Visual tracking method for tiny movement based on OCT (Optical Coherence Tomography)

Abstract

The invention discloses an OCT (Optical Coherence Tomography)-based micro-motion visual tracking method, which relates to the field of micro-motion visual tracking methods and comprises the following steps of: executing continuous OCT circular scanning imaging on a moving target; calculating cross correlation coefficients of each line scan in a certain circular scan and different line scans of the adjacent circular scan one by one; the maximum value of the cross correlation coefficient is solved, the point difference between two line scans corresponding to the maximum cross correlation coefficient at the moment is calculated, and the point difference is the serial number offset; and calculating point differences of all line scans of the circular scanning, and executing micro motion tracking through point difference distribution. Meanwhile, visualization of the tiny movement is achieved based on the speckle movement effect in the continuous circular scanning OCT pattern, and finally visual tracking of the tiny movement is achieved; according to the method, planar motion tracking with configurable measurement range and resolution can be realized, and the defect that the traditional motion tracking method highly depends on the requirements of radiation signal input power and target surface reflectivity and roughness is overcome.

Description

Technical Field

[0001] The present application relates to the field of a method for visualizing and tracking tiny movements, and in particular, to a method for visualizing and tracking tiny movements based on OCT. Background Art

[0002] Motion tracking technology has a wide range of applications in many fields. These motion tracking technologies have favorable resolution and penetration range for specific applications. Traditional motion tracking technologies, such as laser and microwave-based tracking technologies, rely heavily on the reflection of the irradiation signal on the surface of the object being measured, which has certain requirements on the input power of the irradiation signal as well as the surface reflectivity and roughness. Based on the ability of OCT (Optical Coherence Tomoghraphy) to perform high-resolution, non-invasive tomography of biological tissues and materials, several velocity measurement technologies have been studied and proposed, including particle tracking velocimetry, particle streak velocimetry, etc. These technologies are only applicable to the motion of fluids containing moving particles and are difficult to measure planar motion. Summary of the invention

[0003] In order to solve the deficiencies in the prior art, the present invention provides a method for visual tracking of micro-motion based on OCT.

[0004] To achieve the above objectives, the technical solutions adopted in this application are as follows:

[0005] A method for visual tracking of micro-motion based on OCT, comprising:

[0006] S1: Perform continuous OCT circular scanning imaging on the sample;

[0007] S2: for the line scan number sequence obtained by the sample measurement, calculate the correlation coefficient between each line scan in a certain circular scan and different line scans in its adjacent circular scan one by one;

[0008] S3: solving the maximum value of the above mutual correlation coefficient, and calculating the point difference between the two line scans corresponding to the maximum mutual correlation coefficient at this time, wherein the point difference is the sequence number offset;

[0009] S4: Calculate the point difference of all line scans of the circle scan, and realize the motion speed measurement of the sample plane motion through the point difference distribution; that is, the motion speed of the sample plane motion is obtained through the point difference distribution, and the motion speed includes magnitude and direction;

[0010] S5: Combined with the visual effect of speckle movement in circular scanning, the tiny motion can be visualized. The sample motion speed obtained in S4 can verify the movement of speckle, thus realizing the visual tracking of the tiny motion of the sample.

[0011] The present invention obtains the moving sample speed through point difference calculation, and the speckle movement at different positions caused by moving targets in different directions can be seen in the speckle image obtained through visualization, thereby realizing sample visualization. The moving sample speed can prove the movement of the speckle, thereby realizing the visualized tracking of the sample's tiny movement.

[0012] Specifically, the S1 is specifically:

[0013] According to the line scan number N A The optical coherence tomography system continuously scans the sample in a circle and obtains a line scan sequence. Among them, C i represents the i-th circle scan, N A The numerical value representing the number of line scans, represents the jth line scan in the i-th circular scan; the optical coherence tomography system performs beam scanning along a circular trajectory, and the circular scanning speed is v s =2πr / N A t e , where r is the circular scanning radius of the OCT sample arm beam, t e is the time to complete one line scan.

[0014] Specifically, in S2, between two adjacent scanning circles C i and C i+1 The cross-correlation coefficients between different line scans are The calculation method is:

[0015]

[0016] Where ω0 is the scanning beam width, Δd is the distance between adjacent scanning circles with different line scan numbers, here is the scanning line and scan lines distance.

[0017] Further, the S2 is specifically:

[0018] S21. Calculate the relative movement speed of the sample is the motion speed of the motion sample, is the OCT circular scanning motion speed;

[0019] S22. Calculate the relative motion speed v of the sample along the X-axis and Y-axis directions x and v y :

[0020]

[0021] Among them, v s for scalar, which is the set device parameter, v m for The scalar is the speed value of the measured motion sample; in the two-dimensional XY plane, α is the sample motion speed The angle with the X axis, β is the circular scanning motion speed Angle with X axis, β=2πt / (N A t e ), t e Indicates the time to complete a scan;

[0022] S23. Calculate the position P (x, y) of the line scan at time t:

[0023]

[0024] S24. Calculate the number of circles C between two consecutive circles i and C i+1 Midline Scan and The distance Δd:

[0025]

[0026] Among them, t n and t m Indicates different scanning moments;

[0027] S25. Calculate the mutual correlation coefficient:

[0028]

[0029] Specifically, in S3, the maximum value of the above mutual correlation coefficient is obtained by taking the maximum value of the mutual correlation coefficient, that is, Where N is the circular scan C i+1 Midline Scan Line scan point value of ;

[0030] At this time, the two line scans corresponding to the maximum cross-correlation coefficient The spread between

[0031] By configuring the line scan number, radius and imaging exposure time of the OCT circular scan, planar motion tracking with a configurable wide measurable range and resolution is achieved, which has obvious advantages over traditional motion tracking technology. At the same time, thanks to the interference of light, when performing motion tracking, the present invention can better adapt to the input power of the irradiation signal and the surface reflectivity and roughness of the target. In the specific implementation of the present invention, the above technical solution was tested on tape.

[0032] The present invention is not limited to a single speed interval measurement, and can be adjusted by adjusting parameters according to actual needs of measuring different motion speeds.

[0033] The beneficial effects of the present invention are as follows: the OCT-based micro-motion visualization tracking technology proposed by the present invention can realize planar motion tracking with configurable measurement range and resolution, and overcome the traditional motion tracking method's high reliance on the input power of the radiation signal and the reflectivity and roughness of the target surface. At the same time, this method expands the motion tracking capability based on OCT and can produce better applications for some applications, such as motion tracking of biological tissues. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 It is the main flow chart of the present invention;

[0036] Figure 2 is a schematic diagram of an OCT imaging system of the present invention;

[0037] Figure 3 This is a schematic diagram of the tracking principle of micro-motion based on OCT of the present invention;

[0038] Figure 4 It is a schematic diagram of the distance between adjacent line scans and a schematic diagram of the maximum mutual correlation coefficient of the present invention;

[0039] Figure 5 It is a schematic diagram of the visualized motion of the present invention;

[0040] Figure 6 It is a numerical simulation schematic diagram of the present invention;

[0041] Figure 7 It is a schematic diagram of actually measuring different moving speeds and directions of the adhesive tape according to the present invention. DETAILED DESCRIPTION

[0042] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0043] like Figure 1As shown in the figure, a method for visual tracking of micro-motion based on OCT is based on an OCT (Spectraldomain OCT, SD-OCT) imaging system. The system includes an 850-nanometer broadband light source, a spectrometer, a fiber coupler, a first polarization controller, a collimator, glass, a first lens, a transmitting mirror, a second polarization controller, a second lens, a two-position scanning galvanometer, and a third lens. The specific process of the imaging system is as follows: the light emitted by the light source is coupled into the fiber coupler and enters the reference arm with a reflector and the sample arm with the sample to be measured respectively. The light reflected back by the reflector (reference light) and the backscattered light (signal light) of the sample are reunited through the fiber coupler to generate an interference signal. At this time, the coupled light can be regarded as the superposition of the interference between the various monochromatic wave components of the backscattered light from the sample and the corresponding components returned from the reference mirror. The interference signal is output from the other end of the fiber coupler, received by the spectrometer and expanded by the diffraction grating in the spectrometer, collected by the CCD and converted into electrical signals and digitized, and the obtained data is Fourier inverse transformed in the computer to obtain the OCT image. The system structure diagram is shown in the figure. Figure 2 As shown in the figure, the specific principle is an existing technology and will not be described and explained in detail here. OCT imaging based on interferometric measurement technology inevitably has speckles, and OCT imaging speckles also contain information. When performing OCT circular scanning using speckle spatial oversampling, a line scan sequence can be obtained during OCT sampling. The position analysis of adjacent OCT circular scan line scan sequences is performed to obtain the mutual correlation coefficient of the OCT line scans. When the mutual correlation coefficient between line scans (A-line) in different circular scan OCT images is maximized, the point difference (offset) of different line scans of adjacent circles is calculated, and the offset distribution of all line scans of the circular scan is combined to perform planar motion tracking. At the same time, when performing OCT circular scanning on a moving target, different offset distributions will result under different motions, and finally planar motion tracking is achieved, and the speckle movement effect in the continuous circular scan OCT pattern is used to achieve visualization of small motions, and finally visual tracking of small motions is achieved.

[0044] Based on the above principles, the method for this specific implementation includes the following steps:

[0045] S1: Perform continuous OCT circular scanning imaging on the sample; the key part of the proposed technique is the OCT scanning mode used. Circular scanning is used here. OCT circular scanning means that the OCT beam scans along a circular trajectory, and the OCT beam circular scanning speed Where r is the circular scanning radius of the OCT sample arm beam, t e is the time to complete a line scan, N AHere, using speckle spatial oversampling for OCT circular scanning can ensure that the distance between two adjacent a-lines is smaller than the OCT lateral optical resolution to reduce the adverse effects of imaging electronic noise.

[0046] According to the line scan number (A-line) is N A The optical coherence tomography (OCT) system performs continuous circular scanning to obtain a line scan sequence. Among them, C i represents the i-th circle scan, N A The numerical value representing the number of line scans, represents the jth line scan in the i-th circle scan.

[0047] S2: For the line scan number sequence obtained by sample measurement, calculate the correlation coefficient between each line scan (A-line) in a certain circular scan (any circular scan) and the different line scans in its adjacent circular scan one by one; assuming that any circular scan here is represented by C1, calculate the correlation coefficient between a line scan in this circular scan C1 and the different line scans in its adjacent circular scan C2, which is one calculation; then take another line scan in the circular scan C1 and calculate the correlation coefficient between it and the different line scans in the adjacent circle C2; ​​repeat this process so that all line scans in the circular scan C1 are calculated with the different line scans in the adjacent circle C2. Generally, in two adjacent scanning circles C i and C i+1 The cross-correlation coefficients between different line scans are The calculation method is:

[0048]

[0049] Where ω0 is the scanning beam width, Δd is the distance between adjacent scanning circles with different line scan numbers, here, are the scanning lines and scan lines The distance between different line scan numbers is affected by the speed of the moving sample. By performing OCT circular scanning on the moving target, the speed of different moving samples leads to different distances between adjacent line scan numbers, and thus the correlation coefficients of different line scan numbers can be obtained.

[0050] The S2 is specifically:

[0051] S21. Calculate the relative movement speed of the sample is the motion speed of the motion sample, is the OCT circular scanning motion speed; the relative motion speed varies with the scanning position;

[0052] S22. Calculate the relative motion speed v of the sample along the X-axis and Y-axis directions xand v y :

[0053]

[0054] Among them, v s for scalar, which is the set device parameter, v m for The scalar is the speed value of the measured motion sample; in the two-dimensional XY plane, α is the sample motion speed The angle with the X axis, β is the circular scanning motion speed Angle with X axis, β=2πt / (N A t e ), where t e Indicates the time to complete a scan;

[0055] S23. Calculate the position P (x, y) of the line scan at time t:

[0056]

[0057] S24. Calculate the number of circles C between two consecutive circles i and C i+1 Midline Scan and The distance Δd:

[0058]

[0059] Among them, t n and t m Indicates different scanning moments;

[0060] S25. Calculate the mutual correlation coefficient:

[0061]

[0062] S3: Solve the maximum value of the above mutual correlation coefficient, and calculate the point difference between the two line scans corresponding to the maximum mutual correlation coefficient at this time, and the point difference is the serial number offset; for example, the i-th line scan of a circle scan and the j-th line scan of the adjacent circle scan obtain the maximum value of the mutual correlation coefficient, and the point difference is ji. In S3, the maximum value of the above mutual correlation coefficient is solved as follows: take the maximum value of the mutual correlation coefficient, that is, Where N is the circular scan C i+1 Midline Scan Line scan point value of ;

[0063] At this time, the two line scans corresponding to the maximum cross-correlation coefficient The spread (offset) between

[0064] The speed measurement of the sample plane motion is achieved through the point difference distribution; Figure 6 , as shown in 7, different movement speeds will have different spread peaks, and the actual movement speed can be known through the spread peaks; at the same time, when facing moving targets in different directions, the relative movement speed will change with the direction of the circular scanning speed. When the circular scanning direction is the same as the movement direction, that is, when the relative movement speed is the largest, the spread will take an extreme value; when the line scan number N A =4000, corresponding to the circumference of 360°, the point difference distribution measurement when the mutual correlation coefficient is the maximum value for the moving targets in different directions will show the point difference extreme value of the line scan number at different positions, and the actual moving direction of the moving target can be known.

[0065] S4: Calculate the point difference of all line scans of the circle scan (each line scan will be calculated once to obtain the maximum mutual correlation coefficient, and then calculate the point difference), and obtain the movement speed of the sample plane through the point difference distribution, and the movement speed includes the magnitude and direction;

[0066] S5: Combined with the visual effect of speckle movement in circular scanning, the tiny motion can be visualized. The sample motion speed obtained in S4 can verify the movement of speckle, thus realizing the visual tracking of the tiny motion of the sample.

[0067] In the OCT continuous images obtained by continuous circular scanning using an optical coherence tomography system, when scanning a moving target, the speckle image will appear to move in a specific direction at certain fixed positions, such as Figure 5 (a), when the direction of the moving target is changed, the above fixed position will change, such as Figure 5 (b) As shown. Therefore, when the moving target has different speeds in different directions, it will cause fixed positions and moving directions at different positions in the speckle image, and the "fluidity" of the speckle will be more obvious. Finally, the visualization of micro-movement can be achieved by distinguishing the fixed positions and moving directions at different positions in the scanned OCT continuous images.

[0068] The present invention obtains the moving sample speed through point difference calculation, and the speckle movement at different positions caused by moving targets in different directions can be seen in the speckle image obtained through visualization, thereby realizing sample visualization. The moving sample speed can prove the movement of the speckle, thereby realizing the visualized tracking of the sample's tiny movement.

[0069] By configuring the line scan number (A-line), radius and imaging exposure time of the OCT circular scan, planar motion tracking with a configurable wide measurable range and resolution is achieved, which has obvious advantages over traditional motion tracking technology. At the same time, thanks to the interference of light, when performing motion tracking, the present invention can better adapt to the input power of the irradiation signal and the surface reflectivity and roughness of the target. At the same time, in the specific implementation, the technical solution of the present invention was tested on tape.

[0070] OCT imaging based on interferometric measurement technology inevitably has speckle, and OCT imaging speckle also contains information. When performing OCT circular scanning using speckle spatial oversampling, a line scan sequence can be obtained during OCT sampling. The position analysis of adjacent OCT circular scan line scan sequences is performed to obtain the mutual correlation coefficient of the OCT line scans. When the mutual correlation coefficient between line scans (A-line) in different circular scan OCT images is maximized, the point difference (offset) of different line scans of adjacent circles is calculated, and the offset distribution of all line scans of the circular scan is combined to perform planar motion tracking. At the same time, when performing OCT circular scanning on a moving target, different offset distributions will result under different motions, and finally planar motion tracking is achieved, and the speckle movement effect in the continuous circular scan OCT pattern is used to achieve visualization of small motions, and finally visual tracking of small motions is achieved.

[0071] In this specific implementation, the OCT system is based on a conventional spectral domain OCT system, with axial and lateral optical resolutions of approximately 2.5 μm and 8.5 μm, respectively. The lateral plane motion tracking performance of the motion tracking technology based on OCT imaging is demonstrated by using an imaging transparent tape as a moving sample. The transparent tape is attached to a two-dimensional plane motion stage, the OCT imaging exposure time is 25 μs, and the corresponding system sensitivity is 101 dB. In this specific implementation, the OCT circular scanning radius r is 1 mm, and the number of scanning lines N for each circular scanning line is A The OCT circular scans were performed on the transparent tape sample moving in different directions at different speeds using the above parameters.

[0072] Figure 3The schematic diagram of tracking micro-motion based on OCT is shown, which describes the positional relationship between different line scans in two adjacent circular scans. When the transparent tape moves along the positive direction of the X-axis, it is mainly divided into four areas ABCD in the figure. In the line scans with the same number of line scans in two adjacent circles, the relative motion speed is the vector accumulation of one circle of line scan time. In area A, the relative position will show a rightward movement, and the area corresponding to area A in the speckle image will show a parallel movement to the right; in area B, in the lower half, the relative position will show an upward movement, and in the upper half, the relative position will show a downward movement, and the area corresponding to area B in the speckle image will show a center, and both sides will move toward the center; while in area C, the relative position is opposite to that in area A, and the area corresponding to area C in the speckle image will show a parallel movement to the left; similarly, in area D, the relative position is opposite to that in area B, and the area corresponding to area D in the speckle image will show a center, and both sides will spread outward from the center. The BD area is also explained Figure 5 The reasons for the movement and direction of the speckle image.

[0073] Figure 4 (a) shows the distance measurement method of adjacent circle scans with different line scans. Figure 4 (b) shows the line scans in adjacent circle scans and Schematic diagram of the maximum mutual correlation coefficient value.

[0074] Figure 5 (a) shows the "flow" movement and direction of the speckle image at the specific location in the continuous OCT circular scan pattern, when the tape moves along the negative direction of the X axis at a speed of 10 mm per second, that is, the tape spreads outward at the left center and moves toward the center at the right center. When the direction of movement changes, the two centers move synchronously. Figure 5 (b) shows the tape moving along the negative direction of the Y axis at a speed of 10 mm per second. Comparing Figures a and b, we can see that the two centers move synchronously, and the moving distance is half the distance between the two centers. From this, we can infer that: as the angle moves from the negative direction of the X axis to the negative direction of the Y axis, the two centers also move synchronously. When the tape moves along the positive direction of the X axis, it will appear as follows Figure 5 (a) Two centers at the same position, but the movement of the two centers is opposite (i.e. the left center moves toward the center, and the right center spreads outward). On this basis, the direction of the tiny movement can be clearly known according to the position and movement of the left and right centers presented in the speckle image, thus realizing the visualization of the tiny movement.

[0075] Figure 6 The numerical simulation diagram is shown. First, the proposed small motion tracking is numerically simulated. In order to simplify the calculation, we assume that α = 0 and perform numerical simulation here. At the same time, the scanning time te is 200 microseconds, N A is 4000, the scanning circle radius is 1.6 mm, and ω0 is 8 μm. We first simulated the situation where the sample has different movement speeds, including -20 mm / s, -10 mm / s, 0 mm / s, 10 mm / s, and 20 mm / s. Using the above-mentioned micro-motion tracking method, we can obtain the offset distribution of each movement speed, and the corresponding fitting function can be obtained by the least squares method with N=6 times, as shown in Figure 6 shown.

[0076] Figure 7 The results of measuring the tape in different motions and directions are shown. The speeds of 0 mm / s, 2 mm / s, 5 mm / s, 10 mm / s, 15 mm / s, and 20 mm / s are measured along the positive and negative directions of the X-axis, and the corresponding measurement algorithms are executed to obtain the tracking measurement results, such as Figure 7 As shown. Figure 7 It can be seen that different motion speeds have different offsets, which shows that the proposed motion tracking technology can achieve motion measurement at different speeds. However, the presence of electrical noise will cause fluctuations in the offset. In order to improve the reliability of the data, 50 sets of data were averaged to obtain Figure 7 , which also leads to some deviation in the maximum offset.

[0077] The above are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for visual tracking of micro-motion based on OCT, characterized in that: include: S1: Perform continuous OCT circle scanning imaging on the sample, OCT stands for optical coherence tomography; S2: for the line scan number sequence obtained by the sample measurement, calculate the correlation coefficient between each line scan in a certain circular scan and different line scans in its adjacent circular scan one by one; S3: solving the maximum value of the above mutual correlation coefficient, and calculating the point difference between the two line scans corresponding to the maximum mutual correlation coefficient at this time, wherein the point difference is the sequence number offset; S4: Calculate the point difference of all line scans of the circle scan, and obtain the movement speed of the sample plane through the point difference distribution, and the movement speed includes magnitude and direction; S5: Combined with the visual effect of speckle movement in circular scanning, the tiny motion can be visualized. The sample motion speed obtained in S4 can verify the movement of speckle, thus realizing the visual tracking of the tiny motion of the sample.

2. The method for visual tracking of micro-motion based on OCT according to claim 1, characterized in that: The S1 is specifically: According to the line scan number N A The optical coherence tomography system performs continuous circular scanning on the sample to obtain a line scan sequence Among them, C i represents the i-th circle scan, N A The value representing the number of line scans, represents the jth line scan in the i-th circular scan; OCT circular scanning performs beam scanning along a circular trajectory, and the circular scanning speed is v s =2πr / N A t e , where r is the circular scanning radius of the OCT sample arm beam, t e is the time to complete one line scan.

3. The method for visual tracking of micro-motion based on OCT according to claim 2, characterized in that: In S2, between two adjacent scanning circles C i and C i+1 The cross-correlation coefficients between different line scans are The calculation method is: Among them, ω0 is the scanning beam width, Δd is the distance between adjacent scanning circles with different line scan numbers, here is the scanning line and scan lines distance.

4. The method for visual tracking of micro-motion based on OCT according to claim 3, characterized in that: The S2 is specifically: S21. Calculate the relative movement speed of the sample is the motion speed of the motion sample, is the OCT circular scanning motion speed; S22. Calculate the relative motion speed v of the sample along the X-axis and Y-axis directions x and v y : Among them, v s for Scalar, which is the set device parameter; v m for The scalar is the speed value of the measured motion sample; in the two-dimensional XY plane, α is the sample motion speed The angle with the X axis, β is the circular scanning motion speed Angle with X axis, β=2πt / (N A t e ), t e Indicates the time to complete a scan; S23. Calculate the position P (x, y) of the line scan at time t: S24. Calculate the number of circles C between two consecutive circles i and C i+1 Midline Scan and The distance Δd: Among them, t n and t m Indicates different scanning moments; S25. Calculate the mutual correlation coefficient:

5. The method for visual tracking of micro-motion based on OCT according to claim 4, characterized in that: In S3, the maximum value of the above mutual correlation coefficient is obtained by taking the maximum value of the mutual correlation coefficient, that is, Where N is the circular scan C i+1 Midline Scan Line scan point value of ; At this time, the two line scans corresponding to the maximum cross-correlation coefficient The spread between

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