CN102908163B - A kind of frame correlation technique and device thereof and ultrasonic image-forming system - Google Patents
A kind of frame correlation technique and device thereof and ultrasonic image-forming system Download PDFInfo
- Publication number
- CN102908163B CN102908163B CN201110219847.5A CN201110219847A CN102908163B CN 102908163 B CN102908163 B CN 102908163B CN 201110219847 A CN201110219847 A CN 201110219847A CN 102908163 B CN102908163 B CN 102908163B
- Authority
- CN
- China
- Prior art keywords
- pixel
- displacement
- current time
- tissue points
- point
- 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.)
- Active
Links
Landscapes
- Ultra Sonic Daignosis Equipment (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a kind of frame correlation technique and device thereof, wherein method comprises: Displacement Estimation step, for carrying out Displacement Estimation to the pixel of specifying in current time image or tissue points, obtain the parameters of displacement field of this pixel or tissue points, comprise the displacement relation between this pixel or tissue points and its same place in a upper time chart picture and Displacement Estimation uncertain parameters; Frame correlation computations step, for according to described parameters of displacement field determination frame correlation coefficient, and utilizes described frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain described current time picture frame be correlated with after result images.Can ensure to carry out between every two pixels of frame correlation computations or tissue points by Displacement Estimation is real coupling, simultaneously, when can avoid popping one's head in quick movement or histokinesis in conjunction with displacement estimation effect delta frame correlation coefficient, Displacement Estimation error is on the impact of frame correlation computations.
Description
Technical field
The present invention relates to ultra sonic imaging field, be specifically related to a kind of frame correlation technique and device thereof and utilize the ultrasonic image-forming system of the method.
Background technology
In B-mode ultrasonography system, the noise affecting ultrasonograph quality (as signal to noise ratio, contrast resolution) comprises random noise and the speckle noise of hardware system usually.For improving picture quality, in ultrasonic image-forming system, usually adopting complex technique, comprising space compound technology, frequency multiplexed technology and time complex technique.Wherein, time complex technique and frame correlation processing technique, because it is embodied as, this is lower and reduce spatial resolution hardly, and often adopt by ultrasonic image-forming system.General frame relevant treatment can be averaging realization by choosing adjacent a few two field picture.Random noise not in ultrasonoscopy is in the same time uncorrelated, therefore by being averaged effectively can improving signal noise ratio (snr) of image to not image in the same time.Although the speckle noise that static target produces is not random, but in fact the motion of people's in-vivo tissue and the motion of ultrasonic probe all can change speckle noise, therefore, speckle noise in different frame ultrasonoscopy also has more weak dependency usually, thus utilize the technology be averaged on multiple image can reduce the impact of speckle noise equally, improve the contrast resolution of image.But frame relevant treatment is when carrying out imaging to strenuous exercise's target (in as cardiac imaging the cardiac muscle of rapid movement and valve), the temporal resolution of image may be caused to decline and motion blur.
When considering saving storage and computational resource, frame is relevant to be realized by first order recursive low-pass filtering usually, and formula is expressed as:
Y(K)＝αY(K-1)+(1-α)X(K)，0＜α＜1
In formula, X (K) represents current frame image, Y (K) represent current frame image frame be correlated with after output valve, Y (K-1) represent previous frame picture frame be correlated with after output valve, α is adjustable frame correlation coefficient.
At present, the basic thought of some frame correlation techniques is: between the result Y (K-1) after current time image X (K) and previous moment picture frame are correlated with, carry out the determination of frame correlation coefficient or weight according to one of them or relation between the two.Between X (K) and Y (K-1), carry out frame correlation computations or add temporary, the mode pointwise based on pixel or voxel is often used to carry out coefficient calculations, namely need, for each pixel in image or tissue points determine a frame correlation coefficient, then to carry out frame correlation computations or weighted average.And this method does not consider the displacement between previous moment image and a rear time chart picture, can not avoid motion blur, and amount of calculation is large while denoising.
Summary of the invention
In order to while reaching restraint speckle, weaken frame to be correlated with the motion blur brought, embodiment of the present invention provides a kind of frame correlation technique and device thereof, Image estimation based on former and later two moment is published picture the displacement field of picture, adaptive change is done, the phenomenons such as the image blurring and hangover avoiding motion time frame correlation estimation in image layer to cause with the accuracy of Displacement Estimation with time frame degree of correlation.
According to one embodiment of the present invention, a kind of frame correlation technique is provided, comprise: Displacement Estimation step, for carrying out Displacement Estimation to the pixel of specifying in current time image or tissue points, obtain the parameters of displacement field of this pixel or tissue points, comprise the displacement relation between this pixel or tissue points and its same place in a upper time chart picture and Displacement Estimation uncertain parameters; Frame correlation computations step, for according to described parameters of displacement field determination frame correlation coefficient, and utilizes described frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain described current time picture frame be correlated with after result images.
In an embodiment of the present invention, also comprise before Displacement Estimation step: step is selected at control point, for selecting at least one control point on current time image, the pixel that this control point is specified in current time image or tissue points.
In another embodiment of the present invention, also comprise before Displacement Estimation step: displacement initialization step, for arranging initial displacement to the pixel of specifying in current time image or tissue points.
In another embodiment of the invention, also comprise before frame associated process steps: interpolation procedure, for according to described displacement relation, obtained the parameters of displacement field of each pixel or tissue points on current time image by interpolation.
According to another embodiment of the invention, a kind of frame relevant apparatus is provided, comprise: Displacement Estimation module, for carrying out Displacement Estimation to the pixel of specifying in current time image or tissue points, obtain the parameters of displacement field of this pixel or tissue points, comprise the displacement relation between this pixel or tissue points and its same place in a upper time chart picture and Displacement Estimation uncertain parameters; Frame correlation computations module, for according to described parameters of displacement field determination frame correlation coefficient, and utilizes described frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain described current time picture frame be correlated with after result images.
In an embodiment of the present invention, frame relevant apparatus also comprises: control point selection module, for selecting at least one control point on current time image, and the pixel that this control point is specified in current time image or tissue points.
In another embodiment of the present invention, frame relevant apparatus also comprises: displacement initialization module, for arranging initial displacement to the pixel of specifying in current time image or tissue points.
In another embodiment of the invention, frame relevant apparatus also comprises: interpolating module, for according to described displacement relation, is obtained the parameters of displacement field of each pixel or tissue points on current time image by interpolation.
It is real coupling that embodiment of the present invention can ensure to carry out between every two pixels of frame correlation computations or tissue points by Displacement Estimation, simultaneously, when can avoid popping one's head in quick movement or histokinesis in conjunction with displacement estimation effect delta frame correlation coefficient, Displacement Estimation error, on the impact of frame correlation computations, is avoided because frame correlation computations causes the fuzzy of image and conditions of streaking.
Accompanying drawing explanation
Fig. 1 is the ultrasonic image-forming system principle schematic diagram according to one embodiment of the present invention;
Fig. 2 is the structural representation of the frame relevant apparatus according to one embodiment of the present invention;
Fig. 3 is the schematic flow sheet of the frame correlation technique according to embodiment of the present invention one;
Fig. 4 is the schematic flow sheet of the frame correlation technique according to embodiment of the present invention two;
Fig. 5 is the schematic diagram according to one embodiment of the present invention, view data being carried out to frame relevant treatment;
Fig. 6 is the schematic flow sheet of the frame correlation technique according to embodiment of the present invention three;
Fig. 7 is that in Fig. 6 illustrated embodiment, displacement initializes principle schematic diagram;
Fig. 8 is the schematic flow sheet of the frame correlation technique according to embodiment of the present invention four.
Detailed description of the invention
By reference to the accompanying drawings the present invention is described in further detail below by detailed description of the invention.
Numeral or digitized image, comprise the image etc. of ultra sonic imaging, and be have the little two-dimensional points of certain outward appearance or the array of three-dimensional point on display screen or printed copies, described point is called pixel in two dimensional image, in 3-D view, be called tissue points.Be appreciated that when relating to neighborhood of a point, pixel neighborhood of a point is the image block of two dimension, and voxel neighborhood of a point is three-dimensional cuboid.
For subsequent descriptions is convenient, provide as given a definition herein:
(1) corresponding point: suppose that the coordinate position of a certain pixel in current time image is for (m, n), the point corresponding to (m, n) in a upper time chart picture is then called the corresponding point of this pixel; Similarly, suppose that the coordinate position of a certain tissue points in current time image is for (m, n, l), then go up the corresponding point that the point corresponding to (m, n, l) in a time chart picture is called this tissue points.
(2) same place or match point: suppose that a upper time chart picture and current time image exist displacement, a certain pixel in current time image or the front point in a upper time chart picture of tissue points displacement are called same place or the match point of this pixel or this tissue points.
(3) parameters of displacement field: comprise the pixel (x in current time image, or tissue points (x y), y, z) and a upper time chart picture in this pixel or tissue points same place between displacement relation (xmove (x, y), ymove (x,) or (xmove (x, y, z) y), ymove (x, y, z), zmove (x, y,), and the Displacement Estimation uncertain parameters Err (x, y) of this point or Err (x z), y, z).
Frame correlation technique can reduce the noise in ultrasonoscopy, improves contrast resolution and the signal to noise ratio of image, thus improves definition and the readability of ultrasonoscopy, is a requisite link in each ultrasonic system.Image due to different time has relatively independent noise, gets final product effective restraint speckle, improve picture quality by the time domain compound of sequence image.But the movement degree of Different Organs is different, even adjacent two two field pictures of same organ, the movement degree of zones of different is not identical yet, adopt conventional art carry out frame relevant after, the region of motion intense is easy to produce motion blur, thus reduces picture quality.Based on this, the overall thought of embodiment of the present invention is: carry out Displacement Estimation to image, to movement degree different frame degree of correlation also distinguish to some extent.Such as, utilize the relative displacement of the image determination image in continuous print adjacent two moment, the accuracy delta frame correlation coefficient of deformation based estimation simultaneously, carries out frame related operation according to frame correlation coefficient.Can compensate in image according to Displacement Estimation like this and move, simultaneously automatically regulate correlation coefficient according to picture material, while reaching restraint speckle, weaken frame and to be correlated with the motion blur brought.
Embodiment of the present invention provides a kind of ultrasonic image-forming system, as shown in Figure 1, transmitter module 110 is launched ultrasound wave by probe 120 and is entered human body, after the Tissue reflectance of human body, received module 130 receives, the echo-signal received is carried out process through signal processing link 140 and is obtained view data, then sends into frame relevant apparatus 150 and carries out frame relevant treatment, finally shown by display module 160.The wherein frame relevant apparatus 150 frame relevant apparatus that adopts embodiment of the present invention to provide, for reducing the noise in ultrasonic image-forming system, improves contrast resolution and the signal to noise ratio of image, thus improves definition and the readability of ultrasonoscopy.
As shown in Figure 2, the frame relevant apparatus that one embodiment of the present invention provides comprises: Displacement Estimation module 205, for carrying out Displacement Estimation to described control point, obtain the parameters of displacement field at described control point, comprise the estimation uncertain parameters at displacement relation between control point and the same place in a upper time chart picture thereof and described control point; Frame correlation computations module 209, for according to described parameters of displacement field determination frame correlation coefficient, and utilizes described frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain described current time picture frame be correlated with after result images.Wherein, utilize described frame correlation coefficient to described current time image carry out method that frame is correlated with can be utilize described frame correlation coefficient to be correlated with to a upper time chart picture frame after result images and described current time image to carry out frame relevant, thus obtain described current time picture frame be correlated with after result images.
Still as shown in Figure 2, the embodiment of another kind of frame relevant apparatus increases to control point selection module 201 on the basis of aforementioned frame relevant apparatus embodiment, for selecting at least one control point on current time image, the pixel that this control point is specified in current time image or tissue points.In a kind of embodiment, control point selection module 201 and comprise judging unit, for judging whether pixel in current time image or tissue points and its corresponding point in a upper time chart picture are all non-noise point, if be all non-noise point, then select this pixel or tissue points to be control point.
Still as shown in Figure 2, the embodiment of another kind of frame relevant apparatus increases displacement initialization module 203 on the basis of aforementioned frame relevant apparatus embodiment, arranges initial displacement for the control point selected control point selection module 201.
Return Fig. 2, the embodiment of another frame relevant apparatus increases interpolating module 207 on the basis of a upper embodiment, for the displacement relation obtained according to Displacement Estimation module 205, obtained the parameters of displacement field of each pixel or tissue points on current time image by interpolation.
Should be understood that the embodiment of frame relevant apparatus of the present invention can also be the simple deformation of the respective embodiments described above.
Embodiment of the present invention additionally provides the frame correlation technique realizing above-mentioned frame relevant apparatus, describes the frame correlation technique provided according to embodiment of the present invention below in conjunction with Fig. 3-8 in detail.
Embodiment one:
As shown in Figure 3, the flow process of the frame correlation technique that present embodiment provides comprises: Displacement Estimation step S305, for carrying out Displacement Estimation to the pixel of specifying in current time image or tissue points, obtain the parameters of displacement field of this pixel or tissue points, comprise the displacement relation between this pixel or tissue points and its same place in a upper time chart picture and Displacement Estimation uncertain parameters; Frame correlation computations step S309, for according to described parameters of displacement field determination frame correlation coefficient, and utilizes frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain current time picture frame be correlated with after result images.Wherein, utilize described frame correlation coefficient to described current time image carry out method that frame is correlated with can be utilize described frame correlation coefficient to be correlated with to a upper time chart picture frame after result images and described current time image to carry out frame relevant, thus obtain described current time picture frame be correlated with after result images.
Present embodiment, based on the parameters of displacement field of the image in front and back adjacent two moment, makes frame degree of correlation do adaptive change with the accuracy of Displacement Estimation, thus while reaching restraint speckle, weakens frame and to be correlated with the motion blur brought.
Embodiment two:
As shown in Figure 4, present embodiment adds " control point selection " relative to aforementioned embodiments, is to reduce amount of calculation and rejecting the pixel or tissue points that are not easy to follow the tracks of.The flow process of the frame correlation technique of this embodiment comprises: step S401, Displacement Estimation step S405, frame correlation computations step S409 are selected in control point.
Step S401 is selected at control point, specifically, selects at least one control point, the pixel of specify this control point in Displacement Estimation step or tissue points in current time image X (K).In a kind of embodiment, in image X (K), carry out sampling by predetermined step-length and obtain sampled point, this sampled point is control point.But the control point that this method obtains is too much, causes amount of calculation very large, affect algorithm speed.Another kind of embodiment does screening further based on the mean flow rate of sampled point neighborhood to sampled point, namely each sampled point is calculated to the mean flow rate of each sampled point neighborhood based on the neighborhood of pre-sizing, if mean flow rate is less than given threshold value, is judged as the lumen area such as noise region or ventricle trunk, if mean flow rate is greater than given threshold value, judges that sampled point is control point.Although this method can reduce amount of calculation, the impact by image gain and threshold parameter is larger.
In an embodiment of the present invention, select control point in the following way: according to predetermined step-length, sampling is carried out to current time image X (K) and obtain sampled point, predetermined step-length experimentally can be worth setting, is set as 4-10 pixel size in embodiment; Calculate the average Mean of each sampled point in predetermined neighborhood and variance STD, the large I of predetermined neighborhood is experimentally worth setting, is set as 6-10 pixel in embodiment; Judge according to the ratio (i.e. STD/Mean) of variance and average and predetermined threshold, predetermined threshold experimentally can be worth setting, be set as between (0.5-1) in embodiment, if this ratio is more than or equal to predetermined threshold, then judge that this sampled point is as noise spot, if this ratio is less than predetermined threshold, then judge that this sampled point is as control point.This embodiment adopts STD/Mean parameter to carry out control point selection, owing to not relating to brightness of image, therefore, it is possible to remove image gain to the impact of threshold parameter.
Another kind of embodiment of the present invention is improved based on previous embodiment, the information combining a time chart picture carries out the selection at control point, judge whether pixel in current time image or tissue points and its corresponding point in a upper time chart picture are all non-noise point, if be all non-noise point, then judge that this pixel or tissue points are as control point; That is, current time image and on carry out based on STD/Mean judgement in a time chart picture simultaneously, in two time chart pictures, be not only all judged as that the point of noise is just selected as control point, detailed process is as follows:
According to predetermined step-length, as X (K-1), sampling is carried out respectively to current time image X (K) and a upper time chart and obtain the sampled point of current time image X (K) and the upper time chart sampled point as X (K-1), predetermined step-length experimentally can be worth setting, is set as 4-10 pixel size in embodiment;
Respectively at current time image X (K) and a upper time chart as calculating the average Mean of each sampled point in predetermined neighborhood and variance STD in X (K-1), the large I of predetermined neighborhood is experimentally worth setting, is set as 6-10 pixel in embodiment;
Judge according to the ratio (i.e. STD/Mean) of variance and average and predetermined threshold, predetermined threshold experimentally can be worth setting, be set as between (0.5-1) in embodiment, if this ratio is more than or equal to predetermined threshold, then judge that this sampled point is as noise spot, if this ratio is less than predetermined threshold, then judge that this sampled point is as doubtful control point;
According to the coordinate position at the doubtful control point in current time image X (K), judge in a upper time chart is as X (K-1) should the point of coordinate position whether also be doubtful control point, if, then judge that this doubtful control point is control point, otherwise this point is non-controlling point, do not process this point.
The another kind of deformation of the present embodiment is: carry out sampling according to predetermined step-length to current time image X (K) and obtain sampled point; Calculate the average Mean of each sampled point in predetermined neighborhood and variance STD; Judge according to the ratio (i.e. STD/Mean) of variance and average and predetermined threshold; If this ratio is more than or equal to predetermined threshold, then judge that this sampled point is as noise spot; If this ratio is less than predetermined threshold, then, size based on same predetermined neighborhood calculates this sampled point at a upper time chart as the average of the corresponding point neighborhood in X (K-1) and variance, if the STD/Mean of corresponding point is more than or equal to this predetermined threshold, then, this sampled point is still non-controlling point; If the STD/Mean of corresponding point is less than this predetermined threshold, then this sampled point is selected to be control point.Should be understood that the predetermined step-length related to, predetermined Size of Neighborhood, predetermined threshold all experimentally can be worth setting here, or be set as the scope as previous embodiment.
The present embodiment and deformation thereof are all the selections carrying out control point based on the image in front and back adjacent two moment, and not only consider current time image, can effectively remove like this probe fast mobile etc. extreme time the irregular artifact introduced and hangover.
Displacement Estimation step S405, similar with the step S305 of embodiment one, specifically, according to the set Control (m at the control point of the current time image X (K) of step S401 selection, n), each control point Control is searched at a upper time chart as in X (K-1)
ithe same place Match of (i represents control point sequence number)
i(or claim match point), thus obtain the parameters of displacement field at control point, comprises the estimation accuracy coefficient at displacement relation between control point and same place and control point.Suppose control point Control
icoordinate position be (m, n), its same place Match
icoordinate position be (m ', n '), then the displacement relation between control point and same place is m=m '+move (m, n), n=n '+move (m, n), and wherein move (m, n) is displacement vector.
In a kind of embodiment, carry out Displacement Estimation in the following way: obtaining control point Control
ineighborhood Block (Control
i) and corresponding point P
ineighborhood Block (P
i) after, calculate two neighborhood Block (Control
i) and Block (P
i) in the absolute value sum (SAD, SumofAbsoluteDifference) of difference of brightness value of each respective pixel point or tissue points, pixel or the tissue points of corresponding minimum SAD are control point Control
isame place Match
i.According to control point Control
icoordinate position (being assumed to be (m, n)) and same place Match
icoordinate position can calculate displacement vector move (m, n), thus obtain the displacement relation between control point and same place.The Displacement Estimation uncertain parameters Err at this control point is set as that minimum sad value is divided by Block (Control
i) in count.
In another kind of embodiment, obtaining control point Control
ineighborhood Block (Control
i) and corresponding point P
ineighborhood Block (P
i) after, calculate the quadratic sum (SSD, SumofSquaredDifference) of the luminance difference of each respective pixel point or tissue points in these two neighborhoods, pixel or the tissue points of corresponding minimum SSD are control point Control
isame place Match
i.The displacement relation between control point and same place can be obtained equally.Now, the Displacement Estimation uncertain parameters Err at this control point is set as that minimum SSD value is divided by Block (Control
i) in count.
In another embodiment, obtaining control point Control
ineighborhood Block (Control
i) and corresponding point P
ineighborhood Block (P
i) after, calculate the relative coefficient Cor of the Luminance Distribution of these two neighborhoods, formula is
Wherein: x
j∈ Block (Control
i), y
k∈ Block (P
i), k=0 ... N; x
jrepresent control point Control
ineighborhood Block (Control
i) an interior jth pixel or tissue points, y
krepresent corresponding point P
ineighborhood Block (P
i) an interior kth pixel or tissue points, N represents the size of predetermined neighborhood,
represent region Block (Control respectively
i) and Block (P
i) meansigma methods of interior brightness.The pixel of corresponding maximum relative coefficient Cor or tissue points are the same place at control point, now the Displacement Estimation uncertain parameters Err at control point is set as the inverse of maximum relative coefficient Cor, or is set as the negative of maximum relative coefficient Cor.Be appreciated that and no matter adopt which kind of embodiment above-mentioned, the Displacement Estimation uncertain parameters Err obtained is always minima.
Those skilled in the art can also adopt additive method of the prior art to carry out Displacement Estimation, the searching algorithm etc. such as, commonly used in images match.
Frame correlation computations step S409, similar with the step S309 of embodiment one, specifically, according to the parameters of displacement field determination frame correlation coefficient that Displacement Estimation step S405 obtains, and result images after utilizing frame correlation coefficient to be correlated with to a upper time chart picture or a upper time chart picture frame and current time image to carry out frame relevant, thus obtain current time picture frame be correlated with after result images.
The following two kinds method determination frame correlation coefficient can be adopted.
Method one: the Displacement Estimation uncertain parameters Err obtained according to step S405, this coefficient larger expression Displacement Estimation is more inaccurate, and the similarity between control point and same place is lower, and corresponding frame correlation coefficient then should be less; This coefficient less expression Displacement Estimation is more accurate, and the similarity between control point and same place is higher, and corresponding frame correlation coefficient then should be larger.Therefore, frame correlation coefficient is the decreasing function of Displacement Estimation uncertain parameters, needs structure function f along with the larger monotone decreasing of Err (Err) to be used for delta frame correlation coefficient.In an embodiment of the present invention, natural exponential function can be utilized to calculate frame correlation coefficient α (x, y), that is:
α(x，y)＝f(Err)＝ρ·exp[-k*Err]，k＞0
In formula, ρ is the largest frames correlation coefficient of current time of system input, this coefficient by default for setting the relevant different gears of frame (namely the frame of ultrasonic image-forming system be correlated with gear); K is natural Exponents adjustment factor, and it is determined by experience, for regulating the scope of above formula exponential part, thus regulates frame degree of correlation.It should be noted that then in current time image, the frame correlation coefficient in most of region can be very little if k is too large, close to 0, so the scope of k is limited to (0,1].
In other embodiments, this function can also be defined as the monotonic decreasing function of any codomain in [0,1], such as function
Deng.
Method two:
Before and after the frame correlation coefficient of method two combines, in adjacent two time chart pictures, the difference of the brightness value of corresponding point has done further optimization to the frame correlation coefficient obtained in method one, namely, according to the decreasing function of difference and the decreasing function of described Displacement Estimation uncertain parameters of the brightness value of the pixel in current time image or tissue points and its same place in a upper time chart picture, obtain described frame correlation coefficient.In a kind of embodiment, frame correlation coefficient obtains according to following formula:
α′(x，y)＝f(Err)*exp(-b*|g(K)-g(K-1)|)
In formula, α ' (x, y) be frame correlation coefficient, f (Err) is the decreasing function of described Displacement Estimation uncertain parameters, frame correlation coefficient α (the x obtained in its essence i.e. method one, y), K is current time, K-1 was a upper moment, the brightness value that g (K) is the pixel in current time image or tissue points, the brightness value of g (K-1) same place in a upper time chart picture for the pixel in current time image or tissue points, b is adjustment factor, can be obtained by experience.
In 2D image, this formula can be written as follows:
α′(x，y)＝α(x，y)*exp(-b*|X(K，x，y)-Y(K-1，x+xmove(x，y)，y+ymove(x，y))|)
In formula, α (x, y) the frame correlation coefficient α (x, y) for obtaining in method one, X (K, x, y) be the brightness value of pixel (x, y) in current time K image, Y (K-1, x+xmove (x, y), y+ymove (x, y)) be pixel (x in a upper moment K-1 image, y) same place (x+xmove (x, y), y+ymove (x, y)) brightness value, b is adjustment factor, can be obtained by experience.In like manner can obtain the form that in 3D rendering, this formula is corresponding.
After obtaining frame correlation coefficient, be weighted on average according to frame correlation computations formula, to be result images after utilizing frame correlation coefficient to be correlated with to a upper time chart picture frame in a kind of embodiment with current time image carry out, and frame is relevant, that is, formula is:
Y(K)＝αY(K-1)+(1-α)X(K)，0＜α＜1
Wherein, X (K) represents current time image, and Y (K) represents the result of current time image after frame related operation, and Y (K-1) represents the result of a upper time chart picture after frame correlation computations, and α represents frame correlation coefficient.Fig. 5 carries out the relevant schematic diagram of frame according to one embodiment of the present invention to view data.Sequence X (k) represents the view data of system acquisition, and sequence Y (K) represents the view data after frame is correlated with, wherein, K=0 ..., i-1, i ..., k-1, k ..., and i and k is natural number, and K is nonnegative integer.
In Fig. 4 illustrated embodiment, the selection at control point can effectively reduce amount of calculation and reject the control point being not easy to follow the tracks of, and promotes the quality of Displacement Estimation, displacement calculating is carried out for the control point selected, obtain displacement relation and the Displacement Estimation uncertain parameters at each control point, wherein Displacement Estimation uncertain parameters is in fact a tolerance of correspondence image pixel or tissue points distribution of gray level in the neighborhood similarity, the frame correlation coefficient at control point is generated based on this parameter, neighborhood of a point information is attached in the generation of frame correlation coefficient, more effectively can remove the impact of random noise, simultaneously, Displacement Estimation ensure that two points carrying out frame correlation computations are real corresponding relations, avoid the image blurring and conditions of streaking that in image layer, motion time frame correlation computations causes.
Embodiment three:
Present embodiment increases " displacement initialization step " on the basis of embodiment one or embodiment two, it is the hunting zone in order to effectively reduce the same place to the pixel of specifying or tissue points in Displacement Estimation step, reduce amount of calculation, and reduce Displacement Estimation mistake.Be described to increase " displacement initialization step " on the basis of embodiment two below.
As shown in Figure 6, control point selects the step S401 shown in step S601 and Fig. 4 similar, just no longer describes in detail here.
In displacement initialization step S603, initial displacement is set to before carrying out Displacement Estimation each control point.
In a kind of embodiment, the displacement relation obtained after carrying out Displacement Estimation according to a upper time chart picture arranges initial displacement, suppose that the displacement relation obtained after a upper time chart picture carries out Displacement Estimation is m=m '+move (m, n), n=n '+move (m, n), wherein, (m, n) be the coordinate position at the control point in a upper time chart picture, (m ', n ') be the coordinate position of the same place of the control point in a upper time chart picture in a upper time chart picture of a upper time chart picture, initial displacement can be set to move (m, n) or with move (m, n) relevant function or value.
In another kind of embodiment, carry out in the process of Displacement Estimation at current time image, initial displacement can be set to intermediate value or the average of the displacement at the some control point having completed estimation in current control point neighborhood, and current control point is first control point, and its initial displacement is set to 0.As shown in Figure 7, depth direction when vertical direction is scanning probe in figure, be laterally scan-line direction, black square point is current control point, and dark circles form point is the control point having completed Displacement Estimation.In displacement estimation procedure, to the Displacement Estimation that the control point of every a line is carried out successively, wherein, the initial displacement of black square point is intermediate value or the average of the displacement of seven dark circles form points, the control point of the first row boundary is due to close probe, and displacement is usually very little, and arranging its initial displacement is 0.
In Displacement Estimation step S605, when carrying out Displacement Estimation, according to the control point of the current time image selected, the initial displacement in integrating step S603, searches for the same place at each control point in a upper time chart picture.A kind of embodiment, when carrying out Displacement Estimation, supposes that the initial displacement obtained by step S603 is Dis
ini, according to the control point Control of the current time image selected
iobtain the corresponding point P of each control point in a upper time chart picture
iif, P
icoordinate position be (m, n), then point (the m+Dis in a upper time chart picture
ini, n+Dis
ini) field in search each control point same place.Search is used for by increasing initial displacement, search procedure is carried out in the position that same place or match point most possibly exist, be equivalent to increase search dynamics, effectively can reduce hunting zone, reduce amount of calculation, meanwhile, the constraint of carrying out searching for based on initial displacement can increase the flatness of the whole displacement field of all time chart pictures, reduces Displacement Estimation and makes mistakes.Concrete searching method, with abovementioned steps S405, just no longer describes in detail here.
Step S409 shown in frame correlation computations step S609 and Fig. 4 is similar, equally no longer describes in detail.
Embodiment four:
Present embodiment increases " interpolation procedure " on the basis of embodiment one or embodiment two or embodiment three, the parameters of displacement field of each pixel or tissue points in image can be obtained by interpolation, frame relevant treatment is carried out to each pixel or tissue points.Only carrying out frame relevant treatment to control point and compare with embodiment one, two, three, present embodiment improves the accuracy of frame relevant treatment.Be described to increase " interpolation procedure " on the basis of embodiment three below.
As shown in Figure 8, step S801, S803, S805 are similar with the step S601 shown in Fig. 6, S603, S605 respectively, just no longer describe in detail here.
In interpolation procedure S807, according to the Displacement Estimation result at control point, current time image carries out interpolation based on each control point, obtained the parameters of displacement field of each pixel or tissue points in current time image by interpolation.
In a kind of embodiment, to each pixel (x in current time image X (K), or tissue points (x y), y, z), the control point set Control (m obtained after selecting control point based on step S801, n) each control point in, nearest 4 pixels in this control point or 8 tissue points of adjusting the distance carry out linear interpolation, parameters of displacement field (xmove (the x of each pixel in X (K) can be obtained, y), ymove (x, y), Err (x, ) or the parameters of displacement field of tissue points (xmove (x y), y, z), ymove (x, y, z), zmove (x, y, z), Err (x, y, z)).In an embodiment, due to control point be select on sampled point basis after, control point is no longer equally distributed as sampled point, and the weight at each control point and this point are inversely proportional to the distance of (x, y) or (x, y, z).After interpolation, obtain each pixel in current time image X (K) or tissue points to the same place of a upper time chart as X (K-1), namely in current time image X (K) each pixel or tissue points be correlated with to last frame after the one-to-one relationship of result images Y (K-1), based on the accuracy coefficient that this corresponding relation and interpolation obtain, step S809 can be forwarded to and carry out frame correlation computations.
In another kind of embodiment, the Displacement Estimation result at each control point can with decimal, namely the displacement of each pixel or tissue points can be floating number, like this, based on this floating number displacement, specific point is can not find as X (K-1) corresponding with it at a upper time chart, therefore, 4 pixels that this floating number displacement of the present embodiment detection range is nearest or 8 tissue points, based on concrete to floating number position of each point, interpolation goes out the monochrome information of this location point, then carries out frame correlation computations at the location point gone out based on this interpolation.
In frame correlation computations step S809, each pixel now in image or tissue points participate in carrying out frame correlation computations, concrete frame correlation computations process step S409 similar to Figure 4, just no longer describe in detail here.
In Fig. 8 illustrated embodiment, select some control point in the picture, the image X (K) in continuous print adjacent two moment and X (K-1) is utilized to determine the relative displacement at control point, the accuracy (i.e. Displacement Estimation uncertain parameters) that deformation based is estimated provides the frame correlation coefficient at control point, obtained displacement and the correlation coefficient of each pixel or tissue points in image by interpolation, and then carry out the process of frame correlation computations.Therefore, the advantage of Fig. 8 illustrated embodiment is: reduce operand by selecting control point and eliminate the pixel or tissue points not easily followed the tracks of, the hunting zone to same place is reduced in conjunction with initial displacement, frame correlation technique is not only utilized to reach the object of restraint speckle, and, obtain frame correlation coefficient by Displacement Estimation, reduce frame and to be correlated with the motion blur brought.
Be appreciated that, in another embodiment of the invention, the flow process of frame correlation technique comprises: the selection (the step S401 in corresponding aforementioned each embodiment or step S601 or step S801) first carrying out control point, then the Displacement Estimation (the step S405 in corresponding aforementioned each embodiment or step S605 or step S805) at control point is carried out, displacement relation and the Displacement Estimation uncertain parameters (the step S807 in corresponding aforementioned each embodiment) of every bit in image is obtained by interpolation, and carry out frame relevant treatment (the step S409 in corresponding aforementioned each embodiment or step S609 or step S809).
First some embodiments of the present invention select control point in current time image, and the selection at control point effectively reduces amount of calculation and rejects the control point being not easy to follow the tracks of, and promotes the quality of Displacement Estimation.In a upper time chart picture, Displacement Estimation is carried out for the control point selected, obtain the displacement at each control point and tracking error and Displacement Estimation uncertain parameters, tracking error is utilized to calculate the frame correlation coefficient at this control point, obtained displacement relation and the frame correlation coefficient of every bit in image by interpolation method, and carry out frame relevant treatment.Should be understood that frame correlation coefficient is for concrete a certain time chart picture, the frame correlation coefficient that the frame relevant parameter of its all pixel can use control point to obtain, also can for the frame correlation coefficient of correspondence obtained after each pixel or tissue points interpolation.When can avoid popping one's head in mobile or histokinesis fast in conjunction with displacement estimation effect delta frame correlation coefficient, Displacement Estimation error is on the impact of frame correlation computations, tracking error and Displacement Estimation uncertain parameters are also a tolerance of correspondence image neighborhood of pixel points intensity profile similarity simultaneously, based on this parameter delta frame correlation coefficient, more effectively can reject random noise with the algorithm of prior art, promote the effect of frame correlation computations.
In the present invention's each embodiment aforementioned, involved view data can be any 2D or 3D ultrasonic image sequence, as ColorDoppler (color Doppler) image sequence, PowerDoppler (power doppler) image sequence, angiographic image series, radio frequency image sequence etc.For these view data, those skilled in the art can carry out simple deformation according to embodiment of the present invention and be achieved.Be appreciated that, when image is 2D image, involved each control point, corresponding point and same place or match point etc. are pixel, its neighborhood of a point is two-dimensional blocks of data, and corresponding displacement relation is expressed as bivector; When image is 3D rendering, involved each point is tissue points, and its neighborhood of a point is three-dimensional cuboid data, and corresponding displacement relation is expressed as three-dimensional vector.
The each embodiment of the present invention is relevant with frame for Displacement Estimation combination, and deformation based estimates uncertain parameters delta frame correlation coefficient.In a kind of embodiment, neighborhood of a point information is attached in the generation of frame correlation coefficient, namely based on the similarity determination frame correlation coefficient of two vertex neighborhoods, more effectively can removes the impact of random noise.The phenomenons such as Displacement Estimation technology can ensure that two points carrying out frame correlation computations are real corresponding relations, the image blurring and hangover avoiding motion time frame correlation computations in image layer to cause.Each embodiment of the present invention can be used for general imaging of tissue and promotes signal noise ratio (snr) of image, also can be used for ultrasonic contrast image and promotes angiographic results.
Above-described embodiment is citing of the present invention, although disclose most preferred embodiment of the present invention and accompanying drawing for the purpose of illustration, but it will be appreciated by those skilled in the art that: without departing from the spirit and scope of the invention and the appended claims, various replacement, change and amendment are all possible.Therefore, the present invention should not be limited to the content disclosed in most preferred embodiment and accompanying drawing.
Claims (15)
1. a frame correlation technique, is characterized in that, comprising:
Displacement Estimation step, for carrying out the Displacement Estimation relative to a upper time chart picture to the pixel of specifying in current time image or tissue points, obtain the parameters of displacement field of this pixel or tissue points, described parameters of displacement field comprises the Displacement Estimation uncertain parameters of displacement relation between this pixel or tissue points and its same place in a upper time chart picture and this pixel or tissue points;
Frame correlation computations step, for according to the described pixel of parameters of displacement field determination current time image or the frame correlation coefficient of tissue points, and utilize frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain current time picture frame be correlated with after result images;
Also comprise before described Displacement Estimation step: step is selected at control point, for selecting at least one control point on current time image, the pixel that this control point is specified in current time image or tissue points;
Described control point selects step to comprise: judge whether pixel in current time image or tissue points and its corresponding point in a upper time chart picture are all non-noise point, if be all non-noise point, then select this pixel or tissue points to be control point.
2. the method for claim 1, is characterized in that, determines whether non-noise point and selects control point to comprise:
Respectively sampling is carried out to described current time image and a described upper time chart picture according to predetermined step-length and obtain sampled point;
Respectively current time image and on each sampled point is calculated in a time chart picture to the mean and variance of the predetermined neighborhood of this sampled point;
Ratio according to variance and average judges, if this ratio is more than or equal to predetermined threshold, then judges that described sampled point is as noise spot, does not process; If this ratio is less than predetermined threshold, then judge that described sampled point is as doubtful control point;
According to the coordinate position at control point doubtful in current time image, judge whether the point corresponding to this coordinate position in a upper time chart picture is doubtful control point, if so, then select doubtful control point in current time image to be control point;
Or, determine whether non-noise point and select control point to comprise:
According to predetermined step-length, sampling is carried out to described current time image and obtain sampled point;
Calculate the mean and variance of the predetermined neighborhood of each sampled point;
Ratio according to variance and average judges, if this ratio is more than or equal to predetermined threshold, then judges that described sampled point is as noise spot, does not process;
If this ratio is less than predetermined threshold, then calculates average and the variance of the predetermined neighborhood of the corresponding point of described sampled point in a upper time chart picture, if the ratio of the variance of corresponding point and average is less than described predetermined threshold, then select described sampled point to be control point.
3. the method for claim 1, is characterized in that, also comprises: displacement initialization step before described Displacement Estimation step, for arranging initial displacement to the pixel of specifying in current time image or tissue points.
4. method as claimed in claim 3, it is characterized in that, described displacement initialization step comprises: carry out in the process of Displacement Estimation at current time image, has completed intermediate value or the average of some pixels of estimation or the displacement of tissue points in the predetermined neighborhood that the initial displacement of current pixel point or tissue points is set to this pixel or tissue points.
5. the method for claim 1, is characterized in that, described Displacement Estimation step comprises:
According to this pixel or the predetermined neighborhood of tissue points and the predetermined neighborhood of corresponding point, calculate the absolute value sum of difference of the brightness value of each corresponding pixel or tissue points in these two predetermined neighborhoods or the quadratic sum of the difference of brightness value;
The pixel corresponding with the quadratic sum of the absolute value sum of the difference of minimum brightness value or the difference of brightness value or tissue points are this pixel or the same place of tissue points in a upper time chart picture;
Described Displacement Estimation uncertain parameters is quadratic sum the counting divided by all pixels in this pixel or the predetermined neighborhood of tissue points or tissue points of the absolute value sum of the difference of described minimum brightness value or the difference of brightness value;
Or described Displacement Estimation step comprises:
According to this pixel or the predetermined neighborhood of tissue points and the predetermined neighborhood of corresponding point, calculate the relative coefficient of the Luminance Distribution of these two predetermined neighborhoods, formula is:
wherein: x
jfor control point Control
ipredetermined neighborhood Block (Control
i) an interior jth pixel or tissue points, y
kfor corresponding point P
ipredetermined neighborhood Block (P
i) an interior kth pixel or tissue points, N is the size of predetermined neighborhood,
represent the meansigma methods of brightness in the predetermined neighborhood at control point and the predetermined neighborhood of corresponding point respectively;
The pixel corresponding with maximum relative coefficient or tissue points are this pixel or the same place of tissue points in a upper time chart picture;
Described Displacement Estimation uncertain parameters is inverse or the negative of described maximum relative coefficient.
6. the method for claim 1, it is characterized in that, also comprise after described Displacement Estimation step He before described frame correlation computations step: interpolation procedure, for according to described displacement relation, obtained the parameters of displacement field of each pixel or tissue points on current time image by interpolation.
7. the method for claim 1, is characterized in that, the determination of described frame correlation coefficient comprises: described frame correlation coefficient is the decreasing function of described Displacement Estimation uncertain parameters.
8. the method for claim 1, it is characterized in that, the determination of described frame correlation coefficient comprises: according to the pixel in current time image or tissue points and its decreasing function of difference of brightness value of same place in a upper time chart picture and the decreasing function according to described Displacement Estimation uncertain parameters, obtain described frame correlation coefficient.
9. method as claimed in claim 8, it is characterized in that, described frame correlation coefficient obtains according to following formula:
α′(x,y)＝f(Err)*exp(-b*|g(K)-g(K-1)|)
In formula, α ' (x, y) be frame correlation coefficient, f (Err) is the decreasing function of described Displacement Estimation uncertain parameters, K is current time, and K-1 was a upper moment, the brightness value that g (K) is the pixel in current time image or tissue points, the brightness value of g (K-1) same place in a upper time chart picture for the pixel in current time image or tissue points, b is adjustment factor.
10. the method as described in any one of claim 1-9, it is characterized in that, described utilize frame correlation coefficient to carry out described current time image frame is relevant to be comprised: it is relevant that the result images after utilizing frame correlation coefficient to be correlated with to a upper time chart picture frame and current time image carry out frame.
11. 1 kinds of frame relevant apparatus, is characterized in that, comprising:
Displacement Estimation module, for carrying out Displacement Estimation to the pixel of specifying in current time image or tissue points, obtain the parameters of displacement field of this pixel or tissue points, described parameters of displacement field comprises the Displacement Estimation uncertain parameters of displacement relation between this pixel or tissue points and its same place in a upper time chart picture and this pixel or tissue points;
Frame correlation computations module, for according to described parameters of displacement field determination frame correlation coefficient, and utilizes described frame correlation coefficient to carry out frame to described current time image to be correlated with, thus obtain described current time picture frame be correlated with after result images;
Described device also comprises: control point selection module, for selecting at least one control point on current time image, and the pixel that this control point is specified in current time image or tissue points;
Described control point selection module comprises: judging unit, for judging whether pixel in current time image or tissue points and its corresponding point in a upper time chart picture are all non-noise point, if be all non-noise point, then this pixel or tissue points is selected to be control point.
12. devices as claimed in claim 11, is characterized in that, also comprise: displacement initialization module, for arranging initial displacement to the pixel of specifying in current time image or tissue points.
13. devices as claimed in claim 11, is characterized in that, also comprise: interpolating module, for according to described displacement relation, are obtained the parameters of displacement field of each pixel or tissue points on current time image by interpolation.
14. devices as described in any one of claim 11-13, it is characterized in that, described utilize frame correlation coefficient to carry out described current time image frame is relevant to be comprised: it is relevant that the result images after utilizing frame correlation coefficient to be correlated with to a upper time chart picture frame and current time image carry out frame.
15. 1 kinds of ultrasonic image-forming systems, is characterized in that, comprise the frame relevant apparatus as described in any one of claim 11-14.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110219847.5A CN102908163B (en) | 2011-08-02 | 2011-08-02 | A kind of frame correlation technique and device thereof and ultrasonic image-forming system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110219847.5A CN102908163B (en) | 2011-08-02 | 2011-08-02 | A kind of frame correlation technique and device thereof and ultrasonic image-forming system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102908163A CN102908163A (en) | 2013-02-06 |
| CN102908163B true CN102908163B (en) | 2016-01-20 |
Family
ID=47606913
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110219847.5A Active CN102908163B (en) | 2011-08-02 | 2011-08-02 | A kind of frame correlation technique and device thereof and ultrasonic image-forming system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102908163B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102156297B1 (en) * | 2014-04-17 | 2020-09-15 | 삼성메디슨 주식회사 | Medical image apparatus and operating method for the same |
| CN104125474B (en) * | 2014-07-07 | 2017-03-08 | 山东神戎电子股份有限公司 | A kind of self adaptation night vision vedio noise reduction method |
| CN104757999B (en) * | 2015-04-07 | 2018-03-09 | 声泰特（成都）科技有限公司 | A kind of nonlinear imaging method and system based on ultrasonic fundamental wave harmonic |
| JP6724797B2 (en) * | 2017-01-13 | 2020-07-15 | コニカミノルタ株式会社 | Ultrasonic diagnostic device and control method thereof |
| CN106878680A (en) * | 2017-02-24 | 2017-06-20 | 深圳汇创联合自动化控制有限公司 | A kind of easy transmission facility recognition system |
| CN111436905B (en) * | 2020-04-03 | 2024-03-19 | 图湃(北京)医疗科技有限公司 | Optical coherence tomography angiography method and device |
| CN112734665B (en) * | 2020-12-31 | 2023-07-14 | 飞依诺科技股份有限公司 | Ultrasonic image time domain filtering method, equipment and medium for weakening motion blur |
| CN113160072B (en) * | 2021-03-19 | 2023-04-07 | 聚融医疗科技(杭州)有限公司 | Robust self-adaptive frame correlation method and system based on image pyramid |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1472954A (en) * | 2002-07-15 | 2004-02-04 | ���ǵ�����ʽ���� | Circuit and method for improving image quality by fram correlation |
| CN101009021A (en) * | 2007-01-25 | 2007-08-01 | 复旦大学 | Video stabilizing method based on matching and tracking of characteristic |
| JP2008259555A (en) * | 2007-04-10 | 2008-10-30 | Hitachi Medical Corp | Ultrasonic diagnostic equipment |
| CN101527034A (en) * | 2008-03-07 | 2009-09-09 | 深圳迈瑞生物医疗电子股份有限公司 | Method and device for correlating adaptive frames |
| CN101645167A (en) * | 2008-08-06 | 2010-02-10 | 深圳迈瑞生物医疗电子股份有限公司 | Method and device for frame correlation coefficient control and frame correlation processing, and ultrasonic imaging system |
| CN102113900A (en) * | 2010-01-05 | 2011-07-06 | 深圳迈瑞生物医疗电子股份有限公司 | Relevant method and device for color blood flow dynamic frame |
| CN102123667A (en) * | 2008-08-19 | 2011-07-13 | 松下电器产业株式会社 | Ultrasonographic device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9078592B2 (en) * | 2008-10-27 | 2015-07-14 | Wisconsin Alumni Research Foundation | Ultrasonic strain imaging device with selectable cost-function |
-
2011
- 2011-08-02 CN CN201110219847.5A patent/CN102908163B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1472954A (en) * | 2002-07-15 | 2004-02-04 | ���ǵ�����ʽ���� | Circuit and method for improving image quality by fram correlation |
| CN101009021A (en) * | 2007-01-25 | 2007-08-01 | 复旦大学 | Video stabilizing method based on matching and tracking of characteristic |
| JP2008259555A (en) * | 2007-04-10 | 2008-10-30 | Hitachi Medical Corp | Ultrasonic diagnostic equipment |
| CN101527034A (en) * | 2008-03-07 | 2009-09-09 | 深圳迈瑞生物医疗电子股份有限公司 | Method and device for correlating adaptive frames |
| CN101645167A (en) * | 2008-08-06 | 2010-02-10 | 深圳迈瑞生物医疗电子股份有限公司 | Method and device for frame correlation coefficient control and frame correlation processing, and ultrasonic imaging system |
| CN102123667A (en) * | 2008-08-19 | 2011-07-13 | 松下电器产业株式会社 | Ultrasonographic device |
| CN102113900A (en) * | 2010-01-05 | 2011-07-06 | 深圳迈瑞生物医疗电子股份有限公司 | Relevant method and device for color blood flow dynamic frame |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102908163A (en) | 2013-02-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102908163B (en) | A kind of frame correlation technique and device thereof and ultrasonic image-forming system | |
| CN101527034B (en) | Method and device for correlating adaptive frames | |
| US5503153A (en) | Noise suppression method utilizing motion compensation for ultrasound images | |
| JP4795675B2 (en) | Medical ultrasound system | |
| WO2018222724A1 (en) | Methods for super-resolution ultrasound imaging of microvessels | |
| US10456116B2 (en) | Shadow suppression in ultrasound imaging | |
| US9123139B2 (en) | Ultrasonic image processing with directional interpolation in order to increase the resolution of an image | |
| US7706625B2 (en) | Trilateral filter for medical diagnostic imaging | |
| CN102958450B (en) | Three-dimensional elastic image generation method and ultrasonic diagnosis device | |
| CN101866480A (en) | Frame correlation processing method and system in spatial compound imaging | |
| JP2023500769A (en) | A method for high spatio-temporal resolution ultrasound imaging of microvessels | |
| WO2015087227A1 (en) | Image compounding based on image information | |
| US20200184614A1 (en) | Power doppler imaging system and method with improved clutter suppression | |
| US9384568B2 (en) | Method and system for enhanced frame rate upconversion in ultrasound imaging | |
| JP5918200B2 (en) | Ultrasonic diagnostic equipment | |
| US8313435B2 (en) | Clutter signal filtering in an ultrasound system | |
| EP3136974B1 (en) | Elastography visualization | |
| CN111819465B (en) | System and method for adaptively configuring dynamic range for ultrasound image display | |
| US20040225221A1 (en) | Diagnostic ultrasound imaging system with adaptive persistence | |
| JP7520103B2 (en) | Ultrasonic imaging of acoustic attenuation coefficients using elevation synthesis. | |
| US20150342569A1 (en) | Transparency control for medical diagnostic ultrasound flow imaging | |
| CN102867292A (en) | Stepped mean filtering method aimed at imaging data of multibeam forward-looking sonars | |
| WO2022271601A1 (en) | Systems and methods for reverberation clutter artifacts suppression in ultrasound imaging | |
| Al Mukaddim et al. | Cardiac strain imaging with dynamically skipped frames: A simulation study | |
| Zhang et al. | Despeckle filters for medical ultrasound images |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20130206 Assignee: Shenzhen Mindray Animal Medical Technology Co.,Ltd. Assignor: SHENZHEN MINDRAY BIO-MEDICAL ELECTRONICS Co.,Ltd. Contract record no.: X2022440020009 Denomination of invention: A frame correlation method and device, and an ultrasound imaging system Granted publication date: 20160120 License type: Common License Record date: 20220804 |