An OCT-based micro-motion visualization tracking method

Abstract

This invention discloses a micro-motion visualization tracking method based on OCT, belonging to the field of micro-motion visualization tracking methods. The method includes: performing continuous OCT circular scan imaging on a moving target; calculating the cross-correlation coefficient between each line scan in a given circular scan and its adjacent circular scans; solving for the maximum value of the cross-correlation coefficients and calculating the point difference between the two line scans corresponding to the maximum cross-correlation coefficient, where the point difference is the sequence number offset; calculating the point difference of all line scans in the circular scan, and performing micro-motion tracking based on the point difference distribution. Simultaneously, the visualization of micro-motion is achieved based on the speckle movement effect in the continuous circular scan OCT pattern, ultimately realizing the visualization tracking of micro-motion. The method of this invention can achieve planar motion tracking with configurable measurement range and resolution, overcoming the high dependence of traditional motion tracking methods on the input power of the radiation signal and the reflectivity and roughness of the target surface.

Description

Technical Field

[0001] This application relates to the field of a method for visualizing and tracking minute motions, and more specifically, to a method for visualizing and tracking minute motions based on OCT. Background Technology

[0002] Motion tracking technology has wide applications in many fields, offering advantageous resolution and penetration range for specific applications. Traditional motion tracking techniques, such as laser- and microwave-based tracking, largely rely on the reflection of the irradiation signal on the surface of the object being measured, which places certain requirements on the input power of the irradiation signal, as well as the surface reflectivity and roughness. OCT (Optical Coherence Tomography) can provide high-resolution, non-invasive tomographic imaging of biological tissues and materials. Several velocimetry techniques have been proposed, including particle tracking velocimetry and particle stripe velocimetry. However, these techniques are only suitable for fluid motion containing moving particles and are difficult to apply to planar motion. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method for visualizing and tracking minute movements based on OCT.

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

[0005] A method for visualizing and tracking minute motions based on OCT, comprising:

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

[0007] S2: For the sequence of line scans obtained from the sample measurement, calculate the cross-correlation coefficient between each line scan in a certain circular scan and the different line scans in its immediate neighboring circular scans;

[0008] S3: Find the maximum value of the above cross-correlation coefficients, and calculate the point difference between the two line scans corresponding to the maximum cross-correlation coefficient at this time. The point difference is the sequence number offset.

[0009] S4: Calculate the point difference of all line scans in the circular scan, and use the point difference distribution to measure the motion speed of the sample plane; that is, obtain the motion speed of the sample plane through the point difference distribution, and the motion speed includes magnitude and direction;

[0010] S5: Combining the visual effect of speckle movement in circular scanning, the micro-motion is visualized. The sample movement speed obtained in S4 can corroborate the movement of speckle, thus realizing the visualization and tracking of the micro-motion of the sample.

[0011] This invention calculates the velocity of moving samples by point difference and visualizes the speckle movement at different positions caused by moving targets in different directions in the obtained speckle image, thus realizing sample visualization. The velocity of the moving sample can corroborate the movement of the speckle, thereby realizing the visual tracking of minute movements of the sample.

[0012] Specifically, S1 is:

[0013] Based on the line scan number N A The optical coherence tomography system performs continuous circular scans of the sample to obtain a sequence of line scans. Among them, C i N represents the i-th circular scan. A The numerical value representing the number of line scans. This represents the j-th line scan in the i-th circular scan; the optical coherence tomography system performs beam scanning along a circular trajectory at a scanning speed of v. s =2πr / N A t e Where r is the circular scan radius of the OCT sample arm beam, and t e It is the time to complete one line scan.

[0014] Specifically, in S2, in two adjacent scanning circles C i and C i+1 In the middle, the cross-correlation coefficient between different line scans The calculation method is as follows:

[0015]

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

[0017] Furthermore, S2 specifically refers to:

[0018] S21. Calculate the relative velocity of the sample. The velocity of the moving sample. This refers to the speed of the OCT circular scan motion.

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

[0020]

[0021] Among them, v s for The scalar value, v, represents the pre-defined device parameters. m for The scalar value is the measured velocity of the moving sample; in the two-dimensional XY plane, α is the velocity of the sample. The angle with the X-axis, β is the circular scanning speed. The angle with the X-axis, β = 2πt / (N) A t e ), t e Indicates the time required to complete one scan;

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

[0023]

[0024] S24. Calculate the sum of two consecutive circles C. i and C i+1 Midline scan and Distance Δd:

[0025]

[0026] Among them, t n and t m Indicates different scan times;

[0027] S25. Calculate the cross-correlation coefficient:

[0028]

[0029] Specifically, in S3, the maximum value of solving the above cross-correlation coefficient is: taking the maximum value of the cross-correlation coefficient, that is... Where N is the circular scan C i+1 Midline scan The line scan point value;

[0030] At this point, the two lines corresponding to the maximum cross-correlation coefficient are scanned. The difference between them is

[0031] By configuring the number of line scans, radius, and imaging exposure time of the OCT circular scan, planar motion tracking with a configurable wide measurable range and resolution is achieved, offering significant advantages over traditional motion tracking techniques. Furthermore, thanks to light interference, this invention can better adapt to the input power of the irradiation signal and the surface reflectivity and roughness of the target during motion tracking. In a specific implementation of this invention, the above-mentioned technical solution was tested on adhesive tape.

[0032] This invention is not limited to measuring a single speed range; it can be adjusted by changing parameters to meet the actual needs of measuring different motion speeds.

[0033] The beneficial effects of this invention are: the OCT-based micro-motion visualization tracking technology proposed in this invention can achieve planar motion tracking with configurable measurement range and resolution, and overcomes the high dependence of traditional motion tracking methods 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 capabilities based on OCT and can produce better applications for certain tasks, such as motion tracking of biological tissues. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a flowchart of the main process of the present invention;

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

[0037] Figure 3 This is a schematic diagram illustrating the principle of OCT-based tracking of minute movements in this invention.

[0038] Figure 4 This is a schematic diagram of the distance between adjacent line scans and a schematic diagram of the maximum cross-correlation coefficient according to the present invention;

[0039] Figure 5 This is a visual motion diagram of the present invention;

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

[0041] Figure 7 This is a schematic diagram illustrating the actual measurement of different movement speeds and directions of the tape according to the present invention. Detailed Implementation

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

[0043] like Figure 1As shown, a micro-motion visualization and tracking method based on OCT is presented. This method is based on an OCT (Spectraldomain OCT, SD-OCT) imaging system, which includes an 850 nm broadband light source, a spectrometer, an optical fiber coupler, a first polarization controller, a collimating mirror, glass, a first lens, a transmitting mirror, a second polarization controller, a second lens, a two-dimensional scanning galvanometer, and a third lens. The specific process of the imaging system is as follows: the light emitted from the light source is coupled into the optical fiber coupler and then enters the reference arm with a reflector and the sample arm with the sample being tested, respectively. The light reflected back from the reflector (reference light) and the backscattered light from the sample (signal light) are recombined after passing through the optical fiber coupler to generate an interference signal. At this time, the coupled light can be regarded as the superposition of the monochromatic wave components of the backscattered light from the sample and the corresponding components returning from the reference mirror. The interference signal is output from the other end of the optical fiber coupler, received by the spectrometer, expanded by the diffraction grating in the spectrometer, acquired by the CCD and converted into an electrical signal and digitized. The obtained data is then subjected to inverse Fourier transform in the computer to obtain the OCT image. The system structure diagram is shown below. Figure 2 As shown, the specific principle is based on existing technology and will not be described or explained in detail here. OCT imaging based on interferometry inevitably contains speckle patterns, and these speckles also contain information. By utilizing speckle spatial oversampling for OCT circular scanning, a line scan sequence can be obtained during OCT sampling. Positional analysis of adjacent OCT circular scan line scan sequences yields the cross-correlation coefficients of the OCT line scans. By maximizing the cross-correlation coefficients between line scans (A-lines) in different circular scan OCT images, the point difference (offset) between different line scans of adjacent circles is calculated. This offset distribution, combined with the offset distribution of all line scans in the circular scan, is used to perform planar motion tracking. Furthermore, by observing the different offset distributions resulting from different motions when performing OCT circular scans on a moving target, planar motion tracking is ultimately achieved. Finally, the speckle movement effect in continuous circular scan OCT patterns is used to visualize minute movements, thus realizing visualized tracking of minute movements.

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

[0045] S1: Perform continuous OCT circular scanning imaging on the sample; a key part of the proposed technique is the OCT scanning mode used. Circular scanning is used here. OCT circular scanning indicates 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 N is the time to complete one line scan. AThis represents the number of line scans in each OCT circular scan cycle. Here, using speckle spatial oversampling for OCT circular scanning ensures that the distance between two adjacent a-lines is less than the OCT lateral optical resolution, thus reducing the adverse effects of imaging electronic noise.

[0046] Based on the line scan number (A-line) being N A The optical coherence tomography (OCT) system performs continuous circular scans to obtain a sequence of line scans. Among them, C i N represents the i-th circular scan. A The numerical value representing the number of line scans. This represents the j-th line scan in the i-th circular scan.

[0047] S2: For the sequence of line scans obtained from sample measurements, calculate the cross-correlation coefficient between each line scan (A-line) in a given circular scan (any circular scan) and different line scans in its immediate neighboring circular scan. Assuming any circular scan is denoted as C1, calculate the cross-correlation coefficient between one line scan in C1 and different line scans in its immediate neighboring circular scan C2; this is one calculation. Then, take another line scan from C1 and calculate its cross-correlation coefficient with different line scans in its immediate neighboring circular scan C2. Repeat this process until all line scans in C1 have their cross-correlation coefficients calculated with different line scans in its immediate neighboring circular scan C2. Generally, in two adjacent scan circles C... i and C i+1 In the middle, the cross-correlation coefficient between different line scans The calculation method is as follows:

[0048]

[0049] Where ω0 is the scanning beam width, and Δd is the distance between different line scan numbers between adjacent scanning circles, where ω0 and Δd are respectively 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 cross-correlation coefficient of different line scan numbers can be obtained.

[0050] Specifically, S2 is:

[0051] S21. Calculate the relative velocity of the sample. The velocity of the moving sample. This refers to the OCT circular scan motion speed; the relative motion speed changes depending on the scanning position.

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

[0053]

[0054] Among them, v s for The scalar value, v, represents the pre-defined device parameters. m for The scalar value is the measured velocity of the moving sample; in the two-dimensional XY plane, α is the velocity of the sample. The angle with the X-axis, β is the circular scanning speed. The angle with the X-axis, β = 2πt / (N) A t e ), where t e Indicates the time required to complete one scan;

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

[0056]

[0057] S24. Calculate the sum of two consecutive circles C. i and C i+1 Midline scan and Distance Δd:

[0058]

[0059] Among them, t n and t m Indicates different scan times;

[0060] S25. Calculate the cross-correlation coefficient:

[0061]

[0062] S3: Find the maximum value of the above cross-correlation coefficients and calculate the point difference between the two line scans corresponding to the maximum cross-correlation coefficient at this time. The point difference is the sequence number offset; for example, the i-th line scan of a circular scan and the j-th line scan of the adjacent circular scan obtain the maximum value of the cross-correlation coefficient, and the point difference is ji. In S3, the maximum value of the above cross-correlation coefficients is: taking the maximum value of the cross-correlation coefficients, that is... Where N is the circular scan C i+1 Midline scan The line scan point value;

[0063] At this point, the two lines corresponding to the maximum cross-correlation coefficient are scanned. The point difference (offset) between them is

[0064] The motion velocity of a sample planar motion is measured using point difference distribution; for example... Figure 6 As shown in Figure 7, different movement speeds will result in different peak point differences, and the actual movement speed can be determined from the peak point difference. Simultaneously, when facing a moving target in different directions, the relative movement speed changes with the direction of the circular scan speed. When the circular scan direction is the same as the movement direction, that is, when the relative movement speed is at its maximum, the point difference will reach its extreme value. When the number of line scans N... A When the value is 4000, corresponding to 360° of the circumference, the point difference distribution measurement when the cross-correlation coefficient is at its maximum value for moving targets in different directions will show that the horizontal axis represents the extreme value of the point difference of the line scan number at different positions, and thus the actual direction of movement of the moving target can be known.

[0065] S4: Calculate the point difference of all line scans of the circular scan (the point difference calculation is performed once for each line scan when the cross-correlation coefficient is maximized), and obtain the motion speed of the sample plane through the point difference distribution. The motion speed includes magnitude and direction.

[0066] S5: Combining the visual effect of speckle movement in circular scanning, the micro-motion is visualized. The sample movement speed obtained in S4 can corroborate the movement of speckle, thus realizing the visualization and tracking of the micro-motion of the sample.

[0067] In continuous OCT images obtained by performing continuous circular scans using an optical coherence tomography (OCT) system, when scanning a moving target, a speckle pattern will appear to move in a specific direction at certain fixed positions, such as... Figure 5 As shown in (a), when the direction of the moving target is changed, the aforementioned change in the fixed position will occur, such as... Figure 5 As shown in (b), when a moving target has different velocities in different directions, it will result in different fixed positions and directions of movement in the speckle image, making the "fluidity" of the speckle more obvious. Finally, by identifying the fixed positions and directions of movement at different locations in the OCT continuous images obtained from the scan, the visualization of minute movements can be achieved.

[0068] This invention calculates the velocity of moving samples by point difference and visualizes the speckle movement at different positions caused by moving targets in different directions in the obtained speckle image, thus realizing sample visualization. The velocity of the moving sample can corroborate the movement of the speckle, thereby realizing the visual tracking of minute movements of the sample.

[0069] By configuring the number of line scans (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, offering significant advantages over traditional motion tracking techniques. Furthermore, thanks to light interference, this invention can better adapt to the input power of the irradiation signal and the surface reflectivity and roughness of the target during motion tracking. In a practical implementation, the technical solution of this invention was tested on adhesive tape.

[0070] OCT imaging based on interferometry inevitably contains speckle patterns, and these speckles also contain information. By utilizing speckle spatial oversampling for OCT circular scanning, a line scan sequence can be obtained during OCT sampling. Positional analysis of adjacent OCT circular scan line scan sequences yields the cross-correlation coefficients of the OCT line scans. By maximizing the cross-correlation coefficients between line scans (A-lines) in different circular scan OCT images, the point difference (offset) between different line scans of adjacent circles is calculated. This offset distribution, combined with the offset distribution of all line scans in the circular scan, is used to perform planar motion tracking. Furthermore, by observing the different offset distributions resulting from different motions when performing OCT circular scans on a moving target, planar motion tracking is ultimately achieved. Finally, the speckle movement effect in continuous circular scan OCT patterns is used to visualize minute movements, thus realizing visualized tracking of minute movements.

[0071] In this specific implementation, the OCT system is a conventional spectral domain OCT system with axial and lateral optical resolutions of approximately 2.5 μm and 8.5 μm, respectively. The lateral planar motion tracking performance of OCT imaging-based motion tracking technology is demonstrated by using an imaging transparent tape as a motion sample. The transparent tape is adhered to a two-dimensional planar motion stage, the OCT imaging exposure time is 25 microseconds, and the corresponding system sensitivity is 101 dB. In this specific implementation, the OCT circular scan radius r is 1 mm, and the number of scan lines N per circle is... A The value was 4000. Using the above parameters, an OCT circular scan was performed on the transparent tape sample moving at different speeds in different directions.

[0072] Figure 3This diagram illustrates the principle of OCT-based tracking of minute movements, showing the positional relationship of different line scans within two adjacent circular scans. As the transparent tape moves along the positive X-axis, the diagram is divided into four regions: A, B, C, and D. For line scans with the same number of line scans within two adjacent circles, the relative motion velocity is accumulated as a vector over one circle's scan time. In region A, the relative position shifts to the right, corresponding to a parallel rightward shift in the speckle image. In region B, the lower half shows an upward shift, while the upper half shows a downward shift, resulting in a center in the speckle image with both sides moving towards the center. In region C, the relative position is the opposite of region A, resulting in a parallel leftward shift in the speckle image. Similarly, in region D, the relative position is the opposite of region B, resulting in a center in the speckle image with both sides spreading outwards from the center. Regions B and D are also explained... Figure 5 The reasons for the movement and orientation of speckle images.

[0073] Figure 4 (a) shows the distance measurement method for different line scans of adjacent circular scans. Figure 4 (b) shows the midline scan of adjacent circular scans. and A diagram illustrating the maximum cross-correlation coefficient value.

[0074] Figure 5 (a) shows the "flow" movement and direction of the speckle image at a specific location in a continuous OCT circular scan pattern, where the tape moves at a speed of 10 mm / s along the negative X-axis; that is, the tape spreads outward from the left center and moves towards the center on the right center. When the direction of movement changes, the two centers move synchronously. Figure 5 (b) shows the tape moving at a speed of 10 mm / s along the negative Y-axis. Comparing figures a and b, it can be seen that the two centers move synchronously, and the distance they move is half the distance between the two centers. Therefore, it can be inferred that as the tape moves angularly from the negative X-axis to the negative Y-axis, the two centers also move synchronously. When the tape moves along the positive X-axis, it will exhibit the following pattern: Figure 5 (a) Two centers at the same location, but the movements at the two centers are opposite (i.e., the left center moves towards the center, and the right center spreads outward). Based on this, the direction of the minute motion can be clearly known from the location and movement of the left and right centers in the speckle image, thus realizing the visualization of minute motion.

[0075] Figure 6 The numerical simulation results are shown. First, a numerical simulation of the proposed micro-motion tracking was performed. To simplify the calculation, we assume α = 0 and conduct the numerical simulation. Simultaneously, the scan time t...e For 200 microseconds, N A The value is 4000, the scanning circle radius is 1.6 mm, and ω0 is 8 μm. We first simulated the sample moving at different speeds, including -20 mm / s, -10 mm / s, 0 mm / s, 10 mm / s, and 20 mm / s. Using the above micro-motion tracking method, we can obtain the offset distribution for each speed, and the corresponding fitting function can be obtained through the least squares method of order N=6, such as... Figure 6 As shown.

[0076] Figure 7 The results of measuring the tape under different movements and directions are shown in the graph. Speeds of 0 mm / s, 2 mm / s, 5 mm / s, 10 mm / s, 15 mm / s, and 20 mm / s were measured along the positive and negative X-axis, respectively, and the corresponding measurement algorithms were executed to obtain the tracking measurement results, as shown below. Figure 7 As shown. From Figure 7 As can be seen, different motion speeds result in different offsets, indicating that the proposed motion tracking technique can achieve motion measurement at various speeds. However, the presence of electrical noise causes fluctuations in the offset. To improve data reliability, the average of 50 sets of data was used to obtain... Figure 7 This also leads to some deviation in the maximum offset.

[0077] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for visualizing and tracking minute movements based on OCT, characterized in that, include: S1: Perform continuous OCT circular scanning imaging on the sample. OCT stands for Optical Coherence Tomography. S2: For the sequence of line scans obtained from the sample measurement, calculate the cross-correlation coefficient between each line scan in a certain circular scan and the different line scans in its immediate neighboring circular scans; S3: Find the maximum value of the above cross-correlation coefficients, and calculate the point difference between the two line scans corresponding to the maximum cross-correlation coefficient at this time. The point difference is the sequence number offset. S4: Calculate the point difference of all line scans in the circular scan, and obtain the motion speed of the sample plane through the point difference distribution. The motion speed includes magnitude and direction. S5: Combining the visual effect of speckle movement in circular scanning, the micro-motion is visualized. The sample movement speed obtained in S4 can corroborate the movement of speckle, thereby realizing the visual tracking of the micro-motion of the sample. Specifically, S2 is: S21. Calculate the relative velocity of the sample. The velocity of the moving sample. This refers to the speed of the OCT circular scan motion. S22. Calculate the relative velocity of the sample along the X-axis and Y-axis, v. x and v y : Among them, v s for Scalar values, representing pre-defined device parameters; v m for The scalar value is the measured velocity of the moving sample; in the two-dimensional XY plane, α is the velocity of the sample. The angle with the X-axis, β is the circular scanning speed. The angle with the X-axis, β = 2πt / (N) A t e ), t e Indicates the time required to complete one scan; S23. Calculate the position P(x, y) of the linear scan at time t: S24. Calculate the sum of two consecutive circles C. i and C i+1 Midline scan and Distance Δd: Among them, t n and t m Indicates different scan times; S25. Calculate the cross-correlation coefficient:

2. The OCT-based method for visualizing and tracking minute movements according to claim 1, characterized in that, Specifically, S1 is: Based on the line scan number N A The optical coherence tomography system performs continuous circular scans of the sample to obtain a sequence of line scans. Among them, C i N represents the i-th circular scan. A The numerical value representing the number of line scans. This represents the j-th line scan in the i-th circular scan; the OCT circular scan performs beam scanning along the circular trajectory, and the circular scan speed is v. s =2πr / N A t e Where r is the circular scan radius of the OCT sample arm beam, and t e It is the time to complete one line scan.

3. The OCT-based method for visualizing and tracking minute movements according to claim 2, characterized in that, In S2, in two adjacent scanning circles C i and C i+1 In the middle, the cross-correlation coefficient between different line scans The calculation method is as follows: Where ω0 is the scanning beam width, and Δd is the distance between different line scan numbers between adjacent scanning circles, where Δd is the scanning line width. and scan lines The distance.

4. The OCT-based method for visualizing and tracking minute movements according to claim 1, characterized in that, In step S3, the maximum value of solving the aforementioned cross-correlation coefficient is: taking the maximum value of the cross-correlation coefficient, i.e. Where N is the circular scan C i+1 Midline scan The line scan point value; At this point, the two lines corresponding to the maximum cross-correlation coefficient are scanned. The difference between them is

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