A method and system for blood vessel imaging based on normalized time-varying intensity sequence similarity

Abstract

The application relates to a blood vessel imaging method based on normalized time-varying intensity sequence similarity. The blood vessel imaging method obtains two interference spectrum signals through twice data acquisition of the same data acquisition point of a sample, sequentially carries out Fourier transform, amplitude taking, direct current removing and normalization on the two interference spectrum signals to obtain two normalized time-varying intensity sequences, carries out cross-correlation function operation on the two normalized time-varying intensity sequences to distinguish a blood vessel region and a tissue region, and further obtains a contrast image of the blood vessel region. The method can remove body motion artifacts without external additional hardware and / or software, has self-sufficiency against body motion artifacts, can reduce the complexity and cost of an OCT system, and improves the efficiency of sample data processing.

Description

Technical Field

[0001] This invention relates to the fields of optical detection and biomedical engineering, and in particular to a vascular imaging method and system based on normalized time-varying intensity sequence similarity. Background Technology

[0002] Optical coherence tomography (OCT) has significant applications in the biomedical field. Its advantages, including being label-free, non-invasive, non-contact, high imaging resolution, and high detection sensitivity, have led to its widespread use in clinical medicine. OCT technology primarily relies on detecting changes in backscattered light intensity caused by the optical inhomogeneities of biological samples to obtain reflectivity information within the sample, thereby reconstructing a tomographic image of the sample's cross-sectional structure.

[0003] Optical coherence tomography (OCTA) for angiography utilizes the characteristic that the movement of red blood cells in blood vessels causes changes in the intensity of backscattered light to extract vascular images from static tissue. This process requires repeated A-scans or B-scans at the same location to distinguish between dynamic and static signals. During data acquisition, micro-movements of the sample and the machine are unavoidable, leading to pixel mismatches in each repeated scan. Existing OCTA technologies, such as OMAG, speckle variance OCTA, and Doppler OCTA, primarily utilize the signal difference between each scan to detect blood flow. Therefore, when OCTA technology is applied to these mismatched repeated scans, it may produce a large number of motion artifacts.

[0004] Furthermore, the OCTA techniques, such as OMAG and speckle variance OCTA, are highly susceptible to the influence of high-reflectivity areas on the obtained images because the OCTA signals provided by their algorithms are not only related to the degree of signal variation but also affected by the local signal intensity.

[0005] On the other hand, because the aforementioned techniques include a normalization process when calculating the correlation coefficient, correlation / decorrelation-based OCTA will not erroneously detect blood flow due to the presence of highly reflective areas. However, the effectiveness of correlation / decorrelation-based OCTA still relies on the assumption that static tissue signals remain constant over time, and minute movements of the sample and acquisition system can still produce body motion artifacts. Therefore, some hardware- or software-based supplementary techniques have been developed to combine with OCTA to remove the effects of body motion on images, but this increases the complexity and cost of the OCT system or affects data processing efficiency, thus limiting the further application of OCTA. In summary, all current OCTA techniques rely on supplementary methods to remove body motion artifacts and lack self-sufficiency in resisting body motion artifacts. Summary of the Invention

[0006] Based on this, the purpose of the present invention is to provide a vascular imaging method based on normalized time-varying intensity sequence similarity, which can remove body motion artifacts without the need for external additional hardware and / or software and has self-sufficient ability to resist body motion artifacts.

[0007] The technical solution adopted in this invention is as follows.

[0008] A vascular imaging method based on normalized time-varying intensity sequence similarity includes the following steps:

[0009] S10 performs two data acquisitions at the same data acquisition point of the sample to obtain the first interference spectrum signal and the second interference spectrum signal. The data acquisition method is to use the M-scan method to perform an A-scan with a set number of scans.

[0010] S20 performs Fourier transform on the first interference spectral signal and the second interference spectral signal respectively and takes the amplitude to obtain the first original time-varying intensity sequence and the second original time-varying intensity sequence; and calculates the mean of the two original time-varying intensity sequences respectively to obtain the first average original time-varying intensity sequence and the second average original time-varying intensity sequence.

[0011] S30 subtracts the average original time-varying intensity sequence from each original time-varying intensity sequence to obtain the first time-varying intensity sequence and the second time-varying intensity sequence;

[0012] S40 normalizes the first time-varying intensity sequence and the second time-varying intensity sequence respectively to obtain the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence;

[0013] S50 performs cross-correlation function calculation on the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence, extracts the region corresponding to the maximum value of the cross-correlation function as the vascular region, and generates angiography image based on the extracted vascular region.

[0014] Compared to existing technologies, the vascular imaging method of this invention obtains two interference spectral signals by acquiring data twice at the same data acquisition point of the sample. The two interference spectral signals are then subjected to Fourier transform, amplitude calculation, DC term removal, and normalization to obtain two normalized time-varying intensity sequences. A cross-correlation function is then performed on the two normalized time-varying intensity sequences to distinguish between vascular and tissue regions, thereby obtaining an angiographic image of the vascular region. This method removes motion artifacts without requiring external hardware and / or software, possesses self-sufficiency in resisting motion artifacts, reduces the complexity and cost of OCT systems, and improves the efficiency of sample data processing.

[0015] Furthermore, the first interference spectral signal I1(k,t1) in step S10 satisfies:

[0016]

[0017] The second interference spectrum signal I2(k,t2) satisfies:

[0018]

[0019] Where S(k) is the power spectrum of the light source, k is the wavenumber, n is the refractive index of the sample, and R s (z,t) represents the power reflectivity of the sample at depth z at time t, Rr represents the power reflectivity of the reference arm, and φ(z) represents the phase signal of the OCT. r z is the distance from the fiber coupler to the mirror. s This represents the depth distance from the fiber coupler to the sample.

[0020] Further, in step S20, the first original time-varying intensity sequence I1(z,t) 1i )satisfy;

[0021] I1(z,t 1i )=|FT k→z [I1(k,t 1i )]|, i = 1, 2, 3, ..., N;

[0022] The second original time-varying intensity sequence I2(z,t) 2i )satisfy:

[0023] I2(z,t 2i )=|FT k→z [I2(k,t 2i )]|, i = 1, 2, 3, ..., N;

[0024] Where k is the wavenumber, z is the sample depth, FT is the Fourier transform function, and t i Let t be the time sequence of A scans, N be the number of A scans, and i be the time sequence of A scans.

[0025] Further, in step S30, the first time-varying intensity sequence S1(z,t) 1i )satisfy:

[0026]

[0027] The second time-varying intensity sequence S2(z,t) 2i )satisfy:

[0028]

[0029] Where z is the depth of the sample, t i Let t be the time sequence of A scans, N be the number of A scans, and i be the time sequence of A scans.

[0030] Further, in step S40, the first normalized time-varying intensity sequence H1(z,t) 1i )satisfy:

[0031]

[0032] The second normalized time-varying intensity sequence H2(z,t) 2i )satisfy:

[0033]

[0034] Where z is the depth of the sample, t i Let t be the time sequence of A scans, N be the number of A scans, and i be the time sequence of A scans.

[0035] Further, step S50 uses the following cross-correlation function to calculate the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence:

[0036]

[0037] Where τ is the delay time, representing the time position where the two normalized time-varying intensity sequences are most similar, and is the position where the cross-correlation function has its maximum value.

[0038] Meanwhile, a vascular imaging system is provided, including a light source, an optical fiber coupler, a reference arm, a sample arm, a spectrometer, and a processor. The light emitted by the light source is split into reference light and sample light by the optical fiber coupler. The reference light is reflected by the reference arm, and the sample light is reflected by the sample arm and then enters the optical fiber coupler to form interference light. The spectrometer converts the received interference light into an interference spectral signal and transmits it to the processor. The processor executes the steps of the vascular imaging method based on normalized time-varying intensity sequence similarity as described in any of the above claims to process the received interference spectral signal.

[0039] To better understand and implement this invention, the following detailed description is provided in conjunction with the accompanying drawings. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the structure of a vascular imaging system according to an embodiment of the present invention;

[0041] Figure 2 This is a flowchart illustrating a vascular imaging method based on normalized time-varying intensity sequence similarity according to an embodiment of the present invention.

[0042] Figure 3 Three-dimensional microvascular projection images using different imaging methods, among which, Figure 3 (a) is a 3D blood vessel projection image using the OMAG method without image registration. Figure 3(b) is a 3D blood vessel projection image using the OMAG method with image registration. Figure 3 (c) is a three-dimensional vascular projection image of normalized time-varying sequence similarity angiography;

[0043] Figure 4 for Figure 3 A cross-sectional view, in which, Figure 4 (a) is a cross-sectional view of the structure at the same position (white dashed line) in one embodiment of the present invention. Figure 4 (b) A two-dimensional cross-sectional image of a blood vessel using the OMAG method with image registration. Figure 4 (c) is a two-dimensional cross-sectional view of blood vessels without using the OMAG method for image registration. Figure 4 (d) is a two-dimensional cross-sectional view of blood vessels from normalized time-varying sequence similarity angiography. Detailed Implementation

[0044] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings of the embodiments of the present invention.

[0045] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that, unless otherwise stated, “a plurality” means two or more; and the term “and / or” as used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0046] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only for distinction and not to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0047] To address the problem that existing OCTA technology relies on additional hardware or software techniques to remove motion artifacts and lacks the ability of OCTA technology itself to resist motion artifacts, this invention provides a vascular imaging method based on normalized time-varying intensity sequence similarity, and proposes a vascular imaging system based on this method for non-invasive observation of living microvessels, monitoring living conditions, evaluating the therapeutic effects of living patients, and applying it to preventive healthcare.

[0048] For specific implementation details, please refer to [link / reference]. Figure 1The vascular imaging system proposed in this invention includes a light source 1, an optical fiber coupler 2, a reference arm 3, a sample arm 4, a spectrometer 5, and a processor 6. Light emitted from the light source 1 is split into reference light and sample light by the optical fiber coupler 2. The reference light is reflected by the reference arm 3, and the sample light is reflected by the sample arm 4 before entering the optical fiber coupler 2 to form interference light. The spectrometer 5 converts the received interference light into interference spectral signals, which are then transmitted to the processor 6 for processing to generate a vascular image.

[0049] The light source 1 is an SLED broadband light source used to generate a low-coherence beam with a center wavelength of 1310nm and a bandwidth of 50nm.

[0050] The fiber coupler 2 is a 2×2 fiber coupler used to split the low-correlation beam generated by the light source into reference light and sample light in a 50:50 ratio. The reference light is output to the reference arm 3 and the sample light is output to the sample arm 4. It also receives the reference reflected light reflected by the reference arm 3 and the sample reflected light reflected or back-reflected by the sample arm 4, and performs interference processing on the received reference reflected light and sample reflected light, and transmits the interference light to the spectrometer 5.

[0051] The reference arm 3 includes a first transmission collimating mirror 31 and a plane mirror 32. The reference light is collimated by the first transmission collimating mirror 31 and reflected by the plane mirror 32 to form a reflected reference light; the reflected reference light is then transmitted to the fiber coupler 2 after passing through the first transmission collimating mirror 31.

[0052] The sample arm 4 includes a second transmission collimating lens 41, a two-dimensional scanning galvanometer 42, a condenser lens 43, and a sample stage 44. The two-dimensional scanning galvanometer 42 is used to control the data acquisition position. The sample light is collimated sequentially by the second transmission collimating lens 41, adjusted by the two-dimensional scanning galvanometer 42, focused by the condenser lens 43, and projected onto the sample placed on the sample stage 44. After reflection, the reflected light is formed. The reflected light is then transmitted to the fiber optic coupler 2 after passing through the condenser lens 43, the two-dimensional scanning galvanometer 42, and the second transmission collimating lens 41. The sample placed on the sample stage 44 can be a capillary glass tube containing a scattering agent, etc., and the sample can be fixed with the aid of tape or mechanical parts.

[0053] The spectrometer 5 includes a grating 51 and a linear CCD 52. The grating 51 expands the received interference light according to the wavelength, and the linear CCD 52 samples the expanded light beam to form an interference spectrum that is transmitted to the processor 6. The linear CCD 52 has 1024 pixels and a sampling rate of 46.816 kHz.

[0054] The processor 6 is used to process the received interference spectrum to form a two-dimensional or three-dimensional image of the sample.

[0055] Please see Figure 2The processor 6 of the present invention performs the following steps to generate a blood vessel image.

[0056] S10 performs two data acquisitions at the same data acquisition point of the sample to obtain the first interference spectrum signal and the second interference spectrum signal. The data acquisition method is to use the M-scan mode to perform an A-scan with a set number of scans.

[0057] Specifically, at time t, the interference spectrum signal acquired by the linear CCD array can be expressed as:

[0058]

[0059] Where S(k) is the power spectrum of the light source, k is the wavenumber, n is the refractive index of the sample, and R s (z,t) represents the power reflectivity of the sample at depth z at time t, Rr represents the power reflectivity of the reference arm, and φ(z) represents the phase signal of the OCT. r z is the distance from the fiber coupler to the mirror. s This represents the depth distance from the fiber coupler to the sample.

[0060] Therefore, the first interference spectral signal I1(k,t1) satisfies:

[0061]

[0062] The second interference spectrum signal I2(k,t2) satisfies:

[0063]

[0064] The number of scans is set to 200-300 times, and in this embodiment, the number of scans is set to 250 times.

[0065] S20 performs Fourier transform on the first interference spectral signal and the second interference spectral signal respectively and takes the amplitude to obtain the first original time-varying intensity sequence and the second original time-varying intensity sequence; and calculates the mean of the two original time-varying intensity sequences respectively to obtain the first average original time-varying intensity sequence and the second average original time-varying intensity sequence.

[0066] Specifically, to obtain the interference light intensity signal I(z,t) along the depth direction, a Fourier transform is performed on I(k,t) along the k direction, and the amplitude is taken. Its expression is:

[0067] I(z,t)=|FT k→z [I(k,t)]|.

[0068] Therefore, the first original time-varying intensity sequence I1(z,t) 1i )satisfy;

[0069] I1(z,t1i )=|FT k→z [I1(k,t 1i )]|, i = 1, 2, 3, ..., N;

[0070] The mean of its first average original time-varying intensity sequence for:

[0071]

[0072] Where N is the number of scans of A, and i is the time sequence of scans of A.

[0073] The second original time-varying intensity sequence I2(z,t) 2i )satisfy:

[0074] I2(z,t 2i )=|FT k→z [I2(k,t 2i )]|, i = 1, 2, 3, ..., N;

[0075] The mean of the second average original time-varying intensity sequence for:

[0076]

[0077] Where k is the wavenumber, z is the sample depth, FT is the Fourier transform function, and t i Let N be the time sequence of A scan at time t, N be the number of A scans, and i be the time sequence of A scans.

[0078] S30 subtracts the average original time-varying intensity sequence from each original time-varying intensity sequence to obtain the first time-varying intensity sequence and the second time-varying intensity sequence.

[0079] The first time-varying intensity sequence S1(z,t) 1i )satisfy:

[0080]

[0081] The second time-varying intensity sequence S2(z,t) 2i )satisfy:

[0082]

[0083] Where z is the depth of the sample, t i Let t represent the time sequence of A scans, and N represent the number of scans of A.

[0084] Since the original time-varying intensity sequence of the tissue region consists of noise and DC term, and the normalized time-varying intensity sequence of the vascular region consists of periodic signal and DC term, the similarity between DC terms (maximum value of cross-correlation function) is much greater than that of other signals. Therefore, before normalizing the two original time-varying intensity sequences, it is necessary to subtract their respective average original time-varying intensity sequences to eliminate the influence of DC term in the time-varying sequence signal.

[0085] S40 normalizes the first time-varying intensity sequence and the second time-varying intensity sequence respectively to obtain the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence.

[0086] Specifically, the first time-varying intensity sequence and the second time-varying intensity sequence are normalized in the following way, so that both the first time-varying intensity sequence and the second time-varying intensity sequence are normalized to between -1 and 1.

[0087] The first normalized time-varying intensity sequence H1(z,t) 1i )satisfy:

[0088]

[0089] The second normalized time-varying intensity sequence H2(z,t) 2i )satisfy:

[0090]

[0091] Where z is the depth of the sample, t i Let t represent the time sequence of A scans, and N represent the number of scans of A.

[0092] This operation better highlights the periodicity of two time-varying intensity sequences at the same data acquisition point in the vascular region, and the disorder of two normalized time-varying intensity sequences at the same data acquisition point in the tissue region. Normalizing the intensity of the two time-varying sequences ensures that, in the presence of body motion, such as system or sample jitter, a single signal change will not affect the periodicity of the normalized time-varying intensity sequence in the vascular region, and will enhance the disorder of the normalized time-varying intensity sequence in the tissue region, thus avoiding the influence of body motion artifacts.

[0093] S50 performs cross-correlation function calculation on the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence, extracts the region corresponding to the maximum value of the cross-correlation function as the vascular region, and generates angiography image based on the extracted vascular region.

[0094] Specifically, the cross-correlation function is used to calculate the similarity between the two normalized time-varying intensity sequences:

[0095]

[0096] Where τ is the delay time, representing the time position where the two normalized time-varying intensity sequences are most similar, and is the position where the cross-correlation function has its maximum value.

[0097] In vascular regions, two normalized time-varying intensity sequences show higher similarity, corresponding to the maximum value of the cross-correlation function. Therefore, the maximum value of the cross-correlation function is used to distinguish blood vessels from static tissue, thereby obtaining vascular images.

[0098] Please see Figure 3 and Figure 4 Compared to existing technologies, this invention obtains two interference spectral signals by acquiring data twice at the same data acquisition point of the sample. Then, it sequentially performs Fourier transform, amplitude calculation, DC term removal, and normalization on the two interference spectral signals to obtain two normalized time-varying intensity sequences. Finally, it performs cross-correlation function calculation on the two normalized time-varying intensity sequences to distinguish between vascular regions and tissue regions, thereby obtaining an angiographic image of the vascular region. This method removes motion artifacts without the need for external hardware and / or software, has self-sufficient ability to resist motion artifacts, reduces the complexity and cost of OCT systems, and improves the efficiency of sample data processing.

[0099] Based on the same inventive concept, this application also provides a computer-readable storage medium corresponding to the aforementioned embodiment of a vascular imaging method based on normalized time-varying intensity sequence similarity. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the vascular imaging method based on normalized time-varying intensity sequence similarity described in any of the above embodiments.

[0100] This application may take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information may be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0101] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and the present invention also intends to include these modifications and variations.

Claims

1. A vascular imaging method based on normalized time-varying intensity sequence similarity, characterized in that, Includes the following steps: S10 performs two data acquisitions at the same data acquisition point of the sample to obtain the first interference spectrum signal and the second interference spectrum signal. The data acquisition method is to use the M-scan method to perform an A-scan with a set number of scans. S20 performs Fourier transform on the first interference spectral signal and the second interference spectral signal respectively and takes the amplitude to obtain the first original time-varying intensity sequence and the second original time-varying intensity sequence; and calculates the mean of the two original time-varying intensity sequences respectively to obtain the first average original time-varying intensity sequence and the second average original time-varying intensity sequence. S30 subtracts the average original time-varying intensity sequence from each original time-varying intensity sequence to obtain the first time-varying intensity sequence and the second time-varying intensity sequence; S40 normalizes the first time-varying intensity sequence and the second time-varying intensity sequence respectively to obtain the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence; S50 performs cross-correlation function calculation on the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence, extracts the region corresponding to the maximum value of the cross-correlation function as the vascular region, and generates angiography image based on the extracted vascular region.

2. The vascular imaging method according to claim 1, characterized in that, The first interference spectral signal I1(k,t1) in step S10 satisfies: The second interference spectrum signal I2(k,t2) satisfies: Where S(k) is the power spectrum of the light source, k is the wavenumber, n is the refractive index of the sample, and R s (z,t) represents the power reflectivity of the sample at depth z at time t, R r Let z be the power reflectivity of the reference arm, φ(z) be the phase signal of the OCT, and z be the power reflectivity of the reference arm. r z is the distance from the fiber coupler to the mirror. s This represents the depth distance from the fiber coupler to the sample.

3. The vascular imaging method according to claim 2, characterized in that, The first original time-varying intensity sequence I1(z,t) in step S20 1i )satisfy; I1(z,t 1i )=|FT k→z [I1(k,t 1i )]|,i=1,2,3,...,N; The second original time-varying intensity sequence I2(z,t) 2i )satisfy: I2(z,t 2i )=|FT k→z [I2(k,t 2i )]|,i=1,2,3,...,N; Where k is the wavenumber, z is the sample depth, FT is the Fourier transform function, and t i Let t be the time sequence of A scans, N be the number of A scans, and i be the time sequence of A scans.

4. The vascular imaging method according to claim 3, characterized in that, The first time-varying intensity sequence S1(z,t) in step S30 1i )satisfy: The second time-varying intensity sequence S2(z,t) 2i )satisfy: Where z is the depth of the sample, t i Let t be the time sequence of A scans, N be the number of A scans, and i be the time sequence of A scans.

5. The vascular imaging method according to claim 4, characterized in that, The first normalized time-varying intensity sequence H1(z,t) in step S40 1i )satisfy: The second normalized time-varying intensity sequence H2(z,t) 2i )satisfy: Where z is the depth of the sample, t i Let t be the time sequence of A scans, N be the number of A scans, and i be the time sequence of A scans.

6. The vascular imaging method according to claim 5, characterized in that, Step S50 uses the following cross-correlation function to calculate the first normalized time-varying intensity sequence and the second normalized time-varying intensity sequence: Where τ is the delay time, representing the time position where the two normalized time-varying intensity sequences are most similar, and is the position where the cross-correlation function has its maximum value.

7. The vascular imaging method according to any one of claims 1-6, characterized in that, The number of scans in step S10 is set to 200-300.

8. A vascular imaging system, comprising a light source, an optical fiber coupler, a reference arm, a sample arm, a spectrometer, and a processor, wherein light emitted from the light source is split into reference light and sample light by the optical fiber coupler; the reference light is reflected by the reference arm, and the sample light is reflected by the sample arm before entering the optical fiber coupler to form interference light; the spectrometer converts the received interference light into an interference spectral signal and transmits it to the processor, characterized in that, The processor performs the steps of the vascular imaging method based on normalized time-varying intensity sequence similarity as described in any one of claims 1-7 to process the received interference spectral signal.

9. The vascular imaging system according to claim 8, characterized in that, The light source is an SLED broadband light source, used to generate a low-coherence beam with a center wavelength of 1310nm and a bandwidth of 50nm.

10. The vascular imaging system according to claim 9, characterized in that, The spectrometer includes a grating and a linear CCD. The grating expands the received interference light according to the wavelength, and the linear CCD samples the expanded light beam to form an interference spectrum that is transmitted to the processor. The linear CCD has 1024 pixels and a sampling rate of 46.816 kHz.

Images