AOM Enable Parameter Determination Method, Image Acquisition Method and Related Devices

Abstract

The present invention relates to the technical field of flow cytometers, and specifically discloses a method for determining AOM enabling parameters, an image acquisition method, and related devices. Among them, the method for determining AOM enabling parameters includes the steps of: S1. Trigger the AOM driver to operate based on a reference enabling delay time to cooperate with the camera to acquire a reference image dataset; S2. Analyze the graphic characteristics of the light spot to obtain the proportion of valid images in the reference image dataset; S3. Determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enabling delay time as the AOM enabling delay time. Otherwise, reduce the reference enabling delay time and return to step S1; this method determines an AOM enabling delay time that can improve the proportion of valid image acquisition through an iterative process, enabling the AOM driver in the area array detection imaging flow cytometer to accurately match and start with the camera, ensuring clear and effective imaging, and thus improving the imaging quality.

Description

Technical Field

[0001] This application relates to the technical field of flow cytometers. Specifically, it relates to a method for determining AOM enabling parameters, an image acquisition method, and related devices. Background Art

[0002] Flow cytometry is a high-throughput detection technology based on the analysis of the characteristics of microparticles (such as cells). It realizes multi-parameter rapid quantitative analysis through laser-induced fluorescence detection, providing key data support for the study of cell heterogeneity. However, with the continuous deepening of biological research, the limitations of conventional flow cytometry have gradually emerged, such as limited fluorescence dyes and difficulty in obtaining high-content information on the spatial structure of cells. Against this background, a new imaging flow technology has emerged. It combines microscopic vision technology and can provide visual information of individual microparticles based on a large amount of data statistical measurement, helping to intuitively analyze cell structures.

[0003] Currently, there are already commercial imaging flow instruments such as ImageStream and FACSDiscover S8, but they use point scanning or line scanning time-delay integration methods to reconstruct images, with complex systems and potential aberration problems. In contrast, the imaging flow mechanism of area array detection is intuitive and simple, and the image quality is better after image acquisition.

[0004] However, the area array detection imaging flow technology needs to accurately match the moment when microparticles enter the imaging area, the external trigger signal of the camera, and the illumination start timing. If the three are not synchronized, it will lead to blurred cell images or signal loss. Especially when the microparticle flow rate reaches several meters per second, the time window error needs to be controlled at the nanosecond level. The illumination start time is mainly controlled by the AOM enabling parameters of the AOM driver. In related technologies, the AOM enabling parameters need to be regulated by hardware compensation, but it is still difficult to ensure clear and effective imaging.

[0005] In response to the above problems, there is currently no effective technical solution. Summary of the Invention

[0006] The purpose of this application is to provide a method for determining AOM enabling parameters, an image acquisition method, and related devices to accurately determine the AOM enabling parameters, so that the AOM driver in the flow cytometer with area array detection imaging can accurately match and start with the camera.

[0007] In a first aspect, this application provides a method for determining AOM enabling parameters, which is applied in a flow cytometer. The AOM enabling parameters include the AOM enabling delay time. The flow cytometer includes a fluid cell module and an image laser module. The image laser module includes an AOM driver and a camera. The AOM driver is triggered to operate based on the AOM enabling delay time to cooperate with the camera to acquire an image of the fluid cell module.

[0008] The method for determining the AOM enabling parameter includes the following steps:

[0009] S1. Trigger the operation of the AOM driver based on the reference enabling delay time to cooperate with the camera to collect a reference image dataset;

[0010] S2. Analyze the graphic characteristics of the light spot to obtain the proportion of valid images in the reference image dataset;

[0011] S3. Determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enabling delay time as the AOM enabling delay time; otherwise, reduce the reference enabling delay time and return to step S1.

[0012] The method for determining the AOM enabling parameter of the present application determines the AOM enabling delay time through an iterative process. Its processing process is feedback and iteratively adjusted through analyzing the graphic characteristics of the light spots in the actually collected image data, and determines an AOM enabling delay time that can improve the proportion of obtaining valid images, enabling the AOM driver in the area array detection imaging flow cytometer to accurately match and start with the camera, ensuring clear and effective imaging, and thus improving the imaging quality.

[0013] In the method for determining the AOM enabling parameter, step S2 includes:

[0014] S21. Screen the reference image dataset to obtain a first atlas, where the first atlas is a set of images with light spots;

[0015] S22. Extract the graphic characteristics of the light spots in each image in the first atlas, where the graphic characteristics include light spot brightness, longitudinal centroid position, and longitudinal length;

[0016] S23. Screen the first atlas according to the light spot brightness, longitudinal centroid position, longitudinal length, and a preset rule to obtain valid images;

[0017] S24. Calculate the proportion of the number of the valid images in the reference image dataset.

[0018] Through this series of steps, the process of obtaining the proportion of valid images based on the analysis of the graphic characteristics of the light spots becomes specific and executable, improving the accuracy and reliability of the process for determining the AOM enabling delay time.

[0019] In the method for determining the AOM enabling parameter, step S21 includes:

[0020] S211. Calculate the average brightness value of each image in the reference image dataset;

[0021] S212. Extract images from the reference image dataset where the number of pixels with luminance greater than the corresponding average luminance value is greater than or equal to a preset number threshold, and form the first image set.

[0022] This solution provides a specific and operable screening method, improving the accuracy of screening the first image set, laying a foundation for subsequent steps of analyzing the spot characteristics and determining valid images, and thus enhancing the reliability of determining the AOM enabling delay time.

[0023] The AOM enabling parameter determination method described above, wherein in step S23, the preset rules include:

[0024] The spot luminance is within the range of 20 - 80% of the maximum luminance, the distance between the longitudinal centroid position and the center point of the image is less than or equal to 10 pixels, and the longitudinal length is less than or equal to 20 pixels.

[0025] The AOM enabling parameter determination method described above, wherein the AOM enabling parameter further includes the AOM enabling hold time, and the AOM enabling parameter determination method further includes steps executed after determining the AOM enabling delay time:

[0026] S4. Based on different reference enabling hold times and the AOM enabling delay time, trigger the AOM driver to operate to cooperate with the camera to collect multiple spot images;

[0027] S5. Determine the reference enabling hold time corresponding to the spot image with the maximum spot luminance as the AOM enabling hold time.

[0028] The AOM enabling parameter determination method described above, wherein the reference enabling hold time is within a second preset interval, and the upper boundary of the second preset interval is set based on the pixel size, the optical magnification of the flow cytometer, and the fluid flow rate of the fluid cell module.

[0029] In a second aspect, the present application also provides an image acquisition method, which is applied to the acquisition chamber module in a flow cytometer. The flow cytometer includes a fluid cell module, a spectral laser module, an image laser module, and the acquisition chamber module. The image laser module includes an AOM driver and a camera, and the spectral laser module is used to excite the fluid cell module to generate spectral data;

[0030] The image acquisition method includes the following steps:

[0031] After the spectral laser module excites and generates spectral data, trigger the AOM driver to operate based on the AOM enabling parameters determined by the AOM enabling parameter determination method provided in the first aspect to cooperate with the camera to collect image data matching the spectral data.

[0032] The image acquisition method of this application controls the operation of the AOM driver based on the AOM enable parameter determined by the AOM enable parameter determination method provided in the first aspect, realizes precise illumination timing control, enables the timing synchronization between the camera and the AOM driver, performs exposure acquisition during image laser illumination, ensures that the illumination timing is precisely matched with the passage of particles through the imaging area and the exposure timing of the camera, improves the success rate of image acquisition, and enables the acquired images to meet the preset graphic characteristic requirements, solving the problem of blurred or missing images under the condition of high-speed particle flow.

[0033] In a third aspect, this application also provides an AOM enable parameter determination device, which is applied in a flow cytometer. The AOM enable parameter includes the AOM enable delay time. The flow cytometer includes a fluid cell module and an image laser module. The image laser module includes an AOM driver and a camera. The AOM driver is triggered to operate based on the AOM enable delay time to cooperate with the camera to acquire images of the fluid cell module.

[0034] The AOM enable parameter determination device includes:

[0035] A first acquisition module, configured to trigger the operation of the AOM driver based on a reference enable delay time to cooperate with the camera to acquire a reference image data set.

[0036] A first analysis module, configured to analyze and obtain the proportion of valid images in the reference image data set based on the graphic characteristics of the light spot.

[0037] A first determination module, configured to determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enable delay time as the AOM enable delay time; otherwise, reduce the reference enable delay time and trigger the first acquisition module to run again.

[0038] The AOM enable parameter determination device of the spectral laser module of this application determines the AOM enable delay time through an iterative process. Its processing process performs feedback and iterative adjustment through analyzing the graphic characteristics of the light spots in the actually acquired image data, determines an AOM enable delay time that can improve the proportion of valid image acquisition, enables the AOM driver in the area array detection imaging flow cytometer to start precisely matching the camera, ensures clear and effective imaging, and thus improves the imaging quality.

[0039] In a fourth aspect, this application also provides an electronic device, including a processor and a memory. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method provided in the first aspect as described above are run.

[0040] In a fifth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it runs the steps in the method provided in the first aspect as described above.

[0041] As can be seen from the above, the present application provides a method for determining AOM enabling parameters, an image acquisition method and related devices. Among them, the method for determining AOM enabling parameters in the present application determines the AOM enabling delay time through an iterative process. Its processing process performs feedback and iterative adjustment through analyzing the graphic characteristics of the light spot in the actually acquired image data, and determines an AOM enabling delay time that can improve the effective image acquisition ratio, so that the AOM driver in the area array detection imaging flow cytometer can accurately match and start with the camera, ensuring clear and effective imaging, thereby improving the imaging quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flowchart of the method for determining AOM enabling parameters provided in some embodiments of the present application.

[0043] Figure 2 It is a schematic structural diagram of a flow cytometer.

[0044] Figure 3 It is a flowchart of the method for determining AOM enabling parameters provided in other embodiments of the present application.

[0045] Figure 4 It is an effect diagram of the image before and after background enhancement processing.

[0046] Figure 5 It is a schematic structural diagram of the device for determining AOM enabling parameters provided in some embodiments of the present application.

[0047] Figure 6 It is a schematic structural diagram of the device for determining AOM enabling parameters provided in other embodiments of the present application.

[0048] Figure 7 It is a schematic structural diagram of the electronic device provided in the embodiments of the present application.

[0049] Reference numerals: 101, fluid cell module; 102, spectral laser module; 103, image laser module; 301, first acquisition module; 302, first analysis module; 303, first determination module; 304, second acquisition module; 305, second determination module; 104, acquisition chamber module; 401, processor; 402, memory; 403, communication bus. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application usually described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application claimed, but only represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0051] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for differential description and cannot be understood as indicating or implying relative importance.

[0052] In a first aspect, please refer to Figure 1 and Figure 3 , some embodiments of the present application provide a method for determining AOM enabling parameters, which is applied to a flow cytometer. The AOM enabling parameters include the AOM enabling delay time. The flow cytometer includes a fluid cell module 101 and an image laser module 103. The image laser module 103 includes an AOM driver and a camera. The AOM driver is triggered to run based on the AOM enabling delay time to cooperate with the camera to acquire an image of the fluid cell module 101.

[0053] The method for determining AOM enabling parameters includes the following steps:

[0054] S1. Trigger the AOM driver to run based on a reference enabling delay time to cooperate with the camera to acquire a reference image dataset;

[0055] S2. Analyze the graphic characteristics of the light spot to obtain the proportion of valid images in the reference image dataset;

[0056] S3. Determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enabling delay time as the AOM enabling delay time. Otherwise, reduce the reference enabling delay time and return to step S1.

[0057] Specifically, as Figure 2As shown in the figure, the flow cytometer includes a fluid cell module 101, a spectral laser module 102, an image laser module 103, and an acquisition chamber module 104. The spectral laser module 102 is used to excite the fluid cell module 101 to generate lateral spectral data and forward spectral data. Among them, the forward spectral data belongs to a trigger signal, which is used to trigger the acquisition chamber module 104 to delay the trigger of the image laser module 103 to excite the fluid cell module 101 to generate image data matching the lateral spectral data. Among them, the acquisition chamber module 104 respectively delays the trigger of the AOM driver and the camera operation in the image laser module 103 based on the AOM enable parameter and the camera enable parameter, so that the AOM driver and the camera cooperate to acquire the image data in the fluid cell module 101 that matches the lateral spectral data. The camera is a high-speed camera. The AOM driver is used to modulate pulsed laser to excite the fluid cell module 101.

[0058] More specifically, in the embodiment of the present application, the AOM enable parameter mainly includes the AOM enable delay time and the AOM enable hold time. The AOM enable delay time is the delay for the acquisition chamber module 104 to trigger the start of illumination of the AOM driver, and the AOM enable hold time is the duration of illumination. The AOM enable parameter determination method in the embodiment of the present application determines the AOM enable delay time through an iterative process.

[0059] More specifically, step S1 uses a reference enable delay time to trigger the AOM driver and acquires a set of images together with the camera to form a reference image data set. This step provides data for evaluating the effect of the current reference enable delay time. It should be noted that a fixed reference enable hold time is used to control the operation of the AOM driver during the execution of step S1 to ensure the comparability of the data.

[0060] It should be noted that during the process of acquiring the reference image data set, the fluid cell module 101 continuously conveys fluid, and the AOM driver and the camera acquire multiple images based on a preset acquisition frequency to form a reference image data set. If the reference enable delay time used by the AOM driver is set appropriately, there will be images with light spots in the reference image data set.

[0061] More specifically, step S2 analyzes the graphic characteristics of the light spots in the images, identifies the valid images in the data set, and calculates the proportion of these valid images in the entire data set. This step quantifies the imaging effect under the current reference enable delay time. The analysis process is based on the graphic characteristics of the light spots in the images to identify the images in the data set that successfully capture the light spots and are correctly illuminated. These images are called valid images.

[0062] More specifically, in step S3, the calculated ratio of valid images is compared with a preset ratio threshold. If the ratio reaches or exceeds the ratio threshold, it indicates that the current reference enable delay time can obtain a sufficient proportion of valid images, indicating that the start-up delays of the current AOM driver and the camera have an optimal phase difference. Therefore, the current reference enable delay time is determined as the final AOM enable delay time. If the ratio is lower than the ratio threshold, it means that the current reference enable delay time is not ideal and the images with light spots cannot be effectively captured, that is, there is a large deviation in the start-up delays of the AOM driver and the camera. It is necessary to reduce the reference enable delay time to adjust the phase difference of the start-up delays of the AOM driver and the camera, and then return to step S1 to re-perform image acquisition and analysis using the new and reduced reference enable delay time. This iterative process continues until an enable delay time is found at which the ratio of valid images captured meets the preset requirements. Through this method of analyzing actual acquisition data and feedback adjustment, the method can determine an AOM enable delay time that helps to obtain valid images, realizing the algorithmic adaptive determination of the AOM enable delay time.

[0063] The AOM enable parameter determination method of the embodiment of the present application determines the AOM enable delay time through an iterative process. Its processing process performs feedback and iterative adjustment through analyzing the graphic characteristics of the light spots in the actually acquired image data, and determines an AOM enable delay time that can increase the ratio of valid image acquisition, enabling the AOM driver in the area array detection imaging flow cytometer to accurately match the start-up of the camera, ensuring clear and effective imaging, and thus improving the imaging quality.

[0064] In some preferred embodiments, the ratio threshold is preferably 1%.

[0065] Specifically, during the process of step S1 for acquiring the reference image dataset, the fluid cell module 101 continuously transports the fluid containing microparticles. However, most of the images acquired by the cooperation of the AOM driver and the camera may not contain microparticles. The AOM enable parameter determination method of the embodiment of the present application is mainly to determine an effective AOM enable delay time that can excite the microparticles. Therefore, it is only necessary to ensure that there are a small number of valid images in the entire dataset. Therefore, the ratio threshold is set to 1%.

[0066] In some preferred embodiments, the AOM enable parameter determination method further includes a step performed before step S1:

[0067] S0. Set an initial reference enable delay time based on the upper boundary within the first preset interval.

[0068] Specifically, step S0 sets an initial reference enable delay time based on the upper boundary of the first preset interval, providing a clear starting parameter for subsequent image acquisition and analysis. The reduction process in step S3 is also carried out within the first preset interval. This strategy ensures that the adjustment process of the reference enable delay time has a clear starting point and search range, improves the efficiency and reliability of the parameter determination process, and helps to find the AOM enable delay time that meets the requirements more quickly.

[0069] More specifically, setting the first preset interval limits the reference enable delay time, which can effectively reduce the time required to obtain a suitable reference enable delay time. On this basis, step S3 is equivalent to gradually reducing the phase difference between the start delays of the AOM driver and the camera, so that the ratio calculated in step S2 gradually increases until it meets the ratio threshold set in step S3, providing a systematic and controllable search strategy. This ensures that each adjustment is carried out according to a predetermined step size, avoiding random or uncertain adjustments, and improving the stability and efficiency of the determination process.

[0070] In some preferred embodiments, in step S3, the reduction process of the reference enable delay time is carried out within the first preset interval based on the first preset interval.

[0071] Specifically, the first preset interval is 0.02 - 0.10 us, preferably 0.05 us. This means that each reduction is carried out according to a fixed and preset step size, and the reduced value still remains within the set first preset interval.

[0072] In some preferred embodiments, the first preset interval is set based on the camera enable delay time of the camera, and the upper boundary of the first preset interval lags behind the camera enable delay time by at least 2 us.

[0073] Specifically, the above setting aims to solve the problem that the search range does not match the camera working timing when determining the AOM enabling delay time. This setting associates the setting of the first preset range with the camera enabling delay time, ensuring that the search range of the AOM enabling delay time matches the time window for the camera to capture images. Specifically, the first preset range is set based on the camera enabling delay time, establishing the association between the search range of the AOM enabling delay time and the camera's own timing, making the search process more targeted. The upper boundary of the first preset range lags behind the camera enabling delay time by at least 2 us, further limiting the scope of the search range. The camera enabling delay time represents the time point when the camera starts to prepare for shooting. The AOM needs to trigger a laser pulse after this time point to illuminate the fluid cell during the camera shooting. Setting the upper boundary of the search range after the camera enabling delay time and leaving a margin of at least 2 us ensures that the search range covers the effective time window when the AOM may need to trigger, thereby increasing the probability of finding the optimal AOM enabling delay time. Thus, the range for setting the initial reference enabling delay time and subsequent reduction of the search is limited to an interval related to the actual image capture time window of the camera.

[0074] It should be noted that the lower boundary of the first preset range can be set according to the actual situation, for example, set to a time point near or before the camera enabling delay time, such as at least 0.5 us earlier than the camera enabling delay time.

[0075] More specifically, step S0 initializes the reference enabling delay time based on the upper boundary of the first preset range determined by the above setting method, which can limit the search range of the AOM enabling delay time within an interval that matches the camera exposure timing, and ensure that there is a margin after the upper boundary of the search range behind the camera enabling delay time, which can effectively improve the efficiency and accuracy of finding the optimal AOM triggering timing, and ensure that the AOM driver can accurately trigger during the camera exposure, realizing clear and effective image acquisition.

[0076] In some preferred embodiments, the camera enabling delay time satisfies: t CD =H / V - T0, where t CD is the camera enabling delay time, H is the vertical spatial distance from the spectral optical point to the image optical point, V is the fluid flow rate of the fluid cell module 101, and T0 is the electrical signal processing time before the acquisition chamber module 104 receives the spectral data.

[0077] Specifically, based on the foregoing, the camera enabling delay time is a key parameter for determining the search range of the AOM enabling delay time. The above calculation formula clarifies the camera enabling delay time to facilitate the determination of the first preset range.

[0078] More specifically, the fluid cell module 101 generally transports fluid from top to bottom. The spectral laser module 102 and the image laser module 103 are arranged above and below the excitation points (i.e., the aforementioned spectral optical point and image optical point) in the fluid cell module 101 to ensure that the image data collected by the later-triggered image laser module 103 and the particles detected by the spectral data collected by the spectral laser module 102 are the same. Therefore, H is actually the distance between the two excitation points. V represents the movement speed of the particles in the fluid cell module 101, and this speed can be set or measured by controlling the fluid pressure or flow rate. T0 represents the time required for internal electronic signal processing in the system, that is, the delay between the spectral detector receiving the particle signal and the system generating a trigger signal, and this time can be obtained through system calibration. The above calculation formula calculates the time required for the particles to move from the spectral optical point to the image optical point by dividing the particle movement distance H by the flow velocity V. Then subtract the internal processing delay T0 of the system to obtain the precise time point at which the camera needs to be triggered to capture the particle image. By calculating the precise t CD value, it can provide an accurate reference benchmark for determining the AOM enabling delay time in the subsequent stage. Thereby, the efficiency and accuracy of determining the AOM timing are improved, the determination of the camera enabling delay time is based on the actual operating state of the system, the reliability of the determination result is improved, and it helps to collect clear and effective particle images.

[0079] In some preferred embodiments, step S2 includes:

[0080] S21. Screening the reference image dataset to obtain a first image set, where the first image set is a set of images with light spots;

[0081] S22. Extracting the graphic features of the light spots in each image in the first image set, where the graphic features include light spot brightness, longitudinal centroid position, and longitudinal length;

[0082] S23. Screening the first image set according to the light spot brightness, longitudinal centroid position, longitudinal length, and preset rules to obtain valid images;

[0083] S24. Calculating the proportion of the number of valid images in the reference image dataset.

[0084] Specifically, step S21 can be implemented by calculating the average brightness value of each image in the reference image dataset and extracting the images in which the number of pixels with brightness greater than the corresponding average brightness value is greater than or equal to a preset number threshold. To extract the graphic features of the light spot, an image processing algorithm can be used to trace the outline of the light spot in the images of the first atlas, and the brightness of all pixels within the outline is extracted as the light spot brightness. The average value of the vertical coordinates of the pixels within the outline is calculated as the vertical centroid position, and the difference between the vertical coordinates of the top and bottom pixels of the outline is calculated as the vertical length. Screening valid images according to preset rules means comparing the extracted light spot brightness, vertical centroid position, and vertical length with preset numerical ranges or thresholds, and the images that meet all the conditions are determined as valid images. Calculating the proportion is to count the number of valid images and divide it by the total number of images in the reference image dataset.

[0085] More specifically, the above processing method aims to solve the problem of how to accurately identify valid images based on the graphic features of the light spot and calculate their proportion. First, through the screening step, the images without light spots are removed from the reference image dataset to form a set of potential light spot images, namely the first atlas. This preprocessing step reduces the amount of data for subsequent analysis. Then, for each image in the first atlas, three key graphic features of the light spot are extracted: light spot brightness, vertical centroid position, and vertical length. These features provide quantitative information to describe the quality, position, and shape of the light spot. The light spot brightness reflects the illumination and signal intensity, the vertical centroid position indicates the vertical offset degree of the light spot within the image acquisition area, and the vertical length reflects the stretching or compression degree of the light spot in the flow direction. Further, using preset rules, the extracted graphic features are judged. These rules set the conditions that a valid light spot should meet. For example, the light spot brightness should be within a reasonable range, the vertical centroid position should be close to the center of the image, and the vertical length should be within an allowable range. By applying these rules, high-quality and properly positioned light spot images, that is, valid images, can be accurately screened out from the first atlas. Thus, by calculating the proportion of the number of valid images to the total number of images in the original reference image dataset, a quantitative index reflecting the imaging effect under the current AOM enabling delay time is obtained. This proportion value directly quantifies the proportion of successfully captured high-quality light spot images under the current AOM enabling delay time, providing a data basis for judging whether this delay time is appropriate. Through this series of steps, the process of obtaining the proportion of valid images based on the analysis of the graphic features of the light spot becomes specific and executable, improving the accuracy and reliability of the process of determining the AOM enabling delay time.

[0086] In some preferred embodiments, step S21 includes:

[0087] S211. Calculate the average brightness value of each image in the reference image dataset;

[0088] S212. Extract images from the reference image dataset where the number of pixels with brightness greater than the corresponding average brightness value is greater than or equal to a preset number threshold, and form a first image set.

[0089] Specifically, in step S211, the average brightness value represents the overall brightness level of the image. The average brightness value can be calculated by summing the brightness values of all pixels in the image and then dividing by the total number of pixels.

[0090] More specifically, step S212 performs screening based on the calculated average brightness value and the preset number threshold. For each image, count the number of pixels with brightness greater than its average brightness value. If this number reaches or exceeds the preset number threshold, include the image in the first image set. The preset number threshold is a set value used to determine whether there are a sufficient number of pixels with brightness higher than the background, thus indicating the presence of a light spot. By comparing the pixel brightness with the average brightness and setting the number threshold, a quantitative standard is provided to judge whether there is a local high-brightness area in the image.

[0091] More specifically, through the above processing method, the first image set is screened as a set of images that may contain light spots. This method utilizes the characteristic that light spots are usually brighter than the background area. By quantitatively analyzing the pixel brightness distribution, it effectively distinguishes images containing light spots from images with only background noise. The number of pixels with brightness greater than the average brightness reaching a certain threshold indicates the presence of a significant high-brightness area in the image, which conforms to the characteristics of light spots. This solution provides a specific and operable screening method, improves the accuracy of screening the first image set, lays a foundation for analyzing the characteristics of light spots and determining effective images in subsequent steps, and thus improves the reliability of determining the AOM-enabled delay time.

[0092] In some preferred embodiments, between step S21 and step S22, it further includes:

[0093] S2A. Perform contour tracing on the light spots of all images in the first image set and perform background enhancement processing on all images.

[0094] Specifically, after screening out the set of images containing light spots, perform contour tracing operations on the light spots in these images to clarify the boundaries of the light spots. At the same time, perform background enhancement processing on these images, specifically by enhancing the brightness of all pixels by a preset multiple. The contour tracing processing helps to accurately calculate the brightness, longitudinal centroid position, and longitudinal length of the light spots in subsequent steps. The background enhancement processing improves the contrast between the light spots and the background, helps to improve the accuracy of calculating the light spot brightness, and makes the light spot areas with lower brightness easier to be recognized and analyzed.

[0095] More specifically, in this way, when extracting the graphic features of the light spots in each image of the processed first atlas, for example, calculating the sum of the brightness of all pixels within the light spot contour as the light spot brightness, calculating the longitudinal center point based on the contour shape as the longitudinal centroid position, and measuring the longitudinal pixel distance between the top and bottom of the contour as the longitudinal length, more reliable data can be obtained. Based on these more accurate graphic features and preset rules, valid images can be screened out more reliably, and then the proportion of the valid images in the reference image dataset can be calculated.

[0096] Preferably, the background enhancement process is to enhance the brightness of all pixels by 2 times, as Figure 4 shown. The image data on the left side of the figure is the image data without background enhancement processing, and the image data on the right side of the figure is the image data after background enhancement processing. The image data after background enhancement processing has visible light spots to the naked eye.

[0097] In some preferred embodiments, in step S23, the preset rules include:

[0098] The light spot brightness is within the range of 20%-80% of the maximum brightness, the distance between the longitudinal centroid position and the center point of the image is less than or equal to 10 pixels, and the longitudinal length is less than or equal to 20 pixels.

[0099] Specifically, the light spot brightness within a specific range of the maximum brightness is used to exclude light spots with abnormal brightness, and the maximum brightness is the maximum value of the recognizable brightness of the image. The distance between the longitudinal centroid position and the center point of the image is less than or equal to a specific pixel value, which is used to limit the light spot in the central area of the image. The longitudinal length is less than or equal to a specific pixel value, which is used to limit the longitudinal size of the light spot. The setting of these rules is based on the analysis of the graphic features of valid light spots, aiming to identify high-quality images.

[0100] More specifically, when screening the image set with light spots to obtain valid images, each image in the set is analyzed. First, the brightness of all pixels within the light spot contour in the image is obtained, and it is determined whether the brightness of these pixels all falls within the range of 20 - 80% of the maximum brightness. If so, the image exposure degree is considered qualified; otherwise, it is considered that the image has overexposure or underexposure problems. The longitudinal centroid position of the light spot is determined, and the pixel distance between this position and the center point of the image is calculated to determine whether the distance is less than or equal to 10 pixels. In addition, the longitudinal length of the light spot, that is, the pixel distance between the top and bottom of the light spot, is measured to determine whether the length is less than or equal to 20 pixels. Only the images that meet all three of these conditions are determined to be valid images, thereby restricting the longitudinal size of the light spots in the valid images and ensuring that the light spots present a relatively concentrated shape longitudinally. The above preset rules can accurately identify those light spot images with appropriate brightness, located at the center of the image, and appropriate longitudinal size from the images containing light spots, improving the accuracy of the valid image set, and further enhancing the accuracy of the calculation of the proportion of valid images. The accurate proportion calculation provides a reliable basis for determining the subsequent AOM enabling delay time.

[0101] In some preferred embodiments, the AOM enabling parameter further includes the AOM enabling holding time, and the method for determining the AOM enabling parameter further includes the steps performed after determining the AOM enabling delay time:

[0102] S4. Trigger the AOM driver to run in cooperation with the camera to collect multiple light spot images based on different reference enabling holding times and AOM enabling delay times;

[0103] S5. Determine the reference enabling holding time corresponding to the light spot image with the maximum light spot brightness as the AOM enabling holding time.

[0104] Specifically, the above newly added steps are aimed at solving the problem that only determining the AOM enabling delay time is not sufficient to ensure the best image quality, and improving the AOM enabling parameters by introducing the determination of the AOM enabling holding time.

[0105] More specifically, step S4 is executed on the basis of having determined the AOM enabling delay time. By fixing the determined AOM enabling delay time and then changing the AOM enabling holding time (i.e., the reference enabling holding time), it triggers the AOM driver to run and cooperate with the camera to collect multiple images. Different reference enabling holding times correspond to different exposure times, thereby collecting light spot images at different exposure times. The role of this step is to generate a series of image samples for evaluating the effects of different exposure times.

[0106] More specifically, in step S5, multiple spot images collected in step S4 are analyzed, and the image with the maximum spot brightness is selected. The reference enable holding time corresponding to the image with the maximum brightness is determined as the final AOM enable holding time. The spot brightness is usually positively correlated with the exposure time. Within a certain range, the greater the brightness, the more light signals may be received, and the better the image quality. By selecting the holding time corresponding to the image with the maximum brightness, a suitable exposure time can be determined, thereby improving the quality of image acquisition. The AOM enable holding time represents the duration for which the AOM is turned on and directly affects the effective exposure time in the camera.

[0107] It should be noted that in step S1, a reference image dataset is collected based on the initialized AOM enable holding time.

[0108] More specifically, in step S4, for each reference enable holding time, the AOM driver is triggered to run, which turns on after a set delay time and lasts for a set holding time, while the camera cooperates to perform image acquisition. Thus, multiple spot images can be collected, and each image corresponds to a specific reference enable holding time. These images reflect the imaging effects of the spots at different exposure durations. By determining the optimal AOM enable holding time, it can be ensured that spot images with sufficient brightness and clarity are obtained during image acquisition, thereby improving the quality of image acquisition.

[0109] In some preferred embodiments, the reference enable holding time is within a second preset interval, and the upper boundary of the second preset interval is set based on the pixel size, the optical magnification of the flow cytometer, and the fluid flow rate of the fluid cell module 101.

[0110] Specifically, the upper boundary of the second preset interval is preferably such that: T max ≤ L / (F * V), where L is the pixel size, F is the optical magnification of the flow cytometer, V is the fluid flow rate of the fluid cell module 101, and T max is the upper boundary of the second preset interval. The lower boundary of the second preset interval can be set according to the actual situation.

[0111] More specifically, L represents the physical size of a single pixel on the camera image sensor, i.e., the pixel size.

[0112] More specifically, F represents the magnification of the entire optical system of the flow cytometer, which determines how many times the actual size of the particles in the fluid cell is magnified on the image sensor. V represents the speed of fluid flow in the fluid cell module 101, i.e., the speed at which the particles pass through the imaging area. The T calculated by this formula maxRepresents the minimum time required for a particle to move one pixel on the image sensor. Setting the upper limit of the reference enable hold time not to exceed this time ensures that the exposure time matches the movement speed of the particle and the system resolution. If the exposure time exceeds this value, the distance traveled by the particle during exposure will be greater than one pixel, resulting in image blurring. Therefore, setting the upper limit of the reference enable hold time not to exceed L / (F*V) can avoid image smear or blurring caused by too long exposure time, ensure that the collected spot image has sufficient clarity, so as to accurately evaluate the spot brightness at different hold times, and ensure that the finally determined AOM enable hold time can enable the system to collect clear and effective particle images during actual operation.

[0113] More specifically, step S4 is preferably to collect multiple spot images by gradually increasing the reference enable hold time. If there are multiple reference enable hold times corresponding to the spot image with the maximum spot brightness in step S5, the minimum reference enable hold time among these reference enable hold times is taken as the AOM enable hold time to avoid image smear.

[0114] In a second aspect, some embodiments of the present application further provide an image acquisition method, which is applied to the acquisition bin module 104 in a flow cytometer. The flow cytometer includes a fluid cell module 101, a spectral laser module 102, an image laser module 103, and an acquisition bin module 104. The image laser module 103 includes an AOM driver and a camera. The spectral laser module 102 is used to excite the fluid cell module 101 to generate spectral data;

[0115] The image acquisition method includes the following steps:

[0116] After the spectral laser module 102 excites and generates spectral data, trigger the AOM driver to operate based on the AOM enable parameter determined by the AOM enable parameter determination method provided in the first aspect to cooperate with the camera to collect image data matching the spectral data.

[0117] Specifically, this image acquisition method is applied to the acquisition bin module 104 of the flow cytometer, and the start timing of the image acquisition process is set after the spectral laser module 102 excites and generates spectral data. When the particles in the fluid cell module 101 are excited by the spectral laser module 102 to generate spectral data, the acquisition bin module 104 receives the corresponding signal. After receiving the spectral data generation signal, the image acquisition process starts.

[0118] More specifically, the AOM enable parameter for triggering the operation of the AOM driver includes the AOM enable delay time, which is determined by using the AOM enable parameter determination method provided in the first aspect. This determination method aims to find the parameters that can make the acquired image meet the preset graphic characteristics. The AOM driver controls the switch of the AOM, and then controls the illumination timing of the image laser. The camera works in cooperation with the AOM driver to acquire images of particles during the period when the AOM is turned on. The acquired image data is matched with the corresponding spectral data.

[0119] The image acquisition method of the embodiments of the present application controls the operation of the AOM driver based on the AOM enable parameter determined by the AOM enable parameter determination method provided in the first aspect, realizes precise illumination timing control, enables the timing synchronization of the camera and the AOM driver, performs exposure acquisition during the image laser illumination period, ensures that the illumination timing is precisely matched with the passage of particles through the imaging area and the camera exposure timing, improves the success rate of image acquisition, and makes the acquired image meet the requirements of the preset graphic characteristics, solving the problem of blurred or missing images under the condition of high-speed flow of particles.

[0120] In a third aspect, please refer to Figure 5 and Figure 6 , some embodiments of the present application also provide an AOM enable parameter determination device, which is applied in a flow cytometer. The AOM enable parameter includes the AOM enable delay time. The flow cytometer includes a fluid cell module 101 and an image laser module 103. The image laser module 103 includes an AOM driver and a camera. The AOM driver is triggered to operate based on the AOM enable delay time to cooperate with the camera to acquire images of the fluid cell module 101;

[0121] The AOM enable parameter determination device includes:

[0122] A first acquisition module 301, configured to trigger the operation of the AOM driver based on a reference enable delay time to cooperate with the camera to acquire a reference image data set;

[0123] A first analysis module 302, configured to analyze and obtain the proportion of valid images in the reference image data set based on the graphic characteristics of the light spot;

[0124] A first determination module 303, configured to determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enable delay time as the AOM enable delay time; otherwise, reduce the reference enable delay time and trigger the first acquisition module 301 to operate again.

[0125] The AOM enabling parameter determination device according to the embodiment of the present application determines the AOM enabling delay time through an iterative process. Its processing process performs feedback and iterative adjustment through analyzing the graphic characteristics of the light spots in the actually collected image data, determines an AOM enabling delay time that can improve the effective image acquisition ratio, enables the AOM driver in the area array detection imaging flow cytometer to accurately match and start with the camera, ensures clear and effective imaging, and thus improves the imaging quality.

[0126] In some preferred embodiments, the AOM enabling parameter further includes an AOM enabling holding time, and the AOM enabling parameter determination device further includes:

[0127] A second acquisition module 304, configured to trigger the AOM driver to operate based on different reference enabling holding times and AOM enabling delay times to cooperate with the camera to acquire a plurality of light spot images;

[0128] A second determination module 305, configured to determine the reference enabling holding time corresponding to the light spot image with the maximum light spot brightness as the AOM enabling holding time.

[0129] In some preferred embodiments, the AOM enabling parameter determination device according to the embodiment of the present application is used to execute the AOM enabling parameter determination method provided in the first aspect above.

[0130] In a fourth aspect, please refer to Figure 7 , some embodiments of the present application further provide a schematic structural diagram of an electronic device. The present application provides an electronic device, including: a processor 401 and a memory 402. The processor 401 and the memory 402 are interconnected and communicate with each other through a communication bus 403 and / or other forms of connection mechanisms (not marked). The memory 402 stores computer-readable instructions executable by the processor 401. When the electronic device runs, the processor 401 executes the computer-readable instructions to execute the methods in any optional implementation manner of the above embodiments when executed.

[0131] Fifth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method in any optional implementation manner of the above embodiment is executed. Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, abbreviated as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, abbreviated as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, abbreviated as EPROM), programmable read-only memory (Programmable Red-Only Memory, abbreviated as PROM), read-only memory (Read-OnlyMemory, abbreviated as ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0132] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0133] In addition, the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0134] Furthermore, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0135] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0136] The above are only examples of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A method for determining AOM enabling parameters, which is applied in a flow cytometer, is characterized in that The AOM enabling parameter includes the AOM enabling delay time. The flow cytometer includes a fluid cell module and an image laser module. The image laser module includes an AOM driver and a camera. The AOM driver is triggered to operate based on the AOM enabling delay time to cooperate with the camera to acquire images of the fluid cell module; The method for determining the AOM enabling parameter includes the following steps: S1. Trigger the AOM driver to operate based on a reference enabling delay time to cooperate with the camera to acquire a reference image dataset; S2. Analyze the graphic characteristics of the light spots to obtain the proportion of valid images in the reference image dataset; S3. Determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enabling delay time as the AOM enabling delay time. Otherwise, reduce the reference enabling delay time and return to step S1.

2. The AOM enabling parameter determination method according to claim 1, wherein Step S2 includes: S21. Screen the reference image dataset to obtain a first image set, which is a set of images with light spots; S22. Extract the graphic characteristics of the light spots in each image in the first image set. The graphic characteristics include light spot brightness, longitudinal centroid position, and longitudinal length; S23. Screen the first image set according to the light spot brightness, longitudinal centroid position, longitudinal length, and a preset rule to obtain valid images; S24. Calculate the proportion of the number of valid images in the reference image dataset.

3. The AOM enabling parameter determination method according to claim 2, characterized in that, Step S21 includes: S211. Calculate the average brightness value of each image in the reference image dataset; S212. Extract the images in the reference image dataset whose number of pixels with brightness greater than the corresponding average brightness value is greater than or equal to a preset number threshold to form the first image set.

4. The AOM enabling parameter determination method according to claim 2, characterized in that, In step S23, the preset rule includes: The light spot brightness is within the range of 20%-80% of the maximum brightness, the distance between the longitudinal centroid position and the center point of the image is less than or equal to 10 pixels, and the longitudinal length is less than or equal to 20 pixels.

5. The AOM enabling parameter determination method according to claim 1, wherein The AOM enabling parameter further includes the AOM enabling holding time. The method for determining the AOM enabling parameter further includes the steps performed after determining the AOM enabling delay time: S4. Trigger the AOM driver to operate based on different reference enabling holding times and the AOM enabling delay time to cooperate with the camera to acquire multiple light spot images; S5. Determine the reference enabling holding time corresponding to the light spot image with the maximum light spot brightness as the AOM enabling holding time.

6. The AOM enabling parameter determination method according to claim 5, characterized in that The reference enabling holding time is within a second preset interval, and the upper boundary of the second preset interval is set based on the pixel size, the optical magnification of the flow cytometer, and the fluid flow rate of the fluid cell module.

7. An image acquisition method, applied to an acquisition chamber module in a flow cytometer, characterized in that, The flow cytometer includes a fluid cell module, a spectral laser module, an image laser module, and the acquisition chamber module. The image laser module includes an AOM driver and a camera. The spectral laser module is used to excite the fluid cell module to generate spectral data; The method for acquiring images includes the following steps: After spectral laser module excitation generates spectral data, trigger the AOM driver to operate based on the AOM enabling parameter determined by the AOM enabling parameter determination method according to any one of claims 1-6, so as to cooperate with the camera to collect image data matching the spectral data.

8. An AOM enabling parameter determination device, which is applied to a flow cytometer, is characterized in that The AOM enabling parameter includes an AOM enabling delay time. The flow cytometer includes a fluid cell module and an image laser module. The image laser module includes an AOM driver and a camera. The AOM driver is triggered to operate based on the AOM enabling delay time to cooperate with the camera to collect images of the fluid cell module. The AOM enabling parameter determination device includes: A first acquisition module, configured to trigger the AOM driver to operate based on a reference enabling delay time to cooperate with the camera to acquire a reference image data set. A first analysis module, configured to analyze and obtain the proportion of valid images in the reference image data set based on the graphic characteristics of the light spot. A first determination module, configured to determine whether the proportion meets a preset proportion threshold. If so, determine the current reference enabling delay time as the AOM enabling delay time; otherwise, reduce the reference enabling delay time and trigger the first acquisition module to operate again.

9. An electronic device, characterized in that, Comprising a processor and a memory, the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1-7 are run.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps in the method according to any one of claims 1-7 are run.

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