Cardiac tissue intraoperative imaging method based on laser radar statistical gating

Abstract

The invention relates to a heart tissue intraoperative imaging method based on laser radar statistical gating, which comprises the following steps that: a laser radar is used for continuously scanning a set position of a heart area in a single-point manner, and the intensity of reflected light periodically changes along with heartbeat; judging whether an imaging triggering condition is met or not according to the reflected light intensity, and if yes, scanning the imaging area by using a laser radar to obtain scanning data; and constructing a two-dimensional matrix according to the scanning data, extracting a single scattering component and a multiple scattering component from the two-dimensional matrix by adopting a statistical gating mode, and calculating to obtain tissue optical parameters. Compared with the prior art, the laser radar is used for scanning imaging, the signal acquisition requirement of living body heart imaging can be met, a statistical gating mechanism is provided, statistical gating of multiple scattering components in laser radar signals can be achieved, tissue optical parameters are obtained through calculation, and the imaging accuracy is improved. The physiological state and the injury degree of the living myocardial tissue can be timely and accurately known.

Description

Technical Field

[0001] The present invention relates to the field of optical imaging technology, and in particular to a method for intraoperative imaging of cardiac tissue based on laser radar statistical gating. Background Art

[0002] With the continuous advancement of science and technology, intraoperative imaging technology has been widely used in modern surgical operations. Intraoperative imaging technology mainly uses a high-definition micro camera to transmit real-time images to the display, allowing doctors to clearly observe the surgical site.

[0003] In cardiac surgery, due to the complexity of the operation, the requirements for intraoperative imaging are more stringent. Cardiac surgery requires real-time imaging monitoring of myocardial tissue damage in a beating heart. The beating of the heart is caused by the contraction and expansion of the myocardium. It is extremely challenging to accurately and in real time measure the physiological state and degree of damage of living myocardial tissue.

[0004] Due to the rapid beating of the heart, ordinary camera imaging is seriously affected by motion artifacts. If a high-speed camera is used, a very strong lighting intensity is required, which will inevitably affect the physiological state of living tissues. In addition, existing imaging technology can only obtain image data, but cannot obtain relevant tissue parameters. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method for intraoperative imaging of cardiac tissue based on lidar statistical gating. LiDAR is used for scanning imaging to meet the signal acquisition requirements of living heart imaging, and a statistical gating mechanism is proposed to calculate and obtain tissue optical parameters.

[0006] The purpose of the present invention can be achieved by the following technical solution: A method for intraoperative imaging of cardiac tissue based on laser radar statistical gating, comprising the following steps:

[0007] S1. Use a laser radar to continuously scan a set position in the heart area at a single point, wherein the reflected light intensity changes periodically with the heartbeat;

[0008] S2, judging whether the imaging trigger condition is met according to the reflected light intensity, if so, executing step S3, otherwise returning to step S1;

[0009] S3, using a laser radar to scan the imaging area and obtain scanning data;

[0010] S4. Based on the scanning data, a two-dimensional matrix is ​​constructed, and single scattering components and multiple scattering components are extracted from it using a statistical gating method to calculate the tissue optical parameters.

[0011] Furthermore, the single-point sampling time of the laser radar is less than 1us and the single pulse power is higher than 50mW.

[0012] Furthermore, in step S2, if the reflected light intensity reaches a preset light intensity threshold, it is determined that the imaging trigger condition is met.

[0013] Furthermore, the step S3 specifically uses a laser radar to scan the entire imaging area or a set part of the imaging area.

[0014] Furthermore, the step S4 comprises the following steps:

[0015] S41, arranging the scanned data in a scanning order to obtain a two-dimensional matrix;

[0016] S42, performing window sliding processing on the two-dimensional matrix, and extracting a data sub-matrix corresponding to each sliding;

[0017] S43. According to the plurality of data sub-matrices, a statistical gating method is used to determine the first-order distance of the single scattering component, the first-order distance of the multiple scattering components and the second-order center distance, and the tissue optical parameters are calculated.

[0018] Furthermore, the step S42 is specifically to use an M×N window to slide on the two-dimensional matrix, and the center position of the window is the Mth 0 Line No. N 0 Columns are drawn until the entire two-dimensional matrix is ​​covered. Each swipe corresponds to extracting an M×N data matrix Z. The matrix Z contains single scattering components and multiple scattering components, that is, Z = Z S +Z M , where Z s is the single scattering component, Z M is the multiple scattering component.

[0019] Furthermore, the specific process of step S43 is as follows:

[0020] S431, average all the data in the matrix Z to obtain:

[0021]

[0022] After squaring each data in the matrix Z, and then finding the average of all the data, we get:

[0023]

[0024] After cubing each data in the matrix Z and then finding the average of all the data, we get:

[0025]

[0026] Among them, Zij is the data in the i-th row and j-th column of the Z matrix;

[0027] S432, according to x 1 、x 2 、x 3 , corresponding to the calculation of the first-order distance λ of the single scattering component, the first-order distance μ of the multiple scattering component, and the second-order center distance σ 2 ;

[0028] S433, fill λ, μ, σ into the Mth order distance matrix A of the single scattering component, the first order distance matrix B of the multiple scattering component and the standard deviation matrix C of the multiple scattering component respectively 0 Line No. N 0 List;

[0029] S434, repeating steps S431 to S433 until all values ​​of matrices A, B and C are calculated, and the portions of the matrix boundary area that cannot be calculated are filled with 0;

[0030] S435 , calculating and obtaining tissue optical parameters based on the first-order distance matrix A of the single scattering component, the first-order distance matrix B of the multiple scattering component and the standard deviation matrix C of the multiple scattering component.

[0031] Furthermore, the step S432 is specifically to solve the following equation to obtain the first-order distance λ of the single scattering component, the first-order distance μ of the multiple scattering component, and the second-order center distance σ 2 :

[0032]

[0033]

[0034]

[0035] Among them, the second-order center distance σ 2 The standard deviation σ is obtained by taking the square root.

[0036] Furthermore, the tissue optical parameters include deep tissue perfusion, tissue absorption and tissue anisotropy parameters.

[0037] Furthermore, the specific process of step S435 is as follows:

[0038] Assume that the deep tissue perfusion image matrix is ​​P, and its data P in the i-th row and j-th column is ij Calculated by the following formula:

[0039]

[0040] Assume that the image matrix of tissue absorption coefficient is S, and its data S in row i and column j is ij Calculated by the following formula:

[0041]

[0042] Among them, A ij is the data of the i-th row and j-th column of matrix A, a is the proportional coefficient, a>0, l s is the scattering mean free path of the tissue;

[0043] Suppose the image matrix of the tissue anisotropy is G, and its data G in the i-th row and j-th column is ij Solve the following equations by nonlinear iterative method:

[0044]

[0045] Where b is the proportionality coefficient, b>0, and Y(·) is the first kind modified Bessel function.

[0046] Compared with the prior art, the present invention has the following advantages:

[0047] The present invention uses a laser radar to collect laser data for scanning imaging. Its single-point measurement time is short and the optical power is sufficient, which can meet the signal acquisition requirements of living heart imaging. On this basis, a statistical gating method is adopted to realize the statistical gating of multiple scattered components in the laser radar signal, and further calculate the tissue optical parameters, which is conducive to timely and accurate knowledge of the physiological state and degree of damage of living myocardial tissue.

[0048] The present invention uses a laser radar to scan the imaging area, obtains scanning data, and then constructs a two-dimensional matrix based on the scanning data. An M×N window (with the center position being the Mth window) is used on the two-dimensional data matrix. 0 Line No. N 0 The matrix Z is extracted with each stroke. The matrix Z contains single scattering components and multiple scattering components. Then, the statistical gating method is used to analyze the statistical gating of the first-order distance of the single scattering component, the first-order distance of the multiple scattering component and the second-order center distance. By solving the simultaneous equations, the single scattering component and the multiple scattering component can be extracted quickly and accurately, so as to facilitate the subsequent accurate calculation of tissue optical parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0050] Figure 2 A schematic diagram of system connections built for the embodiment;

[0051] Figure 3 Schematic diagram of the application process of the embodiment. DETAILED DESCRIPTION

[0052] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] Example

[0054] like Figure 1 As shown, a method for intraoperative cardiac tissue imaging based on laser radar statistical gating includes the following steps:

[0055] S1. Use a laser radar to continuously scan a set position in the heart area at a single point, wherein the reflected light intensity changes periodically with the heartbeat;

[0056] S2, judging whether the imaging trigger condition is met according to the reflected light intensity, if so, executing step S3, otherwise returning to step S1;

[0057] S3, using a laser radar to scan the imaging area and obtain scanning data;

[0058] S4. Based on the scanning data, a two-dimensional matrix is ​​constructed, and single scattering components and multiple scattering components are extracted from it using a statistical gating method to calculate the tissue optical parameters.

[0059] This embodiment applies the above technical solution to build Figure 2 The system shown includes a laser radar, a computer and a display, wherein the laser radar is used to obtain scanning data, and the computer is used to process and analyze the laser radar scanning data to output imaging results and tissue optical parameters, and display them in real time through the display.

[0060] The specific application process of this embodiment is as follows Figure 3 As shown, the main contents are:

[0061] 1) A laser radar is used to continuously scan a fixed position in the heart area at a single point. The reflected light intensity varies periodically with the heartbeat. In this embodiment, an imaging trigger mechanism is set according to the reflected light intensity. In practical applications, the imaging trigger mechanism may select the maximum or minimum value of the time-varying reflected light intensity (corresponding to heart contraction or diastole, respectively), or other moments in the heartbeat cycle;

[0062] In addition, the imaging trigger mechanism can be set by ECG signals or blood pressure signals monitored during surgery;

[0063] It can also be set using the grayscale values ​​of the RGB channels in a white light illumination color camera video or the values ​​after converting the image into another color space image.

[0064] 2) After the imaging is triggered, the laser radar is used to scan the entire imaging area (in actual applications, imaging data can be collected on a part of the imaging area as needed), and the data is arranged into a two-dimensional matrix in the scanning order (normal data collection process of the laser radar).

[0065] 3) Use an M×N window (with the center at the Mth 0 Line No. N 0 The matrix is ​​moved along the rows and columns until the entire two-dimensional matrix is ​​covered. Each time the matrix is ​​moved, an M×N data matrix Z is extracted. The matrix Z contains single scattering components and multiple scattering components, that is, Z=Z S +Z M .

[0066] 4) Calculation Where Z ij is the data in the i-th row and j-th column of the Z matrix. 1 It is to find the average value of all the data in the matrix Z.

[0067] 5) Calculation x 2 It is to square each data in the matrix Z and then find the average value of all the data.

[0068] 6) Calculation x 3 It is to cube each data in the matrix Z and then find the average value of all the data.

[0069] 7) Let the first-order distance of the single scattering component be λ, the first-order distance of the multiple scattering component be μ, and the second-order center distance be σ 2 . Solve the above three quantities based on the following set of equations. After solving, fill λ, μ, σ into the Mth matrix of matrices A, B and C respectively. 0 Line No. N 0 List.

[0070]

[0071]

[0072]

[0073] It should be noted that, if there is no need to calculate the deep tissue perfusion image subsequently, then step 7) only requires solving the first and third equations mentioned above together.

[0074] 8) Slide the window and repeat steps 4) to 7) until all values ​​of matrices A, B and C are calculated, and the portions of the matrix boundary area that cannot be calculated are filled with 0.

[0075] 9) Let the deep tissue perfusion image matrix be P, and its data P in the i-th row and j-th column is ij Calculated by the following formula:

[0076]

[0077] 10) Let the image matrix of tissue absorption coefficient be S, and its data S in row i and column j be ij Calculated by the following formula:

[0078]

[0079] Among them, A ij is the data in the i-th row and j-th column of matrix A, a is the proportional coefficient (a>0), l s is the scattering mean free path of the tissue (can be obtained by looking up the table).

[0080] 11) Let the image matrix of tissue anisotropy be G. The data G in the i-th row and j-th column is ij Solve the following equations by nonlinear iterative method:

[0081]

[0082] Wherein, b is the proportionality coefficient (b>0), and Y(·) is the first kind modified Bessel function. It should be noted that, in practical applications, the solution of the equation in step 11) can be replaced by an approximate algorithm.

[0083] The deep tissue perfusion image, tissue absorption coefficient image and tissue anisotropy image calculated in steps 9) to 11) are displayed on a display.

[0084] In summary, this solution uses lidar to collect laser data, with a single-point sampling time of less than 1us and a single pulse power of more than 50mW, which meets the signal acquisition requirements for living heart imaging.

[0085] This scheme analyzes the statistical gating of the first-order distance of the single scattering component, the first-order distance of the multiple scattering component and the second-order center distance, and solves them quickly and accurately through a set of simultaneous equations.

[0086] This method can simultaneously obtain parameter images such as deep myocardial tissue perfusion, tissue absorption and tissue anisotropy, among which tissue anisotropy parameter images can be used to quantitatively evaluate myocardial damage.

[0087] This scheme can be well applied to non-contact real-time imaging during cardiac surgery, which is conducive to timely and accurate knowledge of the physiological state and degree of damage of living myocardial tissue during surgery.

Claims

1. A method for intraoperative imaging of cardiac tissue based on LiDAR statistical gating, characterized in that: The following steps are involved: S1. Use a laser radar to continuously scan a set position in the heart area at a single point, wherein the reflected light intensity changes periodically with the heartbeat; S2, judging whether the imaging trigger condition is met according to the reflected light intensity, if so, executing step S3, otherwise returning to step S1; S3, using a laser radar to scan the imaging area and obtain scanning data; S4. Based on the scanning data, a two-dimensional matrix is ​​constructed, and single scattering components and multiple scattering components are extracted from it using a statistical gating method to calculate the tissue optical parameters.

2. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 1, characterized in that: The single-point sampling time of the laser radar is less than 1us and the single-pulse power is higher than 50mW.

3. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 1, characterized in that: In step S2, if the reflected light intensity reaches a preset light intensity threshold, it is determined that the imaging trigger condition is met.

4. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 1, characterized in that: The step S3 specifically uses a laser radar to scan the entire imaging area or a set portion of the imaging area.

5. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 1, characterized in that: The step S4 comprises the following steps: S41, arranging the scanned data in a scanning order to obtain a two-dimensional matrix; S42, performing window sliding processing on the two-dimensional matrix, and extracting a data sub-matrix corresponding to each sliding; S43. According to the plurality of data sub-matrices, a statistical gating method is used to determine the first-order distance of the single scattering component, the first-order distance of the multiple scattering components and the second-order center distance, and the tissue optical parameters are calculated.

6. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 5, characterized in that: The step S42 specifically involves sliding an M×N window on the two-dimensional matrix, with the center of the window being the M0th row and the N0th column, until the entire two-dimensional matrix is ​​covered. Each sliding movement corresponds to extracting an M×N data matrix Z, which includes single scattering components and multiple scattering components, that is, Z=Z S +Z M , where Z S is the single scattering component, Z M is the multiple scattering component.

7. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 6, characterized in that: The specific process of step S43 is as follows: S431, average all the data in the matrix Z to obtain: After squaring each data in the matrix Z, and then finding the average of all the data, we get: After cubing each data in the matrix Z and then finding the average of all the data, we get: Among them, Z ij is the data in the i-th row and j-th column of the Z matrix; S432, according to x1, x2, x3, correspondingly calculate the first-order distance λ of the single scattering component, the first-order distance μ of the multiple scattering component, and the second-order center distance σ 2 ; S433, respectively fill λ, μ, σ into the M0th row and N0th column of the single scattering component first-order distance matrix A, the multiple scattering component first-order distance matrix B, and the multiple scattering component standard deviation matrix C; S434, repeating steps S431 to S433 until all values ​​of matrices A, B and C are calculated, and the portions of the matrix boundary area that cannot be calculated are filled with 0; S435 , calculating and obtaining tissue optical parameters based on the first-order distance matrix A of the single scattering component, the first-order distance matrix B of the multiple scattering component and the standard deviation matrix C of the multiple scattering component.

8. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 7, characterized in that: The step S432 is specifically to solve the following equation to obtain the first-order distance λ of the single scattered component, the first-order distance μ of the multiple scattered components, and the second-order center distance σ 2 : Among them, the second-order center distance σ 2 The standard deviation σ is obtained by taking the square root.

9. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 7, characterized in that: The tissue optical parameters include deep tissue perfusion, tissue absorption and tissue anisotropy parameters.

10. The method for intraoperative cardiac tissue imaging based on laser radar statistical gating according to claim 9, characterized in that: The specific process of step S435 is as follows: Assume that the deep tissue perfusion image matrix is ​​P, and its data P in the i-th row and j-th column is ij Calculated by the following formula: Assume that the image matrix of tissue absorption coefficient is S, and its data S in row i and column j is ij Calculated by the following formula: Among them, A ij is the data of the i-th row and j-th column of matrix A, a is the proportional coefficient, a>0, ls is the scattering mean free path of the tissue; Suppose the image matrix of the tissue anisotropy is G, and its data G in the i-th row and j-th column is ij Solve the following equations by nonlinear iterative method: Wherein, b is the proportionality coefficient, b>0, and Y(·) is the first kind modified Bessel function.

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