Lidar statistics gated intraoperative imaging method for cardiac tissue

Abstract

The application relates to a kind of heart tissue intraoperative imaging methods based on laser radar statistical gating, comprising: using laser radar single point continuous scanning heart region setting position, wherein, reflected light intensity changes periodically with heartbeat;Whether the imaging trigger condition is reached is judged according to the reflected light intensity, if it is judged that yes, scanning is carried out using laser radar to imaging area, and scanning data is acquired;According to scanning data, construct two-dimensional matrix, extract single scattering component and multiple scattering component from it using statistical gating mode, and calculate to obtain tissue optical parameter.Compared with prior art, the application uses laser radar to scan imaging, can meet the signal acquisition requirement of live heart imaging, and proposes statistical gating mechanism, can realize the statistical gating of multiple scattering component in laser radar signal, and calculate to obtain tissue optical parameter, is beneficial to timely and accurately obtain the physiological state and damage degree of live myocardial tissue.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical imaging technology, in particular to a heart tissue intraoperative imaging method based on laser radar statistical gating. BACKGROUND

[0002] With the continuous progress of science and technology, in modern surgery, intraoperative imaging technology has been widely used, which mainly uses high-definition miniature cameras to transmit real-time images to the display, so that doctors can clearly observe the surgical site.

[0003] In cardiac surgery, due to the complexity of the operation, the requirement for intraoperative imaging is more stringent, and the heart surgery needs to monitor the real-time imaging of the myocardial tissue damage of the beating heart. The beating of the heart is caused by the contraction and expansion of the myocardium, and it is extremely challenging to accurately measure the physiological state and damage degree of the living myocardial tissue.

[0004] Due to the rapid beating of the heart, ordinary camera imaging is seriously affected by motion artifacts, and if a high-speed camera is used, it requires very strong illumination light intensity, which will inevitably affect the physiological state of the living tissue. In addition, the existing imaging technology can only obtain image data and cannot obtain related tissue parameters. SUMMARY

[0005] The purpose of the present application is to overcome the defects of the prior art and provide a heart tissue intraoperative imaging method based on laser radar statistical gating. The laser radar 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 application can be achieved by the following technical scheme: a heart tissue intraoperative imaging method based on laser radar statistical gating, comprising the following steps:

[0007] S1, using a laser radar to continuously scan a heart region setting position, wherein the reflected light intensity changes periodically with the heartbeat;

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

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

[0010] S4, constructing a two-dimensional matrix according to the scanning data, extracting single scattering components and multiple scattering components from the matrix by statistical gating, and calculating tissue optical parameters.

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

[0012] Further, in the step S2, if the reflected light intensity reaches the preset light intensity threshold, it is determined that the imaging triggering condition is reached.

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

[0014] Further, the step S4 includes the following steps:

[0015] S41, arranging the scanning data according to the 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, determining the single scattering component first moment, the multiple scattering component first moment and the second center distance by using the statistical gating method, and calculating the tissue optical parameters.

[0018] Further, the step S42 is specifically sliding using an MxN window on the two-dimensional matrix, the center position of the window is the M0th row and the N0th column, until covering the entire two-dimensional matrix, and each sliding corresponds to extracting an MxN data matrix Z, the matrix Z contains the single scattering component and the multiple scattering component, that is: Z=Z S +Z M , wherein Z s is the single scattering component, and Z M is the multiple scattering component.

[0019] Further, the specific process of the step S43 is:

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

[0021]

[0022] After squaring each data in the matrix Z, the average value of all data is obtained:

[0023]

[0024] After cubing each data in the matrix Z, the average value of all data is obtained:

[0025]

[0026] , wherein Z ijData in the i-th row and j-th column of the Z matrix;

[0027] S432, according to x1, x2, x3, corresponding calculation of single scattering component first distance λ, multiple scattering component first distance μ, second center distance σ 2 ;

[0028] S433, respectively, λ, μ, σ filled in single scattering component first distance matrix A, multiple scattering component first distance matrix B and multiple scattering component standard deviation matrix C in the M0-th row and N0-th column;

[0029] S434, repeat steps S431-S433 until the matrix A, B and C are calculated, the matrix boundary area can not be calculated by filling in 0;

[0030] S435, based on single scattering component first distance matrix A, multiple scattering component first distance matrix B and multiple scattering component standard deviation matrix C, the tissue optical parameters are calculated.

[0031] Further, the step S432 is specifically solved by the following equation to obtain single scattering component first distance λ, multiple scattering component first distance μ, second center distance σ 2 :

[0032]

[0033]

[0034]

[0035] Wherein, the second center distance σ 2 After the square root calculation, the standard deviation σ is obtained.

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

[0037] Further, the specific process of step S435 is:

[0038] Let the deep tissue perfusion image matrix be P, and the data P ij is calculated by the following formula:

[0039]

[0040] Let the image matrix of tissue absorption coefficient be S, and the data S ij is calculated by the following formula:

[0041]

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

[0043] An image matrix of anisotropy of the tissue is G, and the data of the i-th row and the j-th column of the matrix G is G ij The following equation group is solved by a nonlinear iterative method:

[0044]

[0045] wherein b is a proportional coefficient, b>0, and Y(·) is a first type of modified Bessel function.

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

[0047] The present application uses a laser radar to collect laser data for scanning imaging, and the single-point measurement time is short and the optical power is sufficient, which can meet the signal collection requirements of in-vivo heart imaging. On this basis, a statistical gating method is used to realize statistical gating of multiple scattering components in the laser radar signal, and the optical parameters of the tissue are further calculated, which is beneficial to timely and accurately obtaining the physiological state and damage degree of the in-vivo myocardial tissue.

[0048] The present application uses a laser radar to scan the imaging area to obtain scanning data, and then constructs a two-dimensional matrix according to the scanning data. A M*N window (the center position is the M0-th row and the N0-th column) is used to slide (single pixel translation along the row and the column) on the two-dimensional data matrix until all the two-dimensional matrix is covered. A M*N data matrix Z is extracted each time the window slides, and the matrix Z contains single scattering components and multiple scattering components. Then, the statistical gating of the single scattering component first moment, the multiple scattering component first moment and the second central distance is analyzed, and the single scattering component and the multiple scattering component are quickly and accurately extracted by solving the equation group, so that the optical parameters of the tissue can be accurately calculated subsequently. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is a method flowchart of the present application;

[0050] Figure 2 is a system connection schematic diagram built by the embodiment;

[0051] Figure 3 is an application process schematic diagram of the embodiment. DETAILED DESCRIPTION

[0052] The present application will be described in detail below in combination with the drawings and specific embodiments.

[0053] EMBODIMENT

[0054] As Figure 1 shown, a kind of heart tissue intraoperative imaging method based on laser radar statistical gating, comprising the following steps:

[0055] S1, using laser radar single point continuously scans heart region set position, wherein, reflected light intensity changes periodically with heartbeat;

[0056] S2, whether the imaging trigger condition is reached according to reflected light intensity, if it is judged to be, then step S3 is executed, otherwise it returns to step S1;

[0057] S3, using laser radar scans imaging area, obtains scanning data;

[0058] S4, according to scanning data, constructs two-dimensional matrix, extracts single scattering component and multiple scattering component from it using statistical gating mode, and calculates to obtain tissue optical parameter.

[0059] The embodiment applies the above technical scheme, builds the system as shown in Figure 2 , comprising laser radar, computer and display, wherein, laser radar is used to obtain scanning data, computer is used to process and analyze laser radar scanning data, to output to obtain imaging result and tissue optical parameter, and is shown in real time through display.

[0060] The specific application process of the embodiment is as shown in Figure 3 , and the main content includes:

[0061] 1) using laser radar single point continuously scans heart region fixed position, reflected light intensity changes periodically with heartbeat, the embodiment sets imaging trigger mechanism according to reflected light intensity, in actual application, imaging trigger mechanism can select the maximum or minimum of time-varying reflected light intensity (corresponding to heart shrinkage or diastole respectively), or other time in heartbeat cycle;

[0062] In addition, imaging trigger mechanism can also be set by intraoperative monitoring electrocardiosignal or blood pressure signal;

[0063] Gray value of RGB channel in white light illumination color camera video or the numerical value after picture is converted to other color space image can also be used to set.

[0064] 2) after imaging trigger, using laser radar scans entire imaging area (in actual application, the part of imaging area can be imaged according to demand Data acquisition), according to scanning order, data is arranged into two-dimensional matrix (normal data acquisition process of laser radar).

[0065] 3) A window of MxN (center position is the M0th row and the N0th column) is used to slide (single pixel translation along row and column) on the two-dimensional data matrix until the whole two-dimensional matrix is covered, and a MxN data matrix Z is extracted each time, which contains single scattering component and multiple scattering component, i.e. Z = Z S + Z M .

[0066] 4) Calculate wherein Z ij is the data of the ith row and the jth column in the matrix Z. x1 is the average value of all data in the matrix Z.

[0067] 5) Calculate x2 is the average value of all data after squaring each data in the matrix Z.

[0068] 6) Calculate x3 is the average value of all data after cubing each data in the matrix Z.

[0069] 7) Let the first-order distance of single scattering component be λ, the first-order distance of multiple scattering component be μ, and the second-order center distance be σ 2 . The above three quantities are solved based on the following equation group. After solving, λ, μ, and σ are filled into the M0th row and the N0th column of matrices A, B, and C, respectively.

[0070]

[0071]

[0072]

[0073] It should be noted that if the deep tissue perfusion image is not needed to be calculated subsequently, step 7) only needs to solve the above first and third equations simultaneously.

[0074] 8) Slide the window and repeat steps 4) to 7) until the calculation of all values of matrices A, B, and C is completed, and the part of the matrix boundary region which cannot be calculated is filled with 0.

[0075] 9) Let the deep tissue perfusion image matrix be P, and the data of the ith row and the jth column of P ij be calculated by the following formula:

[0076]

[0077] 10) Let the image matrix of tissue absorption coefficient be S, and the data of the ith row and the jth column of S ij be calculated by the following formula:

[0078]

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

[0080] 11) An image matrix of the anisotropy of the tissue is G. The data of the i-th row and j-th column of G ij The following equation set is solved by a nonlinear iterative method:

[0081]

[0082] wherein b is a proportional coefficient (b>0), and Y(·) is a first-type modified Bessel function. It should be noted that in practical applications, the equation solving in step 11) can be replaced by an approximate algorithm.

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

[0084] As can be seen from the above, the present scheme uses a laser radar to collect laser data, the single-point sampling time is less than 1us, and the single-pulse power is higher than 50mW, which meets the signal collection requirements of in-vivo heart imaging.

[0085] The present scheme analyzes the statistical gating of the first-order distance of single scattering components, the first-order distance of multiple scattering components and the second-order central distance, and solves the equations to quickly and accurately obtain the parameters.

[0086] The present scheme can simultaneously obtain the images of myocardial deep tissue perfusion, tissue absorption and tissue anisotropy. The tissue anisotropy parameter image can be used for quantitative evaluation of myocardial injury.

[0087] The present scheme can be well applied to non-contact real-time imaging during cardiac surgery, which is conducive to timely and accurately obtaining the physiological state and injury degree of in-vivo myocardial tissue.

Claims

1. A method for intraoperative cardiac tissue imaging 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. Determine whether the imaging trigger condition is met based on the reflected light intensity. If so, proceed to step S3; otherwise, return to step S1. S3. Scan the imaging area using a laser radar to obtain scanning data; S4. Construct a two-dimensional matrix based on the scan data, extract the single scattering component and the multiple scattering component from it using a statistical gating method, and calculate the tissue optical parameters; Step S4 includes the following steps: S41, arranging the scan 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. Determine the first-order distance of the single scattering component, the first-order distance of the multiple scattering component, and the second-order center distance based on the multiple data sub-matrices using a statistical gating method, and calculate the tissue optical parameters; Step S42 is specifically to use the Slide the window, the center of the window is the Rank Columns, until the entire two-dimensional matrix is ​​covered, each swipe corresponds to the extraction of a The data matrix ,matrix Contains single scattering components and multiple scattering components, namely: ,in, is the single scattering component, is the multiple scattering component; The specific process of step S43 is: S431, the matrix Taking the average of all the data in , we get: ， The matrix After squaring each data point and then finding the average value of all data points, we get: ， The matrix After cubing each data point, and then finding the average value of all data points, we get: ， in, for The first Rank Column data; S432, according to 、 、 , corresponding to the calculation of the first-order distance of the single scattering component , the first-order distance of the multiple scattering component , second-order center distance ; S433, respectively 、 、 Fill in the first-order distance matrix of the single scattering component , the first-order distance matrix of multiple scattering components and the multiple scattering component standard deviation matrix No. Rank List; S434, repeat steps S431 to S433 until the matrix 、 and After all values ​​of are calculated, the part of the matrix boundary area that cannot be calculated is filled with 0; S435, based on the first-order distance matrix of single scattering components , the first-order distance matrix of multiple scattering components and the multiple scattering component standard deviation matrix , calculate the tissue optical parameters; The tissue optical parameters include deep tissue perfusion, tissue absorption and tissue anisotropy parameters. The specific process of step S435 is as follows: Assume that the deep tissue perfusion image matrix is , the first Rank Column data Calculated by the following formula: ， Assume that the image matrix of tissue absorption coefficient is , the first Rank Column data Calculated by the following formula: ， in, is a matrix No. Rank Column data, is the proportional coefficient, , is the scattering mean free path of the tissue; Assume that the image matrix of tissue anisotropy is , the first Rank Column data The nonlinear iterative method is used to solve the following equations: ， in, is the proportional coefficient, , is the modified Bessel function of the first kind.

2. The method for intraoperative cardiac tissue imaging based on LiDAR 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 LiDAR 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 LiDAR 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 LiDAR statistical gating according to claim 1, characterized in that: The step S432 is specifically to obtain the first-order distance of the single scattering component by solving the following equation , the first-order distance of the multiple scattering component , second-order center distance : ， ， ， Among them, the second-order center distance The standard deviation is obtained by taking the square root .

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