CN113729593B - Blood flow imaging method for 3D endoscope based on multi-angle scattering random matrix - Google Patents
Blood flow imaging method for 3D endoscope based on multi-angle scattering random matrix Download PDFInfo
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Abstract
The invention relates to a blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix, which comprises the following steps: s1, a light source is connected into n light guide beams of a 3D endoscope, light passing of each light guide beam is controlled in sequence to form an illumination period, original speckle images are synchronously acquired by using near infrared channels of two cameras of the 3D endoscope, and 2n original speckle images are acquired in one illumination period; s2, respectively constructing an initial scattering light intensity matrix for any pixel position; s3, acquiring a single scattering light intensity second-order central moment, a multiple scattering light intensity second-order central moment and a multiple scattering light intensity first-order central moment of the pixel points; s4, traversing all pixel points; and S5, acquiring the single scattering contrast value and the multiple scattering contrast value of each pixel point, and arranging according to the positions of the pixel points to form a single scattering contrast image and a multiple scattering contrast image. Compared with the prior art, the method can obtain more accurate surface layer and deep blood flow information.
Description
Technical Field
The invention relates to the technical field of optical imaging, in particular to a blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix.
Background
3D endoscopy is an emerging tool in surgery that can provide real-time depth perception. By three-dimensionally reconstructing the contour data of internal tissues and organs or focus parts of a human body, the 3D endoscope effectively improves the accuracy, feasibility and scientificity of the current diagnosis and treatment process. At present, 3D endoscopes have been introduced and used in various departments such as abdominal cavity, cranial cavity, digestive system department, and the like.
The clinical use of indocyanine green dye in combination with fluorescence imaging to obtain the visual images of tumor and vascular blood flow is currently available, but this technique is subject to the metabolic cycle of dye injection and is prone to false-positive results. Laser Speckle Contrast Imaging (LSCI) is a simple and low-cost method that can acquire 2D perfusion maps of the entire field of view and provide a dynamic description of blood flow changes in real time, and thus can be used as an intraoperative blood flow monitoring tool. In contrast to fluorescence imaging, LSCI does not require contrast agents and can therefore be used as needed at any time during surgery. The signals recorded by the reflective laser speckle system simultaneously contain single-scattering photons and multiple-scattering photons, which respectively correspond to blood flow information of blood vessels on the surface layer and the deeper layer of an object in an operation, and the conventional LSCI method cannot realize the statistical separation of the single-scattering light intensity and the multiple-scattering light intensity at present.
Most medical clinical diagnosis and treatment not only have the requirement on stereoscopic visualization, but also have the requirement on the development of physiological information such as blood flow of blood vessels at different depths, and if the LSCI technology-based single and multiple scattering light intensity statistical separation can be realized and the LSCI technology-based single and multiple scattering light intensity statistical separation and the LSCI technology-based multiple scattering light intensity statistical separation can be effectively combined with a 3D endoscope, the LSCI technology-based multiple scattering light intensity statistical separation and the LSCI technology-based multiple scattering light intensity statistical separation can be obviously improved, and the LSI technology-based multiple scattering light intensity statistical separation can be obviously improved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix.
The purpose of the invention can be realized by the following technical scheme:
a blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix comprises the following steps:
s1, a near-infrared coherent laser light source is connected into N light guide beams of a 3D endoscope, light passing of each light guide beam is controlled in sequence to form an illumination period, near-infrared channels of two cameras of the 3D endoscope are used for synchronously acquiring original speckle images, and N =2N original speckle images are acquired in one illumination period;
s2, for any pixel position, adopting pixel point gray data of an original speckle image acquired in T illumination periods to construct an initial scattering light intensity matrix with the size of NxT;
s3, acquiring a single scattering light intensity second-order central moment, a multiple scattering light intensity second-order central moment and a multiple scattering light intensity first-order central moment of corresponding pixel points based on the initial scattering light intensity matrix;
s4, sequentially traversing all pixel points in the original speckle image, and repeating the steps S2-S3;
and S5, acquiring a single scattering contrast value of each pixel point based on the single scattering light intensity second-order central moment, acquiring a multiple scattering contrast value of each pixel point based on the multiple scattering light intensity second-order central moment and the multiple scattering light intensity first-order central moment, and arranging and forming a single scattering contrast image representing the surface relative blood flow velocity and a multiple scattering contrast image representing the deep relative blood flow velocity according to the pixel point positions.
Preferably, step S1 specifically includes:
the method comprises the steps that a near-infrared coherent laser light source is connected into N light guide beams of a 3D endoscope, light outlets of the N light guide beams are distributed at the front end of the 3D endoscope in a fixed position, different light guide beams form different angle relations with two cameras and imaging tissues when emitting light, the light guide beams sequentially emit light in turn in an illumination period, near-infrared channels of the two cameras are used for synchronously and continuously acquiring N frames of original speckle images, and the total number of frames recorded in a single illumination period is N =2N.
Preferably, the specific manner of constructing the initial scattering light intensity matrix in step S2 includes:
for each pixel position of the original speckle image, converting pixel point gray data of N original speckle images at N imaging angles in a single illumination period into a column vector;
sequentially arranging the column vectors obtained in the T lighting periods according to the time sequence to construct an initial scattering light intensity matrix SH，SHIs N × T.
Preferably, step S3 specifically includes:
s31, converting the initial scattering light intensity matrix into a covariance matrix;
s32, performing eigenvalue decomposition on the covariance matrix;
s33, using the smallest and next smallest eigenvalues and
calculating the second-order central moment of the multiple scattering light intensity in a distributed manner;
s34, calculating a second-order central moment of the single scattering light intensity based on the second-order central moment of the initial scattering light intensity matrix and the second-order central moment of the multiple scattering light intensity;
s35, solving the first-order central moment of the single scattered light intensity according to the negative index distribution characteristics of the single scattered light intensity, and further solving the first-order central moment of the multiple scattered light intensity.
Preferably, the covariance matrix of step S31 is obtained by the following equation:
wherein, MHIs a covariance matrix, SHIs a matrix of the initial scattered light intensities,
matrix and SHThe dimensions of the two-dimensional bar code are the same,
has an element value of SHThe average of the rows in the matrix where the corresponding position element is located,
is composed of
The transposed matrix of (2).
Preferably, the eigenvalue decomposition of the covariance matrix in step S32 is expressed as:
MH＝UΓVT
wherein, MHIs a covariance matrix, gamma is a diagonal matrix, U and V are eigenvector matrices, and the elements on the main diagonal of the gamma matrix are a covariance matrix MHThe characteristic value of (2).
Preferably, the second-order central moment of the multiple scattering intensity in step S33 is obtained by the following formula:
wherein the content of the first and second substances,
second order central moment, lambda, of the multiple scattered light intensityNMinimum eigenvalue, λ, obtained by eigenvalue decomposition for covariance matrixN-1And (3) carrying out eigenvalue decomposition on the covariance matrix to obtain a second-smallest eigenvalue, wherein alpha and beta are positive real number coefficients, and alpha + beta =1, and Q = N/T.
Preferably, the second central moment of the single scattering intensity in step S34 is obtained by the following formula:
wherein the content of the first and second substances,
the second-order center distance of the single scattering light intensity,
the second order central moment of the multiple scattered light intensity,
the second-order central moment of the initial scattering intensity matrix is obtained, gamma is a positive real number coefficient, and gamma is smaller than 1.
Preferably, the first central moment of the single-scattered light intensity and the first central moment of the multiple-scattered light intensity of step S35 are obtained by:
wherein the content of the first and second substances,
is the first order central moment of the intensity of the single scattering light,
is composed of
The square root of (a) is,
the second-order center distance of the single scattering light intensity,
is the first-order central moment of the multiple scattered light intensity, and mu is the average value of the gray data of the pixel points in the initial scattered light intensity matrix.
Preferably, the single scattering contrast value and the multiple scattering contrast value of each pixel point in step S5 are obtained by the following formula:
wherein, KsIs a value of the contrast ratio of the single scattering,
is composed of
The square root of (a) is,
is the second-order center distance of the single scattering light intensity, KMIn order to obtain a value of contrast for multiple scattering,
is composed of
The square root of (a) is,
the second order central moment of the multiple scattered light intensity,
the first central moment of the multiple scattered light intensity.
Compared with the prior art, the invention has the following advantages:
(1) The invention has more accurate description on the characteristics of the scattering matrix, can realize the statistical separation of the first-order central moment and the second-order central moment, thereby realizing the statistical separation of the light intensity of single scattering and multiple scattering, combines the information of the first-order moment and the second-order moment, can more accurately describe the integral intensity distribution of the single scattering and the multiple scattering, and further obtains more accurate functional information such as blood flow, tissue perfusion and the like.
(2) The invention can obtain the more pure surface blood vessel statistical characteristics and blood flow information and present better imaging effect (single scattering part); the statistical characteristics and blood flow information of blood vessels at deeper parts in the tissue can be presented, and meanwhile, surface reflection points (multiple scattering parts) are effectively removed; because the random matrix is insensitive to rigid motion, the invention can eliminate or reduce imaging artifacts generated by partial physiological motion (breathing, heartbeat and the like).
Drawings
FIG. 1 is a flow chart of a blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix according to the present invention;
fig. 2 is a schematic view of the front end of a 3D endoscope used in the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. Note that the following description of the embodiment is merely a substantial example, and the present invention is not intended to be limited to the application or the use thereof, and is not limited to the following embodiment.
Examples
As shown in fig. 1, the present embodiment provides a blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix, which includes the following steps:
s1, a near-infrared coherent laser light source is connected into N light guide beams of a 3D endoscope, light passing of each light guide beam is controlled in sequence to form an illumination period, original speckle images are synchronously acquired by using near-infrared channels of two cameras of the 3D endoscope, and N =2N original speckle images are acquired in one illumination period. Specifically, the method comprises the following steps: the method comprises the steps that a near-infrared coherent laser light source is connected into N light guide beams of a 3D endoscope, light outlets of the N light guide beams are distributed at the front end of the 3D endoscope in a fixed position, different light guide beams form different angle relations with two cameras and imaging tissues when emitting light, the light guide beams sequentially emit light in turn in an illumination period, near-infrared channels of the two cameras are used for synchronously and continuously acquiring N frames of original speckle images, and the total number of frames recorded in a single illumination period is N =2N. In this embodiment, the near-infrared coherent laser has a center wavelength of 830nm, a power of 20mw, and a 3d endoscope is provided with 4 light guide beams, and sequentially irradiates laser on an observed intraoperative object in turn under active control through a front end of the endoscope (shown in fig. 2, symmetrically distributed), backscattered light from scattering particles (such as red blood cells) is synchronously and continuously collected by near-infrared channels of two (binocular) cameras at the front end of the endoscope (a collection frame rate and an exposure time of the cameras are synchronized with a sequential illumination time of the light guide beams), a single illumination period (the 4 light guide beams are sequentially and alternately illuminated once), and the near-infrared channels of the two cameras collect N =8 frames of original speckle images.
S2, for any pixel position, adopting pixel point gray data of an original speckle image acquired in T lighting periods to construct an initial scattering light intensity matrix with the size of NxT, wherein the specific mode for constructing the initial scattering light intensity matrix in the step S2 comprises the following steps:
for each pixel position of the original speckle image, converting pixel point gray scale data of N original speckle images at N imaging angles in a single illumination period into a column vector;
obtained by arranging T lighting cycles in time sequenceColumn vectors to construct an initial scattered light intensity matrix SH，SHIs NxT;
in this embodiment, T =24.
S3, acquiring a single scattering light intensity second-order central moment, a multiple scattering light intensity second-order central moment and a multiple scattering light intensity first-order central moment of corresponding pixel points based on the initial scattering light intensity matrix;
step S3 specifically includes:
s31, converting the initial scattering light intensity matrix into a covariance matrix, wherein the covariance matrix is obtained through the following formula:
wherein M isHIs a covariance matrix, SHIs the initial scattered light intensity matrix and,
matrix and SHThe dimension of the material is the same as that of the material,
has an element value of SHThe average value of the row of the corresponding position element in the matrix,
is composed of
The transposed matrix of (2).
S32, performing eigenvalue decomposition on the covariance matrix, wherein the eigenvalue decomposition is represented as:
MH＝UΓVT
wherein M isHIs a covariance matrix, gamma is a diagonal matrix, U and V are eigenvector matrices, and the elements on the main diagonal of the gamma matrix are a covariance matrix MHThe characteristic value of (2).
S33, using the smallest and next smallest eigenvalues and
and (5) calculating the second-order central moment of the multiple scattering light intensity. Since the backscattered light collected by the two (binocular) cameras of the 3D endoscope contains both single scattered light and multiply scattered light, the covariance matrix MHMay be represented by the following formula:
MH＝Ms+MM
in the above formula, matrix MSRepresenting the single-scattered part, matrix MMRepresenting the multiple scattering fraction.
Due to the multiple scattering properties of light in tissue, the matrix MMIs a Wishart random matrix, and is in accordance with
When T/N = Q is more than or equal to 1, the probability density function of the characteristic value is as follows:
in the above formula, λ±Is a matrix WMUpper and lower boundaries of eigenvalues, their and matrix WMVariance of (2)
The relationship of (a) is as follows:
if the matrix WMIs finite, and when the number of frames T tends to infinity, the matrix WMMinimum eigenvalue of andlower boundary lambda_Approximately equal; when the number of pixels N and the number of frames T of different imaging angles tend to infinity, the matrix WHMinimum eigenvalue sum matrix WMAre approximately equal. Considering that two (binocular) cameras of the 3D endoscope have a symmetrical relationship with the light beam window, it is necessary to use the minimum and the next smallest eigenvalue sums
And (3) calculating the second-order central moment of the multiple scattering light intensity in a distributed manner, and then obtaining the second-order central moment of the multiple scattering light intensity through the following formula:
wherein, the first and the second end of the pipe are connected with each other,
second-order central moment, lambda, of the intensity of the multiple-scattered lightNMinimum eigenvalue, λ, obtained by eigenvalue decomposition for covariance matrixN-1For the second smallest eigenvalue obtained by decomposing the eigenvalues of the covariance matrix, α and β are positive real coefficients, α + β =1, q = n/T, and in this embodiment, α =0.5, β =0.5, and q =3.
And S34, calculating a second-order central moment of the single scattering light intensity based on the second-order central moment of the initial scattering light intensity matrix and the second-order central moment of the multiple scattering light intensity. For matrix MHThe trace of (a) is decomposed as follows:
the second-order central moment is related to the trace of the matrix by the following equation:
when the number of pixels N and the number of frames T of different imaging angles both tend to infinity, there is the following relationship:
further, the second order central moment of the single scattering intensity can be obtained by:
wherein the content of the first and second substances,
is the second-order center distance of the single scattering light intensity,
the second order central moment of the multiple scattering light intensity,
and gamma is a second-order central moment of the initial scattering light intensity matrix, is a positive real number coefficient, and is smaller than 1.
S35, solving a first-order central moment of the single scattering light intensity according to the negative index distribution characteristics of the single scattering light intensity, and further solving a first-order central moment of the multiple scattering light intensity, wherein the first-order central moment is obtained through the following formula:
wherein the content of the first and second substances,
is the first order central moment of the intensity of the single scattering light,
is composed of
The square root of (a) is,
the second-order center distance of the single scattering light intensity,
is the first-order central moment of the multiple scattered light intensity, and mu is the average value of the gray data of the pixel points in the initial scattered light intensity matrix.
S4, sequentially traversing all pixel points in the original speckle image, and repeating the steps S2-S3;
and S5, acquiring a single scattering contrast value of each pixel point based on the single scattering light intensity second-order central moment, acquiring a multiple scattering contrast value of each pixel point based on the multiple scattering light intensity second-order central moment and the multiple scattering light intensity first-order central moment, and arranging and forming a single scattering contrast image representing the surface relative blood flow velocity and a multiple scattering contrast image representing the deep relative blood flow velocity according to the pixel point positions. Wherein, the single scattering contrast value and the multiple scattering contrast value of each pixel point are obtained by the following formula:
wherein, KSIs a value of the contrast ratio of the single scattering,
is composed of
The square root of (a) is,
is of second order of single scattering intensityCenter distance, KMFor the value of the multiple scattering contrast ratio,
is composed of
The square root of (a) is,
the second order central moment of the multiple scattering light intensity,
the first central moment of the multiple scattered light intensity.
The invention can obtain the more pure surface blood vessel statistical characteristics and blood flow information and present better imaging effect (single scattering part); the statistical characteristics and blood flow information of blood vessels at deeper parts in the tissue can be presented, and meanwhile, surface reflection points (multiple scattering parts) are effectively removed; because the random matrix is insensitive to rigid motion, the invention can eliminate or reduce imaging artifacts generated by partial physiological motion (breathing, heartbeat and the like). Compared with the traditional single-scattering and multiple-scattering light intensity statistical separation method based on a single camera, the method has the advantages that the characteristic description of the scattering matrix is more accurate, the statistical separation of the first-order moment and the second-order central moment can be realized, further, the information of the first-order moment and the second-order moment is combined, the overall intensity distribution of single-scattering and multiple-scattering can be more accurately described, and more accurate functional information such as blood flow, tissue perfusion and the like can be further obtained.
The above embodiments are merely examples and do not limit the scope of the present invention. These embodiments may be implemented in other various manners, and various omissions, substitutions, and changes may be made without departing from the technical spirit of the present invention.
Claims (10)
1. A blood flow imaging method for a 3D endoscope based on a multi-angle scattering random matrix is characterized by comprising the following steps:
s1, a near-infrared coherent laser light source is connected into N light guide beams of a 3D endoscope, light passing of each light guide beam is controlled in sequence to form an illumination period, near-infrared channels of two cameras of the 3D endoscope are used for synchronously acquiring original speckle images, and N =2N original speckle images are acquired in one illumination period;
s2, for any pixel position, adopting pixel point gray data of an original speckle image acquired in T illumination periods to construct an initial scattering light intensity matrix with the size of NxT;
s3, acquiring a single scattering light intensity second-order central moment, a multiple scattering light intensity second-order central moment and a multiple scattering light intensity first-order central moment of corresponding pixel points based on the initial scattering light intensity matrix;
s4, sequentially traversing all pixel points in the original speckle image, and repeating the steps S2-S3;
and S5, acquiring a single scattering contrast value of each pixel point based on the single scattering light intensity second-order central moment, acquiring a multiple scattering contrast value of each pixel point based on the multiple scattering light intensity second-order central moment and the multiple scattering light intensity first-order central moment, and forming a single scattering contrast image representing the surface relative blood flow velocity and a multiple scattering contrast image representing the deep relative blood flow velocity according to the pixel point position arrangement.
2. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 1, wherein the step S1 is specifically as follows:
the method comprises the steps that a near-infrared coherent laser light source is connected into N light guide beams of a 3D endoscope, light outlets of the N light guide beams are distributed at the front end of the 3D endoscope in a fixed position, different light guide beams emit light in different angle relationships with two cameras and imaging tissues, the light guide beams sequentially emit light in turn in an illumination period, near-infrared channels of the two cameras are used for synchronously and continuously acquiring N frames of original speckle images, and the total number of frames recorded in a single illumination period is N =2N.
3. The method for imaging blood flow for a 3D endoscope based on the multi-angle scattering random matrix according to claim 1, wherein the specific manner for constructing the initial scattering light intensity matrix in step S2 includes:
for each pixel position of the original speckle image, converting pixel point gray data of N original speckle images at N imaging angles in a single illumination period into a column vector;
sequentially arranging the column vectors obtained in the T lighting periods according to the time sequence to construct an initial scattered light intensity matrix SH，SHIs N × T.
4. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 1, wherein the step S3 specifically comprises:
s31, converting the initial scattering light intensity matrix into a covariance matrix;
s32, performing eigenvalue decomposition on the covariance matrix;
s33, using the smallest and next smallest eigenvalues and
calculating the second-order central moment of the multiple scattering light intensity in a distributed manner;
s34, calculating a second-order central moment of single scattering light intensity based on the second-order central moment of the initial scattering light intensity matrix and the second-order central moment of multiple scattering light intensity;
s35, solving the first-order central moment of the single scattered light intensity according to the negative index distribution characteristics of the single scattered light intensity, and further solving the first-order central moment of the multiple scattered light intensity.
5. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 4, wherein the covariance matrix of step S31 is obtained by the following formula:
wherein, MHIs a covariance matrix, SHIs the initial scattered light intensity matrix and,
matrix and SHThe dimension of the material is the same as that of the material,
has an element value of SHThe average of the rows in the matrix where the corresponding position element is located,
is composed of
The transposed matrix of (2).
6. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 4, wherein the step S32 is to perform eigenvalue decomposition on covariance matrix as:
MH＝UΓVT
wherein M isHIs a covariance matrix, gamma is a diagonal matrix, U and V are eigenvector matrices, and the elements on the main diagonal of the gamma matrix are a covariance matrix MHThe characteristic value of (2).
7. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 4, wherein the second order central moment of the multiple scattering light intensity in step S33 is obtained by the following formula:
wherein the content of the first and second substances,
second order central moment, lambda, of the multiple scattered light intensityNMinimum eigenvalue, λ, obtained by eigenvalue decomposition for covariance matrixN-1And (3) carrying out eigenvalue decomposition on the covariance matrix to obtain a second-smallest eigenvalue, wherein alpha and beta are positive real number coefficients, and alpha + beta =1, and Q = N/T.
8. The method according to claim 4, wherein the second-order central moment of the single scattering intensity in step S34 is obtained by the following formula:
wherein the content of the first and second substances,
is the second-order center distance of the single scattering light intensity,
the second order central moment of the multiple scattered light intensity,
the second-order central moment of the initial scattering intensity matrix is obtained, gamma is a positive real number coefficient, and gamma is smaller than 1.
9. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 4, wherein the step S35 is obtained by the following formula:
wherein the content of the first and second substances,
is the first order central moment of the intensity of the single scattering light,
is composed of
The square root of (a) is,
the second-order center distance of the single scattering light intensity,
is the first-order central moment of the multiple scattered light intensity, and mu is the average value of the gray data of the pixel points in the initial scattered light intensity matrix.
10. The method for imaging blood flow for 3D endoscope based on multi-angle scattering random matrix according to claim 1, wherein the single scattering contrast value and the multiple scattering contrast value of each pixel point in step S5 are obtained by the following formula:
wherein, KSIs a single-scattering contrast ratio value of the sample,
is composed of
The square root of (a) is,
is the second-order center distance, K, of the single scattering light intensityMIn order to obtain a value of contrast for multiple scattering,
is composed of
The square root of (a) is,
the second order central moment of the multiple scattered light intensity,
the first-order central moment of the multiple scattered light intensity.
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