CN1313055C - Biological tissue displacement evaluating method using two kinds of size - Google Patents
Biological tissue displacement evaluating method using two kinds of size Download PDFInfo
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Abstract
The present invention relates to a biological tissue displacement evaluating method using two kinds of sizes, which belongs to the technical field of ultrasonic elastic imaging. The method comprises the following steps: data d1 with the size of T <a> is taken from the first scanning line data of a two-dimension radio frequency signal of a tissue before being compressed; a crosscorrelation function R (tau) of the small segment of data and the first scanning line data s2 (n) of a two-dimension radio frequency signal of the tissue after being compressed is calculated, and position t'1 to which the maximum value corresponds is determined; data e1 with the size of T<b> is taken from the central position of the data segment d1 of scanning line data s1 (n); a crosscorrelation function R'(tau) of the small segment of data and the scanning line data s2 (n) is calculated to obtain position t'1 to which the maximum value corresponds; finally, the displacement t1 of the small segment of data d1 to which fine adjustment is carried out is obtained; the displacement evaluation of a tissue to each scanning line data corresponds is obtained orderly according to the method. The present invention combines two methods which carry out tissue displacement evaluation by choosing the large size or the small size to enhance strong points and avoid weaknesses of the two tissue displacement evaluation methods, so that the evaluation precision of the tissue displacement is improved.
Description
Technical field
The invention belongs to the ultrasonic elastograph imaging technical field, particularly the biological tissue displacement method of estimation.
Background technology
The variation of biological tissue elasticity modulus is relevant with its pathological phenomenon usually.For example, virulent pathological lesion, for example breast inocarcinoma, carcinoma of prostate, thyroid carcinoma and hepatic metastases etc. are usually expressed as hard brief summary.The breast inocarcinoma is the most common form of breast carcinoma, accounts for 3/4ths of breast carcinoma sum greatly, shows as fine and close lump owing to its density of matrix increases.The breast carcinoma of other types such as intraductal carcinoma and papilloma then show as softish tissue, and benign fibrocystic disease of breast also seldom shows as lump.
The elastic modelling quantity information of biological tissue has important value for the diagnostic procedure of disease.Yet the traditional medicine image mode that comprises x-ray imaging, ultra sonic imaging, computer tomography (CT) and nuclear magnetic resonance (MRI) etc. all can not directly provide the information about the basic mechanical attribute of this tissue of elastic modelling quantity.1991, J.Ophir proposed the method for ultrasonic elastograph imaging (ultrasound elastography), the elastic modelling quantity of tissue is distributed quantitatively estimate, imaging.At present, ultrasonic elastic modulus has become one of medical ultrasound image research focus, is widely used in the detection and the assessment of the infringement (lesion) that breast, prostate, atherosclerotic plaque, myocardium kinetics and high intensity focused ultrasound and radio-frequency (RF) ablation cause.
The ultimate principle of ultrasonic elastograph imaging is: ultrasonic probe is embedded in the extruding flat board, along vertical compress tissue of probe, gathers the forward and backward radiofrequency signal of tissue compression respectively; Tissue will produce a strain along compression direction in the tissue when being compressed, if organization internal elastic modelling quantity skewness, in-house stress distribution is difference to some extent also; The zone that elastic modelling quantity is bigger, the strain ratio that causes is less; Otherwise, the zone that elastic modelling quantity is less, corresponding strain ratio is bigger.Estimate the displacement of organization internal diverse location by certain methods, thereby calculate the stress distribution situation of organization internal, be used for the elastic modelling quantity of intermediate description organization internal to distribute, thereby describe physiology, the pathological state of tissue.
For the two-dimensional ultrasound elastogram, the general Type B ultrasonic probe that adopts linear array, gather the radiofrequency signal of forward and backward each the bar scanning line of probe of tissue compression, carry out above-described Displacement Estimation respectively, thereby the uniaxial train that calculates the corresponding tissue of each bar scanning line distributes.At last the uniaxial train of all scanning line correspondences is distributed and press the scanning line order and form a two-dimentional stress distribution, represent, be used for the elastic modelling quantity distribution of intermediate description organization internal with the form of gray-scale map or pcolor.
General ultrasonic elastograph imaging method may further comprise the steps:
1. utilize commercial B-mode ultrasonic apparatus device (generally adopting linear array probe) to obtain biological tissue to be measured and (be generally tissue, also can be animal tissue, hereinafter to be referred as tissue) a digitized two-dimentional radiofrequency signal before the compression (can adopt analog radio-frequency signal output termination signal amplifier, connect high-speed data acquisition card again, obtain digitized two-dimentional radiofrequency signal; Also can on digitized B-mode ultrasonic apparatus device, directly obtain digitized two-dimentional radiofrequency signal);
2. the probe of hand-held this B-mode ultrasonic apparatus device or utilize motor or screw drives this probe, along probe vertically this tissue is applied a small extruding (it is 1% the order of magnitude that the decrement that tissue is applied generally is controlled at), obtain a digitized two-dimentional radiofrequency signal after the tissue compression;
3. the data of taking out article one scanning line respectively from the forward and backward two-dimentional radiofrequency signal of the tissue compression that obtains of step 1 and 2 are made as s
1(n) and s
2(n), n represents the data sequence number on these two scanning lines, 1≤n≤n
Max, the maximum n of n
MaxProbing depth, the spread speed of ultrasonic waves transmitted in tissue and the sample frequency decision of radiofrequency signal by this B-mode ultrasonic apparatus device;
4. from this scan-line data s
1(n) get the data d that a bit of length is T in
1, its data number is U, U=round (T * U
1), wherein, the unit of T is mm, U
1Represent the data number of the tissue correspondence of 1mm, by spread speed and the sample frequency of the radiofrequency signal decision of ultrasonic waves transmitted in tissue, round () representative rounds up rounds operation, these data d
1Sequence number from n
1To n
1+ U-1, n
1But x is at 1≤n
1Select in the scope of≤U; At τ
1To τ
2Ask this little segment data and scan-line data s in the hunting zone of determining
2(n) cross-correlation function R (τ), computing formula is as follows
Wherein i is the cyclic variable of computational process invading the exterior registration according to sequence number, τ
1Be 0, τ
2Be the decrement that tissue is applied, represent with the number of sampled data; In order to improve the precision of Displacement Estimation, generally also need to carry out interpolation, as conventional interpolation methods such as parabolas to calculating cross-correlation function;
5. the position t of the maximum correspondence of the cross-correlation function R (τ) that obtains of determining step 4
1, t
1Be exactly data d
1Displacement after tissue compression (is s
1(n) sequence number in is from n
1To n
1The segment data d of+U-1
1After tissue compression, move to s
2(n) sequence number in is from n
1-t
1To n
1+ U-1-t
1The position);
6. successively from scan-line data s
1(n) getting a bit of length in is that T is that the data number is the data d of U
2, d
3..., d
N, the sequence number of every segment data V the sampled data that stagger successively, 1≤V≤U, V sampled data will exceed s up to staggering again
1(n) scope, 4,5 identical methods obtain the displacement t of each segment data correspondence successively set by step
2, t
3..., t
N, wherein N is the sum of little segment data; Then displacement sequence t
1, t
2..., t
NBe article one scan-line data s
1(n) Displacement Estimation of Dui Ying tissue;
7. utilize the method identical with step 3-6, obtain the 2nd, 3 successively ..., M bar scan-line data correspondence the Displacement Estimation of tissue, wherein M is the scanning line sum of expression probe, by the probe decision;
8. to article one scan-line data s
1(n) the Displacement Estimation sequence t of Dui Ying tissue
1, t
2..., t
NAsk difference, obtain organizing article one scanning line s
1(n) stress distribution of corresponding tissue, computing formula is as follows,
Wherein, ε
1, ε
2..., ε
N-1Be respectively d
1, d
2..., d
N-1Corresponding organize strain;
9. utilize the method identical with step 8, obtain organizing the 2nd, 3 successively ..., M bar scan-line data correspondence the stress distribution of tissue;
10. the stress distribution of the M bar scan-line data correspondence that step 9 is obtained is synthesized a 2-D data according to the der group of scanning line, and is showed with the form of gray-scale map or pcolor, just obtains the two-dimentional diagram of strains of organizing.
In ultrasonic elastograph imaging, crucial problem is the Displacements Distribution of tissue is estimated, just the step 3-7 of above-described method.The value of cross-correlation function is big more, illustrate that the forward and backward little segment data of compression is identical well more, the maximum value position of cross-correlation function has been represented the position of the correspondence after compression of the little segment data before the compression, thereby can obtain the displacement of this little segment data, just the displacement of the tissue of this segment data correspondence.
In ultrasonic elastograph imaging, the little segment data in the compression front signal of selection is used for following the tracks of the displacement of corresponding segment tissue, is called the tracking wave band.Its length is called follows the tracks of wave band length, perhaps yardstick.It is extremely important in the Displacement Estimation of ultrasonic elastograph imaging to choose suitable yardstick.When the decrement that tissue is applied in the time of smaller (as less than 1%), yardstick is big more, and the information that comprises is many more, and the precision of Displacement Estimation is high more, and is also insensitive more to the interference of random noise.When the decrement that tissue is applied bigger (as 1-5%) time, yardstick is big more, because tissue is compressed, the forward and backward signal superposed part of tissue compression is more little, it is low more to utilize the cross-correlation function maximum value position to carry out the precision of Displacement Estimation, simultaneously, yardstick is big more, is not easy to be subjected to the interference of random noise again more; And when yardstick was less, the forward and backward signal superposed part of tissue compression was bigger, and the precision of Displacement Estimation is higher, yet the Displacement Estimation of this moment is responsive to the interference ratio of random noise again.
In order to increase the degree that the forward and backward signal of tissue compression overlaps, generally adopt approach based on linear interpolation, the signal that is ' compressed ' " stretching " (stretching) is become long together with original signal, thus the registration of waveform before and after the increase compression.In waveform stretching, drawing coefficient is relevant with decrement that tissue is applied or strain (representing with percentage ratio).When drawing coefficient near the tissue strain the time, the registration maximum of waveform, thereby cross-correlation function maximum maximum.But the strain of tissue is unknown before time delay is estimated, the selection of drawing coefficient can only be done roughly to judge according to the degree of depth of displacement that applies and tissue.And because the inhomogeneities of tissue, the strained distribution of organization internal is also inhomogeneous, and therefore specific drawing coefficient is in some part of tissue deficiency that may stretch, and it is excessive to stretch again in some part, and this introduces error conversely again.Therefore, the someone proposes a kind of the wave band of diverse location to be carried out the method for self adaptation drawing coefficient, makes the cross-correlation function maximum maximum of wave band before wave band and the compression after stretching, utilizes the drawing coefficient direct estimation to go out the strain of this position tissue then.But the tensile method of this self adaptation is longer computation time, may be restricted in actual applications.
From angle of practical application, wishing the decrement that tissue is applied, bigger good, can more can " see " details of the stress distribution difference that the organization internal elastic modulus difference causes like this clearly.The general repeatedly method of compression (multi-compression) that adopts is decomposed into little displacement sum with big displacement, to the tissue little displacement of exerting pressure, calculates corresponding stress distribution one by one.At last with the stack of several stress distribution, the stress distribution when obtaining big displacement.Yet this method has increased data acquisition time.
Summary of the invention
The present invention proposes the displacement of tissue method of estimation of two kinds of yardsticks of a kind of employing in order to solve the contradiction of the decrement that tissue is applied large scale and small scale bigger the time.When the tissue compression amount is bigger, two kinds of methods selecting large scale or small scale to carry out the displacement of tissue estimation are combined, can realize the pluses and minuses that these two kinds of displacement of tissue are estimated maximizing favourable factors and minimizing unfavourable ones, improve the precision that displacement of tissue is estimated.
The displacement of tissue method of estimation of two kinds of yardsticks of a kind of employing that the present invention proposes may further comprise the steps:
1. the data of taking out article one scanning line respectively from the forward and backward two-dimentional radiofrequency signal of tissue compression are made as s
1(n) and s
2(n), n represents the data sequence number on these two scanning lines, 1≤n≤n
Max, the maximum n of n
MaxProbing depth, the spread speed of ultrasonic waves transmitted in tissue and the sample frequency decision of radiofrequency signal by this B-mode ultrasonic apparatus device;
2. from this scan-line data s
1(n) getting a bit of yardstick in is T
aData d
1, its data number is U
a, U
a=round (T
a* U
1), wherein, T
aUnit be mm, U
1Represent the data number of the tissue correspondence of 1mm, by spread speed and the sample frequency of the radiofrequency signal decision of ultrasonic waves transmitted in tissue, round () representative rounds up rounds operation, these data d
1Sequence number from n
1To n
1+ U
a-1, n
1Can be at 1≤n
1≤ U
aScope in select; At τ
1To τ
2The hunting zone in ask this little segment data and scan-line data s
2(n) cross-correlation function R (τ), computing formula is as follows
Wherein i is the cyclic variable of computational process invading the exterior registration according to sequence number, τ
1Be 0, τ
2Be the decrement that tissue is applied, represent with the number of sampled data; In order to improve the precision of Displacement Estimation, preferably also need to carry out interpolation processing, as conventional interpolation methods such as parabola interpolations to calculating cross-correlation function;
3. the position t ' of the cross-correlation function R ' maximum correspondence (τ) that obtains of determining step 2
1, t '
1For utilizing yardstick T
aData d when carrying out Displacement Estimation
1Displacement after tissue compression (is s
1(n) sequence number in is from n
1To n
1+ U
a-1 segment data d
1After tissue compression, move to s
2(n) sequence number in is from n
1-t '
1To n
1+ U
a-1-t '
1The position);
4. from this scan-line data s
1(n) the data segment d in
1Middle position to get yardstick again be T
b, sequence number from
Arrive
A bit of data e
1, this data number is U
b, U
b=round (T
b* U
1), wherein, T
bUnit be mm, and satisfy T
b<T
a, preferably get
At τ
3To τ
4Ask this little segment data and scan-line data s in the hunting zone of determining
2(n) " (τ), computing formula is as follows for cross-correlation function R
τ wherein
3And τ
4Be the scope of the meticulous adjustment of displacement of tissue, satisfy following relation: τ
4<τ
2, τ
3=-τ
4, preferably get
In order to improve the precision of Displacement Estimation, preferably also carry out interpolation, as conventional interpolation methods such as parabola interpolations to calculating cross-correlation function;
5. the cross-correlation function R " the position t of maximum correspondence (τ) " that obtains of determining step 4
1, t "
1For utilizing yardstick T
bData e when carrying out Displacement Estimation
1Displacement with respect to t '
1Skew;
6. utilize yardstick T
bThe displacement bias t that estimation obtains "
1To yardstick T
aThe displacement t ' that estimation obtains
1Adjust the segment data d that obtains
1Meticulous adjusted displacement t
1, that is:
t
1=t′
1+t″
1
7. successively from scan-line data s
1(n) getting a bit of yardstick in is T
aBe that the data number is U
aData d
2, d
3..., d
N, the sequence number of every segment data V the sampled data that stagger successively, 1≤V≤U
a, V sampled data will exceed s up to staggering again
1(n) scope, the method that 2-6 is identical obtains the displacement t of each segment data correspondence successively set by step
2, t
3..., t
N, wherein N is the sum of little segment data; Then displacement sequence t
1, t
2..., t
NBe article one scan-line data s
1(n) Displacement Estimation of Dui Ying tissue;
8. utilize the method identical with step 1-7, obtain the 2nd, 3 successively ..., M bar scan-line data correspondence the Displacement Estimation of tissue, wherein M is the scanning line sum of expression probe, by the probe decision.
Principle of the present invention:
The present invention adopts the tracking wave band of two kinds of yardsticks to carry out Displacement Estimation, uses the tracking wave band T of large scale earlier
aCarry out the first estimation of displacement, use the tracking wave band T of small scale then
bCarry out fine tuning.The mode that the thought of the method for two kinds of yardsticks of this employing has been imitated the eye-observation things: see slightly that with large scale the reuse small scale is scrutinized earlier, just the partial thought in whole earlier back.
The present invention utilizes big yardstick to eliminate the influence of random noise, thereby has determined the approximate range of displacement of tissue, utilizes little yardstick to come displacement of tissue is accurately estimated then.Because when utilizing the tracking wave band of small scale to carry out Displacement Estimation, be on large scale is followed the tracks of the basis of estimated result of wave band, to carry out, can in a little scope, calculate cross-correlation function, so the influence of random noise is smaller.This method has been broken the constant thinking of fixed size, has solved the contradiction of the decrement that tissue is applied large scale and small scale bigger the time well, has improved the precision that displacement of tissue is estimated, does not allow to be subject to the influence of random noise again.
From the angle of error analysis, the error of Displacement Estimation can be divided into phase error and pseudo-peak error.Phase error performance is near the disturbance actual displacement value of correspondence tissue of the maximum value position of the cross-correlation function between the forward and backward radio frequency reading line data of compression, and error is less.And the maximum value position that pseudo-peak error shows as this cross-correlation function actual displacement value of the corresponding tissue of substantial deviation, the displacement of tissue of this moment estimates not comprised enough quantity of information.When the decrement that tissue is applied was bigger, yardstick was big more, did not allow to be subject to the interference of random noise more, was not easy to occur pseudo-peak error more, but because the forward and backward signal superposed part of tissue compression is more little, the phase error of this moment is bigger; And yardstick hour, and phase error is reduced, but the pseudo-peak error of this moment is bigger.
The method of two kinds of yardsticks of employing that the present invention proposes is exactly to utilize large scale to reduce pseudo-peak error earlier, utilizes small scale to reduce phase error then, thereby combines the advantage of two kinds of yardsticks, has reduced the interference of error, has improved the precision that displacement of tissue is estimated.
Characteristics of the present invention:
1 adopts the tracking wave band of two kinds of different scales, utilizes the meticulous again adjustment of first rough estimate, elder generation's partial thinking in arrangement back to carry out Displacement Estimation;
2 carry out the rough estimate of displacement earlier with the tracking wave band of large scale, the tracking wave band with small scale carries out meticulous adjustment then;
3 results that utilize meticulous adjustment revise the result of rough estimate, estimate thereby obtain more accurate displacement of tissue.
Description of drawings
The computer artificial result of organizing stress distribution that Fig. 1 obtains for general displacement of tissue method of estimation;
The computer artificial result of organizing stress distribution that the embodiment of the displacement of tissue method of estimation of two kinds of yardsticks of employing that Fig. 2 proposes for the present invention obtains.
The specific embodiment
The displacement of tissue method of estimation of two kinds of yardsticks of employing that the present invention proposes reaches accompanying drawing in conjunction with specific embodiments and is described in detail as follows:
Embodiments of the invention utilize computer program and general ultrasonic scattering model emulation obtain one mimic be organized in the compression before and the compression after the one dimension radiofrequency signal.Tissue thickness is 60mm, and wherein the elastic modelling quantity at 0-30mm place is 3 times of elastic modelling quantity at 30-60mm place, adopt simple one-dimensional model, so the strain at 0-30mm place is strained 1/3 of 30-60mm place.The decrement that tissue is applied is 3.33%, i.e. 1.98mm; The center probe frequency is 3.5MHz, and-three dB bandwidth is 2.0MHz, because adopt simple one-dimensional model, so have only a scanning line; The sample frequency of radiofrequency signal is 20MHz, supposes that ultrasound wave is 1540m/s in in-house spread speed, so the corresponding 1mm/ (1540 * 10 of the tissue of 1mm
3Mm/s/ (20 * 10
6Hz)/2 26 data of ≈, because tissue depth is 60mm, so the data of each bar scanning line are 60 * 26=1560, the decrement that tissue is applied is expressed as 52 sampled datas of 60 * 3.33% * 26 ≈ with the number of sampled data.
The large scale T that present embodiment adopts
aBe 4mm, the hunting zone is 0 to 52; The small scale T that adopts
bBe 1mm (also can adopt 2mm or any yardstick in 1mm to 2mm scope) that the hunting zone (also can be-20 to-20 or satisfied 10≤τ for-10 to 10
4≤ 26 and τ
3=-τ
4From τ
3To τ
4Any scope).
The concrete steps of present embodiment are as follows:
1. establish the forward and backward one dimension radiofrequency signal (being scan-line data) of tissue tissue compression and be respectively s
1(n) and s
2(n); N represents the data sequence number on these two scanning lines, 1≤n≤1560;
2. from this scan-line data s
1(n) getting a bit of yardstick in is T
aData d
1, T
a=4mm, its data number is U, U=104, the sequence number of these data from 32 to 135; In 0 to 52 hunting zone, ask this little segment data and scan-line data s
2(n) cross-correlation function R (τ), computing formula is as follows
3. determine the position t ' of this cross-correlation function R ' maximum correspondence (τ)
1, t '
1Utilize yardstick T exactly
aData d when carrying out Displacement Estimation
1Displacement after tissue compression (is s
1The segment data d of the sequence number (n) from 32 to 135
1After tissue compression, move to s
2(n) sequence number in is from 32-t '
1To 135-t '
1The position);
4. get s
1The a bit of data e of the sequence number (n) from 71 to 96
1, these data e
1Be positioned at data d
1Middle position; These data e
1Yardstick be T
b, T
b=1mm, the data number is U
b, U
b=26; In-10 to 10 hunting zone, ask this little segment data and scan-line data s
2(n) " (τ), computing formula is as follows for cross-correlation function R
5. the cross-correlation function R " the position t of maximum correspondence (τ) " that obtains of determining step 4
1, t "
1Utilize yardstick T exactly
bData e when carrying out Displacement Estimation
1Displacement with respect to t '
1Skew;
6. utilize yardstick T
bThe displacement bias t that estimation obtains "
1To yardstick T
aThe displacement t ' that estimation obtains
1Adjust the segment data d that obtains
1Meticulous adjusted displacement t
1, that is:
t
1=t′
1+t″
1
7. successively from scan-line data s
1(n) getting a bit of yardstick in is T
aBe that the data number is U
aData d
2, d
3..., d
N, the sequence number of every segment data 32 sampled datas that stagger successively, 32 sampled datas will exceed s up to staggering again
1(n) scope, the method that 2-6 is identical obtains the displacement t of each segment data correspondence successively set by step
2, t
3..., t
N, wherein N is the sum of little segment data, N=45; Then displacement sequence t
1, t
2..., t
NBe scan-line data s
1(n) Displacement Estimation of Dui Ying tissue.
The Displacement Estimation effect of present embodiment and conventional method is compared as follows:
Fig. 1 and Fig. 2 are the result's of the result of present embodiment and conventional method comparison.Among Fig. 1 and Fig. 2, abscissa is represented the diverse location organized, and vertical coordinate is represented strained size; The actual strain of dotted line 11 among Fig. 1 and the 21 expression tissues of the dotted line among Fig. 2 distributes; Among Fig. 1 12 estimates the stress distribution of organizing that obtains for adopting conventional method, and 22 among Fig. 2 estimates the stress distribution of organizing that obtains for the method for two kinds of yardsticks of employing of adopting the present invention and proposing.
By Fig. 1 and Fig. 2 as seen, the method of two kinds of yardsticks of employing that the present invention proposes adopts the tracking wave band of two kinds of different scales to carry out Displacement Estimation, the result is better than adopting the constant tracking section of fixed size to carry out the result of conventional method of Displacement Estimation, the precision of Displacement Estimation is higher, is particularly organizing the bigger zone of strain ratio (30-60mm position) more obvious.
Claims (3)
1, the displacement of tissue method of estimation of two kinds of yardsticks of a kind of employing may further comprise the steps:
1) data of taking out article one scanning line respectively from the forward and backward two-dimentional radiofrequency signal of tissue compression are made as s
1(n) and s
2(n), n represents the data sequence number on these two scanning lines, 1≤n≤n
Max, n
MaxMaximum for n;
2) from this scan-line data s
1(n) getting a bit of yardstick in is T
aData d
1, its data number is U
a, U
a=round (T
a* U
1), wherein, T
aUnit be mm, U
1Represent the data number of the tissue correspondence of 1mm, round () representative rounds up rounds operation, these data d
1Sequence number from n
1To n
1+ U
a-1,1≤n
1≤ U
aAt τ
1To τ
2The hunting zone in ask this little segment data and scan-line data s
2(n) cross-correlation function R (τ), computing formula is as follows
Wherein i is the cyclic variable of computational process invading the exterior registration according to sequence number, τ
1Be 0, τ
2Be the decrement that tissue is applied, represent with the number of sampled data;
3) determining step 2) the position t ' of the cross-correlation function R ' maximum correspondence (τ) that obtains
1, t ' then
1For utilizing yardstick T
aData d when carrying out Displacement Estimation
1Displacement after tissue compression, i.e. s
1(n) sequence number in is from n
1To n
1+ U
a-1 segment data d
1After tissue compression, move to s
2(n) sequence number in is from n
1-t '
1To n
1+ U
a-1-t '
1The position;
4) again from this scan-line data s
1(n) the data segment d in
1Middle position to get yardstick be T
b, sequence number from
Arrive
A bit of data e
1, this data number is U
b, U
b=round (T
b* U
1), wherein, T
bUnit be mm, and satisfy T
b<T
aAt τ
3To τ
4The hunting zone in ask this little segment data and scan-line data s
2(n) " (τ), computing formula is as follows for cross-correlation function R
Wherein
τ
3And τ
4Be the scope of the meticulous adjustment of displacement of tissue, satisfy following relation: τ
4<τ
2
5) determining step 4) the cross-correlation function R " the position t of maximum correspondence (τ) " that obtains
1, t then "
1For utilizing yardstick T
bData e when carrying out Displacement Estimation
1Displacement with respect to t '
1Skew;
6) utilize yardstick T
bThe displacement bias t that estimation obtains "
1To yardstick T
aThe displacement t ' that estimation obtains
1Adjust the segment data d that obtains
1Meticulous adjusted displacement t
1, that is:
t
1=t′
1+t″
1
7) successively from scan-line data s
1(n) getting a bit of yardstick in is T
aBe that the data number is U
aData d
2, d
3..., d
N, the sequence number of every segment data V the sampled data that stagger successively, 1≤V≤U
a, V sampled data will exceed s up to staggering again
1(n) scope, set by step 2)-6) identical method obtains the displacement t of each segment data correspondence successively
2, t
3..., t
N, wherein N is the sum of little segment data; Then displacement sequence t
1, t
2..., t
NBe article one scan-line data s
1(n) Displacement Estimation of Dui Ying tissue;
8) utilize and step 1)-7) identical method, obtain the 2nd, 3 successively ..., M bar scan-line data correspondence the Displacement Estimation of tissue, wherein M is the scanning line sum of expression probe.
2, the displacement of tissue method of estimation of two kinds of yardsticks of employing as claimed in claim 1 is characterized in that, also further is included in the described the 2nd), 4) the described cross-correlation function that calculates is carried out interpolation processing in the step.
3, the displacement of tissue method of estimation of two kinds of yardsticks of employing as claimed in claim 1 is characterized in that the described the 4th) yardstick T in the step
bSpan be:
The τ of the meticulous adjusting range of described displacement of tissue
4Value is
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CN102078205A (en) * | 2011-03-04 | 2011-06-01 | 深圳市一体医疗科技股份有限公司 | Displacement estimating method for measuring elasticity of viscoelastic medium and application method |
CN102764141B (en) * | 2012-07-20 | 2014-05-21 | 中国科学院深圳先进技术研究院 | Elastography method, elastography system, and biological tissue displacement estimation method and biological tissue displacement estimation system in elastography |
CN102973296A (en) * | 2012-11-16 | 2013-03-20 | 清华大学 | Vascular tissue displacement estimation method |
CN103211625B (en) * | 2013-01-11 | 2015-08-19 | 深圳市恩普电子技术有限公司 | Based on the biological displacement computational methods of elastogram |
CN103829975B (en) * | 2014-03-17 | 2017-01-18 | 飞依诺科技(苏州)有限公司 | Method for calculating ultrasonic elastography displacement value |
CN106037814B (en) * | 2016-05-13 | 2019-04-02 | 江西师范大学 | Ultrasonic elastography method based on fractal interpolation |
CN110946618B (en) * | 2019-11-24 | 2022-03-29 | 华南理工大学 | Elastic imaging method based on empirical manifold |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6687625B2 (en) * | 2002-04-22 | 2004-02-03 | The Board Of Regents Of The University Of Texas System | Method and apparatus for feature tracking strain estimation for elastography |
WO2004010872A1 (en) * | 2002-07-31 | 2004-02-05 | Hitachi Medical Corporation | Ultrasonic diagnosis system and distortion distribution display method |
-
2004
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6687625B2 (en) * | 2002-04-22 | 2004-02-03 | The Board Of Regents Of The University Of Texas System | Method and apparatus for feature tracking strain estimation for elastography |
WO2004010872A1 (en) * | 2002-07-31 | 2004-02-05 | Hitachi Medical Corporation | Ultrasonic diagnosis system and distortion distribution display method |
Non-Patent Citations (3)
Title |
---|
ULTRASONIC STRAIN RECONSTRUCTION USINGMULTI-SCALE CROSS-CORRELATION METHOD Yu Fan et al,proceeding 19th international conference.IEEE/EMBS 1997 * |
ULTRASONIC STRAIN RECONSTRUCTION USINGMULTI-SCALE CROSS-CORRELATION METHOD Yu Fan et al,proceeding 19th international conference.IEEE/EMBS 1997;超声弹性成像的原理及理论分析 罗建文,白净,国外医学生物医学工程分册,第26卷第3期 2003 * |
超声弹性成像的原理及理论分析 罗建文,白净,国外医学生物医学工程分册,第26卷第3期 2003 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2009132516A1 (en) * | 2008-04-29 | 2009-11-05 | 香港理工大学 | Method for two-dimensionally displacement estimation of elastography |
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