyzing the tracking result.
The invention discloses a high frame rate ultrasonic image vascular wall motion detail tracking system which comprises an image importing module, a singular space-time filtering module, a motion tracking module and a result analyzing module.
The image importing module is used for importing a cluster of images and integrating the images to form a three-dimensional matrix for subsequent calculation.
The singular space-time filtering module comprises: the image reconstruction module reconstructs a three-dimensional matrix obtained by integrating a cluster of images into a two-dimensional space-time matrix according to a time sequence; the singular value decomposition module is used for decomposing the singular values of the space-time matrix and arranging the singular values and the singular vectors according to the sequence of the singular values from large to small; the space-time filtering module is used for filtering a space-time matrix represented by singular values and singular vectors to realize noise suppression; and the image inverse reconstruction module is used for recombining the filtered singular value and singular vector into a two-dimensional space-time matrix, recombining the two-dimensional space-time matrix into a three-dimensional matrix and decomposing the three-dimensional matrix into a cluster of images.
The motion tracking module selects a point on a blood vessel wall on a first frame image as a central point of a tracking block through tracking initialization, defines the size of the tracking block, and selects the point with the largest cross-correlation value as a tracking result through cross-correlation calculation to realize motion tracking of a cluster of images.
The result analysis module can analyze the horizontal and vertical coordinates of the central point of each image obtained by tracking to analyze the heart rate or the elasticity of blood vessels, and can also dynamically play the tracking result to observe image information. Meanwhile, the motion tracking result can be saved.
Examples
The present invention provides a method and a system for tracking details of a vessel wall motion in a high frame rate ultrasound image, and in order to clarify the purpose, technical solution and effect of the present invention, the present invention will be further described in detail with reference to the accompanying drawings and embodiments. It is to be noted that the following examples are merely illustrative of the present invention, but do not limit the present invention.
The method for tracking details of the vascular wall motion of the high frame rate ultrasonic image, as shown in fig. 1, specifically comprises four steps: high frame rate ultrasonic imaging, singular spatial and temporal filtering, vessel wall motion tracking and tracking result analysis.
Firstly, the ultrasonic imaging of the high frame rate adopts plane wave imaging and combines a multi-angle compounding method to obtain the ultrasonic image of the ultra-high frame rate, and the frame rate can reach 400 Hz. That is, the time interval between two ultrasound images is very short, only a few ms, so that the pulsation of the blood vessel wall can be recorded in more detail, the time resolution of the tracking result is higher, and the purpose of recording the details of the motion of the blood vessel wall is achieved. As shown in fig. 2, firstly, transmitting an ultrasonic signal, wherein the transmitted signal is a plane wave ultrasonic signal; and then, receiving ultrasonic signals, wherein all array elements of the ultrasonic transducer participate in receiving in a full-aperture receiving mode. Transmitting at a plurality of angles, and receiving echo waves at each angle; and finally, processing the received signals to obtain the ultrasonic image. And performing beam forming on the echoes of the transmitting signals of each angle, and then performing multi-angle compounding to obtain an ultrasonic image. The plane wave imaging is combined with a multi-angle composite imaging mode, so that the resolution ratio of an image is improved, and the signal-to-noise ratio of an image is kept at a higher level.
And secondly, singular space-time filtering realizes noise filtering by utilizing the difference between echo signals of tissues in an image and random noise. A cluster of images f obtained by high frame rate ultrasonic imagingiI-1, 2,3,4, L L, N, signals present in an image can be classified into the following two categories: 1) the echo signal of the tissue, because the frequency of motion of the tissue is low, has a higher spatial correlation from frame to frame. Therefore, the tissue signal can be regarded as doing low-speed motion in time, and has high correlation in space; 2) random noise signals, which are randomly distributed, and the correlation between two adjacent frames of images is low. Therefore, it can be seen temporally as making high-speed motion, with low correlation spatially. And after the singular value decomposition, the organization signal is mainly contained in the singular vector corresponding to a larger singular value, and the random noise signal is mainly contained in the singular vector corresponding to a smaller singular value. And setting the smaller singular value as 0, so as to filter out the random noise component. The singular spatio-temporal filtering comprises three steps: 1) reconstructing an image; 2) Filtering; 3) and (5) carrying out inverse reconstruction on the image. The specific operation is as follows:
first, image reconstruction. One image in a cluster of images has a size of (n)z,nx) The cluster of images is combined into a three-dimensional image matrix f (n) in time sequencez,nxN). As shown in FIG. 3, each frame image, i.e., f (n)z,nxI), i ═ 1,2,3,4, L L, N, and are combined into a one-dimensional column vector from left to right and from top to bottom. Obtaining N column vectors, each column vector having a size of (N)x×nz1), all the N column vectors are sequentially arranged from left to right to form a two-dimensional matrix F (N)x×nzN), i.e. the spatio-temporal matrix F.
And secondly, filtering. And carrying out singular value decomposition on the time-space matrix F.
1. The above singular value decomposition of the spatio-temporal matrix F may employ the following formula:
F＝UΔV* (1)
where Δ (N, N) is a diagonal matrix, the elements on the diagonal are singular values, U (N)x×nz,N),V(nx×nzAnd N) is an orthonormal matrix which comprises singular vectors corresponding to the singular values, and represents conjugate transformation.
The singular values contained in the Δ after the singular value decomposition are arranged from large to small, the singular vector corresponding to the part with the larger singular value is an organization part, and the singular vector corresponding to the part with the smaller singular value is a random noise part. Filtering can be achieved by setting the smaller singular values to zero.
2. The singular value based filtering may use the following formula:
Ff＝FVIfV*＝UΔfV* (2)
wherein, FfAs a result of random noise filtering, IfFor the filter, it is a diagonal matrix, and the right part diagonal elements are 0.
And thirdly, carrying out inverse reconstruction on the image. In a manner opposite to image reconstruction, a two-dimensional spatio-temporal matrix F (n)x×nzN) inverseReconstructed into a three-dimensional image matrix f (n)z,nxN) and decomposing the three-dimensional image matrix into a cluster of images. The random noise signal in the image at this time has been filtered out.
And thirdly, the vascular wall motion tracking realizes the similarity comparison of image blocks through cross-correlation calculation, thereby realizing the tracking matching between adjacent frame images. The tracking method is totally divided into three steps: 1) initializing; 2) selecting a candidate center point; 3) and (5) cross-correlation tracking. Taking a cluster of ultrasound images as an example, the entire tracking process is shown in fig. 4.
First, initialization. Selecting a point on a vessel wall in a first frame of an image
The size of the trace block cw is set to sizex × sizey, and once determined, the trace blocks used for trace comparison are all of this size thereafter. At a point on the vessel wall
Establishing a reference block cw for the center1The following tracking procedure is all passed through with cw1The cross-correlation values are calculated for comparison.
In the second step, candidate center points are selected. Starting from the second image fiI is 2,3,4, L L, N. Based on the assumptions: during the pulsation of the blood vessel, the absolute values of the displacements generated by the motion of the blood vessel wall are equal in the same time. From this assumption and the image block center point of the previous image, f is determinediTheoretical center point of a tracking block in an image
3. F aboveiTheoretical center point of image
The following formula may be used for the determination of (c):
wherein the content of the first and second substances,
to estimate the center point of the i-th frame which has been determined by calculation, let
And according to the imaging frame rate, determining the maximum displacement of the blood vessel moving at one frame interval as S. Based on this, candidate centroids (x) are generated from the theoretical centroidscp,ycp)。
4. The determination of the candidate center point may use the following formula:
wherein, for the theoretical center point
Obtaining candidate center points (x) by absolute value calculationcp,ycp) The horizontal and vertical coordinates are changed within the range of-S to Smm from left to right and from top to bottom, and candidate center points are generated.
And thirdly, cross-correlation tracking. Calculating an estimated center point from the candidate center points
Assuming that there are M candidate centroids, for each (x)cp,ycp) Constructing a tracking block cw, and calculating cw and cw1The cross correlation coefficient p.
5. The above cross correlation coefficient may be calculated by the following formula:
wherein the trace block cw mathematically represents a matrix.
Representing a matrix formed by the average values of all the elements in the matrix cw,
and the matrix obtained by subtracting the elements at the corresponding positions of the two matrices is shown.
And the matrix obtained by multiplying elements at the corresponding positions of the two matrices is represented. Σ represents the summation over all elements in the matrix.
Finding the position of the maximum cross-correlation coefficient, and selecting f from the candidate center pointsiEstimated center point of image
Corresponding to (f)iHas a tracking block of cwi。
6. The above-mentioned determination of the estimated center point may employ the following formula:
and tracking any two adjacent frames of images to realize the tracking of the vessel wall motion of the whole cluster of images. And obtaining the matched central point and the corresponding image block.
And fourthly, analyzing the tracking result by analyzing the image or the coordinate so as to determine parameters or analyze the elasticity of the blood vessel. The coordinate analysis of the central point can draw the change curve of the horizontal coordinate and the vertical coordinate with respect to time, and the change degree of the generated displacement can reflect the strength of the pulsation of the blood vessel, thereby reflecting the elasticity of the blood vessel. Under reasonable imaging conditions, the coordinate change curve presents periodic distribution, and the motion period of the blood vessel wall is consistent with the cardiac cycle, so that the heart rate can be solved.
The high frame rate ultrasound image vessel wall motion detail tracking system provided by the present invention, as shown in fig. 5, includes: the system comprises an image importing module, a singular space-time filtering module, a blood vessel wall motion tracking module and a tracking result analyzing module.
And constructing a system according to the method for tracking the details of the vascular wall motion in the high frame rate ultrasonic image. In the image import module, a path and a file name are selected to realize data import. Further, an imaging frame rate, a frame number, needs to be input for time scaling. The down-sampling operation can be performed by integrating the requirement of tracking the processing time. If fast tracking is required, a larger down-sampling multiple can be set, and the number of images is reduced. After clicking the down-sampling button, the down-sampled frame number and frame rate are displayed. In the singular space-time filtering module, filtering parameters need to be set, a percentage of tissue signals are reserved, the rest are regarded as random noise signals, and singular values are set to be zero. And then click the filter button to filter. In the vessel wall motion tracking module, parameters such as the center of a first frame image tracking block, the length of the tracking block, the width of the tracking block and the like need to be set, then an initialization button is clicked to perform initialization operation, a start tracking button is clicked, and tracking is performed frame by frame. In the tracking result analysis module, an image display button can be clicked, the tracked result images are played and displayed in the image panel according to the time sequence, and the result images can be clicked and stored. Meanwhile, the abscissa or the ordinate can be selected, the start analysis button is clicked, and a curve of the abscissa or the ordinate changing with time is displayed in the image panel. The status bar in the system records each step of operation in time sequence so as to perform operation backtracking.
The present invention provides an embodiment implemented by the above-mentioned method for tracking details of vascular wall motion of an ultrasound image with a high frame rate, and the present invention is described in detail by the following embodiment.
In an embodiment, radial ultrasound imaging of the subject's carotid artery occurs with periodic up and down motion of the vessel wall as the heart beats. 1000 ultrasound images are acquired at a frame rate of 400 Hz. In the singular space-time filtering, the first 80% of the signals are regarded as tissue signals, the last 20% of the signals are regarded as random noise, and the random noise is filtered by setting singular values to 0. And (3) tracking the motion of the blood vessel wall, wherein the central point of the first image is set to be [ -0.74,17.52] mm, the length of the tracking block is set to be 1.65mm, and the width of the tracking frame is set to be 1.23mm during initialization, so that tracking is performed.
Parameter settings and tracking results in the high frame rate ultrasound image vessel wall motion detail tracking system are shown in the figure 5, and a tracking result image and a change curve of a vertical coordinate along with time are shown in an image panel. The change of the abscissa and the ordinate with time of the tracking result is shown in fig. 6. In the figure, the change curve of the ordinate with time shows a periodic change, and the abscissa does not show a periodicity, because the carotid artery is radially imaged, the blood vessel wall beats up and down, and the ordinate therefore shows a periodic change. The period of change of the ordinate is the cardiac cycle, and it can be seen that one cardiac cycle is 0.62s, which is converted into a heart rate of 96.8. This is consistent with the heart rate measured with a clinical ultrasound device, as shown in fig. 7.
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. For details of non-careless mistakes in the embodiment of the apparatus, please refer to the embodiment of the method of the present invention.
In yet another embodiment of the present invention, a computer device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and is specifically adapted to load and execute one or more instructions to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for the operation of the high frame rate ultrasonic image vascular wall motion detail tracking method.
In yet another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a computer device and is used for storing programs and data. It is understood that the computer readable storage medium herein can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory. One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the above-mentioned embodiment with respect to a high frame rate ultrasound image vessel wall motion detail tracking method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (8)
1. A method for tracking details of the movement of a vascular wall by using an ultrasonic image with a high frame rate is characterized by comprising the following processes,
carrying out high frame rate ultrasonic imaging on the vascular wall to form a cluster of images, carrying out filtering based on singular value decomposition on the cluster of images, recombining the images into a multi-dimensional matrix describing information of each frame, and recovering the multi-dimensional matrix into a cluster of images;
initializing an image, selecting a point on a blood vessel wall on a first frame image as a central point of a tracking block, defining the size of the tracking block, and selecting the point with the largest cross-correlation value as a tracking result through cross-correlation calculation to obtain a matched central point and a corresponding image block;
and analyzing the horizontal and vertical coordinates of the central point of the image of the tracking result to analyze the heart rate or the elasticity of the blood vessel or dynamically playing the tracking result, and observing the image information.
2. The method of claim 1, wherein the vessel wall is imaged with plane waves in high frame rate ultrasound.
3. The method as claimed in claim 1, wherein the high frame rate ultrasound imaging of the blood vessel wall comprises the following procedures,
firstly, ultrasonic signal transmission is carried out on a blood vessel wall, and the transmission signal is a plane wave ultrasonic signal; then, receiving ultrasonic signals, wherein all array elements of the ultrasonic transducer participate in receiving in a full-aperture receiving mode; transmitting at a plurality of angles, and receiving echo waves at each angle; finally, processing the received signals to obtain ultrasonic images; and performing beam forming on the echo of the transmitting signal at each angle, and performing multi-angle compounding to obtain an ultrasonic image.
4. The method as claimed in claim 1, wherein the filtering based on singular value decomposition specifically includes the following procedures,
converting a cluster of images into a three-dimensional matrix, and reconstructing the three-dimensional matrix into a two-dimensional space-time matrix according to a time sequence; and decomposing the singular values of the space-time matrix, arranging the singular values and the singular vectors according to the sequence of the singular values from large to small, carrying out singular value zeroing and carrying out random noise filtering.
5. A high frame rate ultrasonic image vascular wall motion detail tracking system is characterized by comprising an image import module, a singular space-time filtering module, a motion tracking module and a result analysis module;
the image importing module is used for importing a blood vessel wall image and integrating the image to form a three-dimensional matrix;
the singular space-time filtering module is used for filtering the three-dimensional matrix based on singular value decomposition, recombining the three-dimensional matrix into a multi-dimensional matrix describing each frame of information and recovering the multi-dimensional matrix into a cluster of images;
the motion tracking module is used for initializing, selecting a point on a blood vessel wall on a first frame image as a central point of a tracking block, defining the size of the tracking block, and selecting the point with the largest cross-correlation value as a tracking result through cross-correlation calculation;
the result analysis module is used for analyzing the horizontal and vertical coordinates of the central point of each image obtained by tracking to analyze the heart rate or the elasticity of blood vessels or dynamically playing the tracking result and observing the image information.
6. The system according to claim 5, wherein said singular spatiotemporal filtering module comprises: the image reconstruction module, the singular value decomposition module, the space-time filtering module and the image inverse reconstruction module;
the image reconstruction module is used for reconstructing a three-dimensional matrix obtained by integrating a cluster of images into a two-dimensional space-time matrix according to a time sequence;
the singular value decomposition module is used for decomposing the singular values of the space-time matrix and arranging the singular values and the singular vectors according to the sequence of the singular values from large to small;
the space-time filtering module is used for filtering a space-time matrix represented by singular values and singular vectors;
and the image inverse reconstruction module is used for recombining the filtered singular values and singular vectors into a two-dimensional space-time matrix, recombining the two-dimensional space-time matrix into a three-dimensional matrix and recovering the three-dimensional matrix into a cluster of images.
7. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of a high frame rate ultrasound image vessel wall motion detail tracking method as claimed in any one of claims 1 to 4.
8. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of a high frame rate ultrasound image vessel wall motion detail tracking method as claimed in any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111372365.3A CN114098817A (en) | 2021-11-18 | 2021-11-18 | High frame rate ultrasonic image blood vessel wall motion detail tracking method, system, equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111372365.3A CN114098817A (en) | 2021-11-18 | 2021-11-18 | High frame rate ultrasonic image blood vessel wall motion detail tracking method, system, equipment and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114098817A true CN114098817A (en) | 2022-03-01 |
Family
ID=80397942
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111372365.3A Pending CN114098817A (en) | 2021-11-18 | 2021-11-18 | High frame rate ultrasonic image blood vessel wall motion detail tracking method, system, equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114098817A (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101273901A (en) * | 2007-03-30 | 2008-10-01 | 中国科学技术大学 | High frame rate ultrasonic imaging method based on single power signal source and switching network thereof |
| CN103747742A (en) * | 2011-04-14 | 2014-04-23 | 明尼苏达大学评议会 | Vascular characterization using ultrasound imaging |
| CN108697354A (en) * | 2016-02-23 | 2018-10-23 | 梅约医学教育与研究基金会 | Supersonic blood is imaged |
| CN110023782A (en) * | 2016-11-29 | 2019-07-16 | 皇家飞利浦有限公司 | Method and system for being filtered to ultrasound image clutter |
| CN110740688A (en) * | 2017-05-31 | 2020-01-31 | 梅约医学教育与研究基金会 | Method for microvascular super-resolution ultrasound imaging |
| CN111132622A (en) * | 2017-10-27 | 2020-05-08 | 爱飞纽医疗机械贸易有限公司 | Ultrasonic imaging apparatus and clutter filtering method using the same |
| CN112914611A (en) * | 2021-01-29 | 2021-06-08 | 大连东软教育科技集团有限公司 | Ultrasonic microvascular imaging method based on random singular value decomposition and weighted L1 norm |
| CN112932539A (en) * | 2021-01-23 | 2021-06-11 | 西安交通大学 | Device and method for estimating blood vessel blood flow velocity field through transcranial ultrasound |
| CN113499096A (en) * | 2021-06-21 | 2021-10-15 | 西安交通大学 | Imaging platform and method for ultrasonic cross-scale and multi-parameter detection |
-
2021
- 2021-11-18 CN CN202111372365.3A patent/CN114098817A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101273901A (en) * | 2007-03-30 | 2008-10-01 | 中国科学技术大学 | High frame rate ultrasonic imaging method based on single power signal source and switching network thereof |
| CN103747742A (en) * | 2011-04-14 | 2014-04-23 | 明尼苏达大学评议会 | Vascular characterization using ultrasound imaging |
| CN108697354A (en) * | 2016-02-23 | 2018-10-23 | 梅约医学教育与研究基金会 | Supersonic blood is imaged |
| CN110023782A (en) * | 2016-11-29 | 2019-07-16 | 皇家飞利浦有限公司 | Method and system for being filtered to ultrasound image clutter |
| CN110740688A (en) * | 2017-05-31 | 2020-01-31 | 梅约医学教育与研究基金会 | Method for microvascular super-resolution ultrasound imaging |
| CN111132622A (en) * | 2017-10-27 | 2020-05-08 | 爱飞纽医疗机械贸易有限公司 | Ultrasonic imaging apparatus and clutter filtering method using the same |
| CN112932539A (en) * | 2021-01-23 | 2021-06-11 | 西安交通大学 | Device and method for estimating blood vessel blood flow velocity field through transcranial ultrasound |
| CN112914611A (en) * | 2021-01-29 | 2021-06-08 | 大连东软教育科技集团有限公司 | Ultrasonic microvascular imaging method based on random singular value decomposition and weighted L1 norm |
| CN113499096A (en) * | 2021-06-21 | 2021-10-15 | 西安交通大学 | Imaging platform and method for ultrasonic cross-scale and multi-parameter detection |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Gao et al. | Motion tracking of the carotid artery wall from ultrasound image sequences: a nonlinear state-space approach | |
| US10448921B2 (en) | Ultrasound systems and methods for automated fetal heartbeat identification | |
| JP6180539B2 (en) | Automatic placement on a standard surface for real-time fetal heart assessment | |
| US7744533B2 (en) | Ultrasonic diagnostic apparatus, image processing apparatus and image processing method | |
| US20130066211A1 (en) | Systems and methods for composite myocardial elastography | |
| CN102209495A (en) | Ultrasonic lesion identification using temporal parametric contrast images | |
| JP2014023928A (en) | Ultrasound imaging system and method | |
| Benes et al. | Automatically designed machine vision system for the localization of CCA transverse section in ultrasound images | |
| CN103584887B (en) | Ultrasonic image-forming system and method | |
| US20060241457A1 (en) | Cyclical information determination with medical diagnostic ultrasound | |
| CN102946810A (en) | Automated heart rate detection for 3d ultrasonic fetal imaging | |
| JP7041147B6 (en) | Systems and methods that characterize hepatic perfusion of contrast medium flow | |
| JP2007518512A (en) | Image segmentation for displaying myocardial perfusion | |
| CN112292086B (en) | Ultrasound lesion assessment and associated devices, systems, and methods | |
| US20080125652A1 (en) | Method and System for Deriving a Fetal Heart Rate Without the Use of an Electrocardiogram in Non-3d Imaging Applications | |
| CN110809801A (en) | System and method for simultaneous visualization and quantification of wall shear stress in blood vessels | |
| JP4659974B2 (en) | Ultrasonic diagnostic equipment | |
| JP2005511188A (en) | On-line image generation device for a site where a contrast medium is introduced | |
| CN114037626A (en) | Blood vessel imaging method, device, equipment and storage medium | |
| CN117562577A (en) | Ultrasonic vector flow velocity imaging method and system based on singular value decomposition filtering | |
| Hennersperger et al. | Vascular 3D+ T freehand ultrasound using correlation of doppler and pulse-oximetry data | |
| JP4709937B2 (en) | Ultrasonic diagnostic apparatus and image processing apparatus | |
| JP7366221B2 (en) | Triple-mode ultrasound imaging for anatomical, functional and hemodynamic imaging | |
| CN114098817A (en) | High frame rate ultrasonic image blood vessel wall motion detail tracking method, system, equipment and readable storage medium | |
| CN113498542A (en) | Method and system for obtaining physiological measurements from a subject |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |