Diffusion speckle-based blood flow quantification system and detection method

Abstract

Provided is a blood flow quantitative detection system based on diffusion speckle, comprising: a laser for emitting measurement laser; an optical fiber probe for integrating a multimode light source optical fiber and a plurality of detection optical fibers, the light source optical fiber being connected to the laser for vertically projecting the measurement laser to the surface of a to-be-detected object; the plurality of detection optical fibers being capable of forming different source-detection distances with the light source optical fiber for collecting diffusion speckle signals at different depths after the measurement laser is vertically projected to the to-be-detected object; a camera unit for receiving the diffusion speckle signals collected by the detection optical fibers at different exposure times; an analog signal output module for outputting analog signals to the laser to adjust the intensity of the measurement laser, preventing the camera unit from being saturated when the exposure time is changed; and a computer for controlling the analog signal output module to output the analog signals and controlling the exposure time of the camera unit, and processing the received diffusion speckle signals to obtain blood flow quantitative information.

Description

Technical Field

[0001] This disclosure relates to the field of precision instrument technology, and in particular to a blood flow quantitative detection system and method based on diffuse speckle. Background Technology

[0002] Various types of blood vessels are distributed throughout the tissues of an organism, serving as channels for blood flow. Blood flow transports the oxygen inhaled and various nutrients absorbed by the organism to all parts of the body, and is closely related to the body's metabolism. However, because various types of blood vessels are distributed at different depths in the tissues of an organism, the technology for detecting blood flow in blood vessels at different depths still needs to be improved. Summary of the Invention

[0003] (I) Technical Solution

[0004] One aspect of this disclosure provides a blood flow quantitative detection system based on speckle pattern, comprising: a laser for emitting a measurement laser; an optical fiber probe for integrating a multimode source fiber and multiple probe fibers, wherein the source fiber is connected to the laser for vertically projecting the measurement laser onto the surface of a test object; the multiple probe fibers are capable of forming different source-detector distances with the source fiber to collect speckle signals at different depths obtained after the measurement laser is vertically projected onto the test object; a camera unit coupled to the probe fibers in the optical fiber probe for receiving speckle signals collected by the probe fibers at different exposure times; an analog signal output module connected to the laser for outputting an analog signal to the laser to adjust the measurement laser intensity and prevent saturation of the camera unit when the exposure time changes; and a computer connected to the analog signal output module and the camera unit respectively for controlling the analog signal output module to output an analog signal and controlling the exposure time of the camera unit, and processing the received speckle signals to obtain blood flow quantitative information.

[0005] According to an embodiment of this disclosure, the laser is a semiconductor laser, the center wavelength of the emitted measurement laser is 785 nm, the coherence length exceeds 30 m, and the maximum output power is 50 mW.

[0006] According to an embodiment of this disclosure, the fiber optic probe integrates one light source fiber and at least three probe fibers. The light source fiber and the probe fibers in the fiber optic probe are arranged in parallel and on the same plane. The at least three probe fibers maintain different set distances from the light source fiber to form different source-detection distances.

[0007] According to an embodiment of this disclosure, the camera unit includes a CCD camera with a resolution of 1920*1200, a bit depth of 12 bits, and a frame rate of 300fps. The exposure time, photosensitive area, bit depth, and frame rate of the CCD camera are all adjustable.

[0008] According to the embodiments of this disclosure, a 50*50 pixel area in the horizontal direction of the center of the probe fiber projection is selected as the region of interest. When the exposure time of the camera unit and the source-probe distance change, the average pixel value in the region of interest is kept between 75 and 95, and the maximum value does not exceed 255, so as to maintain the speckle signal strength.

[0009] According to embodiments of this disclosure, the exposure time setting range of the CCD camera is set to 0.02-30ms, including multiple exposure time setting values. The corrected spatial speckle contrast K(T) for each exposure time setting value is calculated and saved.

[0010] K(T)=σ s (T) / ;

[0011] Where σ s (T) is the standard deviation of pixels in the region of interest at exposure time T. It is the average value of pixels within the region of interest.

[0012] According to embodiments of this disclosure, spatial speckle contrast is denoised and motion artifacts are eliminated by computer. Then, multi-exposure data curve fitting is performed based on a multi-exposure speckle model and a curve fitting model to extract quantitative blood flow information.

[0013] According to embodiments of this disclosure, the multi-exposure speckle model is represented as follows:

[0014]

[0015] Where K is the spatial speckle contrast, T is the camera exposure time, and x is the scaling factor, x = T / τ c , τ c It is the decorrelation time, β is the normalization factor for the speckle averaging effect; ρ is the dynamic scattering fraction, ρ = I f / (I s +I f ), where I f For the dynamic scattering part, I s This is the static scattering component; V noise It is irrelevant noise.

[0016] According to embodiments of this disclosure, the curve fitting model is based on least squares Levenberg-Marquardt implementation.

[0017] In another aspect, this disclosure provides a method for quantitative blood flow detection based on speckle pattern, wherein blood flow is detected using the speckle-based blood flow quantitative detection system described above. The method includes: Operation S10: emitting a measurement laser from a laser; Operation S20: integrating a multimode light source fiber and multiple probe fibers via an optical fiber probe, wherein the light source fiber is used to vertically project the measurement laser onto the surface of the object under test; the multiple probe fibers can form different source-probe distances with the light source fiber to collect speckle signals at different depths obtained after the measurement laser is vertically projected onto the object under test; Operation S30: receiving speckle signals collected by the probe fibers at different exposure times via a camera unit; Operation S40: outputting an analog signal to the laser via an analog signal output module to adjust the measurement laser intensity and prevent saturation of the camera unit when the exposure time changes; and Operation S50: controlling the analog signal output module to output an analog signal and controlling the exposure time of the camera unit via a computer, and processing the received speckle signals to obtain quantitative blood flow information.

[0018] (II) Beneficial Effects

[0019] As can be seen from the above technical solutions, the blood flow quantitative detection system and method based on diffuse speckle in this disclosure have at least one or a part of the following beneficial effects:

[0020] (1) Combining laser speckle contrast analysis with multi-exposure speckle model can eliminate the influence of static scatterers and noise, and obtain more accurate quantitative blood flow information through curve fitting.

[0021] (2) Using optical fiber for light transmission changes the traditional LSCI method of using wide field of view illumination. It concentrates the laser energy at one point, and the obtained light signal is a diffuse speckle signal, which improves the detection depth.

[0022] (3) The fiber optic probe integrates three sets of source-detector pairs at different distances. During measurement, it is slightly in contact with the plane of the object to be measured, so that the fiber is perpendicular to the plane to be measured. According to the theory of diffused light propagation, photons are emitted from the source fiber and reach the detector fiber through a banana-shaped transmission path. Monte Carlo simulation provides a reference for its penetration depth and can be used to measure blood flow information at different depths.

[0023] (4) Multimode fiber can obtain multiple speckles in each frame of the camera image. By calculating the spatial speckle contrast, it makes up for the disadvantage of low time resolution of single-mode fiber system. Under the premise of ensuring laser coherence, the system sampling rate is kept consistent with the camera frame rate. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of a blood flow quantitative detection system based on diffuse speckle pattern according to an embodiment of the present disclosure;

[0025] Figure 2 This is a schematic diagram of the cross-section of the fiber optic probe according to an embodiment of the present disclosure;

[0026] Figure 3 This is a flowchart illustrating the principle of the curve fitting model in this embodiment of the disclosure;

[0027] Figure 4 This is a flowchart of the Monte Carlo simulation of an embodiment of this disclosure;

[0028] Figure 5 This is a flowchart illustrating the detection depth calculation process according to an embodiment of the present disclosure;

[0029] Figure 6 This is a schematic diagram of the composition of the blood flow phantom model according to an embodiment of the present disclosure;

[0030] Figure 7 This is a graph showing the ICT linear fitting results of the blood flow phantom model in this embodiment of the present disclosure;

[0031] Figure 8 This is a comparison chart of ρ values ​​for blood flow phantom models according to embodiments of this disclosure;

[0032] Figure 9 This is a graph showing the in vivo blood flow ICT changes according to an embodiment of this disclosure;

[0033] Figure 10 This is a comparison diagram of in vivo blood flow ρ values ​​according to embodiments of this disclosure;

[0034] Figure 11 This is a schematic flowchart of a blood flow quantitative detection method based on diffuse speckle pattern according to an embodiment of the present disclosure.

[0035] [Explanation of key component symbols in the accompanying drawings of this disclosure embodiment]

[0036] 1-Laser, 2-Fiber optic probe, 3-Light source fiber, 4-Detection fiber, 5-Camera unit, 6-Analog signal output module, 7-Computer, 8-Subject to test. Detailed Implementation

[0037] This disclosure provides a blood flow quantitative detection system and method based on diffuse speckle, which can quickly measure blood flow at different depths and obtain accurate blood flow quantitative information.

[0038] Laser Speckle Contrast Imaging (LSCI) is a non-invasive optical imaging technique that utilizes the speckle effect generated by the high coherence of laser light to reflect hemodynamic information in biological tissues. LSCI calculates the spatial standard deviation σ of pixels within a selected window of the camera. s (T) and average strength The ratio of the speckle contrast ratio K to the piezoelectric autocorrelation function is used to represent blood flow. In implementing this disclosure, the inventors learned that when the exposure time T is much greater than the decorrelation time τ of the electric field autocorrelation function... c At this time, the square of the inverse of the speckle contrast, l / K, can be obtained from a single long-exposure image. 2 This is used to represent blood flow. However, when a static scatterer is present, this method introduces a bias, l / K 2 The relationship with blood flow is not linear, making accurate quantitative measurement impossible. Furthermore, traditional LSCI uses wide-field illumination, primarily focusing on photons scattered in a single pass through human tissue, limiting the penetration depth of photons in the medium. Its detection depth is concentrated within 1 mm, making it difficult to obtain blood flow information from deep tissues. Diffuse Correlation Spectroscopy (DCS), on the other hand, focuses on photons scattered multiple times in human tissue, capable of detecting blood flow information up to 15 mm deep. However, it requires single-mode fiber and high-sensitivity single-photon counting avalanche photodiodes for photon detection, acquiring only one speckle signal in each frame of the detection camera, and then obtaining blood flow information by calculating the intensity autocorrelation function of multiple frames. Therefore, its equipment and calculations are complex, and its temporal resolution is low.

[0039] To address the following issues: (1) the inability to obtain accurate quantitative blood flow information in the presence of static scatterers using single long-exposure laser speckle contrast; (2) insufficient detection depth of traditional laser speckle technology; and (3) low time resolution of single-photon counting in diffusion-related spectra, this disclosure provides a quantitative blood flow detection system and method based on diffusion speckle.

[0040] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0041] In this embodiment of the disclosure, a blood flow quantitative detection system based on diffuse speckle is provided, combined with Figure 1 and Figure 2 As shown, the blood flow quantitative detection system based on speckle diffusion includes:

[0042] Laser 1, used to emit a measurement laser;

[0043] Fiber optic probe 2 is used to integrate multimode light source fiber 3 and multiple probe fibers 4. The light source fiber 3 is connected to laser 1 and is used to project the measurement laser vertically onto the surface of the object under test. The multiple probe fibers 4 can form different source-probe distances with the light source fiber 3 to collect diffuse speckle signals at different depths after the measurement laser is vertically projected onto the object under test.

[0044] Camera unit 5 is coupled to the probe fiber 4 in the fiber optic probe 2 and is used to receive the diffuse speckle signals collected by the probe fiber 4 at different exposure times.

[0045] Analog signal output module 6, connected to the laser 1, is used to output an analog signal to the laser 1 to adjust the intensity of the measured laser and prevent saturation of the camera unit 5 when the exposure time changes; and

[0046] Computer 7 is connected to analog signal output module 6 and camera unit 5 respectively. It is used to control analog signal output by analog signal output module 6 and control exposure time of camera unit 5, and process the received diffuse speckle signal to obtain quantitative blood flow information.

[0047] According to an embodiment of this disclosure, the laser 1 is a semiconductor laser, and the center wavelength of the emitted measurement laser is 785nm; the coherence length exceeds 30m, and the maximum output power is 50mW.

[0048] According to embodiments of this disclosure, in conjunction with Figure 1 and Figure 2 As shown, the fiber optic probe 2 integrates one light source fiber 3 and at least three probe fibers 4. The light source fiber 3 and probe fibers 4 in the fiber optic probe 2 are arranged in parallel and on the same plane. The at least three probe fibers 4 maintain different preset distances from the light source fiber 3 to form different source-probe distances. For example, the source-probe distances between the three probe fibers and the light source fiber are 5mm, 8mm, and 12mm, respectively, and the received optical signal is a diffuse speckle signal.

[0049] According to an embodiment of this disclosure, the camera unit 5 includes a CCD camera with a resolution of 1920*1200, a bit depth of 12 bits, and a frame rate of 300fps. The exposure time, photosensitive area, bit depth, and frame rate of the CCD camera are all adjustable.

[0050] According to the embodiments of this disclosure, a 50*50 pixel area in the horizontal direction of the center of the probe fiber projection is selected as the region of interest. When the exposure time of the camera unit 5 and the source-probe distance change, the average pixel value in the region of interest is kept between 75 and 95, and the maximum value does not exceed 255, so as to maintain the speckle signal intensity.

[0051] According to embodiments of this disclosure, the exposure time setting range of the CCD camera is set to 0.02-30ms, including multiple exposure time setting values. The corrected spatial speckle contrast K(T) for each exposure time setting value is calculated and saved.

[0052] K(T)=σ s (T) / ;

[0053] Where σ s (T) is the standard deviation of pixels in the region of interest at exposure time T. It is the average value of pixels within the region of interest.

[0054] According to embodiments of this disclosure, the spatial speckle contrast is denoised by computer 7 and motion artifacts are eliminated. Then, multi-exposure data curve fitting is performed based on the multi-exposure speckle model and curve fitting model to extract quantitative blood flow information.

[0055] According to embodiments of this disclosure, the multi-exposure speckle model is represented as follows:

[0056]

[0057] Where K is the spatial speckle contrast, T is the camera exposure time, and x is the scaling factor, x = T / τ c , τ c It is the decorrelation time, β is the normalization factor for the speckle averaging effect; ρ is the dynamic scattering fraction, ρ = I f / ( I s+I f ), where I f For the dynamic scattering part, I s This is the static scattering component; V noise It is irrelevant noise.

[0058] According to embodiments of this disclosure, the curve fitting model is based on least squares Levenberg-Marquardt implementation.

[0059] More specifically, this disclosure provides a blood flow quantitative detection system based on diffuse speckle, comprising: a laser for emitting a measurement laser; an optical fiber probe for integrating a multimode source fiber and a probe fiber, wherein the source fiber projects the measurement laser perpendicularly onto the surface of the object to be measured, and the probe fiber collects diffuse speckle signals at different depths; a camera unit for coupling the probe fiber and connecting it to a computer, receiving speckle signals collected by the probe fiber at different exposure times and processing them by the computer; an analog signal output module for connecting the laser and the computer, outputting an analog signal to adjust the laser intensity and prevent saturation of the camera unit when the exposure time changes; and a computer for connecting the analog signal output module and the camera unit, controlling the laser intensity and camera exposure time, processing the received speckle signals, calculating the spatial speckle contrast K at multiple exposure times, and obtaining the inverse correlation time (ICT) and dynamic scattering fraction ρ of blood flow according to a multi-exposure speckle contrast model.

[0060] According to an embodiment of this disclosure, the analog signal output module includes a data acquisition card and a differential amplifier, with an output voltage range of -15V to +15V.

[0061] According to an embodiment of this disclosure, the photosensitive area of ​​the camera unit is adjusted to 600*400 pixels, and the bit depth is adjusted to 8 bits, so that the camera frame rate is stabilized at 300fps, i.e., the system sampling rate is 300Hz. A 50*50 pixel area in the horizontal direction of the center of the probe fiber projection is selected as the region of interest (ROI). The camera exposure time is changed to a range of 0.02-30ms, specifically 0.02ms, 0.05ms, 0.1ms, 0.2ms, 0.3ms, 0.5ms, 1ms, 2ms, 4ms, 6ms, 8ms, 12ms, 20ms, and 30ms. The spatial speckle contrast K(T) at each exposure time is calculated and saved.

[0062] K(T)=σ s (T) / (1);

[0063] Where σ s (T) is the standard deviation of pixels within the ROI at exposure time T. It is the average value of the pixels within the ROI.

[0064] According to an embodiment of this disclosure, the saved speckle contrast K is input into a MATLAB curve fitting program, based on a multi-exposure speckle model, namely:

[0065]

[0066] The multi-exposure speckle model described above is used to fit multi-exposure data curves and extract quantitative blood flow information. Here, K is the spatial speckle contrast, T is the camera exposure time, and x is the scaling factor, x = T / τ. c , τ c It is the decorrelation time, β is the normalization factor for the speckle averaging effect; ρ is the dynamic scattering fraction, ρ = I f / (I s +I f ), where I f For the dynamic scattering part, I s This is the static scattering component; V noise It is irrelevant noise.

[0067] According to an embodiment of this disclosure, the curve fitting process includes: firstly, when only a static scatterer exists, acquiring the multi-exposure speckle contrast K, and calculating the β value of the system using formula (2), where the detection system provided in this disclosure has β = 0.2478; then setting the upper and lower limits of the fitting parameters, where x is [0, Inf], ρ is [0, 1], and V noise The values ​​are [0, 1]. Finally, K and T are input into the fitting program to obtain the fitting parameter values ​​ICT and ρ.

[0068] According to embodiments of this disclosure, the curve fitting model is implemented using the least squares-based Levenberg-Marquardt algorithm, the flowchart of which is shown below. Figure 3 As shown, the steps include:

[0069] S1: Define the multi-exposure speckle model as a function f, then K = f(T) i a j The independent variable is exposure time T, and the dependent variable is speckle contrast K. The input functions are: function f, exposure time T, speckle contrast K, damping factor λ, initial values ​​of fitting parameters a, and the least squares sum of residuals MIN.

[0070] S2: Calculate the residuals Where K = f(T) i a j ), where i is the subscript number of the exposure time T and its corresponding speckle contrast K, and j is the subscript number of the fitting parameter a;

[0071] S3: Determine the step size based on λ Where J is the Jacobian matrix, containing all the first-order partial derivatives of the function f, J T Let I be the transpose of the Jacobian matrix, and let I be the identity matrix.

[0072] S4: According to h LM Update parameters in and These are the parameters before and after the update, respectively.

[0073] S5: Based on the new parameters Calculate the new residual

[0074] S6: Compare the residual S1 with the least squares sum MIN;

[0075] S7: If S1 < MIN, output the fitting parameter a and the residual S1;

[0076] S8: If S1 > MIN, compare the magnitudes of S1 and S, adjust the damping factor λ, and continue iterating from step S2 until the fitting parameter a that meets the conditions is output.

[0077] Furthermore, the definitions of the various elements and methods described above are not limited to the specific structures, shapes, or methods mentioned in the embodiments. Those skilled in the art can easily modify or substitute them, for example:

[0078] (1) Other wavelengths of lasers that meet the requirements of penetration depth and coherence can be selected.

[0079] (2) The source-detector distance can be other fixed sizes depending on the detection depth requirements, or an adjustable source-detector distance device can be used;

[0080] (3) The camera unit can be a CCD camera or a CMOS camera with other resolutions and bit depths;

[0081] (4) Laser power control can be performed using any suitable method depending on the type of laser.

[0082] Another aspect of this disclosure provides a method for quantitative blood flow detection based on speckle pattern, wherein blood flow is detected using the aforementioned quantitative blood flow detection system based on speckle pattern. Figure 11 As shown, the blood flow quantitative detection method based on speckle diffusion includes:

[0083] Operation S10: Emit a measurement laser via the laser;

[0084] Operation S20: The multimode light source fiber 3 and multiple probe fibers 4 are integrated through the fiber optic probe. The light source fiber 3 is used to project the measurement laser vertically onto the surface of the object under test. The multiple probe fibers 4 can form different source-probe distances with the light source fiber 3 to collect diffuse speckle signals at different depths after the measurement laser is vertically projected onto the object under test.

[0085] Operation S30: Receive diffuse speckle signals collected by the probe fiber 4 at different exposure times through the camera unit 5;

[0086] Operation S40: Output an analog signal to the laser 1 via the analog signal output module 6 to adjust the intensity of the measured laser, preventing saturation of the camera unit 5 when the exposure time changes; and

[0087] Operation S50: The computer 7 controls the analog signal output module 6 to output analog signals and controls the exposure time of the camera unit 5, and processes the received diffuse speckle signal to obtain quantitative blood flow information.

[0088] More specifically, in the implementation process, Monte Carlo simulation is used to provide a reference for the detection depth of different source-probe pairs; based on the above detection depth, a blood flow phantom model is made, blood flow at different depths is measured to obtain ICT and ρ, and the measurement accuracy of the detection system is verified; local tissue is moderately heated, and different source-probe pairs are used to measure the ICT and ρ values ​​before and after moderate heating to evaluate the changes in blood flow and recovery.

[0089] According to embodiments of this disclosure, as follows Figure 4 The flowchart shown illustrates a Monte Carlo simulation. Input parameters include: typical optical properties of human tissue at 785nm wavelength, and the absorption coefficient μ is set. a =0.025cm -1 Reduced scattering coefficient μ s = 8.5cm -1 The anisotropy factor was 0.9; the number of photons used in the simulation was 10⁸; the position of each photon after scattering was recorded during the simulation. A flowchart for calculating the source-detector pair depth based on the position of each photon scattering is shown below. Figure 5 As shown, the steps are as follows:

[0090] Record the depth h of the photon after each scattering event;

[0091] Calculate the average depth h after each scattering, and use it as the penetration depth h1 of the photon;

[0092] Calculate the average of all photon penetration depths h1, and use it as the average detection depth hmean of the source-detector pair;

[0093] Record the maximum depth hm among all photon scattering events;

[0094] Calculate the average of the maximum depths hm of all photons, and use it as the maximum detection depth hmax of the source-detector pair.

[0095] The average detection depths corresponding to the 5mm, 8mm, and 12mm source-detector pairs are approximately 1.8mm, 3.1mm, and 4.6mm, respectively, and the maximum detection depths are approximately 3.5mm, 5.2mm, and 6.7mm, respectively.

[0096] According to embodiments of this disclosure, a blood flow phantom model is fabricated based on the aforementioned average detection depth. A polytetrafluoroethylene (PTFE) block is used to simulate a static scatterer in human tissue; two identical PTFE tubes are embedded at different distances from the surface of the PTFE block, parallel to its surface, to simulate blood vessels at different depths in the human body; a syringe pump is used to inject a fat emulsion solution into the tubes at different flow rates to simulate human blood flow; the flow of blood in the superficial and deep layers is controlled separately, and three sets of source-detector pairs are used to measure and obtain ICT and ρ values, which are then compared to verify the accuracy of the detection system.

[0097] According to embodiments of this disclosure, the above-described detection system is used for in vivo blood flow detection before and after moderate heating. First, three sets of source-probe pairs are used to measure blood flow information of the same site under normal conditions; then, the site to be tested is moderately heated to induce changes in blood flow, and the ICT and ρ values ​​are measured again using three sets of source-probe pairs to assess changes in blood flow and recovery.

[0098] In the following detailed description, specific details are set forth to provide a full understanding of the embodiments of this disclosure for ease of explanation.

[0099] According to embodiments of this disclosure, such as Figure 1 As shown, the blood flow quantitative detection system based on speckle includes: a laser 1 for emitting a measurement laser; an optical fiber probe 2 for integrating a multimode light source fiber 3 and a detection fiber 4; the light source fiber 3 vertically projects the measurement laser onto the surface of the object to be tested, and the detection fiber 4 collects speckle signals at different depths; a camera unit 5 for coupling the detection fiber 4 and connecting it to a computer 7, receiving speckle signals collected by the detection fiber 4 at different exposure times and processing them by the computer 7; an analog signal output module 6 for connecting the laser 1 and the computer 7, outputting an analog signal to adjust the laser intensity and prevent the camera unit 5 from saturating when the exposure time changes; and a computer 7 for connecting the analog signal output module 6 and the camera unit 5, controlling the laser intensity and camera exposure time, and processing the received speckle signals to obtain blood flow quantitative information according to the multi-exposure speckle contrast model of formula (2).

[0100] According to an embodiment of this disclosure, laser 1 is a semiconductor laser, with its output end connected to one end of the light source optical fiber via an SFC connector. The emitted laser has a center wavelength of 785nm, allowing for deep penetration into human tissue and providing information on deep tissue blood flow. The coherence length exceeds 30m, maintaining high coherence when using multimode optical fiber. The maximum output power is 50mW, and it is equipped with a temperature control controller, requiring less than 2s for stabilization during intensity adjustment, effectively improving the temporal resolution of multi-exposure quantitative measurements. The input control terminal of laser 1 is connected to an analog signal output module 6 for adjusting the laser intensity.

[0101] According to an embodiment of this disclosure, the fiber optic probe 2 integrates one light source fiber 3 and three detection fibers 4. One end of the light source fiber 3 is connected to a laser via an SFC fiber optic connector for light transmission, and the other end is integrated into the fiber optic probe 2, parallel to and in the same plane as the detection fibers 4, while maintaining fixed source-detection distances of 5mm, 8mm, and 12mm respectively. Figure 2 The diagram shows a cross-sectional view of the fiber optic probe. Three probe fibers 4 are integrated at one end onto the fiber optic probe 2, and the other end is coupled to the camera unit 5, making slight contact with its photosensitive area, thus projecting the acquired diffuse speckle signal perpendicularly onto the photosensitive area. During measurement, the fiber optic probe 2 is placed against the measurement plane of the object under test 8, maintaining relative stillness, especially in in-body measurements, to reduce the impact of motion artifacts on measurement accuracy. Optionally, a light-shielding material can be used to cover the fiber optic probe 2 and the object under test 8 during measurement to reduce noise.

[0102] According to an embodiment of this disclosure, camera unit 5 is a CCD camera with a resolution of 1920*1200, a bit depth of 12 bits, a frame rate of up to 300fps, and adjustable exposure time. Camera unit 5 is connected to computer 7 via USB 3.0, ensuring image transmission rate.

[0103] According to an embodiment of this disclosure, the analog signal output module 6 includes a data acquisition card and a differential amplifier. The data acquisition card outputs a voltage range of 0–3.3V, connects to a computer 7, and is controlled by a LabVIEW host computer program DAQ module. It outputs two analog signals to the input of the differential amplifier. One signal remains constant, while the other signal is changed to alter the module's output signal and adjust the laser intensity. The differential amplifier has a gain of 10, and its output is directly connected to the control port of the laser 1 to control the laser intensity. The analog signal output module 6 outputs a voltage range of -15V to +15V, controlling the laser power between 0–50mW. When the exposure time of the camera unit 5 and the source-detector distance change, it maintains the average pixel value within the ROI at 75–95, with a maximum value not exceeding 255, which is the maximum value of the camera's 8-bit bit depth, to maintain the speckle signal intensity and prevent it from becoming too low or saturated.

[0104] According to the embodiments of this disclosure, the photosensitive area of ​​the camera unit 5 is adjusted to 600*400 pixels, and the bit depth is adjusted to 8 bits, so that the camera frame rate is stabilized at 300fps, that is, the system sampling rate is 300Hz. The size of the camera photosensitive area, bit depth, and frame rate can be adjusted according to the specific imaging range and sampling rate requirements; then, a 50*50 pixel area in the horizontal direction of the center of the probe fiber projection is selected as the region of interest (ROI). Since this disclosure is a single-point quantitative measurement, spatial speckle contrast is used for calculation, and there is no need to consider the spatial resolution problem. Therefore, a 50*50 pixel area is selected as the ROI. Ordinary technicians can increase the ROI area to improve the signal-to-noise ratio; finally, the camera exposure time range is changed to 0.02-30ms, specifically 0.02ms, 0.05ms, 0.1ms, 0.2ms, 0.3ms, 0.5ms, 1ms, 2ms, 4ms, 6ms, 8ms, 12ms, 20ms, and 30ms, and the corrected spatial speckle contrast K(T) is calculated and saved for each exposure time:

[0105] K(T)=σ s (T) / (1);

[0106] Where σ s (T) is the standard deviation of pixels within the ROI at exposure time T. This is the average value of pixels within the ROI. The exposure time range and number can be adjusted accordingly: increasing the exposure time range increases the linear range of flow measurement; increasing the number of exposures improves measurement accuracy but decreases temporal resolution.

[0107] According to an embodiment of this disclosure, computer 7 inputs the collected multi-exposure speckle contrast data into a MATLAB curve fitting program. First, noise reduction is performed on K: N frames of spatial speckle contrast K are collected for each exposure time, N=300, with a collection time of 1 second. For longer exposure times, the required collection time increases, and N can be adjusted according to the time resolution requirements. Due to artifacts caused by human breathing and other movements, these K values ​​fluctuate around the baseline value. This disclosure sorts the 300 frames of K from largest to smallest, removes the first 100 frames with excessively high K values ​​and the last 100 frames with excessively low K values ​​to eliminate the influence of motion artifacts, and then calculates the average value of the remaining 100 frames of K as the calculation frame for each exposure time; then, according to the multi-exposure speckle model, i.e.:

[0108]

[0109] use Figure 3 The curve fitting model shown is used to fit curves to multi-exposure data and extract quantitative blood flow information.

[0110] According to embodiments of this disclosure, a method for quantitative blood flow detection based on diffuse speckle patterns, using the aforementioned detection system, includes the following steps:

[0111] Based on Monte Carlo simulation, the detection depth of different source-probe pairs was determined. Based on the above detection depth, a blood flow phantom model was made, and blood flow at different depths was measured to obtain ICT and ρ, verifying the measurement accuracy of the detection system. The local tissue was moderately heated, and the ICT and ρ values ​​before and after moderate heating were measured using different source-probe pairs to evaluate the changes in blood flow and recovery.

[0112] According to embodiments of this disclosure, the average detection depth provided by Monte Carlo simulation is used to... Figure 6 The blood flow phantom model shown was used for quantitative flow measurement to verify the accuracy of the detection system. The phantom model included: a polytetrafluoroethylene (PTFE) block to simulate a static scatterer in human tissue, with two 2mm diameter circular holes parallel to its surface for inserting circular tubes; two PTFE circular tubes, 2mm outer diameter and 1mm inner diameter, one tube with its lower surface 2mm from the phantom surface to simulate superficial blood vessels, and the other tube with its lower surface 5mm from the phantom surface to simulate deep blood vessels; a 1% fat emulsion solution prepared using a 20% fat emulsion solution and distilled water to simulate human blood; and a syringe pump to inject the fat emulsion solution into the circular tubes, maintaining an injection flow rate range of 47.1-471 μL / min, with a maximum flow velocity of 10mm / s within the tubes. The flow rates were measured using 5mm and 12mm source-probe pairs, controlling the flow on and off of superficial and deep blood flow respectively, obtaining quantitative values ​​ICT and ρ, which were then linearly fitted. Figure 7 , Figure 8 The figures show the linear fitting results of the ICT (Inductively Coupled Transmission) model and the comparison of the ρ (Positive Flow Value) values ​​of the blood flow phantom model, respectively. It can be seen that the measured values ​​of different source-detector pairs exhibit a good linear relationship, eliminating the influence of static scatterers and enabling accurate measurement over a wide flow range. With a 12mm source-detector distance, the measurement can cover both layers of blood flow, resulting in increased ICT and ρ. When only deep blood flow is present, the ICT and ρ measured by the 12mm pair decrease. The 5mm source-detector pair can only detect superficial vessels, therefore the changes in ICT and ρ for superficial and double-layer blood flow are not significant.

[0113] According to embodiments of this disclosure, during in vivo measurements, an infrared therapy lamp is used to moderately heat the area to be measured, inducing changes in blood flow. The area to be measured on the human skin is the inner side of the forearm; optionally, the wrist, fingertips, or other locations can be used. A constant distance of 30cm is maintained between the infrared therapy lamp and the forearm. The uniform moderate heating time is 10 minutes, and the recovery time is 34 minutes to maintain measurement consistency, which can be adjusted according to actual conditions. Three sets of source-detector distance measurements are taken for each group, and the average value is calculated to reduce random errors during the measurement process. Based on the exposure time range and number selected in this disclosure, measurements are performed every 2 minutes. Figure 9 The image shows the changes in ICT before and after the physiotherapy lamp was moderately heated. Figure 10 The ρ value was divided into baseline value before moderate heating, 0-16 min after moderate heating, 18-34 min after moderate heating, and after recovery. The average value of ρ was taken for each interval. With the increase of source-probe distance, the detection depth increases, the number of covered blood vessels increases, and the blood flow increases, thus the measured ICT and ρ increase. After moderate heating of the therapeutic lamp, vasodilation and increased blood flow, ICT and ρ were significantly higher than before moderate heating and after recovery. As time changed, the tissue gradually returned to its normal state, and the measured value of ICT gradually decreased from the highest point to the normal value, and ρ was also comparable to the baseline value before moderate heating.

[0114] Based on the above results, there are significant differences in the measurement results and changes of the three source-detector pairs. The detection system and detection method provided in this disclosure can accurately measure blood flow at a single point at different depths.

[0115] The embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. It should be noted that implementations not illustrated or described in the drawings or the main text of the specification are forms known to those skilled in the art and are not described in detail. Furthermore, the definitions of the various elements and methods described above are not limited to the specific structures, shapes, or methods mentioned in the embodiments, and those skilled in the art can easily modify or substitute them.

[0116] Based on the above description, those skilled in the art should have a clear understanding of the blood flow quantitative detection system and detection method based on diffuse speckle pattern of this disclosure.

[0117] In summary, this disclosure provides a blood flow quantitative detection system and method based on diffuse speckle, which, combined with a multi-exposure speckle contrast model, can eliminate the influence of static scatterers and noise, obtaining accurate blood flow information, including inverse decorrelation time and dynamic scattering fraction ρ. Based on the above detection system, this invention also provides a blood flow quantitative detection method based on diffuse speckle, comprising: providing a reference for the detection depth of different source-probe pairs according to Monte Carlo simulation; fabricating a blood flow phantom model according to the above detection depth, measuring the ICT and ρ of blood flow at different depths to verify the measurement accuracy of the detection system; and moderately heating a local tissue, using different source-probe pairs to measure the ICT and ρ values ​​before and after moderate heating to evaluate changes in blood flow and recovery.

[0118] It should also be noted that the above are different embodiments provided by this disclosure. These embodiments are used to illustrate the technical content of this disclosure and are not intended to limit the scope of protection of this disclosure. A feature of one embodiment can be applied to other embodiments through suitable modifications, substitutions, combinations, or separations.

[0119] It should be noted that, unless otherwise specified herein, having "a" element is not limited to having a single element, but may include one or more of the elements.

[0120] Furthermore, unless otherwise specified, the ordinal numbers such as "first," "second," etc., are used only to distinguish multiple elements with the same name and do not indicate any hierarchy, order of execution, or process sequence among them. A "first" element and a "second" element may appear together in the same component or separately in different components. The presence of an element with a higher ordinal number does not necessarily indicate the presence of another element with a lower ordinal number.

[0121] In this document, unless otherwise specified, the term "characteristic A" or "and / or" and "characteristic B" means that A exists alone, B exists alone, or A and B exist simultaneously; the term "characteristic A" and "and" or "and" and "and" and "characteristic B" means that A and B exist simultaneously; the terms "including," "containing," "having," and "containing" refer to, but are not limited to, these.

[0122] Furthermore, in this document, terms such as "above," "below," "left," "right," "front," "back," or "between" are used only to describe the relative positions of multiple elements and can be extended to include translation, rotation, or mirroring. Additionally, unless otherwise specified, the statement "one element is on another element" or similar statements do not necessarily indicate that the element is in contact with the other element.

[0123] Furthermore, unless specifically described or required to occur in a specific order, the order of the above steps is not limited to those listed above and can be varied or rearranged according to the desired design. Moreover, the above embodiments can be used in combination with each other or with other embodiments based on design and reliability considerations; that is, technical features from different embodiments can be freely combined to form more embodiments.

[0124] The specific embodiments described above further illustrate the purpose, technical solutions, and beneficial effects of this disclosure. It should be understood that the above descriptions are merely specific embodiments of this disclosure and are not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. A blood flow quantitative detection system based on diffuse speckle pattern, comprising: Laser (1), used to emit a measuring laser; An optical fiber probe (2) is used to integrate a multimode light source fiber with at least three probe fibers (4). The light source fiber (3) is connected to a laser (1) to project the measurement laser vertically onto the surface of the object under test. The at least three probe fibers (4) and the light source fiber (3) are arranged in parallel and on the same plane. The at least three probe fibers (4) and the light source fiber (3) maintain different set distances to form different source-detector distances, so as to collect the diffuse speckle signals at different depths obtained after the measurement laser is vertically projected onto the object under test. The camera unit (5) is coupled to the probe fiber (4) in the fiber optic probe (2) for receiving the diffuse speckle signal collected by the probe fiber (4) at different exposure times. The analog signal output module (6) is connected to the laser (1) and is used to output an analog signal to the laser (1) to adjust the intensity of the measured laser and prevent the camera unit (5) from saturating when the exposure time changes. as well as The computer (7) is connected to the analog signal output module (6) and the camera unit (5) respectively. It is used to control the analog signal output module (6) to output analog signals and control the exposure time of the camera unit (5), and to process the received diffuse speckle signal to obtain quantitative blood flow information.

2. The blood flow quantitative detection system based on diffuse speckle according to claim 1, wherein the laser (1) is a semiconductor laser, the center wavelength of the emitted measurement laser is 785nm, the coherence length exceeds 30m, and the maximum output power is 50mW.

3. The blood flow quantitative detection system based on diffuse speckle according to claim 1, wherein the camera unit (5) includes a CCD camera with a resolution of 1920×1200, a bit depth of 12 bits, and a frame rate of 300fps, wherein the exposure time, photosensitive area, bit depth, and frame rate of the CCD camera are all adjustable.

4. According to the blood flow quantitative detection system based on speckle as described in claim 3, a 50×50 pixel area in the horizontal direction of the center of the probe fiber projection is selected as the region of interest. When the exposure time of the camera unit (5) and the source-probe distance change, the average pixel value in the region of interest is kept at 75-95 and the maximum value is not more than 255, so as to maintain the speckle signal intensity.

5. In the blood flow quantitative detection system based on diffuse speckle as described in claim 3, the exposure time setting range of the CCD camera is set to 0.02-30ms, including multiple exposure time setting values, and the corrected spatial speckle contrast K(T) is calculated and saved for each exposure time setting value. ； in It is the standard deviation of pixels in the region of interest at exposure time T. It is the average value of pixels within the region of interest.

6. The blood flow quantitative detection system based on diffuse speckle according to claim 5, wherein the spatial speckle contrast is denoised by computer (7) and motion artifacts are eliminated, and then multi-exposure data curve fitting is performed according to the multi-exposure speckle model and curve fitting model to extract blood flow quantitative information.

7. The blood flow quantitative detection system based on diffusion speckle according to claim 6, wherein the multi-exposure speckle model is expressed as: ； Where K is the spatial speckle contrast, T is the camera exposure time, and x is the scaling factor, x = T / τ c , τ c It is the decorrelation time, β is the normalization factor for the speckle averaging effect; ρ is the dynamic scattering fraction, ρ=I f / (I s +I f ), where I f For the dynamic scattering part, I s This is the static scattering component; V noise It is irrelevant noise.

8. The blood flow quantitative detection system based on diffuse speckle as described in claim 6, wherein the curve fitting model is implemented based on least squares Levenberg-Marquardt.

9. A method for quantitative blood flow detection based on speckle pattern, comprising detecting blood flow using the quantitative blood flow detection system based on speckle pattern as described in any one of claims 1-8, wherein the method comprises: Operation S10: Emit a measurement laser through the laser (1); Operation S20: The multimode light source fiber and at least three probe fibers (4) are integrated through the fiber optic probe (2), wherein the light source fiber (3) is used to project the measurement laser vertically onto the surface of the object to be measured; the at least three probe fibers (4) can form different source-probe distances with the light source fiber (3) to collect the diffuse speckle signals at different depths obtained after the measurement laser is vertically projected onto the object to be measured. Operation S30: Receive diffuse speckle signals collected by the probe fiber (4) at different exposure times through the camera unit (5); Operation S40: Output an analog signal to the laser (1) through the analog signal output module (6) to adjust the intensity of the measured laser and prevent the camera unit (5) from saturating when the exposure time changes; as well as Operation S50: The computer (7) controls the analog signal output module (6) to output analog signals and controls the exposure time of the camera unit (5), and processes the received diffuse speckle signal to obtain quantitative blood flow information.

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