An ultra-high frame rate endoscopic photoacoustic imaging system and imaging processing method

Abstract

This application relates to the field of endoscopic imaging technology, and in particular to an ultra-high frame rate endoscopic photoacoustic imaging system and imaging processing method. Based on the precise synchronous timing control of pulsed laser emission by the control unit, high-speed scanning of the high-speed scanning galvanometer, and acquisition of photoacoustic signals, the system performs three-dimensional SVD tissue suppression, interactive ROI extraction, light intensity consistency localization, independent component SVD filtering, and mode-based velocity correction on the acquired photoacoustic signals to obtain a dynamic spectrum containing the magnitude and direction of blood flow velocity. This achieves ultra-high frame rate photoacoustic endoscopic imaging within the endoscopic field of view, and further enables high frame rate blood flow vectorization measurement, which is suitable for dynamic monitoring and quantitative analysis of organ microcirculation blood flow.

Description

Technical Field

[0001] This application relates to the field of endoscopic imaging technology, and in particular to an ultra-high frame rate endoscopic photoacoustic imaging system and imaging processing method. Background Technology

[0002] Currently, early detection and accurate assessment of clinical cavity tumors (such as head and neck or digestive tract tumors) remain significant challenges. While existing imaging techniques such as CT and MRI have become routine tools for diagnosis and staging, CT has limited ability to differentiate between local inflammation and tumors, while MRI suffers from long imaging times, significant artifacts, and insensitivity to calcification and cortical bone, and is difficult to perform rapid hemodynamic monitoring. Traditional white light endoscopy, as the standard method for detecting cavity lesions, only provides superficial morphological information and lacks the ability to assess functional indicators such as deep tissue infiltration and blood perfusion.

[0003] Photoacoustic imaging, as an emerging non-invasive imaging technique, combines the high contrast of optical imaging with the greater tissue penetration depth of ultrasound imaging, providing both structural and functional information simultaneously. It is particularly suitable for detecting vascular networks and blood flow distribution. However, existing photoacoustic endoscopy systems are still limited in hemodynamic imaging by insufficient imaging frame rate, making it difficult to achieve real-time and accurate analysis of red blood cell movement at the microcirculation level.

[0004] Existing laser speckle blood flow imaging technology (such as the patent application number CN201711290393.4, "An Improved Laser Speckle Contrast Blood Flow Imaging Method") can achieve superficial blood flow monitoring, but its decorrelation algorithm cannot eliminate motion artifacts caused by respiration / heartbeat, resulting in a reduced signal-to-noise ratio in small blood vessels (see abnormal background brightness in nude mouse ear imaging results). Furthermore, this technology is based on the principle of surface optical scattering, and its imaging depth is limited, making it difficult to apply to deep tissue imaging inside cavity organs. Summary of the Invention

[0005] Therefore, it is necessary to provide an ultra-high frame rate endoscopic photoacoustic imaging system and imaging processing method to address the above problems.

[0006] In one embodiment, the present invention provides an ultra-high frame rate photoacoustic imaging system, including a control unit, a pulsed light source assembly, a first optical path transmission assembly, an endoscope imaging system, a data acquisition unit, and a processing unit. The control unit is connected to the pulsed light source assembly, the endoscope imaging system, and the data acquisition unit, and is used to generate and output synchronous timing pulses to synchronously control the pulsed light source assembly to emit pulsed laser light, drive the endoscope imaging system to perform photoacoustic imaging, and control the data acquisition unit to acquire imaging signals. The endoscope imaging system is applied to an endoscope device, which sequentially includes a second optical path transmission assembly, a high-speed scanning galvanometer, a third optical path transmission assembly, and a photoacoustic transducer. The pulsed laser light sequentially passes through the first and second optical path transmission assemblies to reach the high-speed scanning galvanometer for deflection scanning, and then is focused by the third optical path transmission assembly to reach the tissue under test, generating a photoacoustic signal on the tissue. The generated photoacoustic signal is received by the photoacoustic transducer located on the side wall of the endoscope device and converted into an electrical signal. The data acquisition unit acquires the electrical signal and sends it to the processing unit for analysis and processing.

[0007] In one embodiment, the first optical path transmission component includes an optical fiber coupler and a single-mode optical fiber; the second optical path transmission component includes an adjustable aspherical collimator, a first reflector, and a second reflector; and the third optical path transmission component includes a rod lens, a focusing lens, and a transparent acoustic mirror. The pulsed laser emitted by the pulsed light source component is coupled through the optical fiber coupler into the single-mode optical fiber and then into the endoscope device. After entering the endoscope device, the pulsed laser is collimated by the adjustable aspherical collimator and incident on the second reflector. It is then reflected by the first reflector to reach the surface of the high-speed scanning galvanometer. After being deflected by the galvanometer, the light path is extended by the rod lens and focused by the focusing lens to reach the tissue to be tested, generating a photoacoustic signal on the tissue. The generated photoacoustic signal is reflected by the transparent acoustic mirror and received by a photoacoustic transducer located on the side wall of the endoscope device, which converts it into an electrical signal.

[0008] In one embodiment, the endoscope device is an integrated photoacoustic endoscope probe, including a biocompatible metal housing, wherein the adjustable aspherical collimator, first reflector, second reflector, high-speed scanning galvanometer, rod lens, focusing lens, light-transmitting reflector and photoacoustic transducer are disposed within the metal housing.

[0009] In one embodiment, the present invention also provides an ultra-high frame rate photoacoustic imaging processing method, wherein the photoacoustic imaging processing method acquires photoacoustic signals based on the aforementioned ultra-high frame rate photoacoustic imaging system, and includes: S1, acquire photoacoustic and electrical signals, and reconstruct and generate the original photoacoustic endoscopic three-dimensional image sequence based on the acquired photoacoustic and electrical signals; S2, perform three-dimensional spatiotemporal singular value (SVD) decomposition on the generated original photoacoustic endoscopic three-dimensional image sequence to obtain the preprocessed photoacoustic endoscopic three-dimensional image sequence; S3, for the preprocessed photoacoustic endoscopic three-dimensional image sequence, extract the blood vessel ROI on the reference frame, cut out the corresponding three-dimensional image data region (ROI region), and calculate the displacement vector data by red blood cell particle displacement data of the three-dimensional image data sequence in the ROI region based on the consistency of pixel light intensity between adjacent frames. S4 performs independent component SVD filtering and anomaly correction based on the mode distribution of blood flow velocity amplitude on the displacement vector data to generate a denoised and corrected dynamic map of blood flow velocity vector.

[0010] In one embodiment, S2 includes: S21, the optical flow field of the original photoacoustic endoscopic three-dimensional image sequence is decomposed into x / y direction components, and a three-dimensional spatiotemporal matrix is ​​independently constructed for each component, and singular value decomposition (SVD) is performed. in, , Let be the spatiotemporal matrix to be decomposed; , It is a left singular vector matrix; , It is a singular value matrix; , It is a right singular vector matrix; S22, truncate and retain the first k principal singular components for signal reconstruction; in, , This is the new x- and y-direction displacement spacetime matrix obtained after SVD filtering, with noise removed; , The first k columns of the left singular vector matrix; , The first k singular values ​​of the singular value matrix; , Represents the first k columns of the right singular vector matrix; In one embodiment, in S3, based on the consistency of light intensity of corresponding pixels of the same red blood cell particle in two adjacent frames, the position with the best matching light intensity is searched pixel by pixel in the ROI region, and the displacement vector data of the particle is calculated.

[0011] In one embodiment, S4 includes: S41, Perform SVD filtering on the obtained displacement vector data for independent components; S42, within the ROI region, the abnormal displacement vectors deviating from the threshold are corrected based on the mode distribution of blood flow velocity amplitude to obtain the corrected displacement vector data; S43, calculate blood flow velocity based on the corrected displacement vector data, and generate a denoised and corrected dynamic map of blood flow velocity vector.

[0012] In one embodiment, S42 includes: S421, Calculate the velocity amplitude of all pixels within the ROI mask: ; S422, Statistical velocity amplitude histogram, determining the mode. ; S423, Filter outliers that deviate from the threshold: ; S424, correct the velocity amplitude at the outlier point to The interval is defined as η, where η is a preset allowable deviation scaling factor.

[0013] In one embodiment, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the photoacoustic imaging processing method described in any of the preceding claims.

[0014] In one embodiment, the present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of any of the photoacoustic imaging processing methods described above.

[0015] Compared to existing technologies, the photoacoustic imaging system and imaging processing method provided in this embodiment of the invention are based on FPGA for precise synchronous timing control of pulsed laser emission, high-speed scanning of high-speed scanning mirror, and acquisition of photoacoustic signals. The acquired photoacoustic signals are subjected to three-dimensional SVD tissue suppression, interactive ROI extraction, light intensity consistency localization, independent component SVD filtering, and mode-based velocity correction to obtain a dynamic spectrum containing blood flow velocity magnitude and velocity vector direction. This achieves ultra-high frame rate photoacoustic endoscopic imaging within the endoscopic field of view, and further enables high frame rate blood flow vectorization measurement, making it suitable for dynamic monitoring and quantitative analysis of organ microcirculation blood flow. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Furthermore, the accompanying drawings are not drawn to a 1:1 scale, and the relative dimensions of the various components are shown in the drawings only as examples and not necessarily to actual scale.

[0019] Figure 1 A schematic diagram of the structure of an ultra-high frame rate endoscopic photoacoustic imaging system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the endoscope device provided in an embodiment of the present invention; Figure 3 This is a schematic flowchart of the photoacoustic imaging processing method provided in an embodiment of the present invention.

[0020] Explanation of reference numerals in the attached figures: 1. Photoacoustic transducer; 2. Photoacoustic endoscope housing; 3. High-speed scanning galvanometer; 4. First reflecting mirror; 5. Second reflecting mirror; 6. Collimator; 7. Rod lens; 8. Focusing lens; 9. Transmitting and reflecting mirror. Detailed Implementation

[0021] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0022] See Figure 1 , Figure 1 A schematic diagram of an ultra-high frame rate photoacoustic imaging system according to an embodiment of this application is shown. The ultra-high frame rate photoacoustic imaging system provided in this embodiment includes a control unit, a pulsed light source assembly, a first optical path transmission assembly, an endoscope imaging system, a data acquisition unit, and a processing unit. The control unit is connected to the pulsed light source assembly, the endoscope imaging system, and the data acquisition unit, and is used to generate and output synchronous timing pulses to synchronously control the pulsed light source assembly to emit pulsed laser light, drive the endoscope imaging system to perform photoacoustic imaging, and control the data acquisition unit to perform photoacoustic signal acquisition. Specifically, see [link to documentation]. Figure 2The endoscopic imaging system is applied to an endoscopic device, including a second optical path transmission component, a high-speed scanning galvanometer, a third optical path transmission component, and a photoacoustic transducer 1. The pulsed laser sequentially passes through the first optical path transmission component and the second optical path transmission component to reach the high-speed scanning galvanometer 3. After being deflected by the galvanometer, the pulsed laser is focused by the third optical path transmission component and reaches the tissue to be tested, generating a photoacoustic signal on the tissue. The generated photoacoustic signal is received by the photoacoustic transducer 1 located on the side wall of the endoscopic device and converted into an electrical signal. The data acquisition unit acquires the electrical signal and sends it to the processing unit for analysis and processing.

[0023] Specifically, in this embodiment, the control unit can be implemented, for example, using a field-programmable gate array (FPGA). The FPGA outputs synchronous timing pulses to trigger the pulsed light source component to emit pulsed laser light, drive the high-speed scanning mirror to perform deflection scanning, and synchronously control the data acquisition unit to acquire signals, achieving sub-microsecond matching of excitation, scanning, and acquisition. Understandably, the pulsed light source component, the high-speed scanning mirror, the photoacoustic transducer, and the data acquisition card are hardware execution units. The pulsed light source component is preferably a 532 nm wavelength high-repetition-rate pulsed laser. The synchronous timing pulses output by the FPGA synchronously trigger and control the emission of the pulsed laser, the deflection scanning of the high-speed scanning mirror, and the signal acquisition of the data acquisition card, thereby achieving sub-microsecond synchronization of hardware actions. The high-speed scanning mirror is a two-dimensional scanning mirror based on microelectromechanical systems (MEMS) technology. The FPGA development board generates specific, high-precision synchronous timing pulses through custom logic. These synchronous timing pulses simultaneously and independently control the excitation of the high-repetition-rate pulsed laser, the deflection and scanning of the high-speed scanning galvanometer, and the opening of the acquisition window of the data acquisition card. This ensures that the pulsed laser excitation, beam scanning position, and signal acquisition are strictly matched in time, providing a basic timing guarantee for ultra-high frame rate imaging.

[0024] The first optical path transmission component includes an optical fiber coupler and a single-mode optical fiber, as further described in [link to relevant documentation]. Figure 2The second optical path transmission component includes an adjustable aspherical collimator 6, a first reflecting mirror 4, and a second reflecting mirror 5. The third optical path transmission component includes a rod lens 7, a focusing lens 8, and a light-transmitting acoustic mirror 9. Both the second and third optical path components are disposed within the endoscope device. Understandably, the endoscope device is an integrated photoacoustic endoscope probe, including a biocompatible metal housing. The adjustable aspherical collimator 6, the first reflecting mirror 4, the second reflecting mirror 5, the high-speed scanning galvanometer 3, the rod lens 7, the focusing lens 8, the light-transmitting acoustic mirror 9, and the photoacoustic transducer 1 are disposed within the metal housing. In this embodiment, the pulsed laser emitted by the pulsed light source assembly is coupled into the single-mode optical fiber via the fiber coupler and then enters the endoscope probe. After entering the endoscope probe, the pulsed laser is collimated by the adjustable aspherical collimator 6 and incident on the second reflecting mirror 5. It is then reflected by the first reflecting mirror 4 and reaches the surface of the high-speed scanning galvanometer 3. The scanning pulsed laser is then relayed by the rod lens 7 and the optical path is extended. After being focused by the focusing lens 8, it reaches the tissue to be tested and generates a photoacoustic signal on the tissue. The generated photoacoustic signal is reflected by the transparent acoustic mirror 9 and received by the photoacoustic transducer 1 located on the side wall of the endoscope device, and converted into an electrical signal. The transparent acoustic mirror is an ultrasonic reflecting mirror located at the end of the optical path (it is transparent to the pulsed laser wavelength and reflects the photoacoustic signal wavelength); the photoacoustic transducer is an ultrasonic transducer used to receive the photoacoustic signal; the data acquisition unit includes a signal amplifier, a bandpass filter, and a data acquisition card. The electrical signal received by the photoacoustic transducer 1 is amplified by the signal amplifier, filtered by the bandpass filter, and then acquired by the data acquisition card.

[0025] In this embodiment, when the pulsed laser is reflected by the first reflecting mirror 4 onto the surface of the high-speed scanning galvanometer 3, the FPGA drives the high-speed scanning galvanometer 3 to achieve beam deflection and scanning. Compared with traditional MEMS scanning galvanometer solutions, this embodiment significantly improves the scanning rate and light reflectivity by using a high-speed scanning galvanometer for deflection scanning, while maintaining a small size for the endoscope probe, thus ensuring the flexibility and imaging quality of the endoscope imaging system. Simultaneously, the signal amplifier can employ dual-stage amplification, with the first amplifier gain reaching 50 dB and the second amplifier gain reaching 46 dB, to ensure effective acquisition of weak photoacoustic signals. Furthermore, the overall diameter of the endoscope is as small as 2 mm, and the working distance can reach 20 cm, effectively meeting the needs of deep tissue imaging.

[0026] The high-speed scanning galvanometer 3 utilizes a micro-motor to rotate at high speed, performing torsional scanning motion under torque. Its response to the driving voltage exhibits highly linear characteristics. The FPGA controls the high-speed scanning galvanometer 3 to perform high-speed, precise two-dimensional scanning by generating high-precision, high-stability synchronous timing pulse signals. Its excellent linear response characteristics allow it to better adapt to the electronic control of the FPGA and the high-speed scanning mode. Understandably, the high scanning frequency of the high-speed scanning galvanometer (greater than 7000 Hz per second), combined with the high repetition rate of the pulsed laser (megahertz), achieves high-speed, precise coverage of the imaging points, further improving the imaging frame rate of the photoacoustic imaging system.

[0027] Moreover, in this embodiment, the processing unit runs on a computer, including a self-written C++ acquisition program and a GPU parallel data processing program based on the CUDA architecture. The GPU parallel data processing program based on the CUDA architecture fully utilizes the many-core multi-threaded parallel computing capabilities of NVIDIA GPUs to process up to 500 MB of spatial point data in real time. It accelerates the processing of massive photoacoustic signal data transmitted from the high-speed data acquisition card in real time, completes photoacoustic image reconstruction and maximum value projection calculation, and improves the data processing speed to meet the requirements of ultra-high frame rate imaging, thus overcoming the data processing bottleneck.

[0028] Furthermore, in one embodiment, the present invention also provides an ultra-high frame rate photoacoustic imaging processing method. This imaging processing method is based on the ultra-high frame rate photoacoustic imaging system provided above. In the photoacoustic imaging system, the control unit outputs a synchronous timing pulse signal to drive a pulsed laser to generate a 532 nm pulsed laser. The pulsed laser enters the endoscope device via a collimator. The laser beam is reflected by a high-speed scanning galvanometer and focused by a rod lens and a focusing lens before acting on the surface of the tissue to be tested. The generated photoacoustic signal is reflected by a light-transmitting acoustic mirror and received by a photoacoustic transducer on the sidewall of the endoscope, converted into an electrical signal, and transmitted to a signal amplifier via a coaxial cable. After amplification and filtering, the signal is acquired by a data acquisition card and sent to a computer. The computer processes the acquired signal and completes photoacoustic image reconstruction to obtain a photoacoustic image sequence containing dynamic information of red blood cell particles. Specifically, the photoacoustic imaging processing method includes: S1, acquire photoacoustic and electrical signals, and reconstruct and generate the original photoacoustic endoscopic three-dimensional image sequence based on the acquired photoacoustic and electrical signals; S2, perform three-dimensional spatiotemporal singular value (SVD) decomposition on the generated original photoacoustic endoscopic three-dimensional image sequence to obtain the preprocessed photoacoustic endoscopic three-dimensional image sequence; Specifically, step S2 includes: S21, construct a three-dimensional spatiotemporal matrix from the original photoacoustic endoscopic three-dimensional image sequence and perform singular value decomposition (SVD). Specifically, the optical flow field in the original photoacoustic endoscopic 3D image sequence is decomposed into x / y direction components, and a spatiotemporal matrix is ​​independently constructed for each component, followed by singular value decomposition: In the above formula, , Let be the spatiotemporal matrix to be decomposed; , It is a left singular vector matrix; , It is a singular value matrix; , It is a right singular vector matrix; S22, truncate and retain the first k principal singular components for signal reconstruction; in, , This is the new x- and y-direction displacement spacetime matrix obtained after SVD filtering, with noise removed; , The first k columns of the left singular vector matrix; , The first k singular values ​​of the singular value matrix; , Represents the first k columns of the right singular vector matrix; Understandably, performing three-dimensional spatial-temporal singular value decomposition (SVD) filtering on the generated raw photoacoustic endoscopic three-dimensional image sequence can effectively suppress high-energy but relatively static tissue background signals and significantly improve the signal-to-noise ratio of red blood cell dynamic signals. In another embodiment, after performing three-dimensional spatiotemporal singular value decomposition (SVD) on the generated raw photoacoustic endoscopic three-dimensional image sequence, each frame of the image is further subjected to bilateral filtering for noise reduction, linear normalization, and contrast-limited adaptive histogram equalization processing in sequence to further enhance red blood cell-related signals. Bilateral filtering for noise reduction, linear normalization, and contrast-limited adaptive histogram equalization processing can be implemented using existing technologies, and will not be elaborated on in this embodiment.

[0029] S3, for the preprocessed photoacoustic endoscopic three-dimensional image sequence, extract the blood vessel ROI on the reference frame, cut out the corresponding three-dimensional image data region (ROI region), and calculate the displacement vector data by red blood cell particle displacement data of the three-dimensional image data sequence in the ROI region based on the consistency of pixel light intensity between adjacent frames. Specifically, in step S3, based on the consistency of light intensity of corresponding pixels of the same red blood cell particle in two adjacent frames, the position with the best matching light intensity is searched pixel by pixel in the ROI region, and the displacement vector data of the particle is calculated.

[0030] In this scenario, assuming that the photoacoustic signal intensity of the target particle remains stable for a short period of time before and after its movement, the displacement vector data of the particle can be calculated by searching for the position with the best matching light intensity pixel by pixel within the ROI region.

[0031] S4, perform independent component SVD filtering and anomaly correction based on the mode distribution of blood flow velocity amplitude on the displacement vector data to generate a denoised and corrected dynamic map of blood flow velocity vector. Step S4 specifically includes: S41, Perform SVD filtering on the obtained displacement vector data for independent components; Specifically, step S41 is configured as follows: S411, flatten each component into a matrix on the ROI by spatial pixels; , , ,in, All are flattened by row. Matrix; u is the horizontal component; v is the vertical component; x is the row index; y is the column index; N is the number of pixels within the ROI; M is the spatial mask; R is the real number field; T is the total number of original temporal sampling points.

[0032] S412, truncate and reconstruct the flattened matrix after removing the mean; Specifically, first take the mean of the flattened matrix to obtain... , ; in, , The matrix after flattening and removing the mean; This is the spatial mode matrix (left singular vector); It is a singular value diagonal matrix; This is the time mode matrix (right singular vector). Further... , Perform truncation and reconstruction separately, selecting the first k truncation modes for reconstruction: , ,in , These are the truncated and reconstructed matrices, respectively.

[0033] S413, recover the mean of the reconstructed matrix: Map each row back to its corresponding pixels to obtain , .

[0034] in, This is the "global time baseline" that is subtracted from each column during the mean-reduction step; and To reconstruct and restore the mean three-dimensional spatiotemporal field.

[0035] S42, within the ROI region, the abnormal displacement vectors deviating from the threshold are corrected based on the mode distribution of blood flow velocity amplitude to obtain the corrected displacement vector data; Specifically, step S42 is configured as follows: S421, Calculate the velocity amplitude of all pixels within the ROI mask: ; S422, Statistical velocity amplitude histogram, determining the mode. ; S423, Filter outliers that deviate from the threshold: ,in, It is a relative deviation threshold used to determine whether a speed value is abnormal; S424, correct the velocity amplitude at the outlier point to The interval is defined as η, where η is a preset allowable deviation scaling factor.

[0036] S43, calculate blood flow velocity based on the corrected displacement vector data, and generate a denoised and corrected dynamic map of blood flow velocity vector.

[0037] Compared to existing technologies, the photoacoustic imaging system and imaging processing method provided in this embodiment of the invention are based on FPGA for precise synchronous timing control of pulsed laser emission, high-speed scanning of high-speed scanning mirror, and acquisition of photoacoustic signals. The acquired photoacoustic signals are subjected to three-dimensional SVD tissue suppression, interactive ROI extraction, light intensity consistency localization, independent component SVD filtering, and mode-based velocity correction to obtain a dynamic spectrum containing blood flow velocity magnitude and velocity vector direction. This achieves ultra-high frame rate photoacoustic endoscopic imaging within the endoscopic field of view, and further enables high frame rate blood flow vectorization measurement, making it suitable for dynamic monitoring and quantitative analysis of organ microcirculation blood flow.

[0038] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the photoacoustic imaging method provided in the above embodiments.

[0039] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the photoacoustic imaging method provided in the above embodiment.

[0040] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0041] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0042] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A photoacoustic imaging processing method with ultra-high frame rate, characterized in that, include: S1, acquire photoacoustic and electrical signals, and reconstruct and generate the original photoacoustic endoscopic three-dimensional image sequence based on the acquired photoacoustic and electrical signals; S2, decompose the optical flow field of the generated original photoacoustic endoscopic three-dimensional image sequence into x / y direction components, and independently construct each decomposed component into a three-dimensional spatiotemporal matrix to perform three-dimensional spatiotemporal singular value decomposition, and obtain the preprocessed photoacoustic endoscopic three-dimensional image sequence. S3, for the preprocessed photoacoustic endoscopic three-dimensional image sequence, extract the blood vessel ROI on the reference frame, cut out the corresponding three-dimensional image data area, and according to the consistency of light intensity of the corresponding pixel points of the same red blood cell particle in two adjacent frames, search for the position with the best matching light intensity pixel by pixel in the three-dimensional image data area, and calculate the displacement vector data of the particle. S4 performs independent component SVD filtering and anomaly correction based on the mode distribution of blood flow velocity amplitude on the displacement vector data to generate a denoised and corrected dynamic map of blood flow velocity vector.

2. The photoacoustic imaging processing method according to claim 1, characterized in that, S2 include: S21, decompose the optical flow field of the original photoacoustic endoscopic three-dimensional image sequence into x / y direction components, and independently construct a three-dimensional spatiotemporal matrix for each component, and perform singular value decomposition; in, , Let be the spatiotemporal matrix to be decomposed; , It is a left singular vector matrix; , It is a singular value matrix; , It is a right singular vector matrix; S22, truncate and retain the first k principal singular components for signal reconstruction; in, , This is the new x- and y-direction displacement spacetime matrix obtained after SVD filtering, with noise removed; , The first k columns of the left singular vector matrix; , The first k singular values ​​of the singular value matrix; , This represents the first k columns of the right singular vector matrix.

3. The photoacoustic imaging processing method according to claim 1, characterized in that, S4 include: S41, Perform SVD filtering on the obtained displacement vector data for independent components; S42, within the three-dimensional image data region, the abnormal displacement vector deviating from the threshold is corrected based on the mode distribution of the blood flow velocity amplitude to obtain the corrected displacement vector data; S43, calculate blood flow velocity based on the corrected displacement vector data, and generate a denoised and corrected dynamic map of blood flow velocity vector.

4. The photoacoustic imaging processing method according to claim 3, characterized in that, S42 includes: S421, Calculate the velocity magnitude of all pixels within the ROI mask: ; S422, Statistical velocity amplitude histogram, determining the mode. ; S423, Filter outliers that deviate from the threshold: ; S424, correct the velocity amplitude at the outlier point to The interval is defined as η, where η is a preset allowable deviation scaling factor.

5. An ultra-high frame rate endoscopic photoacoustic imaging system for generating the photoacoustic electrical signal according to any one of claims 1-4, characterized in that, The endoscopic photoacoustic imaging system includes a control unit, a pulsed light source assembly, a first optical path transmission assembly, an endoscopic imaging system, a data acquisition unit, and a processing unit. The control unit is connected to the pulsed light source assembly, the endoscopic imaging system, and the data acquisition unit, and is used to generate and output synchronous timing pulses to synchronously control the pulsed light source assembly to emit pulsed laser light, drive the endoscopic imaging system to perform photoacoustic imaging, and control the data acquisition unit to acquire imaging signals. The endoscopic imaging system is applied to an endoscopic device, including a second optical path transmission assembly, a high-speed scanning galvanometer, a third optical path transmission assembly, and a photoacoustic transducer. The pulsed laser light passes sequentially through the first optical path transmission assembly and the second optical path transmission assembly. After the component reaches the high-speed scanning galvanometer for deflection scanning, it is then focused by the third optical path transmission component and reaches the tissue to be tested, generating a photoacoustic signal on the tissue. The generated photoacoustic signal is received by a photoacoustic transducer located on the side wall of the endoscope device and converted into an electrical signal. The data acquisition unit acquires the electrical signal and sends it to the processing unit for analysis and processing. The high-speed scanning galvanometer is a MEMS two-dimensional scanning mirror. The control unit generates high-precision synchronous timing pulses and simultaneously and independently controls the excitation of the pulse light source component, the deflection scanning of the two-dimensional scanning mirror, and the signal acquisition of the data acquisition unit, ensuring that the pulse laser excitation, beam scanning, and signal acquisition are matched and synchronized in time.

6. The endoscopic photoacoustic imaging system according to claim 5, characterized in that, The first optical path transmission component includes an optical fiber coupler and a single-mode optical fiber; the second optical path transmission component includes an adjustable aspherical collimator, a first reflecting mirror, and a second reflecting mirror; the third optical path transmission component includes a rod lens, a focusing lens, and a transparent acoustic mirror. The pulsed laser emitted by the pulsed light source component is coupled into the single-mode optical fiber via the optical fiber coupler and then enters the endoscope device. After entering the endoscope device, the pulsed laser is collimated by the adjustable aspherical collimator and incident on the second reflecting mirror. It is then reflected by the first reflecting mirror to reach the surface of the high-speed scanning galvanometer. After being deflected by the galvanometer, the pulsed laser is relayed by the rod lens and its optical path is extended. It is then focused by the focusing lens to reach the tissue to be tested and generates a photoacoustic signal on the tissue. The generated photoacoustic signal is reflected by the transparent acoustic mirror and received by a photoacoustic transducer located on the side wall of the endoscope device, which converts it into an electrical signal.

7. The endoscopic photoacoustic imaging system according to claim 6, characterized in that, The endoscope device is an integrated photoacoustic endoscope probe, including a biocompatible metal housing. The adjustable aspherical collimator, first reflector, second reflector, high-speed scanning galvanometer, rod lens, focusing lens, light-transmitting reflector, and photoacoustic transducer are all housed within the metal housing.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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