Method for rapidly detecting fluorescence lifetime

Abstract

The invention provides a method for rapidly detecting fluorescence lifetime, which comprises the following steps: sending a set acquisition parameter signal to a signal generator, and adjusting the working state of the signal generator according to the received parameter; controlling the laser to irradiate the to-be-detected sample through the signal generator, turning off the laser after the irradiation is finished, and waiting for the interval time set by the user; controlling an external triggering function of the camera through a signal generator, collecting a sample image, calling an SDK (Software Development Kit) of the camera through a computer to obtain a shot image, and storing the shot image in a memory; analyzing the sample image; repeating the steps until a cycle termination condition is achieved; and analyzing all the sample images, and outputting a corresponding fluorescence lifetime curve and a fluorescence lifetime value according to the selected fluorescence point and the analysis option. The method aims to overcome the defects that a mainstream fluorescence lifetime detection method is high in equipment cost, long in detection time, prone to being interfered by the environment, low in precision and the like, and can be used for calculating the multi-index fluorescence lifetime.

Description

Technical Field

[0001] The invention relates to the technical field of fluorescence lifetime detection, and in particular to a method for rapid fluorescence lifetime detection. Background Art

[0002] Fluorescence lifetime is a characteristic data of some fluorescent substances. When a substance is excited by a laser beam, the molecules of the substance absorb energy and transition from the ground state to an excited state, and then emit fluorescence in the form of radiation transition to return to the ground state. When the excitation light is removed, the time required for the fluorescence intensity of the molecule to drop to 1 / e of the maximum fluorescence intensity I0 during excitation is called the fluorescence lifetime, which is usually represented by τ.

[0003] The current mainstream methods for measuring fluorescence lifetime are mainly the following:

[0004] 1. Time-correlated single photon counting: This is a high-precision measurement technology that measures the fluorescence lifetime by recording the arrival time of a single photon. Its disadvantage is that a longer measurement time is required to reduce noise interference, and the detection equipment requires high precision and huge cost.

[0005] 2. Stroboscopic technology: Use a periodic excitation light source to determine the fluorescence lifetime by measuring the phase and amplitude changes of the fluorescence signal. Its disadvantage is that it requires a specific pulse light source and high-voltage pulse equipment, which increases the complexity and cost of the experiment, and is easily affected by ambient light.

[0006] 3. Phase modulation method: The fluorescence lifetime is determined by modulating the phase of the excitation light and measuring the phase change of the fluorescence signal. Its disadvantage is that when the sample attenuation is not a single exponential, it is more difficult to analyze and the equipment system is more complicated.

[0007] 4. Streak camera method: Use a high-speed camera to record the fluorescence decay process. It is suitable for fast fluorescence lifetime measurement. The disadvantage is that streak cameras are usually expensive and the imaging speed is not as fast as other methods due to the limitation of camera scanning speed.

[0008] In addition, with the development of computer technology, there are also methods that use deep learning technology to measure fluorescence lifetime. However, due to its narrow applicability, low accuracy, and the huge amount of data required, it has not become mainstream. Summary of the invention

[0009] In order to solve the problem that there are various shortcomings in the methods of measuring fluorescence lifetime in the prior art, the purpose of the present invention is to provide a method for rapid detection of fluorescence lifetime, which aims to solve the shortcomings of mainstream fluorescence lifetime detection methods such as high equipment cost, long detection time, susceptibility to environmental interference, low precision, etc., and can be used for the calculation of multi-exponential fluorescence lifetime.

[0010] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0011] A method for rapid detection of fluorescence lifetime comprises the following steps:

[0012] Step S1, system initialization;

[0013] Step S2, through the software interface, the user sets the basic parameters of the measurement, and after confirming the input, the measurement process is generated according to these parameters and starts to be executed;

[0014] Step S3, sending the set acquisition parameter signal to the signal generator, and the signal generator adjusts its working state according to the received parameters;

[0015] Step S4, controlling the laser to irradiate the sample to be tested for a predetermined time through a signal generator, turning off the laser after the irradiation is completed, and waiting for the interval time set by the user;

[0016] Step S5, controlling the external trigger function of the camera through a signal generator, collecting a sample image, calling the SDK of the camera through a computer to obtain the captured image, and storing it in a memory;

[0017] Step S6, analyzing the sample image;

[0018] Step S7, repeating steps S3-S6 until the loop termination condition is met, and then stopping the loop;

[0019] Step S8, analyzing all sample images stored in the memory, and outputting corresponding fluorescence lifetime curves and fluorescence lifetime values ​​according to the selected fluorescence points and analysis options.

[0020] According to a method for rapid fluorescence lifetime detection provided by the present invention, step S1 specifically comprises:

[0021] Start the initialization process;

[0022] Through the camera's built-in SDK interface, set the camera's exposure time to 10ms;

[0023] Use the camera's built-in SDK interface to set the camera's acquisition mode to external trigger mode;

[0024] Before starting a new measurement, clear the cached image data in the computer memory;

[0025] Open the serial communication interface of the computer and establish the connection between the computer and the signal generator;

[0026] Through the serial port command set provided by the signal generator itself, set the output channels of the signal generator to CH1 and CH2, and configure CH2 to automatically output the signal after waiting for a preset time after CH1 stops outputting the signal;

[0027] Through the serial port command set provided by the signal generator itself, set the output signal type of the signal generator, set CH1 to output a high-level signal to control the start of the laser, and set CH2 to output a pulse signal to trigger the camera's image acquisition.

[0028] According to a method for rapid fluorescence lifetime detection provided by the present invention, when it starts to be executed, the time interval parameter between signal generator CH1 and CH2 is set through a serial port command set provided by the signal generator itself;

[0029] Set the signal generator CH1 to output a high level signal through the serial port command to turn on the laser;

[0030] Set the high level duration, the signal generator CH1 changes to low level, and the laser is turned off;

[0031] After the high level of signal generator CH1 ends, signal generator CH2 waits for the set time interval and then sends a pulse signal to trigger the camera to take pictures;

[0032] Get the sample image captured through the API provided by the camera SDK;

[0033] Analyze the captured sample images.

[0034] According to a method for rapid detection of fluorescence lifetime provided by the present invention, the following selections are made according to the analysis results of the image, including:

[0035] If the image quality meets the preset standard, the acquisition cycle continues and the next acquisition parameters are adjusted and set as needed;

[0036] If the image quality does not meet the standard, the error processing process will be entered. If the image is detected to be overexposed, it will prompt that the image is overexposed and adjust the exposure time; if the signal is detected to be too weak, it will prompt that the signal is too weak and cannot be analyzed; after the error prompt, the current acquisition process ends;

[0037] If the preset number of cycles or other termination conditions are reached, the cycle is terminated and the next analysis is performed.

[0038] According to a method for rapid fluorescence lifetime detection provided by the present invention, in step S6, a single sample image is analyzed, specifically comprising:

[0039] Use Opencv::Rect to obtain image B with a quarter of the central area of ​​sample image A;

[0040] Traverse the grayscale values ​​corresponding to all pixels in image B and divide them into 10 intervals according to the data bits of the camera; count all pixels into 10 intervals according to the grayscale values;

[0041] Analyze the data in 10 intervals;

[0042] Determine whether the image corresponding to the current interval time has been collected once, including: if the image corresponding to the interval time is collected for the first time, then put image A into the computer cache, use the current time interval as a new collection parameter, and return a value of 1; or, if the image corresponding to the interval time is collected for the second time, then record the name of the last collected image as A';

[0043] Take the average of images A and A' in the cache, generate an image C and put it into the memory queue.

[0044] According to a method for rapid detection of fluorescence lifetime provided by the present invention, it is determined whether the number of images in the current memory queue is greater than 10, including: if the number of images is less than 10, the current time interval plus the time interval of a single increase is used as a new time interval acquisition parameter, and a value of 1 is returned; or, if the number of images is greater than or equal to 10, the latest three images in the queue are taken, and the average value of all pixels of each image and the overall average value are calculated;

[0045] Determine the difference between the pixel averages of the three images, including: if the ratio of the maximum average difference of the three images to the overall average is greater than 0.5%, then the current time interval plus the single-increase time interval is used as the new time interval acquisition parameter, and the return value is 1; or, if the ratio of the maximum average difference of the three images to the overall average is ≤ 0.5%, then the process ends and the return value is 0.

[0046] According to a method for rapid fluorescence lifetime detection provided by the present invention, data within 10 intervals are analyzed, specifically including:

[0047] If the number of pixels in the lowest interval accounts for more than 70%, and the average pixel value of image B is also in the lowest interval, then: if the number of images in the memory queue is ≥10 at this time, it is considered that the data is sufficient, the process ends, and the return value is 0; if the number of images in the memory queue is <10 at this time, it is considered that the signal is too weak, and the return value is -2

[0048] If the percentage of pixels in the highest interval is greater than 10%, the image is considered overexposed and the return value is -1.

[0049] If none of the above conditions are met, in other cases, the image brightness is considered appropriate.

[0050] According to a method for rapid fluorescence lifetime detection provided by the present invention, step S8 specifically comprises:

[0051] Retrieve all stored sample images from the memory queue;

[0052] According to the camera bit number and offset, calculate and set the maximum value dMax and minimum value dMin limited by the data fitting;

[0053] On the user interface, the user is allowed to select the data point coordinates P (x1, y1) that need to be analyzed;

[0054] Get the grayscale value at coordinate P from the last three images in the memory queue;

[0055] Calculate the average value f0 of these three gray values;

[0056] Correct the grayscale values ​​of all images in the queue at coordinate P, that is, subtract f0 from the grayscale values ​​at point P, and write the corrected grayscale values ​​into the data list List1;

[0057] Select data greater than dMin and less than dMax from the data list List1 and store them in the new data list List2.

[0058] According to a method for rapid detection of fluorescence lifetime provided by the present invention, a user interface is provided to allow a user to select a fluorescence lifetime model. After the calculation is completed, the coefficient R is determined according to the fitting. 2 Further selection is made, where R 2 Between 0-1;

[0059] Use the nonlinear least squares fitting method to fit the data in the data list List2 and its corresponding interval time;

[0060] The Levenberg-Marquardt class of the Eigen library is used for fitting, with X step interval = 1, Y step interval = 1, number of fittings = 1000, and the fitting formula is expressed as follows:

[0061] y=a1e -b1x +a2e -b2x +…+a n e -bnx

[0062] Output the fitting results a1, b1..., and calculate the fitting determination coefficient R 2 , evaluate the fitting effect;

[0063] Among them, R 2 =1-(SSE / SST), SSE is the residual sum of squares, and SST is the total sum of squares.

[0064] According to a method for rapid detection of fluorescence lifetime provided by the present invention, a fitting curve is drawn on a user interface and the fluorescence lifetime is displayed. The fluorescence lifetime formula is expressed as the following formula:

[0065]

[0066] Among them, fluorescence lifetime τ1=1 / b1; τ2=1 / b2; τ3=1 / b3.

[0067] It can be seen that compared with the prior art, the present invention has the following beneficial effects:

[0068] 1. The present invention can obtain the fluorescence lifetime data of any point in the fluorescence image in a short time, and can select single exponential or multi-exponential fluorescence curve analysis. The whole system structure is relatively simple, and the component cost is low. The detection result is not easily affected by the detection ambient light.

[0069] 2. The present invention does not require expensive pulse light sources and high-voltage pulse equipment, thus reducing equipment costs; and utilizes specialized software algorithms and process algorithms to eliminate the interference of ambient light to the greatest extent, resulting in short measurement time and high accuracy.

[0070] 3. The present invention can achieve high-precision measurement of fluorescence lifetime by precisely controlling the signal generator, laser, camera and other equipment. The automated process reduces errors caused by human operation and improves measurement efficiency.

[0071] 4. The automated process and data storage function of the present invention ensure the reliability and repeatability of the experimental data. Multiple cycles of measurement and data analysis can further improve the accuracy and stability of the measurement results.

[0072] 5. The present invention can easily set the basic parameters of measurement through the software interface, without the need for complex equipment debugging, real-time feedback and intuitive image acquisition and analysis functions, so that users can monitor the experimental process in real time and obtain results in a timely manner.

[0073] 6. The present invention is not only applicable to the rapid detection of fluorescence lifetime, but also can be applied to many fields such as molecular biology, spectral analysis, medical detection, etc. In the context of drug screening, biomolecular research, etc., this method has unique advantages and can provide users with a fast and accurate spectral testing method.

[0074] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 It is a schematic diagram of the connection principle of the system hardware used in an embodiment of a method for rapid fluorescence lifetime detection of the present invention.

[0076] Figure 2 It is a flow chart of an embodiment of a method for rapid fluorescence lifetime detection of the present invention.

[0077] Figure 3 This is a flow chart about system initialization in an embodiment of a method for rapid fluorescence lifetime detection of the present invention.

[0078] Figure 4 It is a flow chart of overall detection process control in an embodiment of a method for rapid fluorescence lifetime detection of the present invention.

[0079] Figure 5 It is a flow chart of single sample image analysis in an embodiment of a method for rapid fluorescence lifetime detection of the present invention.

[0080] Figure 6 It is a flow chart for analyzing all images in an embodiment of a method for rapid fluorescence lifetime detection of the present invention.

[0081] Figure 7 It is a schematic diagram of a fluorescent stick picture taken in a non-completely darkroom environment in an embodiment of a method for rapid detection of fluorescence lifetime of the present invention. DETAILED DESCRIPTION

[0082] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0083] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0084] See also Figure 1 The hardware required in this embodiment includes: a signal generator (which is required to output two signals, set the output signal type, and set the time interval between the two signal outputs), a laser that supports signal control, a grayscale camera that supports external triggering function, a computer where the analysis software is located, and connecting cables for various hardware.

[0085] In this embodiment, the system hardware connection is described as follows:

[0086] The first signal output of the signal generator is connected to the laser control terminal through the CH1 cable; the second signal output of the signal generator is connected to the camera external trigger input interface through the CH2 cable; the camera is connected to the computer where the analysis software is located through its own signal transmission line (such as USB, network cable, acquisition card, etc.); the signal generator control port is connected to the computer where the analysis software is located through a serial port line.

[0087] See also Figures 2 to 7 The present invention provides a method for rapid detection of fluorescence lifetime, the method comprising the following steps:

[0088] Step S1, system initialization;

[0089] Step S2, through the software interface, the user sets the basic parameters of the measurement. After confirming the input, the measurement process is generated according to these parameters, such as the set start time, single interval time, expected number of cycle photos, etc., and starts execution;

[0090] Step S3, sending the set signal interval time and other acquisition parameter signals to the signal generator, and the signal generator adjusts its working state according to the received parameters;

[0091] Step S4, controlling the laser to irradiate the sample to be tested for a predetermined time (e.g., 1 second) through a signal generator, turning off the laser after the irradiation is completed, and waiting for the interval time set by the user;

[0092] Step S5, controlling the external trigger function of the camera through a signal generator, collecting a sample image, calling the SDK of the camera through a computer to obtain the captured image, and storing it in a memory;

[0093] Step S6, analyzing the sample image;

[0094] Step S7, repeating steps S3-S6 until the loop termination condition is met, and then stopping the loop;

[0095] Step S8, analyzing all sample images stored in the memory, and outputting corresponding fluorescence lifetime curves and fluorescence lifetime values ​​according to the selected fluorescence points and analysis options.

[0096] In this embodiment, the analysis software runs on an independent working host, and its software and hardware environment is as follows:

[0097] CPU: Intel i5 and above;

[0098] Memory: 8GB and above;

[0099] Hard disk: 500GB and above;

[0100] Graphics card: Geforce GTX 1060 and above;

[0101] System: Windows 7 and above;

[0102] Software third-party libraries: opencv, Eigen;

[0103] In this embodiment, if Figure 3 As shown, the above step S1 specifically includes:

[0104] Start the initialization process;

[0105] Through the camera's built-in SDK interface, set the camera's exposure time to 10ms;

[0106] Use the camera's built-in SDK interface to set the camera's acquisition mode to external trigger mode;

[0107] Before starting a new measurement, clear the cached image data in the computer memory;

[0108] Open the serial communication interface of the computer and establish the connection between the computer and the signal generator;

[0109] Through the serial port command set provided by the signal generator itself, set the output channels of the signal generator to CH1 and CH2, and configure CH2 to automatically output the signal after waiting for a preset time after CH1 stops outputting the signal;

[0110] Through the serial port command set provided by the signal generator itself, set the output signal type of the signal generator, set CH1 to output a high-level signal to control the start of the laser, and set CH2 to output a pulse signal to trigger the camera's image acquisition.

[0111] In this embodiment, if Figure 4 As shown, according to the user interface input parameters (starting time interval, single increase time interval, expected total number of times), an initial measurement process is generated;

[0112] When the execution starts, the time interval parameters between CH1 and CH2 of the signal generator are set through the serial port command set provided by the signal generator itself;

[0113] Set the signal generator CH1 to output a high level signal through the serial port command to turn on the laser;

[0114] Set the high level duration (such as 1s), the signal generator CH1 changes to a low level, and the laser is turned off;

[0115] After the high level of signal generator CH1 ends, signal generator CH2 waits for the set time interval and then sends a pulse signal to trigger the camera to take pictures;

[0116] Get the sample image captured through the API provided by the camera SDK;

[0117] Analyze the captured sample images.

[0118] In this embodiment, the following selections are made based on the analysis results of the image:

[0119] If the image quality meets the preset standard, the acquisition cycle continues and the next acquisition parameters are adjusted and set as needed;

[0120] If the image quality does not meet the standard, the error processing process will be entered. If the image is detected to be overexposed, it will prompt that the image is overexposed and adjust the exposure time; if the signal is detected to be too weak, it will prompt that the signal is too weak and cannot be analyzed; after the error prompt, the current acquisition process ends;

[0121] If the preset number of cycles or other termination conditions are reached, the cycle is terminated and the next analysis is performed.

[0122] In step S6, if Figure 5 As shown, a single sample image is analyzed, including:

[0123] Use Opencv::Rect to obtain image B with a quarter of the central area of ​​sample image A;

[0124] Traverse the grayscale values ​​corresponding to all pixels in image B, and divide them into 10 intervals according to the data bits of the camera (for example, for a 14-bit camera, the data range is 0-16383, then the intervals are 0-1638, 1639-3277, ..., 14745-16383; for a 16-bit camera, the data range is 0-65535, then the intervals are 0-6553, 6554-13107, ..., 58982-65535); count all the pixels into 10 intervals according to the grayscale values;

[0125] Analyze the data in 10 intervals, including:

[0126] If the number of pixels in the lowest interval accounts for more than 70%, and the pixel average of image B calculated using cv::Mat::Mean is also in the lowest interval, then: if the number of images in the memory queue is ≥10 at this time, it is considered that the data is sufficient, the process ends, and the return value is 0; if the number of images in the memory queue is <10 at this time, it is considered that the signal is too weak, and the return value is -2

[0127] If the percentage of pixels in the highest interval is greater than 10%, the image is considered overexposed and the return value is -1;

[0128] If none of the above conditions are met, in other cases, the image brightness is considered appropriate.

[0129] Determine whether the image corresponding to the current interval has been collected once (the same interval is designed to be collected twice and averaged to eliminate the interference of ambient light changes and noise), including:

[0130] If the image corresponding to the interval time is collected for the first time, then image A is put into the computer cache, the current time interval is used as the new collection parameter, and the value 1 is returned;

[0131] The image corresponding to this interval is the second acquisition, so the name of the last acquisition image is recorded as A';

[0132] Take the average of images A and A' in the cache, generate an image C and put it into the memory queue.

[0133] Determine whether the number of images in the current memory queue is greater than 10. There are two cases:

[0134] If the number of images is less than 10, the current time interval plus the single-increment time interval is used as the new time interval acquisition parameter, and the return value is 1.

[0135] If the number of images is greater than or equal to 10, take the three latest images in the queue and calculate the average value of all pixels of each image (denoted by f1, f2, f3 from small to large) and the overall average value (denoted by f0, f0 = (f1+f2+f3) / 3).

[0136] To determine the difference between the average values ​​of the pixels of the three images, there are two cases:

[0137] If the ratio of the maximum average difference of the three images to the overall average is greater than 0.5% (i.e. (f3-f1) / f0>0.005), the current time interval plus the single-increase time interval is used as the new time interval acquisition parameter, and the return value is 1;

[0138] If the ratio of the maximum average difference of the three images to the overall average is ≤ 0.5% (ie (f3-f1) / f0≤0.005), the process ends and the return value is 0.

[0139] In this embodiment, if Figure 6 As shown, the above step S8 specifically includes:

[0140] Retrieve all stored sample images from the memory queue;

[0141] According to the camera bit number and offset, calculate and set the maximum value dMax and minimum value dMin of the data fitting limit. This parameter is related to the camera bit number and its own offset. Generally, 95% and 5% of the camera's highest bit data are selected (if it is a 14-bit camera, dMax = 16383*0.95 = 15564; dMin = 16383*0.05 = 819).

[0142] On the user interface, the user is allowed to select the data point coordinates P (x1, y1) that need to be analyzed;

[0143] Get the grayscale value at coordinate P from the last three images in the memory queue;

[0144] Calculate the average value f0 of these three gray values;

[0145] Correct the grayscale values ​​of all images in the queue at coordinate P, that is, subtract f0 from the grayscale values ​​at point P, and write the corrected grayscale values ​​into the data list List1;

[0146] Select data greater than dMin and less than dMax from the data list List1 and store them in the new data list List2.

[0147] The user interface allows the user to select the fluorescence lifetime model. After the calculation is completed, the coefficient R is determined based on the fitting. 2 Make further selections (R 2 Between 0 and 1, the closer it is to 1, the better the fitting effect). 2 Between 0-1;

[0148] Use the nonlinear least squares fitting method to fit the data in the data list List2 and its corresponding interval time; use the Levenberg-Marquardt class of the Eigen library for fitting, X step interval = 1, Y step interval = 1, fitting times = 1000, and the fitting formula is expressed as the following formula:

[0149] y=a1e -b1x +a2e -b2x +…+a n e -bnx

[0150] Output the fitting results a1, b1..., and calculate the fitting determination coefficient R 2 , evaluate the fitting effect;

[0151] Among them, R 2 =1-(SSE / SST), SSE is the residual sum of squares, and SST is the total sum of squares.

[0152] A fitting curve is drawn on the user interface, and the fluorescence lifetime is displayed. The fluorescence lifetime formula is expressed as follows:

[0153]

[0154] Among them, fluorescence lifetime τ1=1 / b1; τ2=1 / b2; τ3=1 / b3.

[0155] In practical applications, this embodiment has been verified on existing equipment:

[0156] 1. Select RIGOL DG812 as the signal generator;

[0157] 2. The laser uses SMA905 interface fiber laser with a wavelength of 808nm;

[0158] 3. Select Xeneth 14-bit grayscale camera as the data acquisition camera;

[0159] 4. The test sample should be a fluorescent stick that can emit infrared fluorescence;

[0160] like Figure 7 As shown, Figure 7 This is a picture of a fluorescent stick taken in a non-completely dark room environment:

[0161] The user initially sets the shooting parameters as follows:

[0162] 1. Camera exposure time: 10ms

[0163] 2. Start time interval: 20us

[0164] 3. Incremental time interval: 30us

[0165] 4. Expected number of times: 70 times

[0166] The test results are shown in the following table:

[0167]

[0168] The actual number of shots was 32, and the time taken was 77 seconds. From the results, it can be seen that the sample is more suitable for the single exponential model, and the fluorescence lifetime data analyzed at three different positions are basically consistent, with an error of less than 2% from the average value, and is not easily affected by ambient light.

[0169] In summary, the present invention can obtain the fluorescence lifetime data of any point in the fluorescence image in a short time, and can select single exponential or multi-exponential fluorescence curve analysis. The entire system structure is relatively simple, and the component cost is low, and the detection result is not easily affected by the detection ambient light. The present invention does not require expensive pulse light sources and high-voltage pulse equipment, which reduces the equipment cost; and uses special software algorithms and process algorithms to remove the interference of ambient light to the greatest extent, with short measurement time and high accuracy.

[0170] Furthermore, the present invention can achieve high-precision measurement of fluorescence lifetime by precisely controlling the signal generator, laser, camera and other equipment. The automated process reduces errors caused by human operation and improves measurement efficiency.

[0171] Furthermore, the automated process and data storage function of the present invention ensure the reliability and repeatability of experimental data, and multiple cycles of measurement and data analysis can further improve the accuracy and stability of measurement results.

[0172] Furthermore, the present invention can easily set basic measurement parameters through the software interface without complicated equipment debugging, real-time feedback and intuitive image acquisition and analysis functions, so that users can monitor the experimental process in real time and obtain results in a timely manner.

[0173] Furthermore, the present invention is not only applicable to the rapid detection of fluorescence lifetime, but also can be applied to multiple fields such as molecular biology, spectral analysis, medical detection, etc. In the context of drug screening, biomolecular research, etc., this method has unique advantages and can provide users with a fast and accurate spectral testing method.

[0174] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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.

[0175] The above-mentioned embodiments are only preferred embodiments of the present invention and cannot be used to limit the scope of protection of the present invention. Any non-substantial changes and substitutions made by technicians in this field on the basis of the present invention shall fall within the scope of protection required by the present invention.

Claims

1. A method for rapid detection of fluorescence lifetime, characterized in that: The following steps are involved: Step S1, system initialization; Step S2, through the software interface, the user sets the basic parameters of the measurement, and after confirming the input, the measurement process is generated according to these parameters and starts to be executed; Step S3, sending the set acquisition parameter signal to the signal generator, and the signal generator adjusts its working state according to the received parameters; Step S4, controlling the laser to irradiate the sample to be tested for a predetermined time through a signal generator, turning off the laser after the irradiation is completed, and waiting for the interval time set by the user; Step S5, controlling the external trigger function of the camera through a signal generator, collecting a sample image, calling the SDK of the camera through a computer to obtain the captured image, and storing it in a memory; Step S6, analyzing the sample image; Step S7, repeating steps S3-S6 until the loop termination condition is met, and then stopping the loop; Step S8, analyzing all sample images stored in the memory, and outputting corresponding fluorescence lifetime curves and fluorescence lifetime values ​​according to the selected fluorescence points and analysis options.

2. The method according to claim 1, characterized in that. The step S1 specifically includes: Start the initialization process; Through the camera's built-in SDK interface, set the camera's exposure time to 10ms; Use the camera's built-in SDK interface to set the camera's acquisition mode to external trigger mode; Before starting a new measurement, clear the cached image data in the computer memory; Open the serial communication interface of the computer and establish the connection between the computer and the signal generator; Through the serial port command set provided by the signal generator itself, set the output channels of the signal generator to CH1 and CH2, and configure CH2 to automatically output the signal after waiting for a preset time after CH1 stops outputting the signal; Through the serial port command set provided by the signal generator itself, set the output signal type of the signal generator, set CH1 to output a high-level signal to control the start of the laser, and set CH2 to output a pulse signal to trigger the camera's image acquisition.

3. The method according to claim 1, characterized in that: When the execution starts, the time interval parameters between CH1 and CH2 of the signal generator are set through the serial port command set provided by the signal generator itself; Set the signal generator CH1 to output a high level signal through the serial port command to turn on the laser; Set the high level duration, the signal generator CH1 changes to low level, and the laser is turned off; After the high level of signal generator CH1 ends, signal generator CH2 waits for the set time interval and then sends a pulse signal to trigger the camera to take pictures; Get the sample image captured through the API provided by the camera SDK; Analyze the captured sample images.

4. The method according to claim 3, characterized in that: Based on the analysis results of the image, make the following selections, including: If the image quality meets the preset standard, the acquisition cycle continues and the next acquisition parameters are adjusted and set as needed; If the image quality does not meet the standard, the error processing process will be entered. If the image is detected to be overexposed, it will prompt that the image is overexposed and adjust the exposure time; if the signal is detected to be too weak, it will prompt that the signal is too weak and cannot be analyzed; after the error prompt, the current acquisition process ends; If the preset number of cycles or other termination conditions are reached, the cycle is terminated and the next analysis is performed.

5. The method according to claim 1, characterized in that: In step S6, the single sample image is analyzed, specifically including: Use Opencv::Rect to obtain image B with a quarter of the central area of ​​sample image A; Traverse the grayscale values ​​corresponding to all pixels in image B and divide them into 10 intervals according to the camera's data bits; count all pixels into 10 intervals according to their grayscale values; Analyze the data in 10 intervals; Determine whether the image corresponding to the current interval time has been collected once, including: if the image corresponding to the interval time is collected for the first time, then put image A into the computer cache, use the current time interval as a new collection parameter, and return a value of 1; or, if the image corresponding to the interval time is collected for the second time, then record the name of the last collected image as A'; Take the average of images A and A' in the cache, generate an image C and put it into the memory queue.

6. The method according to claim 5, characterized in that: Determine whether the number of images in the current memory queue is greater than 10, including: if the number of images is less than 10, then use the current time interval plus the single-increase time interval as the new time interval acquisition parameter, and return a value of 1; or, if the number of images is greater than or equal to 10, take the latest 3 images in the queue, and calculate the average value of all pixels of each image and the overall average value; Determine the difference between the pixel averages of the three images, including: if the ratio of the maximum average difference of the three images to the overall average is greater than 0.5%, then the current time interval plus the single-increase time interval is used as the new time interval acquisition parameter, and the return value is 1; or, if the ratio of the maximum average difference of the three images to the overall average is ≤ 0.5%, then the process ends and the return value is 0.

7. The method according to claim 5, characterized in that: Analyze the data in 10 intervals, including: If the number of pixels in the lowest interval accounts for more than 70%, and the average pixel value of image B is also in the lowest interval, then: if the number of images in the memory queue is ≥10 at this time, it is considered that the data is sufficient, the process ends, and the return value is 0; if the number of images in the memory queue is <10 at this time, it is considered that the signal is too weak, and the return value is -2 If the percentage of pixels in the highest interval is greater than 10%, the image is considered overexposed and the return value is -1. If none of the above conditions are met, in other cases, the image brightness is considered appropriate.

8. The method according to claim 1, characterized in that The step S8 specifically includes: Retrieve all stored sample images from the memory queue; According to the camera bit number and offset, calculate and set the maximum value dMax and minimum value dMin limited by the data fitting; On the user interface, the user is allowed to select the data point coordinates P (x1, y1) that need to be analyzed; Get the grayscale value at coordinate P from the last three images in the memory queue; Calculate the average value f0 of these three gray values; Correct the grayscale values ​​of all images in the queue at coordinate P, that is, subtract f0 from the grayscale values ​​at point P, and write the corrected grayscale values ​​into the data list List1; Select data greater than dMin and less than dMax from the data list List1 and store them in the new data list List2.

9. The method according to claim 8, characterized in that: The user interface allows the user to select the fluorescence lifetime model. After the calculation is completed, the coefficient R is determined based on the fitting. 2 Further selection is made, where R 2 Between 0-1; Use the nonlinear least squares fitting method to fit the data in the data list List2 and its corresponding interval time; The Levenberg-Marquardt class of the Eigen library is used for fitting, with X step interval = 1, Y step interval = 1, number of fittings = 1000, and the fitting formula is expressed as follows: y=a1e -b1x +a2e -b2x +…+a n by -bnx Output the fitting results a1, b1..., and calculate the fitting determination coefficient R 2 , evaluate the fitting effect; Among them, R 2 =1-(SSE / SST), SSE is the residual sum of squares, and SST is the total sum of squares.

10. The method according to claim 9, characterized in that: A fitting curve is drawn on the user interface, and the fluorescence lifetime is displayed. The fluorescence lifetime formula is expressed as follows: Among them, fluorescence lifetime τ1=1 / b1; τ2=1 / b2; τ3=1 / b3.

Images