Frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method

Abstract

The invention relates to a frequency domain OCT (Optical Coherence Tomography) multiple scattering component statistical gating and tissue optical parameter extraction method, which comprises the following steps of: carrying out continuous multiple sampling on a single sampling position in an imaging area by using frequency domain OCT, constructing a matrix by using k-space data obtained by sampling, and solving a covariance matrix of the matrix as random matrix description; modeling the description as low-rank disturbance of a Wishart random matrix; based on the statistical characteristics of Wishart random matrix low-rank disturbance, statistical gating is carried out on the ballistic component and the multiple scattering component, and a ballistic signal matrix and a multiple scattering component matrix are reconstructed respectively; and according to ballistic component information in the ballistic signal matrix and multi-scattering component information in the multi-scattering component matrix, through inverse Fourier transform and in combination with an expanded Huygens-Fresnel formula, calculating a tissue absorption coefficient and a tissue anisotropy parameter. Compared with the prior art, extraction of multiple scattering components in the frequency domain OCT can be achieved, and the tissue absorption coefficient and the tissue anisotropy parameter can be obtained.

Description

Technical Field

[0001] The invention relates to the technical field of optical coherence tomography, and in particular to a method for frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction. Background Art

[0002] Optical coherence tomography (OCT) is a new high-resolution tomographic imaging mode. Its working principle is mainly based on interference spectroscopy and fast Fourier transform. It obtains longitudinal depth information by measuring the spectrum of the interference signal and performing fast Fourier transform on it. After frequency domain OCT collects the light beams representing the different depth information of the sample, it can solve the intensity information of the sample depth through Fourier (inverse) transform, thereby realizing the parallel acquisition of sample axial information.

[0003] In order to ensure the imaging quality of tissue structures, it is necessary to extract and reconstruct the scattering signals in the frequency domain OCT. In the prior art, for example, Chinese patent ZL202110867339.1 proposes a visible light OCT ballistic scattering signal extraction method, which establishes a random matrix description in k-space and uses the maximum eigenvalue of the Wishart random matrix to reconstruct the ballistic scattering component. Although this scheme can extract the ballistic scattering component, due to the interaction effect between the ballistic scattering component and the multiple scattering component, the above scheme cannot accurately extract the single scattering classification, nor can it extract the multiple scattering components. In addition, the above scheme is also unable to obtain tissue functional information (such as tissue absorption coefficient and tissue anisotropy parameters). Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method for statistical gating of multiple scattered components of frequency domain OCT and extraction of tissue optical parameters, which can realize the extraction of multiple scattered components in frequency domain OCT and further calculate the tissue absorption coefficient and tissue anisotropy parameters using the multiple scattered components.

[0005] The object of the present invention can be achieved by the following technical solution: A method for statistical gating of multiple scattered components of frequency domain OCT and extraction of tissue optical parameters, comprising the following steps:

[0006] S1. Use frequency domain OCT to continuously sample multiple times at a single sampling position in the imaging area, use the k-space data obtained by sampling to construct a matrix and calculate its covariance matrix as a random matrix description, and model the description as a low-rank perturbation of the Wishart random matrix;

[0007] S2. Based on the statistical characteristics of the low-rank perturbation of the Wishart random matrix, perform statistical gating on the ballistic component and the multiple scattering component, and reconstruct the ballistic signal matrix and the multiple scattering component matrix respectively;

[0008] S3. According to the ballistic component information in the ballistic signal matrix and the multiple scattering component information in the multiple scattering component matrix, through inverse Fourier transform and combined with the extended Huygens-Fresnel formula, calculate the tissue absorption coefficient and the tissue anisotropy parameter.

[0009] Further, the specific process of step S1 includes: For a single sampling position in the x-y plane of the imaging area, that is, a single A-line, perform L samplings. Each sampling obtains the k-space data of a single A-line, with a total of M data points. Then construct a matrix K of M rows and L columns, K = K B +K M , each column of the matrix K is the k-space data of a single A-line obtained by one measurement, K B is the ballistic component, which is a low-rank matrix of M rows and L columns, and K M is the multiple scattering component, which is a full-rank matrix of M rows and L columns;

[0010] The optimal parameter c is achieved by controlling the number of samplings. Among them, c = L / M, 0 < c < ∞, that is, the aspect ratio of the matrix. Construct a matrix from the k-space data and find its covariance matrix to describe and model the low-rank perturbation of the Wishart random matrix as The symbol represents the conjugate transpose of the matrix.

[0011] Further, the low-rank perturbation C of the Wishart random matrix is a matrix of L rows and L columns, C = C L +C M , where C L is a low-rank matrix of L rows and L columns,

[0012] C M is a full-rank Wishart random matrix of L rows and L columns,

[0013] Further, the process of reconstructing the ballistic signal matrix in step S2 includes:

[0014] Based on the low-rank perturbation of the Wishart random matrix, use the L eigenvalues {s1, s2,..., S L} of the matrix C to solve the quadratic equation to obtain {θ1, θ2,..., θ L}, and select those greater than from {θ1, θ2,..., θ L} The eigenvalues ​​of {θ1, θ2, ..., θ q}, as an estimate of the eigenvalue of the ballistic component;

[0015] For the eigenvalues ​​{θ1, θ2, ..., θ q} Take the square root to get the singular value And construct the matrix S as the main diagonal elements B , perform singular value decomposition on the K matrix Reconstructing the ballistic component matrix

[0016] Furthermore, the quadratic equation is: θ 2 +(σ 2 -σ 2 c-λ)θ+σ 2 cs=0, when solving, take the positive root among the two roots.

[0017] Furthermore, the process of reconstructing the multiple scattering component matrix in step S2 includes:

[0018] Based on the Tracy-Widom theorem, the multiple scattering component K is solved using the minimum eigenvalue. M The variance statistical parameter σ of the matrix elements 2 ;

[0019] Since the multiple scattering component K M Corresponding to the Wishart random matrix C with Gaussian statistics M , C M The statistical distribution of the eigenvalues ​​of the matrix satisfies the unnormalized Marchenko-Pastur distribution, so the complete estimate of the eigenvalues ​​of the multiple scattering components is obtained by sampling according to the Marchenko-Pastur statistical distribution {λ M1 ,λ M2 , ..., λ ML};

[0020] The complete estimate [λ M1 ,λ M2 , ..., λ ML} Take the square root to get the singular value And construct the matrix S as the main diagonal elements M , reconstruct the multiple scattering component matrix Take the first column of the matrix as the multiple scattering component in the A-line at that position.

[0021] Furthermore, the variance statistical parameter σ 2 Specifically:

[0022]

[0023] Among them, s L is the minimum non-zero eigenvalue of the C matrix obtained from the measured data, <y>The value range of is (-1000~+1000), which is obtained based on the numerical calculation of Tracy-Widom theorem.

[0024] Furthermore, the Marchenko-Pastur statistical distribution is specifically:

[0025]

[0026] Among them, C M The matrix has L eigenvalues, namely {λ1,λ2,...,λ L }, p(λ) is the probability density function of the eigenvalue, and are the maximum and minimum values ​​of the possible range of non-zero eigenvalues.

[0027] Furthermore, step S3 includes the following steps:

[0028] S31, perform inverse Fourier transform on the multiple scattered components to obtain the time domain multiple scattered components A M (z), take the square of its modulus to obtain the multiple scattering intensity information I M (z)=|A M (z)| 2 , where z is the axial depth coordinate;

[0029] S32. Calculate the tissue absorption coefficient parameter map based on the multiple scattering intensity information combined with the characteristics of the multiple scattering invariant of light in the tissue:

[0030]

[0031]

[0032] Among them, I M0 (z) is the proportionality coefficient, and its value range is a real number not less than zero. <s>is the physical size of the coherence volume, <s>Depends on the spatial resolution of the OCT system, l z is the axial resolution, l x and l y is the lateral resolution;

[0033] S33, perform inverse Fourier transform on the ballistic component to obtain the time domain ballistic component A B (z) and its corresponding intensity information, B (z)=|A B (z)| 2 , and then calculate the scattering intensity information:

[0034]

[0035] Among them, I B0 (z) is the proportionality coefficient, and its value range is a real number not less than zero;

[0036] S34. Perform inverse Fourier transform directly on the original single A-line k-space data to obtain A(z), and take the square of the modulus of A(z) to obtain the original scattering intensity information I(z)=|A(z)| 2 , using the tissue absorption coefficient μa(z), remove the influence of the absorption effect in the original scattering intensity information and obtain a scattering signal without absorption effect

[0037] S35, scattering signal I without absorption effect d (z), and the extended Huygens-Fresnel formula is used to fit it to obtain Then the tissue anisotropy parameter g(z) is calculated.

[0038] Furthermore, the expanded Huygens-Fresnel formula in step S35 is specifically:

[0039]

[0040]

[0041] The tissue anisotropy parameters are specifically:

[0042]

[0043] Where I0 is the incident light intensity, ω0 is the incident beam waist, and z R is the Rayleigh length of the Gaussian beam, z f is the focal depth of the beam, and n is the imaging medium.

[0044] Compared with the prior art, the present invention has the following advantages:

[0045] The present invention uses the k-space data of frequency domain OCT to establish a random matrix statistical description for a single sampling position in the imaging area, constructs a matrix of the k-space data, and calculates its covariance matrix, so as to model the random matrix description as a low-rank perturbation of the Wishart random matrix; then, based on the low-rank perturbation of the Wishart random matrix, the ballistic signal matrix and the multiple scattering component matrix are reconstructed respectively; then, according to the ballistic component information in the ballistic signal matrix and the multiple scattering component information in the multiple scattering component matrix, the tissue absorption coefficient and the tissue anisotropy parameter are calculated by inverse Fourier transform and combined with the extended Huygens-Fresnel formula. Thus, the extraction of multiple scattering components in frequency domain OCT is realized based on the k-space statistical gating method, and the tissue absorption coefficient and the tissue anisotropy parameter are further calculated using the multiple scattering components. Compared with the prior art, the present invention can accurately extract the multiple scattering components, can implement statistical gating for the multiple scattering components separately, and can calculate the absorption coefficient for each voxel and the tissue anisotropy parameter for each voxel.

[0046] The present invention constructs a matrix of k-space data and calculates its covariance matrix, which is used as a random matrix description to model the low-rank perturbation of the Wishart random matrix, and then designs a scheme for reconstructing the ballistic component matrix and the multiple scattering component matrix, which can accurately extract single scattering classification and achieve the purpose of extracting multiple scattering components.

[0047] The present invention is based on the ballistic component information in the ballistic signal matrix, the multiple scattering component information in the multiple scattering component matrix and the original k-space data, and obtains the multiple scattering intensity information, the tissue absorption coefficient parameter map, the ballistic component scattering intensity information, the original scattering intensity information, and the scattering signal without absorption effect through inverse Fourier transform, and then fits with the extended Huygens-Fresnel formula to solve the tissue anisotropy parameters, thereby ensuring the accurate extraction of tissue optical parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0049] Figure 2a to 2c It is a schematic diagram of the actual application process of the present invention. DETAILED DESCRIPTION

[0050] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] like Figure 1 As shown, a method for statistical gating of multiple scattered components of frequency domain OCT and extracting tissue optical parameters comprises the following steps:

[0052] S1. Continuously sample a single sampling position within the imaging region multiple times using frequency-domain OCT. Construct a matrix from the sampled k-space data and calculate its covariance matrix as a random matrix description, and model this description as a low-rank perturbation of a Wishart random matrix;

[0053] S2. Based on the statistical characteristics of the low-rank perturbation of the Wishart random matrix, perform statistical gating on the ballistic component and the multiple-scattering component, and reconstruct the ballistic signal matrix and the multiple-scattering component matrix respectively;

[0054] S3. According to the ballistic component information in the ballistic signal matrix and the multiple-scattering component information in the multiple-scattering component matrix, through inverse Fourier transform and combined with the extended Huygens-Fresnel formula, calculate the tissue absorption coefficient and the tissue anisotropy parameter.

[0055] Applying the above scheme to practice, as Figure 2a to 2c shown, the specific content includes:

[0056] Step 1. For a single sampling position (a single A-line) within the imaging region (x-y plane), establish a random matrix statistical description using the k-space data of frequency-domain OCT.

[0057] Sample the same sampling position L times. Each time of sampling obtains the k-space data of a single A-line e with a total of M data points, and then construct a matrix K of M rows and L columns. Control the number of samplings to achieve the optimal parameter c = L / M (0 < c < ∞), that is, the aspect ratio of the matrix. Construct a matrix from the k-space data and calculate its covariance matrix to model it as a low-rank perturbation of a Wishart random matrix, that is The symbol represents the conjugate transpose of the matrix.

[0058] where K = K B + K M , and each column is the k-space data of a single A-line obtained by one measurement. K B is the ballistic component, which is a low-rank matrix of M rows and L columns; K M is the multiple-scattering component, which is a full-rank matrix of M rows and L columns.

[0059] C is a matrix of L rows and L columns, is a low-rank matrix of L rows and L columns, is a full-rank Wishart random matrix of L rows and L columns.

[0060] It should be noted that in practical applications, the construction of the C matrix is According to the characteristics of matrix operations, the construction of the C matrix can also be carried out in the following way, Then the subsequent steps can be adjusted accordingly.

[0061] In addition, when scanning, different schemes can be used to construct the k-space spatiotemporal matrix corresponding to a single A-line: (1) multiple scans of the same A-line (this method has a long sampling time, high spatial resolution, and is suitable for high-resolution imaging);

[0062] (2) Adjacent A-lines in the same B-Scan (sampling time does not increase, but some spatial resolution is lost);

[0063] (3) A-lines that are spatially adjacent in adjacent B-Scans;

[0064] (4) A combination of the above sampling methods (1) to (3), such as sampling the same A-line multiple times and utilizing adjacent A-lines.

[0065] Step 2: Let the L eigenvalues ​​of the C matrix be {s1, s2, ..., s L } (arrange from large to small), and substitute each eigenvalue into the following formula to solve {θ1, θ2, ..., θ L }.

[0066] θ 2 +(σ 2 -σ 2 c-λ)θ+σ 2 cs=0

[0067] It should be noted that this is a quadratic equation, and the positive root is taken among the two roots.

[0068] Step 3: From {θ1, θ2, ..., θ L } to filter out all the The values ​​of {θ1, θ2, ..., θ q }, as an estimate of the eigenvalue of the ballistic component.

[0069] Step 4: For the eigenvalues ​​{θ1, θ2, ..., θ q } Take the square root and get the singular value And construct the matrix S as the main diagonal elements B . Perform singular value decomposition on the K matrix Reconstructing the ballistic component matrix

[0070] Step 5: Based on the Tracy-Widom theorem, use the minimum eigenvalue to solve the multiple scattering component K M The variance statistical parameter σ of the matrix elements 2 .

[0071]

[0072] Among them, s L is the minimum non-zero eigenvalue of the C matrix obtained from the measured data, <y>The value range is (-1000~+1000), which is based on the numerical calculation of Tracy-Widom theorem.

[0073] Step 6: Multiple scattering component K M Corresponding to the Wishart random matrix C with Gaussian statistics M , C M The statistical distribution of the eigenvalues ​​of the matrix satisfies the unnormalized Marchenko-Pastur distribution.

[0074]

[0075] Among them, C M The matrix has L eigenvalues, namely {λ1,λ2,...,λ L }. p(λ) is the probability density function of the eigenvalue. and are the maximum and minimum values ​​of the range of possible values ​​for a non-zero eigenvalue.

[0076] Step 7: Perform statistical sampling on the statistical distribution established in step 6 to obtain a complete estimate of the characteristic values ​​of a set of multiple scattered components {λ M1 ,λ M2 , ..., λ ML }.

[0077] It should be noted that in step 7, if a statistical sampling is performed on the statistical distribution once, only one set of eigenvalues ​​of the multiple scattered components is obtained, which may result in sampling errors. In practice, the statistical distribution can be sampled independently multiple times to generate multiple sets of eigenvalue estimates and average the multiple sets, thereby significantly reducing the sampling errors.

[0078] Step 8: Take the square root of the eigenvalues ​​obtained in step 7 to obtain the singular values And construct the matrix S as the main diagonal elements M . Reconstruct the multiple scattering component matrix Take the first column of the matrix as the multiple scattering component in the A-line at that position.

[0079] Step 9: Perform inverse Fourier transform on the multiple scattered components to obtain the time domain multiple scattered components A M (z), take the square of its modulus to obtain the multiple scattering intensity information I M (z)=|A M (z)| 2 , where z is the axial depth coordinate.

[0080] Step 10: Combine the multiple scattering intensity information with the characteristics of the multiple scattering invariant of light in the tissue to calculate the tissue absorption coefficient parameter map:

[0081]

[0082] Among them, I M0 (z) is the proportionality coefficient, and its value range is a real number not less than zero. In practical applications, its value can be obtained through standard product testing or Monte Carlo simulation. (s> is the physical size of the coherent volume, Depends on the spatial resolution of the OCT system (l z is the axial resolution, l x and l y is the lateral resolution).

[0083] Step 11: Perform inverse Fourier transform on the ballistic component to obtain the time domain ballistic component A B (z), and its corresponding intensity information I B (z)=|A B (z)| 2 , and then calculate the scattering intensity information:

[0084]

[0085] Among them, I B0 (z) is the proportionality coefficient, and its value range is a real number not less than 0. In practical applications, its value can be obtained through standard product testing or Monte Carlo simulation.

[0086] Step 12: Perform inverse Fourier transform on the original single A-line k-space data to obtain A(z), and take the square of the modulus of A(z) to obtain the original scattering intensity information I(z) = |A(z)| 2 . Using tissue absorption coefficient μ a (z), remove the influence of absorption effect in the original scattering intensity information and obtain the scattering signal without absorption effect

[0087] Step 13: Scattering signal I without absorption effect d (z), and the extended Huygens-Fresnel formula is used to fit it, and we obtain

[0088]

[0089] Where I0 is the incident light intensity, ω0 is the incident beam waist, z R is the Rayleigh length of the Gaussian beam, z f is the focal depth of the beam, and n is the imaging medium.

[0090] Step 14: Solve the tissue anisotropy parameter g(z):

[0091]

[0092] Step 15, repeating the process of steps 1 to 14 for the sampling positions along the x direction or the y direction in the imaging area, so as to realize a B-scan imaging;

[0093] Repeating steps 1 to 14 for all sampling positions in the imaging area can achieve three-dimensional imaging.

[0094] Embodiment 1

[0095] This embodiment applies the above technical solution to spectral domain OCT, which uses a broadband light source in the near-infrared band. In a B-scan (512 positions along the x direction), L = 16 measurements are performed on each position. After completing the B-scan, a matrix K is established as a column vector for each set of A-line data (16 measurements). Steps 1 to 14 are applied to calculate the multiple scattered components |A along the A-line. M (z)|, tissue absorption coefficient μ a After all 512 positions are processed, the multiple scattering component map, tissue absorption coefficient map, and tissue anisotropy parameter map corresponding to the B-san can be formed.

[0096] Embodiment 2

[0097] This embodiment is directed to visible light OCT and applies the above technical solution. Visible light OCT uses a wide-spectrum light source or a supercontinuum light source in the visible light band. Complete a B-scan (512 positions along the x direction). For each A-line, use its own and the 16 adjacent A-line data (a total of 17 A-line data) as column vectors to establish a matrix K. Apply steps 1 to 8 to calculate and obtain the k-space data of the multiple scattered components along the A-line. In step 9, use the short-time Fourier inverse transform with a Gaussian window to obtain the A corresponding to the 12 center wavelengths. M (z). For each wavelength A M (z) Step 10 is performed for each position, and the processing result is fitted with the absorption spectra of oxygenated and deoxygenated hemoglobin to determine the ratio of the two hemoglobins and calculate the blood oxygen saturation. When all 512 positions are processed, the blood oxygen saturation map corresponding to the B-san can be formed.

[0098] In summary, compared with the existing technology, the existing technology has errors in extracting ballistic components and cannot accurately extract multiple scattered components. This scheme can achieve statistical gating of multiple scattered components separately;

[0099] In the ballistic component obtained by the prior art, the scattering coefficient and the absorption coefficient are coupled together, and the absorption coefficient cannot be calculated for each voxel, while the present solution can calculate the absorption coefficient for each voxel;

[0100] The prior art cannot calculate tissue anisotropy parameters for each voxel, but the present solution can calculate tissue anisotropy parameters for each voxel.< / y> < / s> < / s> < / y>

Claims

1. A method for statistical gating of multiple scattered components of frequency domain OCT and extraction of tissue optical parameters, characterized in that: The following steps are involved: S1. Use frequency domain OCT to continuously sample multiple times at a single sampling position in the imaging area, use the k-space data obtained by sampling to construct a matrix and calculate its covariance matrix as a random matrix description, and model the description as a low-rank perturbation of the Wishart random matrix; S2. Based on the statistical characteristics of low-rank perturbations of Wishart random matrices, statistical gating is performed on the ballistic component and the multiple scattering component to reconstruct the ballistic signal matrix and the multiple scattering component matrix respectively. S3. According to the ballistic component information in the ballistic signal matrix and the multiple scattering component information in the multiple scattering component matrix, the tissue absorption coefficient and tissue anisotropy parameter are calculated by inverse Fourier transform and combined with the extended Huygens-Fresnel formula.

2. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 1, characterized in that: The specific process of step S1 includes: performing L samplings for a single sampling position in the xy plane of the imaging area, that is, a single A-line, and obtaining k-space data of a single A-line each time, with a total of M data points, and then constructing a matrix K with M rows and L columns, K=K B +K M , each column of the matrix K is the k-space data of a single A-line obtained from a measurement, K B is the ballistic component, which is a low-rank matrix with M rows and L columns, K M is the multiple scattering component, which is a full rank matrix with M rows and L columns; The optimal parameter c is achieved by controlling the number of samplings, where c = L / M, 0 < c < ∞, i.e., the aspect ratio of the matrix. The k-space data is constructed into a matrix, and its covariance matrix is calculated to be used as a random matrix to describe the low-rank perturbation modeled as a Wishart random matrix, that is, to obtain The symbol represents the conjugate transpose of the matrix.

3. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 2, characterized in that: The low-rank perturbation C of the Wishart random matrix is ​​a matrix with L rows and L columns, C=C L +C M , where C L is a low-rank matrix with L rows and L columns, C M is a full-rank Wishart random matrix with L rows and L columns, 4. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 3, characterized in that: The process of reconstructing the trajectory signal matrix in step S2 includes: Based on the low-rank perturbation of the Wishart random matrix, the L eigenvalues ​​of the matrix C {s1,s2,…,s L Solving the quadratic equation yields {θ1,θ2,…,θ L }, from {θ1,θ2,…,θ L }Filter out those greater than The eigenvalues ​​of {θ1,θ2,…,θ q }, as an estimate of the eigenvalue of the ballistic component; For the eigenvalues ​​{θ1,θ2,…,θ q } Take the square root to get the singular value And construct the matrix S as the main diagonal elements b , perform singular value decomposition on the K matrix Reconstructing the ballistic component matrix 5. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 4, characterized in that: The quadratic equation is: 2 +(σ 2 -σ 2 c-λ)θ+σ 2 cs=0, when solving, take the positive root among the two roots.

6. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 4, characterized in that: The process of reconstructing the multiple scattering component matrix in step S2 includes: Based on the Tracy-Widom theorem, the multiple scattering component K is solved using the minimum eigenvalue. M The variance statistical parameter σ of the matrix elements 2 ; Since the multiple scattering component K M Corresponding to the Wishart random matrix C with Gaussian statistics M , C M The statistical distribution of the eigenvalues ​​of the matrix satisfies the unnormalized Marchenko–Pastur distribution, so the complete estimate of the eigenvalues ​​of the multiple scattering components is obtained by sampling according to the Marchenko–Pastur statistical distribution {λ M1 ,λ M2 ,…,λ ML }; The obtained complete estimate {λ M1 ,λ M2 ,…,λ ML } Take the square root to get the singular value And construct the matrix S as the main diagonal elements M , reconstruct the multiple scattering component matrix Take the first column of the matrix as the multiple scattering component in the A-line at that position.

7. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 6, characterized in that: The variance statistical parameter σ 2 Specifically: Among them, s L is the minimum non-zero eigenvalue of the C matrix obtained from the measured data, <y> The value range of is (-1000~+1000), which is obtained based on the numerical calculation of Tracy-Widom theorem.< / y> 8. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 7, characterized in that: The Marchenko–Pastur statistical distribution is specifically: Among them, C M The matrix has L eigenvalues, namely {λ1,λ2,…,λ L }, p(λ) is the probability density function of the eigenvalue, and are the maximum and minimum values ​​of the possible range of non-zero eigenvalues.

9. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 8, characterized in that: The step S3 comprises the following steps: S31, perform inverse Fourier transform on the multiple scattered components to obtain the time domain multiple scattered components A M (z), take the square of its modulus to obtain the multiple scattering intensity information I M (z)=|A M (z)| 2 , where z is the axial depth coordinate; S32. Calculate the tissue absorption coefficient parameter map based on the multiple scattering intensity information combined with the characteristics of the multiple scattering invariant of light in the tissue: Among them, I M0 (z) is the proportionality coefficient, and its value range is a real number not less than zero. <s>is the physical size of the coherence volume, <s>Depends on the spatial resolution of the OCT system, l z is the axial resolution, l x and l y is the lateral resolution;< / s> < / s> <s> <s> S33, perform inverse Fourier transform on the ballistic component to obtain the time domain ballistic component A B (z) and its corresponding intensity information I B (z)=|A B (z)| 2 , and then calculate the scattering intensity information: Among them, I B0 (z) is the proportionality coefficient, and its value range is a real number not less than zero; S34. Perform inverse Fourier transform directly on the original single A-line k-space data to obtain A(z), and take the square of the modulus of A(z) to obtain the original scattering intensity information I(z)=|A(z)| 2 , using the tissue absorption coefficient μ a (z), remove the influence of absorption effect in the original scattering intensity information and obtain the scattering signal without absorption effect S35, scattering signal I without absorption effect d (z), and the extended Huygens-Fresnel formula is used to fit it to obtain Then the tissue anisotropy parameter g(z) is calculated.

10. A frequency domain OCT multiple scattering component statistical gating and tissue optical parameter extraction method according to claim 9, characterized in that: The expanded Huygens-Fresnel formula in step S35 is specifically: The tissue anisotropy parameters are specifically: Where I0 is the incident light intensity, ω0 is the incident beam waist, and z R is the Rayleigh length of the Gaussian beam, z f is the focal depth of the beam, and n is the imaging medium. < / s> < / s>

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