CN116725492A - Blood vessel imaging method and system based on optical coherence tomography - Google Patents
Blood vessel imaging method and system based on optical coherence tomography Download PDFInfo
- Publication number
- CN116725492A CN116725492A CN202310851997.0A CN202310851997A CN116725492A CN 116725492 A CN116725492 A CN 116725492A CN 202310851997 A CN202310851997 A CN 202310851997A CN 116725492 A CN116725492 A CN 116725492A
- Authority
- CN
- China
- Prior art keywords
- signal
- imaging
- decorrelation
- signals
- dimensional
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000003384 imaging method Methods 0.000 title claims abstract description 68
- 238000012014 optical coherence tomography Methods 0.000 title claims abstract description 55
- 210000004204 blood vessel Anatomy 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 claims abstract description 31
- 238000002583 angiography Methods 0.000 claims abstract description 29
- 238000001228 spectrum Methods 0.000 claims abstract description 28
- 238000001914 filtration Methods 0.000 claims abstract description 14
- 238000002310 reflectometry Methods 0.000 claims abstract description 11
- 230000003595 spectral effect Effects 0.000 claims abstract description 9
- 238000005070 sampling Methods 0.000 claims abstract description 8
- 238000003672 processing method Methods 0.000 claims abstract description 4
- 230000002792 vascular Effects 0.000 claims description 16
- 238000005259 measurement Methods 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 12
- 238000010191 image analysis Methods 0.000 claims description 11
- 238000005457 optimization Methods 0.000 claims description 9
- 238000005516 engineering process Methods 0.000 abstract description 5
- 230000003068 static effect Effects 0.000 description 11
- 230000017531 blood circulation Effects 0.000 description 10
- 238000010586 diagram Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 210000003743 erythrocyte Anatomy 0.000 description 4
- 239000008280 blood Substances 0.000 description 3
- 210000000601 blood cell Anatomy 0.000 description 3
- 238000005314 correlation function Methods 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 210000004369 blood Anatomy 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 2
- 239000002872 contrast media Substances 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 101100408782 Arabidopsis thaliana PNSB1 gene Proteins 0.000 description 1
- 101100408783 Arabidopsis thaliana PNSB2 gene Proteins 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 238000000265 homogenisation Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 210000004088 microvessel Anatomy 0.000 description 1
- 231100000957 no side effect Toxicity 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000241 respiratory effect Effects 0.000 description 1
- 230000029058 respiratory gaseous exchange Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 210000003462 vein Anatomy 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0062—Arrangements for scanning
- A61B5/0066—Optical coherence imaging
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/02007—Evaluating blood vessel condition, e.g. elasticity, compliance
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0261—Measuring blood flow using optical means, e.g. infrared light
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/006—Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/404—Angiography
Abstract
The invention discloses a blood vessel imaging method and a system based on optical coherence tomography, wherein the method comprises the following operations: scanning a sample by using a spectral domain OCT imaging acquisition system and acquiring interference spectrum signals point by point; carrying out uniform sampling and inverse Fourier transform operation on the interference spectrum signal in the wave number domain to obtain the axial depth reflectivity information of any point of the sample; for N B-scan section structure signals at any y-axis coordinate position, performing time domain decorrelation by using a decorrelation function to obtain decorrelation signals; the structural signal, the decorrelation signal and the intensity mask signal are multiplied to obtain a three-dimensional signal of angiography imaging, and an angiography image representing the two-dimensional front surface is drawn by performing maximum projection along the depth direction in combination with an image processing method of three-dimensional median filtering and Gaussian filtering. The image contrast and definition of angiographic imaging realized based on OCT technology are improved by the method and the system of the invention.
Description
Technical Field
The invention relates to the technical field of angiography imaging, in particular to a vascular imaging method and a vascular imaging system based on optical coherence tomography.
Background
Contrast imaging of human blood vessels can be achieved by injecting exogenous contrast agents and adopting imaging equipment, however, the contrast agents can have certain side effects on human bodies. The OCT technology is a method utilizing illumination imaging, does not directly contact with a human body, has no invasiveness, has no side effect on the human body in the imaging mode, and can realize micron-sized high-resolution imaging in three dimensions in space by adopting a microscope objective. The OCT signals include static tissue signals, dynamic blood and blood cell signals when imaging living biological tissue. Static tissue signals have a high correlation in the time domain, whereas dynamic blood and blood cell signals have a higher non-correlation in the time domain. By utilizing the OCT technology, the same section can be scanned and imaged for multiple times, a certain time delay exists in each imaging, the time signal of any pixel of the available section is a complex signal, and the decorrelation method for the signal comprises the following steps: phase-based decorrelation, amplitude-based decorrelation and complex amplitude-based decorrelation. For the phase-based decorrelation method, only phase information is considered, and both the physiological jitter of a living organism and the vibration of an imaging system generate disturbance on the phase, so that the influence of the factors needs to be removed, and therefore, the method is easy to generate larger background noise. The amplitude-based decorrelation method only considers intensity information, but the intensity changes produced by flowing blood and red blood cells are not very obvious, so that the method is not sensitive enough to extract the information of the vascular part and lacks for the contrast imaging of small blood vessels. The decorrelation method based on complex amplitude considers phase and intensity components at the same time, so that the sensitivity of vascular imaging is improved.
The complex amplitude-based decorrelation method mainly comprises a complex difference method and a normalized complex and complex conjugate product method, the complex difference method is also used for correcting phase disturbance generated by global jitter of organisms, and the normalized complex and complex conjugate product method is used for extracting phase disturbance factors in the multiplication process of the complex and complex conjugate product method and adopts modulo operation (shown as an expression a), so that the phase factors are automatically eliminated, phase correction is not required to be carried out in advance, and the set decorrelation function is thatThe curve type is shown in fig. 4. However, although the static background is set to zero as much as possible, and the blood flow information is reserved, the noise introduced by system interference, the noise introduced by the acquisition process and the noise introduced by the biological tissue respiratory heart state have an indefinite effect on the static tissue, and meanwhile, the difference of the blood flow information has correlation, so that the blood flow information cannot be effectively extracted by a differential method or a complex decorrelation method. Therefore, based on OCT technology, the angiography imaging method realized by physical means still has the phenomena of larger image background noise influence and lower vascular contrast.
Disclosure of Invention
In order to solve the problems, the invention provides a blood vessel imaging method and a system based on optical coherence tomography, which can effectively enhance the difference between a blood flow signal and a static tissue background signal and improve the image contrast and definition of angiography imaging realized based on OCT technology.
In order to achieve the above object, the present invention is realized by the following technical scheme:
the invention relates to a blood vessel imaging method based on optical coherence tomography, which comprises the following operations: scanning a sample by using a spectral domain OCT imaging acquisition system and acquiring interference spectrum signals point by point;
performing uniform sampling and inverse Fourier transform operation on interference spectrum signals by using an OCT image reconstruction method to obtain axial depth reflectivity information of any point of a sample, and recording the axial depth reflectivity information as a complex signal as R (x, y, z, t), wherein x, y and z are used for representing pixel positions, t represents repeated measurement times of 1,2, …, N and N are continuous measurement times, and R represents complex numbers;
for the structural signals of the x-z sections of the N B-scan at any y-axis coordinate position, performing time domain decorrelation by adopting a decorrelation function to obtain decorrelation signals;
the structural signal, the decorrelation signal and the intensity mask signal are multiplied to obtain a three-dimensional signal of angiography imaging, and an angiography image representing a two-dimensional front surface is drawn by performing maximum projection along the depth direction in combination with an image processing method of three-dimensional median filtering and Gaussian filtering
The invention further improves that: scanning a sample by using a spectrum domain OCT imaging acquisition system and acquiring interference spectrum signals point by point specifically comprises the following steps: repeated collection was performed on the same sample B-scan: the spectral domain OCT imaging system continuously and repeatedly scans the X-z section of the B-scan along the X-axis at the same Y-axis position, the repetition number is N, then the spectral domain OCT imaging system moves a position along the Y-axis, and continuously and repeatedly scans the X-z section of the B-scan along the X-axis again, the repetition number is N, until the scanning of the Y-axis is completed.
The invention further improves that: the decorrelation function expression is:
wherein, in a depth window, normalized complex cross-correlation at arbitrary depth pixel positionsw (m) is a depth-direction switching window of length 2l+1, R * For complex conjugate of complex number R, t is the number of repeated measurements, z represents the position of the pixel of the x-z section of B-scan on the z axis, g is the decorrelation signal, l is the constant value, m is the independent variable, and the value is 2l+1.
The invention further improves that: the specific steps of multiplying the structural signal, the decorrelated signal and the intensity mask signal to obtain a three-dimensional signal for angiographic imaging include:
a. obtaining structural signals: the structural signals of the x-z sections of the N B-scan at any one y coordinate are acquired and expressed in logarithmic form as: i struct ＝log 10 (|R| 2 ) Wherein R represents a complex number, I struct Is a structural signal;
b. making an intensity mask signal: setting a threshold value for the decorrelated signal g, setting a value lower than the threshold value to 0, setting a value higher than the threshold value to 1, and recording the binarized intensity mask signal as I mask ；
c. The product of the structural signal, the decorrelation signal and the intensity mask signal is used for representing the three-dimensional signal of angiography imaging, and the expression is as follows:
I angio ＝I struct ×g×I mask ；
wherein I is angio Three-dimensional signals imaged for angiography.
The invention relates to a blood vessel imaging system based on optical coherence tomography, which comprises an OCT image acquisition system module, an OCT structure image reconstruction module, a blood vessel image analysis acquisition module and an image optimization processing module;
the OCT image acquisition system module is used for acquiring interference spectrum information of any point of a sample by using a spectrum domain OCT imaging mode through a point-by-point scanning imaging method;
the OCT structure image reconstruction module is used for carrying out homogenizing sampling and inverse Fourier transform operation on the interference spectrum signals obtained by the OCT image acquisition system module in a wave number domain to obtain axial depth reflectivity information of any point of a sample and is a complex signal;
the blood vessel image analysis and acquisition module is used for performing time domain decorrelation on the complex signals and extracting three-dimensional signals imaged by angiography;
the image optimization processing module is used for carrying out three-dimensional median filtering and Gaussian filtering optimization processing on three-dimensional signals of sample angiography imaging, and drawing angiography images representing the two-dimensional front face by carrying out maximum projection on the optimized three-dimensional signals along the depth direction.
The invention further improves that: the OCT image acquisition system module adopts a B-M mode.
The invention further improves that: the blood vessel image analysis and acquisition module adopts a decorrelation function to carry out time domain decorrelation on complex signals, and the expression of the decorrelation function is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,w (m) is a depth-direction switching window of length 2l+1, R * For complex conjugate of complex number R, t is the number of repeated measurements, z represents the position of the pixel of the x-z section of B-scan on the z axis, g is the decorrelation signal, l is the constant value, m is the independent variable, and the value is 2l+1.
The invention further improves that: the three-dimensional signal expression of angiography imaging extracted by the vessel image analysis and acquisition module is as follows:
I angio ＝I struct ×g×I mask ；
wherein I is mask For intensity mask signal, I struct Is a structural signal, I angio Three-dimensional signals imaged for angiography.
The beneficial effects of the invention are as follows: according to the invention, on the basis of signal decorrelation, the designed decorrelation function is used for further optimizing and removing uncorrelated disturbance noise existing in the static tissue signal, and simultaneously further optimizing and removing a small amount of signal background with correlation existing in the dynamic blood flow signal, so that the contrast of blood vessel imaging is effectively improved, and finer blood vessel vein distribution can be better represented.
Drawings
FIG. 1 is a schematic flow diagram of a method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the system principle of an embodiment of the present invention;
FIG. 3 is a schematic diagram of a decorrelation function according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a graph in the background of the invention;
FIG. 5 is a block diagram of an OCT image acquisition system in accordance with an embodiment of the present invention;
FIG. 6 is an angiographic image obtained by measuring and analyzing the ear of a living mouse according to the method of the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
As shown in fig. 2, the vascular imaging system based on optical coherence tomography comprises an OCT image acquisition system module, an OCT structure image reconstruction module, a vascular image analysis acquisition module and an image optimization processing module; the OCT image acquisition system module acquires interference spectrum information of any point by utilizing a spectrum domain OCT imaging mode through a point-by-point scanning imaging method. The interference spectrum signal obtained by the OCT structure image reconstruction module is subjected to re-homogenization sampling in a wave number domain to obtain a new interference spectrum signal, and the spectrum signal is subjected to inverse Fourier transform processing to obtain axial depth reflectivity information of any point, and the axial depth reflectivity information is a complex signal and is recorded as R (x, y, z, t). The vessel image analysis and acquisition module is used for performing time domain decorrelation on the complex signals and extracting three-dimensional signals imaged by angiography. The image optimization processing module is used for carrying out three-dimensional median filtering and Gaussian filtering optimization processing on the three-dimensional signals of the sample angiography imaging, and drawing angiography images representing the two-dimensional front face by carrying out maximum projection on the optimized three-dimensional signals along the depth direction.
The OCT image acquisition system module adopts a B-M mode, namely, at the same y-axis position, the X-z section of the B-scan is continuously and repeatedly scanned along the x-axis, the repetition number is N, then the X-z section of the B-scan is continuously and repeatedly scanned along the x-axis again after moving a position along the y-axis, and the repetition number is N until the scanning along the y-axis is completed. The light source of the OCT image acquisition system module is a wide-spectrum light source, the 3dB bandwidth is covered with more than 100nm, and the spectral energy output is stable. The OCT image acquisition system module further comprises an imaging objective lens, a point-by-point scanning module, a reference arm light path, a sample arm light path and a detection module. Wherein, the imaging objective lens is a micro objective lens with the magnification of 10 times, and NA is 0.26. The point-by-point scanning module is a two-dimensional scanning galvanometer, can respectively carry out moving scanning along the x-axis and the y-axis, and the scanning frame rate of the A-scan can reach 70KHz. The optical devices in the reference arm light path and the sample arm light path are the same, so that dispersion effect is not generated, and other influences on interference results are avoided. The detection module is a spectrometer system comprising a diffraction grating, a focusing lens and an array camera. The diffraction grating line pair number is 1800 lines/mm, the array camera can collect 2048 pixels, and 70KHz signal collection is realized.
The specific structure of the OCT image acquisition system module is shown in fig. 5, and the working principle is as follows: the supercontinuum laser can output a section of collimated light beam with the 3dB spectral width of 100nm through a band-pass filter F, the central wavelength of the wave band is 550nm, and other wave band ranges can be selected. The collimated light beam is subjected to light spot beam expansion to 5mm through a 4F lens system L1 and a 4F lens system L2, the light spot is uniformly divided into two equal-power light spots through a beam splitter BS, one light spot enters a reference arm light path, firstly passes through an adjustable attenuation sheet NDF1, then the light spot is focused on a reflecting mirror M1 through a microscope objective OBJ1, the light beam returns to the beam splitter from the original path of the reflecting mirror, the other light spot enters a sample arm light path, also passes through an adjustable attenuation sheet NDF2, then passes through a two-dimensional scanning vibrating mirror, enters the microscope objective OBJ2 through the reflecting mirror M2, irradiates the sample surface, and back scattered light exits from the sample and returns to the beam splitter along the original path. The light beam returned from the reference arm and the light beam returned from the sample arm are combined and then enter the 4F lens system L3 and the 4F lens system L4 for light spot beam shrinking, the light spectrum is dispersed through the transmission diffraction grating, and all wavelengths are focused at each pixel position of one array camera through the focusing lens L5. The two-dimensional scanning galvanometer and the array camera are controlled simultaneously, so that interference spectrum signals at any plane scanning point position can be collected and read, and the number of collected wavelengths is 2048 pixels.
The blood vessel image analysis and acquisition module comprises the following specific operation steps:
1) In order to extract the vascular component, compared with static information, the tissue component has stronger signal correlation in multiple measurements, blood flows in the blood vessel and simultaneously has the movement of red blood cells, and the signal correlation in multiple measurements is weaker, and the following decorrelation function is adopted to realize the effective extraction of the vascular information:
wherein, in a depth window, normalized complex cross-correlation at arbitrary depth pixel positionsw (m) represents a depth-wise switching window of length 2l+1, t represents the number of repeated measurements 1,2, …, N, R * The complex conjugate of R is represented, l is a constant value, m is an independent variable, 2l+1, z represents the position of the pixel of the x-z section of the B-scan on the z axis, and g is a decorrelation signal.
For complex OCT signals R (x, y, z, t), which can be considered as invariant signals in static tissue, i.e. independent of the t-variable, the a-value approaches 1 when decorrelating, but the a-value may deviate from 1 value because noise introduced by system interference, noise introduced by the acquisition process and noise introduced by biological tissue respiration heart state will all have an effect on static tissue; meanwhile, for signals at the positions of blood vessels, the value a tends to 0 when decorrelation is performed due to the fact that the blood flow and the flow of red blood cells change along with the t variable in real time, but for capillary blood vessels and other micro-vessels, the blood flow is slow, the rapid and efficient acquisition can enable the signal change to be small, and the value a is separated from the value 0. The decorrelation of the value a can cause the contrast ratio of the blood vessel and the static tissue to be poor, and when the value a is slightly far away from the values 0 and 1, the value g can be further close to the values 1 and 0 by adopting the decorrelation function of the invention, as shown in figure 3, so that the contrast ratio between the blood vessel and the tissue is effectively improved, and the influence of various noises on imaging is reduced;
2) In order to embody that the vascular component is derived from structural information, the structural signals of the x-z sections of N B-scan at any y coordinate are acquired and expressed in a logarithmic form, and can be recorded as: i struct ＝log 10 (R 2 )；
3) To further isolate tissue background noise, a threshold is set for the decorrelated signal g, the value below the threshold signal is set to 0, and the value above the threshold signal is set to 1; the binarized intensity mask signal is denoted as I mask The method comprises the steps of carrying out a first treatment on the surface of the 4) For efficient characterization of angiographic image information, a product of three signals is used, which can be noted: i angio ＝I struct ×g×I mask 。
With respect to the curve of the conventional correlation function as shown in fig. 4, the signal in the blue dotted box in fig. 3 is more toward 0 than at the same position in fig. 4, and the signal in the green dotted box in fig. 4 is more toward 1 than at the same position in fig. 4. It can be seen that when there is a certain uncorrelated noise in the background signal, noise suppression can be performed by the correlation function of the present invention; meanwhile, a small amount of correlation signals exist in the blood flow signals, and the correlation function is effectively inhibited. Therefore, the contrast of the blood vessel imaging can be effectively improved based on the decorrelation function of the invention.
As shown in fig. 1, the method for imaging blood vessels based on optical coherence tomography of the present invention comprises the following specific steps:
s1, scanning a sample by using a spectrum domain OCT imaging acquisition system and acquiring interference spectrum signals point by point; s2, carrying out uniform sampling and inverse Fourier transform operation on interference spectrum signals by utilizing an OCT image reconstruction method to obtain axial depth reflectivity information of any point of a sample, and recording as a complex signal, wherein x, y and z are used for representing pixel positions, t represents repeated measurement times of 1,2, …, N and N are continuous measurement times, and R represents complex numbers;
s3, performing time domain decorrelation on structural signals of the X-Z sections of the N B-scan at any y-axis coordinate position by adopting a decorrelation function to obtain decorrelation signals;
s4, multiplying the structural signal, the decorrelation signal and the intensity mask signal to obtain a three-dimensional signal of angiography imaging, and drawing an angiography image representing the two-dimensional front surface by carrying out maximum projection along the depth direction in combination with the three-dimensional median filtering and Gaussian filtering image processing method.
The acquisition mode adopted in S1 is a B-M mode, and at the same y-axis position, the x-z sections of the B-scan are continuously and repeatedly scanned along the x-axis for at least more than 2 times, and in this embodiment, the number of times adopted is 5 times, so as to obtain structural signals of the x-z sections of the 5B-scan at the y-axis position, then, a position is moved along the y-axis, and the x-z sections of the B-scan are continuously and repeatedly scanned along the x-axis again, and the number of times is 5 until the scanning in the y-axis is completed, and the acquired interference spectrum signals are structural signals of the x-z sections of all the B-scan at the y-axis position, which can be recorded as a four-dimensional array S (x, y, λ, t), in this embodiment, x is 512, λ is 2048, and t takes values of 1,2,3,4,5.
In S2, the four-dimensional array S (x, y, λ, t) is converted from wavelength dimension data to wave number domain data, a new set of data sets S '(x, y, k, t) is obtained by uniformly sampling in the wave number domain through interpolation operation, and reflectivity information in the depth direction can be obtained by performing inverse fourier transform operation on the wave number dimension, and is denoted as R (x, y, z, t) =fft (S' (x, y, k, t)).
S3 for extraction of vascular componentThe tissue components are static information, the signal correlation is strong in multiple measurements, blood flows in blood vessels and simultaneously red blood cells move, the signal correlation is weak in multiple measurements, and for structural signals of the x-z sections of N B-scan at any y-axis coordinate position, the effective extraction of the blood vessel information can be realized by adopting the following decorrelation function:wherein->w (m) represents a depth-wise switching window of length 2l+1, in this embodiment l is 5, t is 1,2, …,5, R * Representing the complex conjugate of R. A three-dimensional array g (x, y, z) representing the decorrelated signal is thus obtained.
In S4, the intensity average is performed on the structural signals of the x-z sections of the 5B-scan at any y coordinate, and the structural signals are expressed in a logarithmic form and can be recorded as: i struct ＝log 10 (mean(|R| 2 4)) to obtain a new three-dimensional structure array I representing the structural signal struct (x,y,z)。
In order to further isolate tissue background noise, a threshold is set for the decorrelated signal g, the value below the threshold signal is set to 0, and the value above the threshold signal is set to 1; the binarized intensity mask signal is denoted as I mask (x,y,z)。
For efficient characterization of angiographic image information, a product of three signals is used, which can be noted as: i angio ＝I struct ×g×I mask The three-dimensional signal of the angiography imaging is a three-dimensional data set which can be expressed as I angio (x,y,z)。
For three-dimensional data set I angio (x, y, z) performing three-dimensional median filtered image processing, and three-dimensional Gaussian filtered image processing flow, further drawing an angiographic image representing a two-dimensional frontal surface by performing maximum projection along a depth direction of the optimized three-dimensional image information, wherein the depth range can be selected according to the vascular position, and the depth range is in the embodimentThe acquired pixel interval is 120 to 200, and the obtained blood vessel image is shown in fig. 6.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
While the foregoing is directed to embodiments of the present invention, other and further details of the invention may be had by the present invention, it should be understood that the foregoing description is merely illustrative of the present invention and that no limitations are intended to the scope of the invention, except insofar as modifications, equivalents, improvements or modifications are within the spirit and principles of the invention.
Claims (8)
1. A blood vessel imaging method based on optical coherence tomography is characterized in that: the method comprises the following operations: scanning a sample by using a spectral domain OCT imaging acquisition system and acquiring interference spectrum signals point by point;
performing uniform sampling and inverse Fourier transform operation on the interference spectrum signal by using an OCT image reconstruction method to obtain axial depth reflectivity information of any point of a sample which is a complex signal, and marking the axial depth reflectivity information as R (x, y, z, t), wherein x, y and z are used for representing pixel positions, t represents repeated measurement times of 1,2, …, N and N are continuous measurement times, and R represents a complex number;
for the structural signals of the x-z sections of the N B-scan at any y-axis coordinate position, performing time domain decorrelation by adopting a decorrelation function to obtain decorrelation signals;
the structural signal, the decorrelation signal and the intensity mask signal are multiplied to obtain a three-dimensional signal of angiography imaging, and an angiography image representing the two-dimensional front surface is drawn by performing maximum projection along the depth direction in combination with an image processing method of three-dimensional median filtering and Gaussian filtering.
2. A method of imaging blood vessels based on optical coherence tomography in accordance with claim 1, wherein: scanning a sample by using a spectrum domain OCT imaging acquisition system and acquiring interference spectrum signals point by point specifically comprises the following steps: repeated collection was performed on the same sample B-scan: the spectral domain OCT imaging system continuously and repeatedly scans the X-z section of the B-scan along the X-axis at the same Y-axis position, the repetition number is N, then the spectral domain OCT imaging system moves a position along the Y-axis, and continuously and repeatedly scans the X-z section of the B-scan along the X-axis again, the repetition number is N, until the scanning of the Y-axis is completed.
3. A method of imaging blood vessels based on optical coherence tomography in accordance with claim 1, wherein: the decorrelation function expression is:
wherein, in a depth window, normalized complex cross-correlation at arbitrary depth pixel positionsw (m) is a depth-direction switching window of length 2l+1, R * For complex conjugate of complex number R, t is the number of repeated measurements, z represents the position of the pixel of the x-z section of B-scan on the z axis, g is the decorrelation signal, l is the constant value, m is the independent variable, and the value is 2l+1.
4. A method of vessel imaging based on optical coherence tomography according to claim 3, wherein: the specific steps of multiplying the structural signal, the decorrelated signal and the intensity mask signal to obtain a three-dimensional signal for angiographic imaging include:
a. obtaining structural signals: obtaining any one ofThe structural signal of the x-z section of the N B-scan at one y-coordinate is intended and expressed in logarithmic form as: i struct ＝log 10 (|R| 2 ) Wherein R represents a complex number, I struct Is a structural signal;
b. making an intensity mask signal: setting a threshold value for the decorrelated signal g, setting a value lower than the threshold value to 0, setting a value higher than the threshold value to 1, and recording the binarized intensity mask signal as I mask ；
c. The product of the structural signal, the decorrelation signal and the intensity mask signal is used for representing the three-dimensional signal of angiography imaging, and the expression is as follows:
I angio ＝I struct ×g×I mask ；
wherein I is angio Three-dimensional signals imaged for angiography.
5. A vascular imaging system based on optical coherence tomography, characterized in that: the blood vessel imaging system comprises an OCT image acquisition system module, an OCT structure image reconstruction module, a blood vessel image analysis acquisition module and an image optimization processing module;
the OCT image acquisition system module is used for acquiring interference spectrum information of any point of a sample by using a spectrum domain OCT imaging mode through a point-by-point scanning imaging method;
the OCT structure image reconstruction module is used for carrying out homogenizing sampling and inverse Fourier transform operation on the interference spectrum signals obtained by the OCT image acquisition system module in a wave number domain to obtain axial depth reflectivity information of any point of a sample which is a complex signal;
the blood vessel image analysis and acquisition module is used for performing time domain decorrelation on the complex signals and extracting three-dimensional signals imaged by angiography;
the image optimization processing module is used for carrying out three-dimensional median filtering and Gaussian filtering optimization processing on three-dimensional signals of sample angiography imaging, and drawing angiography images representing the two-dimensional front face by carrying out maximum projection on the optimized three-dimensional signals along the depth direction.
6. A vascular imaging system based on optical coherence tomography as defined in claim 5, wherein: the OCT image acquisition system module adopts a B-M mode.
7. A vascular imaging system based on optical coherence tomography as defined in claim 5, wherein: the blood vessel image analysis and acquisition module adopts a decorrelation function to carry out time domain decorrelation on complex signals, and the expression of the decorrelation function is as follows:
wherein, in a depth window, normalized complex cross-correlation at arbitrary depth pixel positionsw (m) is a depth-direction switching window of length 2l+1, R * For complex conjugate of complex number R, t is the number of repeated measurements, z represents the position of the pixel of the x-z section of B-scan on the z axis, g is the decorrelation signal, l is the constant value, m is the independent variable, and the value is 2l+1.
8. A vascular imaging system based on optical coherence tomography as recited in claim 7, wherein: the three-dimensional signal expression of angiography imaging extracted by the vessel image analysis and acquisition module is as follows:
I angio ＝I struct ×g×I mask ；
wherein I is mask For intensity mask signal, I struct Is a structural signal, I angio Three-dimensional signals imaged for angiography.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310851997.0A CN116725492B (en) | 2023-07-11 | 2023-07-11 | Blood vessel imaging method and system based on optical coherence tomography |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310851997.0A CN116725492B (en) | 2023-07-11 | 2023-07-11 | Blood vessel imaging method and system based on optical coherence tomography |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116725492A true CN116725492A (en) | 2023-09-12 |
| CN116725492B CN116725492B (en) | 2023-12-12 |
Family
ID=87915139
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310851997.0A Active CN116725492B (en) | 2023-07-11 | 2023-07-11 | Blood vessel imaging method and system based on optical coherence tomography |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116725492B (en) |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070201033A1 (en) * | 2006-02-24 | 2007-08-30 | The General Hospital Corporation | Methods and systems for performing angle-resolved fourier-domain optical coherence tomography |
| CN102389290A (en) * | 2011-08-01 | 2012-03-28 | 温州医学院眼视光研究院 | Frequency-domain optical coherence tomography method and system |
| US20160307314A1 (en) * | 2015-04-15 | 2016-10-20 | Kabushiki Kaisha Topcon | Oct angiography calculation with optimized signal processing |
| US20160317020A1 (en) * | 2015-05-01 | 2016-11-03 | Oregon Health & Science University | Phase gradient optical coherence tomography angiography |
| CN106166058A (en) * | 2016-08-04 | 2016-11-30 | 温州医科大学 | One is applied to optical coherence tomography blood vessel imaging method and OCT system |
| US20170319060A1 (en) * | 2016-05-03 | 2017-11-09 | Oregon Health & Science University | Systems and methods to compensate for reflectance variation in oct angiography |
| CN107374583A (en) * | 2017-05-31 | 2017-11-24 | 执鼎医疗科技（杭州）有限公司 | One kind eliminates pseudo- image method and storage medium and imaging system in OCT blood vessel imagings |
| US10016137B1 (en) * | 2017-11-22 | 2018-07-10 | Hi Llc | System and method for simultaneously detecting phase modulated optical signals |
| WO2019075376A1 (en) * | 2017-10-13 | 2019-04-18 | The Research Foundation For The State University Of New York | Wavelength-division-multiplexing swept-source optical doppler tomography |
| CN109907731A (en) * | 2019-01-31 | 2019-06-21 | 浙江大学 | The three-dimensional flow angiographic method and system of optical coherence tomography based on feature space |
| CN113040763A (en) * | 2021-04-28 | 2021-06-29 | 浙江大学 | Blood glucose test method and device based on OCTA |
| CN113706567A (en) * | 2021-07-19 | 2021-11-26 | 浙江大学 | Blood flow imaging quantitative processing method and device combining blood vessel morphological characteristics |
| CN113712527A (en) * | 2021-07-19 | 2021-11-30 | 浙江大学 | Three-dimensional blood flow imaging method and system based on amplitude decorrelation |
| CN114209278A (en) * | 2021-12-14 | 2022-03-22 | 复旦大学 | Deep learning skin disease diagnosis system based on optical coherence tomography |
| CN114748032A (en) * | 2022-02-25 | 2022-07-15 | 天津市索维电子技术有限公司 | Motion noise compensation method based on OCT blood vessel imaging technology |
-
2023
- 2023-07-11 CN CN202310851997.0A patent/CN116725492B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070201033A1 (en) * | 2006-02-24 | 2007-08-30 | The General Hospital Corporation | Methods and systems for performing angle-resolved fourier-domain optical coherence tomography |
| CN102389290A (en) * | 2011-08-01 | 2012-03-28 | 温州医学院眼视光研究院 | Frequency-domain optical coherence tomography method and system |
| US20160307314A1 (en) * | 2015-04-15 | 2016-10-20 | Kabushiki Kaisha Topcon | Oct angiography calculation with optimized signal processing |
| US20160317020A1 (en) * | 2015-05-01 | 2016-11-03 | Oregon Health & Science University | Phase gradient optical coherence tomography angiography |
| US20170319060A1 (en) * | 2016-05-03 | 2017-11-09 | Oregon Health & Science University | Systems and methods to compensate for reflectance variation in oct angiography |
| CN106166058A (en) * | 2016-08-04 | 2016-11-30 | 温州医科大学 | One is applied to optical coherence tomography blood vessel imaging method and OCT system |
| CN107374583A (en) * | 2017-05-31 | 2017-11-24 | 执鼎医疗科技（杭州）有限公司 | One kind eliminates pseudo- image method and storage medium and imaging system in OCT blood vessel imagings |
| WO2019075376A1 (en) * | 2017-10-13 | 2019-04-18 | The Research Foundation For The State University Of New York | Wavelength-division-multiplexing swept-source optical doppler tomography |
| US10016137B1 (en) * | 2017-11-22 | 2018-07-10 | Hi Llc | System and method for simultaneously detecting phase modulated optical signals |
| CN109907731A (en) * | 2019-01-31 | 2019-06-21 | 浙江大学 | The three-dimensional flow angiographic method and system of optical coherence tomography based on feature space |
| CN113040763A (en) * | 2021-04-28 | 2021-06-29 | 浙江大学 | Blood glucose test method and device based on OCTA |
| CN113706567A (en) * | 2021-07-19 | 2021-11-26 | 浙江大学 | Blood flow imaging quantitative processing method and device combining blood vessel morphological characteristics |
| CN113712527A (en) * | 2021-07-19 | 2021-11-30 | 浙江大学 | Three-dimensional blood flow imaging method and system based on amplitude decorrelation |
| CN114209278A (en) * | 2021-12-14 | 2022-03-22 | 复旦大学 | Deep learning skin disease diagnosis system based on optical coherence tomography |
| CN114748032A (en) * | 2022-02-25 | 2022-07-15 | 天津市索维电子技术有限公司 | Motion noise compensation method based on OCT blood vessel imaging technology |
Non-Patent Citations (5)
| Title |
|---|
| KAUSIK BASAK等: "Automated detection of air embolism in OCT contrast imaging: Anisotropic diffusion and active contour based approach", 《2012 THIRD INTERNATIONAL CONFERENCE ON EMERGING APPLICATIONS OF INFORMATION TECHNOLOGY》 * |
| 左超等: "计算光学成像：何来，何处，何去，何从？", 《红外与激光工程》, vol. 51, no. 2, pages 158 - 341 * |
| 李明等: "基于三亚VHF雷达的场向不规则体观测研究:4.太阳活动低年夏季F区回波", 《地球物理学报》, vol. 57, no. 1, pages 1 - 9 * |
| 杨珊珊等: "光学相干层析功能成像及脑中风研究进展", 《中国激光》, vol. 47, no. 2, pages 195 - 206 * |
| 靖志成等: "光学相干层析成像的原理、应用与发展", 《重庆师范大学学报(自然科学版)》, vol. 38, no. 4, pages 107 - 120 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116725492B (en) | 2023-12-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109907731B (en) | Three-dimensional blood flow radiography method based on optical coherence tomography of feature space | |
| JP5969701B2 (en) | Imaging system and method for imaging an object | |
| US7859679B2 (en) | System, method and arrangement which can use spectral encoding heterodyne interferometry techniques for imaging | |
| Ralston et al. | Deconvolution methods for mitigation of transverse blurring in optical coherence tomography | |
| CN105559756A (en) | Microangiography method and system based on total space modulation spectrum segmentation angle combining | |
| CN108670239B (en) | Three-dimensional blood flow imaging method and system based on feature space | |
| CN107788950B (en) | Blood flow imaging method and system based on self-adaptive threshold segmentation | |
| CN105996999B (en) | Method and system for measuring sample depth resolution attenuation coefficient based on OCT | |
| Jain et al. | Full-field optical coherence tomography for the analysis of fresh unstained human lobectomy specimens | |
| US20160066798A1 (en) | Methods and Systems for Determining Hemodynamic Properties of a Tissue | |
| CN113331809B (en) | Method and device for imaging three-dimensional blood flow in cavity based on MEMS micro galvanometer | |
| CN110881947B (en) | Optical coherence tomography imaging method | |
| CN112294260B (en) | Magnetic compatible optical brain function imaging method and device | |
| WO2016023502A1 (en) | Phase-inverted sidelobe-annihilated optical coherence tomography | |
| CN104545872B (en) | Method and device for reconstructing three-dimensional micro blood flow distribution on basis of linearly dependent coefficients | |
| CN112136182A (en) | System and method for blood flow imaging based on Gabor optical coherence tomography | |
| Sathyanarayana et al. | Recovery of blood flow from undersampled photoacoustic microscopy data using sparse modeling | |
| CN113017593B (en) | Blood vessel tail artifact removing method and system based on blood flow signal intensity layered filtering | |
| CN111053531A (en) | Handheld oral angiography device and method based on sweep frequency optical coherence tomography | |
| Shintate et al. | High-speed optical resolution photoacoustic microscopy with MEMS scanner using a novel and simple distortion correction method | |
| CN111543971B (en) | Blood flow quantification method and system for time-space self-adaptive sample ensemble decorrelation operation | |
| CN109691978A (en) | Relevant optical scanning ophthalmoscope towards ocular blood flow fast imaging | |
| CN116725492B (en) | Blood vessel imaging method and system based on optical coherence tomography | |
| CN112535465A (en) | Three-dimensional blood flow velocity imaging method and device based on lamella light | |
| Wang et al. | Compressive‐sensing swept‐source optical coherence tomography angiography with reduced noise |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A vascular imaging method and system based on optical coherence tomography imaging Granted publication date: 20231212 Pledgee: China Construction Bank Corporation Nanjing Jiangbei new area branch Pledgor: Jiangsu Jinshi Chuanqi Technology Co.,Ltd. Registration number: Y2024980010778 |