CN102973296A - Vascular tissue displacement estimation method - Google Patents
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Abstract
The invention relates to a vascular tissue displacement estimation method. The steps of the vascular tissue displacement estimation method include step one, collecting a radio frequency signal before vascular tissue is compressed and the radio frequency signal after the vascular tissue is compressed, and then conducting cross correlation analysis between the radio frequency signal before compression and the radio frequency signal after compression by adoption of a big data window with a compression point as a center to obtain a cross correlation function between the big data window before compression and the big data window after compression; step two, filtering the cross correlation function generated in the step one, and calculating rough displacement d1 of the radio frequency signal at the time of the big data window by utilization of a comprehensive correlation function; step three, stretching the radio frequency signal after the vascular tissue is compressed according to the displacement d1 by utilization of a signal re-correlation method, and rebuilding correlativity of the radio frequency signal after the vascular tissue is compressed and the radio frequency signal before the vascular tissue is compressed; step four, conducting cross correlation analysis between the re-correlated radio frequency signal and the radio frequency signal before the vascular tissue is compressed by adoption of a small data window to obtain residual displacement d2 of the small data window after the vascular tissue is compressed; and step five, superposing the displacement d1 obtained from estimation of the displacement of the big data window and the displacement d2 obtained from the estimation of the displacement of the small data window to obtain a final displacement field. The vascular tissue displacement estimation method can be widely applied in the technical field of ultrasound elastography.
Description
Technical field
The present invention relates to a kind of Ultrasonic Elasticity Imaging field, particularly about a kind of vascular tissue offset estimation method.
Background technology
A large amount of physiology and pathological process often are accompanied by the variation of tissue elasticity in the human body, and therefore, elasticity is a key character of reaction biological tissue.Apoplexy be one highly cause death, disabling condition, 80% apoplexy is to be caused by angiemphraxis and local anemia, is that the institute of breaking by the atherosclerosis vulnerable plaque causes and surpass 60% local brain tissue ischemia.The stability of speckle is decided by its chemical constituent, the factors such as cell material and new vessels formation.Large quantity research points out to have the speckle of specific modality, and larger lipid core is namely arranged, and the outside covers the layer fibrous cap, and charges into the speckle of internal blood vessel, breaks under the blood pressure effect of beating and then causes thrombosis easilier.The heterogeneity of speckle has significant difference in elastic characteristic.Therefore ultrasonic elastograph imaging is the composition of definite speckle, and infers that its vulnerability provides a kind of possible method.Elastogram is determined the elastic characteristic of tissue by detecting tissue for the response of various external sources/endogenous mechanicalness excitation usually.
Elasticity of compression imaging is proposed in 1991 by people such as J.Ophir, has the resolution height, cost is low and be easy to and the advantage such as existing ultrasonic device combination.As shown in Figure 1, its ultimate principle is: the ultrasonic radiofrequency signal of two frames before and after the collection machinery excitation (static state or quasistatic), utilize time delay (time delay) estimator to estimate the displacement of tissue compression front and back, the subsequently strain figure (strain image) that obtains organizing of the first-order difference by the displacement calculating field, i.e. elastic graph (elastogram).Because it is differently strained that the tissue of different hardness presents, elastic graph can reflect that the hardness of tissue distributes.The mechanical excitation here can be external source, such as the certain decrement (as shown in Figure 1) that tissue is applied by compressive plate; Also can be endogenous, shrink such as the active of cardiac muscle, or the blood vessel deformation that causes of the blood pressure of beating.
Since the elastogram algorithm of the propositions such as J.Ophir based on the radiofrequency signal correlation analysis, many elastogram algorithm developments get up.Generally speaking, the ultrasonic elastograph imaging algorithm can be divided into two large types: a class is based on the strain algorithm for estimating of gradient computing, namely first the displacement of tissue is estimated, then Displacement Estimation is done difference processing, the stress distribution that obtains organizing is such as time domain cross correlation algorithm, phase-detection method, zero crossing tracing etc.; Another kind of is direct strain algorithm for estimating, not take displacement of tissue as in the middle of estimated value, directly obtain the stress distribution organized, stretch algorithm, spectrum related algorithm etc. such as self adaptation.In these methods, the time domain cross-correlation method is because its stronger anti-noise ability becomes the most basic a kind of method, and its basic point of departure is the distortion that the side-play amount of cross-correlation function peak value can be used for following the tracks of tissue.The cross-correlation method on basis is to calculate compression front signal and compression back echo Signal cross correlation coefficient in certain data window length, then calculate the side-play amount of the peak point of this cross-correlation coefficient with respect to zero point, be the relative displacement of two segment signals on time domain, and with this relative displacement as their expressed organizational units.After the local displacement of tissue is determined fully, shift value is carried out the stress distribution that calculus of differences can obtain organizing.
This simple cross-correlation displacement estimation method is larger at some volumes, has reached preferably effect in the relatively simple tissue elasticity imaging of structure.But usually have histokinesis's complexity at blood vessel and speckle elastogram process, dynamic is strong, is subject to the practical problems such as interference of various pseudo-shadows and noise.Therefore, traditional one dimension cross correlation algorithm is not satisfactory the Displacement Ageing fruit of estimating carotid artery vascular and speckle, and is subjected to pseudo-peak error interference more serious.
The employed data window length of cross correlation algorithm is the important parameter that determines the displacement estimation effect.When organizing when only having rigid motion, use long radiofrequency signal will be conducive to improve the effect of estimation.But when having distortion, the signal decorrelation that is caused by strain will reduce the performance of time delay estimator, increase estimate variance.So, theoretically, under the condition that strain exists, use the short data window about several wavelength to be conducive to reduce the variance of Displacement Estimation, and help to improve the resolution of displacement field.Short data window is subject to the interference of pseudo-peak error easily, and introduces a large amount of spiced salt shape noises but in practice.
Summary of the invention
For the problems referred to above, the purpose of this invention is to provide and a kind ofly can improve resolution, reduce variance, and effectively reduce vascular tissue's offset estimation method at pseudo-peak.
For achieving the above object, the present invention takes following technical scheme: a kind of vascular tissue offset estimation method, it may further comprise the steps: 1) collected the radiofrequency signal before vascular tissue's compression and the radiofrequency signal after the compression by existing device, centered by compression point, to before compressing and the radiofrequency signal after the compression adopt large data window to carry out cross-correlation analysis, the large data window before obtaining compressing with compress after large data window between cross-correlation function; 2) correlation function that is obtained by step 1) is carried out correlation filtering, obtain comprehensive correlation function, the displacement d1 of radiofrequency signal when recycling comprehensive correlation function and calculating large data window; 3) utilize again correlation technique of signal, according to step 2) in the radiofrequency signal of displacement d1 after to tissue compression carry out stretch compensation, with radiofrequency signal after the alternative original compression of the radiofrequency signal behind the stretch compensation, the radiofrequency signal after the reconstruction tissue compression and the dependency of compression front signal; 4) adopt the small data window that the radiofrequency signal after step 3) is relevant again and the radiofrequency signal before the compression are carried out cross-correlation analysis, obtain compressing the residual displacement d2 of rear small data window; 5) will be by step 2) large data window Displacement Estimation the displacement d1 that obtains and the displacement d2 that step 4) small data window Displacement Estimation obtains superpose, and obtains final displacement field.
Large data window in described step 1) and the step 3) and the offset estimation method of small data window are as follows: (1) uses concentric large data window to calculate comparatively coarse Displacement Estimation d1; (2) use with the large concentric small data window of data window vascular tissue is carried out cross-correlation analysis again, move first the position of small data window by displacement d1, and calculate the displacement d2 of small data window after mobile near the position with cross-correlation method; (3) real displacement that obtains the small data window according to step (1) and step (2) is d=d
1+ d
2
The present invention is owing to take above technical scheme, it has the following advantages: 1, the present invention is owing to adopt the again method that combines of method of correlation of multiple-length data window, correlation filtering and signal, bring into play simultaneously the advantage of the whole bag of tricks, and then reach raising resolution, reduction variance, reduce the purpose at pseudo-peak.2, the present invention adopts and to carry out correlation filtering to carry out the cross-correlation function that cross-correlation analysis obtains with large data window, obtain comprehensive correlation function, and the displacement of radiofrequency signal when utilizing comprehensive correlation function to calculate large data window, the pseudo-peak noise of similar spiced salt shape can effectively be removed in the displacement field like this.3, the present invention adopts concentric large data window to calculate comparatively coarse Displacement Estimation, and large data window can suppress pseudo-peak to a certain extent, helps to improve the stability of Displacement Estimation.Therefore, can increase the hunting zone when using large data window, to capture larger displacement of tissue.4, the present invention is owing to adopting the small data window to carry out cross-correlation analysis through the radiofrequency signal of again correlation technique processing and the signal before the compression again after large data window and correlation filtering processing, obtain compressing the residual displacement of rear small data window, like this size data window combination, can utilize simultaneously the pseudo-peak of large data window establishment, utilize the small data window to improve displacement resolution, reduce the offset estimation variance.The present invention can be widely used in the Ultrasonic Elasticity Imaging field.
Description of drawings
Fig. 1 is ultrasonic elastograph imaging principle schematic in the prior art;
Fig. 2 is offset estimation method overall flow sketch map of the present invention;
Fig. 3 is the comparison sketch map that the present invention adopts length travel field, correlation filtering method front and back; Wherein Fig. 3 (a) is the displacement field that directly obtains according to the correlation function maximum; Fig. 3 (b) is behind correlation filtering, the displacement field that calculates according to comprehensive correlation function;
Fig. 4 is that the multiple-length data window method that the present invention adopts is estimated the displacement principle sketch map; Wherein Fig. 4 (a) is the coarse Displacement Estimation value that obtains when adopting large data window; Fig. 4 (b) adopts the small data window to carry out the residual displacement estimated value that obtains behind the correlation technique again;
Fig. 5 is correlation filtering principle schematic of the present invention; Wherein Fig. 5 (a) is data window (dashed rectangle) sketch map for the treatment of data estimator window (solid-line rectangle) and carrying out correlation filtering on every side with it; Fig. 5 (b) treats data estimator window and its cross-correlation function curve of each data window on every side among correlation filtering nuclear (two-dimentional Hamming window) and Fig. 5 (a); Fig. 5 (c) does the weighted linear resulting comprehensive correlation function curve that superposes with the cross-correlation function in the filtering core scope.
The specific embodiment
Below in conjunction with drawings and Examples the present invention is described in detail.
As shown in Figure 2, a kind of vascular tissue's offset estimation method that can effectively improve blood vessel offset estimation effect provided by the invention, its step is as follows:
1) collected the radiofrequency signal before vascular tissue's compression and the radiofrequency signal after the compression by existing equipment, centered by compression point, to before compressing and the radiofrequency signal after the compression adopt large data window to carry out cross-correlation analysis, the large data window before obtaining compressing with compress after large data window between cross-correlation function.
2) cross-correlation function that is obtained by step 1) is carried out correlation filtering, obtain comprehensive correlation function, the displacement d1 of radiofrequency signal when recycling comprehensive correlation function and calculating large data window; If without correlation filtering, the displacement field that then directly obtains according to the correlation function maximum contains the pseudo-peak noise (shown in Fig. 3 (a)) of a large amount of similar spiced salt shapes, and the present invention adopts the displacement field that obtains behind correlation filtering can effectively remove the pseudo-peak noise (shown in Fig. 3 (b)) of similar spiced salt shape.
3) utilize again correlation technique of signal, according to step 2) in the radiofrequency signal of displacement d1 after to tissue compression carry out stretch compensation, with radiofrequency signal after the alternative original compression of the radiofrequency signal behind the stretch compensation, the radiofrequency signal after the reconstruction tissue compression and the dependency of compression front signal.
The present invention adopts correlation technique can effectively reduce the Displacement Estimation variance again, and the radiofrequency signal after correlation technique compresses by stretch tissue is again rebuild itself and the dependency that compresses front signal, strengthens dependency, can significantly reduce the noise that is organized in the displacement field like this.
4) adopt the small data window that the radiofrequency signal before the radiofrequency signal after step 3) is relevant again and the compression is carried out cross-correlation analysis, obtain compressing the residual displacement d2 of rear small data window, like this can establishment puppet peak, to reduce the offset estimation variance.
5) will be by step 2) large data window Displacement Estimation the displacement d1 that obtains and the displacement d2 that step 4) small data window Displacement Estimation obtains superpose, and obtains final displacement field.
Above-mentioned steps 1) and the offset estimation method of the large data window in the step 3) and small data window as follows:
(1) shown in Fig. 4 (a), use concentric large data window to calculate comparatively coarse Displacement Estimation d1, large data window can suppress pseudo-peak to a certain extent, helps to improve the stability of Displacement Estimation.Therefore, can increase the hunting zone when using large data window, to capture larger displacement of tissue.
(2) shown in Fig. 4 (b) (black box is the small data window among the figure), use with the large concentric small data window of data window vascular tissue is carried out cross-correlation analysis again, because the displacement d1 that the large data window of use obtains and the real displacement of small data window approach but are accurate not, for estimating the displacement of small data window, move first the position of small data window by displacement d1, and near mobile rear position, calculate the displacement d2 of small data window with cross-correlation method.Because the main displacement of vascular tissue has been included among the displacement d1, residual displacement d2 is less, and this moment, the hunting zone of small data window can foreshorten in the wave-length coverage, thereby avoided pseudo-peak.
The real displacement that (3) can obtain the small data window according to step (1) and step (2) is d=d
1+ d
2Hence one can see that, and the multiple-length data window method that the present invention adopts can utilize large data window to the resistance of pseudo-peak error simultaneously, and the low variance characteristics of small data window.
Above-mentioned steps 2) in, the correlation filtering method is: the cross-correlation function of certain data window and near data window thereof is weighted on average, and finally generate a comprehensive correlation function, determine again the displacement of this data window by the maximum that calculates this comprehensive correlation function.
For example, shown in Fig. 5 (a), be the displacement of solid-line rectangle data window in the drawing for estimate, at first set a correlation filtering nuclear (shown in Fig. 5 (b)), this filtering core is the two-dimensional space window function, usually is set as the Hamming window, and its center overlaps with treating the data estimator window.Then, the data window in the filtering core institute coverage (being dotted line and solid-line rectangle data window among Fig. 5 (a)) cross-correlation function separately is weighted linear superposition, and obtains comprehensive correlation function (shown in Fig. 5 (c)).The weight coefficient of each data window is selected (such as Fig. 5 (b)) by its locus in filtering core.The comprehensive cross-correlation coefficient that obtains as stated above has the space smoothing effect, and the resistance at pseudo-peak is strengthened greatly.
In sum, the present invention adopts the again method that combines of method of correlation of multiple-length data window, correlation filtering and signal, brings into play simultaneously the advantage of the whole bag of tricks, and then reaches and improve resolution, reduce variance, reduces the purpose at pseudo-peak.
Below by a specific embodiment the present invention is further introduced.
Embodiment:
Present embodiment adopts the IU22 ultrasonic image-forming system of Philips company, is equipped with L9-3 type hand-held probe.In the experiment, behind selected area-of-interest under the B ultrasonic guiding (blood vessel major axis visual angle), the continuous acquisition radiofrequency signal is about 4 cardiac cycles altogether, and sample rate is fixed as 32MHz, and the frame per second of ultra sonic imaging is set to 47Hz, imaging width 38mm(320 bar scanning line).
Selecting the reason at major axis visual angle is to avoid the vasomotion direction inconsistent with the acoustic beam direction.After data acquisition is finished, radiofrequency signal is uploaded to PC carries out off-line analysis, and according to the displacement of tissue between vascular tissue of the present invention offset estimation method estimation two continuous frames.The parameter setting that at first carries out cross-correlation analysis by large data window is: longitudinal data window length 1.80mm, lateral length 0.85mm, the vertical 0.07mm in data window interval, side direction 0.17mm; The template length of using when carrying out correlation filtering is vertical 1.1mm, side direction 0.85mm; Vertical and the lateral displacement of then calculating according to back stretches to the radiofrequency signal after compressing, and namely realizes the relevant again of signal; After being correlated with, the data window length when carrying out cross-correlation analysis by the small data window is vertical 0.70mm, side direction 0.51mm again.In twice Displacement Estimation, all use cross-correlation method; Displacement estimates by carrying out that the two-dimensional cross correlation function is replaced vertically and the side direction interpolation, and gets its maximum and obtain.
The various embodiments described above only are used for explanation the present invention; the connection of each parts and structure all can change to some extent; on the basis of technical solution of the present invention; all improvement and equivalents of connection and the structure of individual component being carried out according to the principle of the invention all should not got rid of outside protection scope of the present invention.
Claims (2)
1. vascular tissue's offset estimation method, it may further comprise the steps:
1) collected the radiofrequency signal before vascular tissue's compression and the radiofrequency signal after the compression by existing device, centered by compression point, to before compressing and the radiofrequency signal after the compression adopt large data window to carry out cross-correlation analysis, the large data window before obtaining compressing with compress after large data window between cross-correlation function;
2) correlation function that is obtained by step 1) is carried out correlation filtering, obtain comprehensive correlation function, the displacement d1 of radiofrequency signal when recycling comprehensive correlation function and calculating large data window;
3) utilize again correlation technique of signal, according to step 2) in the radiofrequency signal of displacement d1 after to tissue compression carry out stretch compensation, with radiofrequency signal after the alternative original compression of the radiofrequency signal behind the stretch compensation, the radiofrequency signal after the reconstruction tissue compression and the dependency of compression front signal;
4) adopt the small data window that the radiofrequency signal after step 3) is relevant again and the radiofrequency signal before the compression are carried out cross-correlation analysis, obtain compressing the residual displacement d2 of rear small data window;
5) will be by step 2) large data window Displacement Estimation the displacement d1 that obtains and the displacement d2 that step 4) small data window Displacement Estimation obtains superpose, and obtains final displacement field.
2. a kind of vascular tissue as claimed in claim 1 offset estimation method, it is characterized in that: the large data window in described step 1) and the step 3) and the offset estimation method of small data window are as follows:
(1) use concentric large data window to calculate comparatively coarse Displacement Estimation d1;
(2) use with the large concentric small data window of data window vascular tissue is carried out cross-correlation analysis again, move first the position of small data window by displacement d1, and calculate the displacement d2 of small data window after mobile near the position with cross-correlation method;
(3) real displacement that obtains the small data window according to step (1) and step (2) is d=d
1+ d
2
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103735287A (en) * | 2013-12-05 | 2014-04-23 | 中国科学院苏州生物医学工程技术研究所 | Method for estimating intravascular ultrasonic elastography two-dimensional multistage hybrid displacement |
| CN105232087A (en) * | 2015-11-05 | 2016-01-13 | 无锡祥生医学影像有限责任公司 | Ultrasonic elastic imaging real-time processing system |
| CN115527616A (en) * | 2022-11-09 | 2022-12-27 | 北京昭衍新药研究中心股份有限公司 | Estimation method for obtaining total number of cells in flow cytometry and application |
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| CN1586411A (en) * | 2004-08-06 | 2005-03-02 | 清华大学 | Two dimension complex interrelative biological tissue displacement evaluating method |
| CN1586409A (en) * | 2004-08-20 | 2005-03-02 | 清华大学 | Biological tissue displacement evaluating method using two kinds of size |
| CN101569543B (en) * | 2008-04-29 | 2011-05-11 | 香港理工大学 | Two-dimension displacement estimation method of elasticity imaging |
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Patent Citations (3)
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| CN1586411A (en) * | 2004-08-06 | 2005-03-02 | 清华大学 | Two dimension complex interrelative biological tissue displacement evaluating method |
| CN1586409A (en) * | 2004-08-20 | 2005-03-02 | 清华大学 | Biological tissue displacement evaluating method using two kinds of size |
| CN101569543B (en) * | 2008-04-29 | 2011-05-11 | 香港理工大学 | Two-dimension displacement estimation method of elasticity imaging |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103735287A (en) * | 2013-12-05 | 2014-04-23 | 中国科学院苏州生物医学工程技术研究所 | Method for estimating intravascular ultrasonic elastography two-dimensional multistage hybrid displacement |
| CN103735287B (en) * | 2013-12-05 | 2015-11-18 | 中国科学院苏州生物医学工程技术研究所 | A kind of intravascular ultrasound elastogram two-dimensional multistage mixing displacement estimation method |
| CN105232087A (en) * | 2015-11-05 | 2016-01-13 | 无锡祥生医学影像有限责任公司 | Ultrasonic elastic imaging real-time processing system |
| CN105232087B (en) * | 2015-11-05 | 2018-01-09 | 无锡祥生医疗科技股份有限公司 | Ultrasonic elastograph imaging real time processing system |
| CN115527616A (en) * | 2022-11-09 | 2022-12-27 | 北京昭衍新药研究中心股份有限公司 | Estimation method for obtaining total number of cells in flow cytometry and application |
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Application publication date: 20130320 |